Next Article in Journal
Imaging and Metabolic Diagnostic Methods in the Stage Assessment of Rectal Cancer
Previous Article in Journal
Correction: Ionna et al. Sentinel Lymph Node Biopsy (SLNB) for Early-Stage Head and Neck Squamous-Cell Carcinoma of the Tongue: Twenty Years of Experience at I.N.T. “G.Pascale”. Cancers 2024, 16, 1153
Previous Article in Special Issue
The Treatment of Hepatocellular Carcinoma with Major Vascular Invasion
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Extracellular Vesicles, Circadian Rhythms, and Cancer: A Comprehensive Review with Emphasis on Hepatocellular Carcinoma

1
McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
2
Division of Surgical Oncology and Gastrointestinal Surgery, Department of Surgery, Houston Methodist Hospital, Houston, TX 77030, USA
*
Author to whom correspondence should be addressed.
Cancers 2024, 16(14), 2552; https://doi.org/10.3390/cancers16142552 (registering DOI)
Submission received: 20 June 2024 / Revised: 12 July 2024 / Accepted: 14 July 2024 / Published: 16 July 2024
(This article belongs to the Special Issue Diagnosis and Treatment for Hepatocellular Tumors (Volume II))

Abstract

:

Simple Summary

Extracellular vesicles (ECVs), especially exosomes, play a crucial role in hepatocellular carcinoma (HCC) by facilitating intercellular communication and influencing circadian rhythms, thereby affecting HCC progression and treatment responses. Exosomes serve as biomarkers for early cancer detection, drug delivery vehicles, and modulators of immune responses. They promote angiogenesis, modulate the tumor microenvironment, and spread drug resistance. Advanced techniques for isolating cell-specific exosomes and aligning treatments with natural circadian rhythms show promise for early detection and personalized therapies. Understanding how exosomal cargo is sorted and interacts with circadian genes could revolutionize HCC diagnostics and treatments, improving patient outcomes. Utilizing liver-specific proteins for precise exosome isolation can enhance early detection and treatment efficacy, paving the way for more personalized and effective cancer therapies.

Abstract

This review comprehensively explores the complex interplay between extracellular vesicles (ECVs)/exosomes and circadian rhythms, with a focus on the role of this interaction in hepatocellular carcinoma (HCC). Exosomes are nanovesicles derived from cells that facilitate intercellular communication by transporting bioactive molecules such as proteins, lipids, and RNA/DNA species. ECVs are implicated in a range of diseases, where they play crucial roles in signaling between cells and their surrounding environment. In the setting of cancer, ECVs are known to influence cancer initiation and progression. The scope of this review extends to all cancer types, synthesizing existing knowledge on the various roles of ECVs. A unique aspect of this review is the emphasis on the circadian-controlled release and composition of exosomes, highlighting their potential as biomarkers for early cancer detection and monitoring metastasis. We also discuss how circadian rhythms affect multiple cancer-related pathways, proposing that disruptions in the circadian clock can alter tumor development and treatment response. Additionally, this review delves into the influence of circadian clock components on ECV biogenesis and their impact on reshaping the tumor microenvironment, a key component driving HCC progression. Finally, we address the potential clinical applications of ECVs, particularly their use as diagnostic tools and drug delivery vehicles, while considering the challenges associated with clinical implementation.

1. Introduction

Extracellular vesicles (ECVs), including exosomes, are secreted by diverse cell types, ranging from fibroblasts to cancer cells, and play a critical role in facilitating the intercellular transmission of signals through bioactive molecules like nucleic acids, proteins, lipids, and metabolites. ECVs can vary in size, content, and surface markers, reflecting the diverse origins of their parent cells. This heterogeneity influences extracellular vesicle (ECV) function, as different subpopulations may have distinct effects on recipient cells [1,2,3]. The significance of ECVs is underscored by their ubiquitous presence in diverse body fluids, including bile, blood, breast milk, urine, cerebrospinal fluid, and saliva [4,5,6].
The circadian rhythm functions as an internal biological clock, regulating physiological activities throughout a 24 h period. The circadian rhythm’s impact on cellular activities extends to the synthesis and packaging of ECV cargo, influencing variations in its composition throughout the day [7,8,9,10,11]. Disruptions to the circadian clock have been implicated in tumor development, progression, and responses to treatment across different types of cancers [12,13,14,15,16], which has a bearing on tailoring targeted therapeutic strategies to specific types of cancer [17,18]. Early detection and treatment of cancer is pivotal for enhancing patient outcomes. Therefore, sensitive and specific biomarkers are critical in early cancer detection and the monitoring of progression and treatment response. The sensitivity and specificity of the biomarkers currently available for cancer detection are inadequate, especially in accurately distinguishing between individuals at high or low risk for the disease [19,20,21,22,23]. Given their distinct composition and rich biological data, ECVs are an innovative and novel source of cancer biomarkers. One emerging barrier is their heterogeneity, with diverse subpopulations of tumor-derived ECVs playing varying roles in progression and metastasis [24,25,26,27,28].
Hepatocellular carcinoma (HCC) comprises over 90% of liver cancers and ranks as the fifth most common cancer and the third leading cause of cancer death worldwide, with 840,000 new cases and 780,000 deaths annually [29,30]. Underlying tissue alterations from hepatitis contribute to late-stage detection (85% at intermediate-to-advanced stages). Patients with early-stage disease are eligible for liver-directed therapies (including ablation), surgical resection, and liver transplantation [31]. Five-year survival with these potentially curative therapies can exceed 70%; in contrast, five-year survival after palliative therapies for advanced-stage disease is generally less than 5% [32,33]. Due to suboptimal surveillance methods for HCC (i.e., abdominal imaging with ultrasound, computed tomography, or magnetic resonance imaging) and persistent poor utilization and uptake among high-risk populations, most patients, unfortunately, present with advanced disease [32]. The only biomarker currently validated for clinical use for screening for HCC, alpha-fetoprotein (AFP), has marginal sensitivity and specificity (approximately 60 and 80%, respectively); not surprisingly, most societal guidelines recommend its use only in combination with abdominal ultrasound [32,34,35,36]. Other biomarkers that have been tested alone and in combination with AFP in large retrospective longitudinal studies, such as AFP-L3 and DCP, have similarly marginal performance characteristics [37]. As such, an urgent need exists for newer, more accurate, non-invasive biomarkers for early detection and diagnosis of HCC that do not necessarily need to be used in combination with abdominal imaging (which adds cost and impairs more widespread uptake, particularly across under-resourced settings). Several studies have indicated a close association between ECVs and the onset and progression of HCC. A thorough investigation into ECVs, including circadian influences, may reveal insights into tumor formation and metastasis mechanisms, offering novel approaches to early diagnosis and treatment [38,39,40].

2. Exosome Biogenesis

Traditional extracellular vesicles (ECVs) include exosomes (40–150 nm), microvesicles, and apoptotic bodies. Recent research has identified additional types, such as autophagic ECVs, stress-induced ECVs, and matrix vesicles [41,42,43]. The formation of exosomes occurs through a complex and highly regulated process, where intraluminal vesicles (IVLs) are created through inward budding endosomal membranes, with the sorting and enrichment of exosome components; exosomes are then disgorged from multivesicular bodies (MVBs) [44,45] (Figure 1).
Exosomes may release their material into the intracellular environment or internalize it into early endosomes. Early endosomes mature and form exosome-like vesicles, which can either be recycled and resecreted or degraded after fusion with a lysosome, supporting the recipient cell’s metabolism [45,46]. The genomic health of cells and distinct cell types can further influence the regulation of exosome biogenesis [47]. Exosomes are formed through two pathways: the endosomal sorting complex required for transport (ESCRT)-dependent pathway, and the ESCRT-independent pathway. The ESCRT-dependent pathway is considered the most important mechanism to sort cargoes and mediate membrane shaping for exosome formation. Numerous molecules, including the ESCRT complex, are involved in the sorting of ubiquitinated proteins into ILVs through this pathway. However, in the ESCRT-independent pathway, MBV and ILV formation occurs through the sphingomyelinase enzyme, using chaperones and tetraspanins (CD63 or CD81) to assist in cargo binding and membrane formation. Exosomal proteins, either luminal or surface-bound, enable subtyping with surface markers like CD9, CD63, and CD81, which are integral to exosome formation and function. Proteins such as GTPases, Annexins, and Rab GTPases facilitate endosomal processes and vesicle trafficking. Glycoproteins like β-galactosidase improve the exosome-targeting accuracy [48,49,50,51,52,53,54,55,56,57]. Exosomes also exhibit abundant nucleic acids, indicating an active sorting mechanism during their biogenesis [58], such as DNA, mRNA, and non-coding RNA (ncRNA) species [57,59]. MicroRNAs (miRNAs) stand out as one of the most abundant RNA species in exosomes, playing diverse roles in biological processes that are especially relevant to cancer, such as exocytosis, hematopoiesis, and angiogenesis, contributing to exosome-mediated cellular communication. Additional exosomal RNA species, like long ncRNA (lncRNA), circular RNAs (circRNAs), or small nuclear RNA, also impact biological processes, particularly influencing tumor development [60,61]. Exosomes affect target cells by binding to plasma membrane receptors or internalizing and releasing their contents, altering cellular processes and metabolism [45,46]. Current evidence suggests the selective packaging of ECV cargo, as shown by significant protein and RNA level variability compared to parental cells [62,63]. While the exact cargo-sorting mechanisms are unclear, RNA-binding proteins, Rab GTPases, and post-translational modifications, like ubiquitination and phosphorylation, are implicated [64]. Factors such as endoplasmic reticulum stress or phenotypic activation can influence ECV abundance and composition [65]. Current research focuses on the potential applications of these exosomal components as non-invasive biomarkers for disease diagnosis and prognosis.

3. The Role of Exosomes/ECVs in Oncogenesis

ECVs/exosomes play a critical role in the oncogenic process, facilitating the transfer of nucleic acids and proteins that disrupt cellular homeostasis and stimulate cancer initiation, progression, and metastasis. ECVs can carry oncogenic signatures that have the potential to transform recipient cells by altering gene expression and inducing malignant transformations [24,66,67].
Exosomes modulate immune responses, facilitating tumor cell evasion of immune surveillance and promoting metastatic spread. ECVs can transport immunosuppressive molecules that inhibit cytotoxic T cells and natural killer cells, allowing tumor cells to proliferate unchecked. Exosomes can also enhance metastasis by restructuring the extracellular matrix, which enables tumor cells to invade adjacent tissues and migrate to distant organs. Additionally, they play a vital role in the horizontal transfer of drug-resistance traits among cancer cell populations, spreading a chemoresistance that makes treatment more challenging. Clinically, exosomes can be extracted from body fluids like blood or urine and have the potential to monitor cancer non-invasively. The molecular composition of exosomes reflects the pathological state of their cells of origin, providing insights that are crucial in early detection, tracking disease progression, or adjusting therapeutic strategies. Through the analysis of exosomal biomarkers, clinicians can identify specific molecular signatures indicative of cancer presence, evaluate the aggressiveness of the disease, identify drug resistance, and monitor therapeutic response. This capability is essential in implementing personalized treatment plans that optimize therapy effectiveness and improve overall patient prognosis, making exosomes a cornerstone of modern oncological research and treatment strategies [24,48,66,67,68,69]. Table 1 aggregates the changes in exosomal ncRNA levels across various cancer types, revealing how these molecules could serve as biomarkers for diagnosis, prognosis, and treatment monitoring, particularly highlighting the extensive range of applications in diverse cancer contexts.

3.1. Hepatic-Cell-Derived ECVs: Cargo and Functions

Approximately 80% of the liver’s volume is made up of hepatocytes, which are crucial in physiological processes, while 6.5% consists of non-parenchymal cells, like liver sinusoidal endothelial cells (LSECs), hepatic stellate cells (HSCs), cholangiocytes, and Kupffer cells. Minority cell populations support hepatocytes and maintain the hepatic environment. The liver’s lobular structure promotes effective bidirectional intercellular communication and molecular information transfer through ECVs (Figure 2). For example, hepatocyte-derived ECVs carry arginase-1, which modulates endothelial cell function, and sphingosine-1-phosphate, which promotes liver regeneration. LSEC-derived ECVs modulate hepatic stellate cell activity, and HSC-derived ECVs may facilitate HCC progression. Cholangiocyte-derived ECVs affect bile acid homeostasis and promote healing. This encapsulates the varied currently known roles and cargo of hepatic-cell-derived ECVs in liver function and disease [93,94,95,96,97,98,99,100,101].
In addition to playing a direct role in HCC, ECVs from hepatocytes and adipocytes carry specific cargoes that enhance steatosis and immune activation, driving the progression of chronic liver diseases like non-alcoholic fatty liver disease and alcoholic liver disease and ultimately increasing the downstream risk for HCC [102]. For example, hepatocyte-derived ECVs contain miRNAs such as miRNA-122, miRNA-192, and miRNA-128-3p, as well as mitochondrial DNA, influencing inflammation and metabolic dysregulation in non-alcoholic liver disease [103,104]. In alcoholic liver disease, hepatocyte-derived ECVs carry CD40 ligand and mitochondrial DNA, promoting inflammation and immune cell activation [105]. However, adipocyte-derived ECVs carry miRNA-99b target hepatocytes to promote steatosis [106]. Additionally, circulating ECVs in HCC display altered expression of surface markers, including Annexin V, EpCAM, ASGR1, and CD133, offering a panel of markers to distinguish HCC from cholangiocarcinoma and other malignancies [107,108].

3.2. Exosomes in HCC Initiation, Progression, Metastasis, and Angiogenesis

In HCC, ECVs, particularly exosomes, play a fundamental role in initiation, progression, and metastasis. These vesicles facilitate complex signal transductions within the tumor microenvironment, significantly enhancing cellular communication between tumor cells and surrounding non-tumor cells. ECVs transport a variety of bioactive molecules, including miRNAs and proteins, which are instrumental in promoting cellular transformations, inflammatory responses, and adaptive mechanisms essential to tumor survival and expansion. Through their cargo, ECVs upregulate inflammatory cytokines and support adaptive responses under hypoxic conditions, contributing to tumor growth and the spread of cancer cells. They also induce critical processes such as epithelial–mesenchymal transition (EMT) and manipulate the immune landscape, enhancing the tumor’s invasiveness and capacity to evade immune detection [38,109]. Additionally, the acidic microenvironment in HCC further stimulates ECVs to strengthen the expression of miRNAs that promote cell proliferation and invasion, intensifying the aggressiveness of cancer [110]. Table 2 contains selected examples and emphasizes the various roles of ECVs in the context of HCC.

3.3. ECVs and Tumor Microenvironment

ECVs, including exosomes, are critical mediators within the tumor microenvironment, which is essential for tumor progression and metastasis. In HCC, the tumor microenvironment often becomes acidic and hypoxic, influencing the behavior of ECVs. This acidic environment arises due to inadequate perfusion in early tumors, leading to hypoxia and a reliance on anaerobic metabolism, which elevates lactate production and acidifies the tumor microenvironment [131]. This metabolic reprogramming, known as the “Warburg effect”, occurs even in the presence of sufficient oxygen. Due to these acidic conditions, ECV levels increase and enhance the proliferation, migration, and invasion of recipient cells [132]. Moreover, hypoxia modulates the expression of cell surface receptors and ceramides through hypoxia-inducible factors, further facilitating tumor metastasis [133,134].
ECVs and various non-immune cells in the tumor microenvironment, such as cancer-associated fibroblasts (CAFs), endothelial cells, and adipocytes, play a crucial role in tumor progression and metastasis. CAFs, arising from diverse cell origins, including fibroblasts and mesenchymal stem cells, are pivotal in the microenvironment, as they deposit extracellular matrix proteins and facilitate tumor invasion. Studies have shown that ECVs released by highly metastatic HCC cells contain miRNA-1247-3p, which can transform normal fibroblasts into CAFs, enhancing metastasis through the secretion of pro-inflammatory cytokines. Conversely, CAF-derived ECVs with reduced levels of miRNA-150-3p have been found to suppress the migration and invasion of HCC cells [135,136]. Cargo from endothelial-cell-derived ECVs facilitate angiogenesis, enhancing HCC proliferation and metastasis [86,120,122,137,138]. Additionally, adipocytes within the tumor microenvironment, particularly cancer-associated adipocytes, contribute to tumor progression by creating a hypoxic environment, promoting inflammation, and remodeling the extracellular matrix. These interactions between ECVs and the tumor microenvironment highlight the complexity of HCC pathogenesis, emphasizing the need for targeted therapeutic strategies. Moreover, ECVs’ role within the tumor microenvironment is crucial in advancing both cancer treatment and diagnostics.

3.4. Diagnostic Biomarkers in HCC

Due to the absence of reliable biomarkers, the early diagnosis of HCC is challenging, with most cases identified at advanced stages [34]. There is growing interest in potentially using “liquid biopsies” for the early detection of HCC [139,140]. Although several hypermethylated target genes identified in circulating cell-free DNA have been shown to be specifically associated with HCC, their expression in the peripheral blood is very low, particularly in the setting of early-stage disease [139]. Non-coding microRNAs and long non-coding RNAs, which play regulatory roles in various diseases and cancers, have also been investigated as potential biomarkers for HCC. Although their utility is somewhat limited due to differences across ethnic populations and underlying etiologies of HCC, studies have suggested that when used in combination with each other, as well as with AFP, they can show an excellent diagnostic performance (i.e., area under the curve (AUC) > 90%) particularly when enriched within exosomes (rather than when detected in exosome-depleted serum fractions) [141,142,143,144].
ECVs are promising diagnostic markers for cancer due to their lipid bilayer, which preserves crucial biomolecules and ensures stability in bodily fluids, enabling minimally invasive and more reliable detection [145]. This resilience ensures that both fresh and long-term-stored exosome samples maintain important tumor information for analysis [67,146,147,148].
Exosomes in HCC have potential clinical applications, as they promote immune escape, angiogenesis, metastasis, and tumor invasion. They can also confer drug resistance and modulate immunotherapy responses. Exosomes may serve as biomarkers for detecting and monitoring HCC, highlighting their relevance to targeted therapies and personalized medicine (Figure 3). In addition to total circulating ECV markers, specific cell membrane proteins can integrate into secreted ECV membranes [149]. These cell-type-specific surface proteins aid in the immunoaffinity-based isolation of ECVs from particular cells or tissues, enhancing disease biomarker detection sensitivity and specificity. Goetzl et al. have pioneered a novel method in the field of non-invasive biomarkers by isolating fetal central-nervous-system-derived exosomes from maternal blood. This innovative technique enables the detection and characterization of fetal brain injuries through a non-invasive approach, significantly advancing prenatal diagnostics and monitoring [150,151,152,153]. Similarly, research has demonstrated the efficacy of using asialoglycoprotein receptor 1 (ASGR1) to purify hepatocyte-derived exosomes, significantly improving liver disease biomarker detection [154]. In the context of HCC, isolating HCC-derived ECVs is critical in developing precise biomarkers, offering a targeted approach compared to total circulating ECVs. Mass spectrometry of exosomal proteins from HCC cell lines has identified approximately 1400 proteins that facilitate intercellular communication and correlate with clinical parameters, such as tumor size, TNM stage, portal vein tumor thrombosis, and overall survival. This targeted isolation provides superior diagnostic and prognostic capabilities compared to conventional biomarkers like alpha-fetoprotein (AFP), enhancing the specificity and sensitivity of disease detection and enabling more effective personalized treatment strategies for HCC patients [155,156]. Also, it has been shown that the quantity of serum ECVs notably increases during the cirrhotic stage and early stages of HCC compared to healthy liver tissue [157,158], suggesting a potential role of HCC-derived ECVs in the early detection of HCC [148].
Lipids play a dual role in exosomes. They act as structural components of the exosomal membrane and protect the cargo from peripheral degradation. They are essential contributors to exosome formation and release. It is common to see enrichment of specific lipids in ECVs, creating a “lipid signature” that could be used for diagnosis/prognosis in HCC [159,160]. For example, HepG2/C3a-cell-derived ECVs have specific lipid profiles with higher free cholesterol, ceramides, phosphatidylserine, and sphingomyelin but lower phosphoinositide levels [161,162,163]. A clinical study showed significant differences in lipid profiles between HCC and non-HCC patients, identifying higher levels of sphingosines, dilysocardiolipins, and (O-acyl)-1-hydroxy fatty acids with HCC, highlighting their potential as non-invasive diagnostic biomarkers [164].
Several studies have highlighted the potential of exosomal miRNAs as early diagnostic biomarkers from HCC cells. Exosomal miRNAs offer superior stability and reduced susceptibility to interference from other blood components, enhancing their biomarker potential compared to serum-free miRNAs [165,166,167]. Hyo et al. identified exosomal miRNA-10b-5p as a promising biomarker (AUC, 0.934; sensitivity, 90.7%; specificity, 75.0%; cutoff, 1.8-fold). Another study advocated for the combination of exosomal miRNA-466-5p and miRNA-4746-5p, achieving an AUC of 0.947 (CI, 0.889–0.980; sensitivity, 81.8%; specificity, 91.7%) [167,168,169]. Decreased miRNA-638 levels in HCC patient serum correlate with adverse tumor characteristics, while elevated levels correlate with improved survival [170]. Additionally, exosomal miRNA-320d levels in serum samples could be used to distinguish HCC patients from healthy controls. Decreased exosomal miRNA-320d levels were associated with advanced tumor stage and positive lymph node metastasis and, therefore, with shorter overall and disease-free survival, indicating poor prognosis in HCC [171].
While the studies on exosomal DNA in HCC are limited, researchers are currently focusing on its potential in tumor diagnosis [38,172]. Yan et al. discovered a significant elevation in the cell-free DNA levels of HCC patients compared to non-HCC patients. The isolation and analysis of disease-specific ECVs represent significant advancements in biomarker research, improving the accuracy and efficacy of non-invasive diagnostics and personalized medicine.

3.5. ECVs in Immunotherapy and Therapy Resistance

Exosomes and ECVs significantly influence HCC therapy through their dual roles in immune modulation and drug resistance. These vesicles regulate immune responses that are crucial to personalized cancer treatment, notably via interactions with the PD-1/PD-L1 axis [173,174]. Additionally, ECVs can act as precise drug delivery vehicles, enhancing the targeting and dosage customization of treatments like Doxorubicin and Paclitaxel, thus reducing toxicity while improving effectiveness [175,176,177,178,179].
Beyond PD-1/PD-L1 inhibition therapy, ECVs also impact the efficacy of other immune checkpoint inhibitors. Tumor-derived ECVs can carry ligands for these checkpoints, modulating the immune environment and contributing to immune evasion by tumors [180,181,182].
Although primarily used for hematologic malignancies, recently, CAR T-cell therapy has been explored for solid tumors, like HCC. ECVs can modulate the tumor microenvironment, enhancing CAR T-cell persistence and functionality [183]. For instance, mesenchymal-stem-cell-derived ECVs have been shown to enhance CAR T-cell anti-tumor activity by modulating the immune environment. Additionally, ECVs from HCC cells can carry immunosuppressive molecules, such as TGF-β and IL-10, inhibiting CAR T-cell activity [182,184,185]. Engineering ECVs to carry pro-inflammatory cytokines or immune checkpoint inhibitors can potentially counteract this suppression and enhance the efficacy of CAR T-cell therapy.
Dendritic-cell-derived ECVs are particularly promising as immunotherapeutic agents. These ECVs contain immunostimulatory components, functioning as antigen-presenting entities. They can promote an immune-cell-dependent tumor rejection response by enhancing the activation of CD8+ T cells and remodeling the tumor microenvironment. Tumor-derived ECVs also stimulate anti-tumor immune responses and deliver tumor-associated antigens to dendritic cells, enabling efficient antigen presentation on major histocompatibility complex (MHC) molecules to T cells. Inspired by CAR T-cell therapy, researchers have used dendritic-cell-derived ECVs to present MHC–antigen complexes, triggering effective anti-tumor immunity. These engineered ECVs can offer an effective alternative to CAR T cells by promoting T-cell binding to cancer cells [183,186].
Moreover, engineered ECVs are emerging as a promising therapeutic strategy for tumor immunomodulation. For example, exoASO-STAT6 uses ECVs to deliver antisense oligonucleotides that disrupt STAT6 signaling in tumor-associated macrophages. This method has shown strong anti-tumor activity in preclinical models and is currently being tested in clinical trials for advanced HCC [187,188,189].
Another critical function of ECVs is mediating resistance to therapies, particularly chemotherapy. They transport molecules, such as specific proteins or RNA, that induce drug resistance, spreading it throughout the tumor. Identifying biomarkers within exosomes that signal resistance allows clinicians to develop tailored treatment plans. These plans might include agents that sensitize tumors to intended therapies, boosting the efficacy of standard treatments without increasing side effects [84,190,191,192,193,194,195].
Exosomes’ capability to carry both water-soluble and lipid-soluble drugs highlights their potential to expand the effectiveness of various cancer therapies. Their versatility and compatibility with biological systems make them valuable in precision medicine, aiming to customize cancer treatments to individual patient profiles for better outcomes [196,197].
Moreover, ECVs have the capacity to enhance and modulate immune responses, positioning them as a promising strategy for novel vaccine formulations. ECVs can potentially activate granulocytes or natural killer cells and interact with CD8, CD4, and B cells, eliciting antigen-specific immune responses. The combination of ECVs with antigens may induce a humoral immune response comparable to that elicited by the antigen alone. This finding suggests that ECVs could serve as vaccine adjuvants, enhancing the efficacy of vaccines [187,188,198].
Recent clinical trials by Escudier et al. and Morse et al. have focused on dendritic-cell-derived exosomes, demonstrating their potential in advancing cancer therapies. These studies show promising results in terms of both safety and efficacy. The positive outcomes indicate the feasibility of integrating exosome-based approaches into standard cancer treatment protocols, leading to more personalized and effective strategies [196,197,199]. Table 3 provides additional details on the role of ECVs in enhancing immunotherapy and managing therapy resistance, showcasing their multifaceted contributions to improving HCC treatment. Exosomes and ECVs are crucial in advancing HCC therapy. Their functions in immune modulation, drug delivery, and overcoming resistance position them at the forefront of personalized cancer treatment strategies, with ongoing research and clinical trials continually revealing their full potential.

4. The Molecular Basis of Circadian Rhythms in Mammals

Mammals synchronize their circadian rhythms primarily with the light–dark cycles in their environment, a process mediated by ocular photoreception that relays signals to the suprachiasmatic nucleus of the hypothalamus. This region coordinates the synchronization of circadian clocks across the body’s various tissues. Peripheral clocks are entrained by signals such as humoral cues, metabolic factors, and body temperature fluctuations [201,202,203]. At the molecular level, the circadian clock is driven by autoregulatory transcription–translation feedback loops (TTFLs) involving transcription factors like brain and muscle ARNT-like 1 (BMAL1) and circadian locomotor output cycles kaput (CLOCK). These proteins form the CLOCK-BMAL1 heterodimer that binds to E-Box sequences, promoting the expression of clock-regulated genes, including Period (PER) and Cryptochrome Circadian Regulator (CRY). PER and CRY proteins inhibit BMAL1 activity, and their stability is regulated by ubiquitin ligases and kinases, establishing a new oscillatory cycle. Additional regulators such as REV-ERBs and retinoic acid receptor-related orphan receptors create another feedback loop by repressing or activating BMAL1 expression, respectively [204,205] (Figure 4). Other molecular oscillators can also function independently of the transcription-based clock in various species [201,206].
Circadian disruptions stem from environmental, genetic, and pathobiological factors. They influence the body’s internal clocks, disturbing critical physiological functions, such as sleep, alertness, motor skills, body temperature regulation, urinary system functionality, hormone secretion, immune responses, cytokine release, and cell cycle progression [207,208,209]. Shift work, jet lag, exposure to artificial light at night, irregular meal timings, alcohol consumption, and late-night physical activities are the main environmental factors contributing to circadian misalignment [209]. Genetic mutations in circadian clock genes and neurodevelopmental genetic differences further disrupt circadian function, increasing the risk of various diseases, including cancer [12,14,205,210,211]. Aging, obesity, hyperglycemia, and inflammatory states can exacerbate the dysregulation of circadian rhythmicity, augmenting cancer risk [212,213,214].

4.1. Circadian Regulation of ECVs

Multiple lines of evidence support the circadian clock’s influence on intercellular communication via ECVs, particularly exosomes. Rhythmic gene expression and protein abundance indirectly affect the temporal-specific loading of proteins in small ECVs, while the circadian clock directly governs the abundance of targeted cargo proteins in exosomes through the controlled expression of sorting proteins in the endosomal pathway. Studies have shown that ECV quantity exhibits time-dependent changes, indicating circadian variation [215], while the circadian clock directly influences the cargo content of exosomes [200]. Additionally, disruptions in circadian rhythms, such as those induced by night shift work, can alter the exosomal cargo, impacting metabolic health [216]. Plasma ECVs display dynamic changes in size distribution throughout the day, with implications for intercellular communication [217]. Overall, the circadian regulation of ECV characteristics, including size, concentration, and cargo composition, underscores the critical influence of the circadian clock in ECV biology for diagnostics and therapeutics. These rhythmic changes, governed by the circadian clock, have broad implications for intercellular communication and physiological processes, including those relevant to cancer. Understanding the role of the circadian clock in shaping ECV behavior in cancer contexts is crucial for developing time-sensitive strategies to diagnose, monitor, and treat various malignancies, including HCC, by optimizing treatment efficacy and patient outcomes. The impact of circadian rhythms on exosome secretion also suggests that aligning therapeutic interventions with these natural cycles could enhance treatment effectiveness and reduce adverse effects [8,200].
Table 4 summarizes studies on circadian influence on ECVs, showing rhythmic variations in size, concentration, and cargo composition.

4.2. Circadian Clock and HCC

Liver metabolism is intricately governed by circadian rhythms, adjusting to changes in feeding times and dietary patterns [222,223,224,225,226]. Central to this regulation are crucial circadian genes such as CRY, BMAL1, and CLOCK, which play pivotal roles in managing glucose levels and fat metabolism [227,228]. Disruptions in the liver’s internal clock, whether from genetic factors or external influences like jet lag, significantly affect metabolic processes, including bile acid regulation. Studies link circadian rhythm disruptions to increased cancer risk, with abnormal gene expression being common in tumors [84,217,229]. Night shifts and rotating work schedules are associated with higher cancer incidence and were recognized as a probable carcinogen by the International Agency for Research on Cancer in 2007, which was reaffirmed in 2019 [230]. Circadian clocks regulate key cellular functions like growth, apoptosis, and DNA repair, impacting tumor behavior [14,205,231,232,233,234,235]. The disruption of circadian rhythms due to chronic jet lag has been linked to accelerated liver carcinogenesis, as well as increased susceptibility to non-alcoholic fatty liver disease, leading to the spontaneous development of HCC [236]. Recent findings have linked variations in circadian clock genes with survival rates and clinical outcomes in HCC patients [237]. The development of small-molecule modulators targeting the core circadian clock offers a new promising approach in cancer therapy, potentially leading to innovative treatments [238,239,240]. Research has consistently underscored the role of clock genes in the molecular mechanisms of HCC [241], driving focused efforts to develop therapeutic strategies that target these proteins to effectively treat HCC [241,242,243,244].

4.3. The Impact of the Circadian Clock on Cancer Progression via ECVs

Melatonin, a key signal of darkness, plays a vital role in regulating sleep–wake cycles and shows promise in treating conditions such as sleep disorders and jet lag, as well as enhancing cancer therapies by improving the effects of chemotherapy [245,246]. Melatonin increases the properties of exosomes, potentially enhancing their therapeutic efficacy, such as in reducing inflammatory factors and immune evasion markers like PD-L1 in cancer therapy.
Cheng et al. observed a suppression of PD-L1 expression in macrophages co-cultured with exosomes from HCC cells treated with 0.1mM melatonin, while they observed an increase in PD-L1 expression and cytokine levels in macrophages co-cultured with untreated HCC cells. This led to the conclusion that melatonin-treated exosomes effectively reduced PD-L1 expression and cytokine secretion. Therefore, manipulating circadian rhythms through exosomes could offer innovative strategies for combating inflammation and immune evasion in HCC, inhibiting STAT3 activation and potentially improving therapeutic outcomes for patients with this challenging disease [247].
In addition to the emerging evidence in HCC, there are additional data pointing to a more overarching role of circadian rhythm in cancers in general. The circadian clock regulator modulates tumorigenesis [248]. To be precise, BMAL1, an essential transcription factor regulating numerous clock target genes [249,250], promotes metastasis in colorectal cancer by enhancing exosome secretion, illustrating its crucial role in cancer progression tied to circadian regulation [17]. Research using a mouse model of nocturnal shift work showed changes in the intestinal flora and plasma ECV components affecting clock genes [251]. SIRT1, interacting with CLOCK-BMAL1, regulates PER2 and exosome secretion, impacting the tumor microenvironment and progression in breast and ovarian cancer [252,253,254,255,256,257,258], and is crucial in tumor dynamics and metastasis [259]. ECVs regulate key signaling pathways like GSK-3 and AMPK via non-coding RNAs, affecting the circadian regulators CRY and BMAL1/CLOCK [258,260,261,262]. Exosomes also modulate circadian gene expression through post-transcriptional mechanisms, playing a role in rhythmicity and offering therapeutic potential [9,263]. Additionally, exosomal miRNAs like miRNA-7239-3p from microglia influence circadian genes, impacting conditions such as glioma progression [264]. An interesting proteomic study on medulloblastoma-derived exosomes detected that the presence of proteins influenced by the circadian clock, such as transcription factors like HNF4A, can impact pathways associated with various malignancies. HNF4A, a circadian-regulated transcription factor, modulates metabolic processes and adjusts tissue-specific circadian networks by transrepressing CLOCK-BMAL1 [244,265,266]. In HCC, the fetal variant of P2-HNF4α, typically upregulated, significantly alters the expression of BMAL1, influencing cancer progression dynamics. The presence of these proteins in exosomes suggests that circadian-influenced exosomal proteins could serve as non-invasive biomarkers for early cancer detection. Table 5 summarizes a structured overview of selected circadian biology that intersects with cancer progression through the lens of ECV dynamics.

5. Conclusions

This review highlights the significant interplay between ECVs, especially exosomes, and the development and progression of HCC, as well as the potential clinical roles of ECVs in detection and treatment. Disruptions in circadian rhythms may alter ECV function, potentially initiating or exacerbating HCC. These vesicles facilitate crucial intercellular communication and may modify circadian rhythms in recipient cells, influencing disease progression.
Exosomal cargo-sorting mechanisms in HCC involve RNA-binding proteins, Rab GTPases, and post-translational modifications. For example, the overexpression of VpsA4, an ATPase essential to the ESCRT pathway, modifies exosomal miRNA levels in HCC cells [276]. Rab GTPases and RNA-binding proteins are also critical in exosome biogenesis and influence cell signaling and tumor progression [277]. Moreover, exosomal lipids are also essential in exosome biogenesis and function [278]. Further research into the sorting mechanisms of exosomal cargo is crucial. Understanding the roles of RNA-binding proteins, Rab GTPases, and post-translational modifications will enhance our comprehension of how exosomes influence disease processes. Additionally, the effect of circadian clock genes on the tumor microenvironment, particularly regarding immune cell infiltration and overall cancer progression, underscores the importance of exploring how circadian genes impact exosome-mediated communication.
ECVs facilitate intercellular communication through their diverse cargo. Quantitative proteomic analyses across various cell lines, including hepatocytes, have identified unique ECV protein profiles that can predict small changes in serum [279]. In addition, exosomal biomarkers, such as miRNAs and circRNAs, showed higher sensitivity and specificity than AFP, a traditional biomarker widely used in clinical practice for detecting HCC [34,51]. To date, several methods for exosome isolation have been developed to enhance precision and throughput, including microfluidics-based isolation, density gradient ultracentrifugation, immunoaffinity capture, size-exclusion chromatography, polymer-based precipitation, ultrafiltration, field-flow fractionation, and differential ultracentrifugation. Immunoaffinity capture techniques use antibodies targeting specific exosome markers, enabling selective isolation from specific cell types like hepatocytes [280,281].
Exosomal biomarkers are stable in bodily fluids and offer non-invasive detection methods, providing detailed insights into tumor dynamics, including growth, metastasis, and treatment responses [24]. However, despite these advantages, the clinical implementation of exosomal biomarkers faces several challenges. The heterogeneity of exosomes, derived from various cell types, leads to variability in their content and function, complicating the isolation of tumor-specific exosomes [56,282]. Current isolation methods, such as ultracentrifugation and immunoaffinity capture, vary in efficiency and specificity, underscoring the need for standardized protocols to ensure reproducibility and reliability in clinical settings [281]. Accurate quantification and characterization of exosomal biomarkers are challenging due to their small size and complex cargo, necessitating the development of more precise and sensitive analytical technologies [52]. Furthermore, extensive clinical trials and validation studies are required to establish the efficacy of exosomal biomarkers in routine clinical practice. Regulatory approval for new diagnostic tools based on exosomal biomarkers involves rigorous evaluation and adherence to standards [52,283]. Addressing these challenges can highlight the potential advantages of exosomal biomarkers and support their successful clinical implementation in HCC diagnosis and treatment [284].
Innovative techniques for non-invasive biomarkers, such as isolating cell-specific exosomes, could offer promising avenues for early disease detection and intervention. One study showed that employing ASGR1 to purify exosomes derived from hepatocytes improved the detection of liver disease biomarkers [154]. To further refine this technique, focusing on additional liver-specific proteins such as hepatocyte-specific antigens, liver-specific transport proteins, and liver fatty-acid-binding proteins could significantly enhance the precision and efficacy of these diagnostic tools.
Furthermore, aligning medical treatments with the patient’s body clock through chronotherapy or pharmacological manipulations of the circadian clock could retard tumor growth [205,285]. Ideally, insights from the circadian regulation of exosome release and composition should be considered to optimize treatment efficacy. Therefore, the time of blood sample collection should be considered covariable in the design of clinical studies. This parameter may promote insights into how the circadian clock influences the biology of cancer via exosomal proteins, which are crucial mediators in intercellular communication.
Understanding the complex interplay among exosomal components, cancer biology, and the circadian rhythm is essential. This relationship forms the basis of a rich field of study that promises to broaden our understanding of the mechanisms underlying malignancy and innovate diagnostic and therapeutic strategies. The ultimate goal is to leverage this knowledge to develop more personalized, timely, and effective treatment approaches, improving clinical outcomes for patients with HCC.
Future research should integrate these findings into clinical practice to enhance the precision and efficacy of HCC treatments. Leveraging ECVs for early disease detection, targeted drug delivery, and immune modulation in HCC provides significant advantages, including higher sensitivity and specificity in diagnostics, improved therapeutic outcomes, and reduced systemic toxicity compared to existing methods. However, addressing challenges such as exosome heterogeneity, isolation, and standardization is critical. Developing standardized protocols for exosome isolation and characterization, elucidating the mechanisms of ECV biogenesis and cargo sorting, and conducting comprehensive clinical trials are essential steps to validate the clinical utility of exosome-based therapies.

Author Contributions

All authors contributed their intellectual input, discussed the information, and made improvements to the manuscript. Conceptualization, B.F.; writing—original draft preparation, L.U.; writing—review and editing; L.G. and N.F.E., writing, supervising, editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Willms, E.; Johansson, H.J.; Mäger, I.; Lee, Y.; Blomberg, K.E.M.; Sadik, M.; Alaarg, A.; Smith, C.E.; Lehtiö, J.; EL Andaloussi, S.; et al. Cells release subpopulations of exosomes with distinct molecular and biological properties. Sci. Rep. 2016, 6, 22519. [Google Scholar] [CrossRef]
  2. Dhar, R.; Gorai, S.; Devi, A.; Muthusamy, R.; Alexiou, A.; Papadakis, M. Decoding of exosome heterogeneity for cancer theranostics. Clin. Transl. Med. 2023, 13, e1288. [Google Scholar] [CrossRef]
  3. Almeria, C.; Kreß, S.; Weber, V.; Egger, D.; Kasper, C. Heterogeneity of mesenchymal stem cell-derived extracellular vesicles is highly impacted by the tissue/cell source and culture conditions. Cell Biosci. 2022, 12, 51. [Google Scholar] [CrossRef]
  4. Ha, D.; Yang, N.; Nadithe, V. Exosomes as therapeutic drug carriers and delivery vehicles across biological membranes: Current perspectives and future challenges. Acta Pharm. Sin. B 2016, 6, 287–296. [Google Scholar] [CrossRef]
  5. Zhu, L.; Sun, H.-T.; Wang, S.; Huang, S.-L.; Zheng, Y.; Wang, C.-Q.; Hu, B.-Y.; Qin, W.; Zou, T.-T.; Fu, Y.; et al. Isolation and characterization of exosomes for cancer research. J. Hematol. Oncol. 2020, 13, 152. [Google Scholar] [CrossRef]
  6. Huda, M.N.; Nafiujjaman, M.; Deaguero, I.G.; Okonkwo, J.; Hill, M.L.; Kim, T.; Nurunnabi, M. Potential Use of Exosomes as Diagnostic Biomarkers and in Targeted Drug Delivery: Progress in Clinical and Preclinical Applications. ACS Biomater. Sci. Eng. 2021, 7, 2106–2149. [Google Scholar] [CrossRef]
  7. Kojima, S.; Shingle, D.L.; Green, C.B. Post-transcriptional control of circadian rhythms. J. Cell Sci. 2011, 124 Pt 3, 311–320. [Google Scholar] [CrossRef]
  8. Guo, J.; Cheng, P.; Yuan, H.; Liu, Y. The Exosome Regulates Circadian Gene Expression in a Posttranscriptional Negative Feedback Loop. Cell 2009, 138, 1236–1246. [Google Scholar] [CrossRef] [PubMed]
  9. Li, Z.; Li, Y.; Xu, X.; Gu, J.; Chen, H.; Gui, Y. Exosomes rich in Wnt5 improved circadian rhythm dysfunction via enhanced PPARγ activity in the 6-hydroxydopamine model of Parkinson’s disease. Neurosci. Lett. 2023, 802, 137139. [Google Scholar] [CrossRef] [PubMed]
  10. Hahn, K.; Sundar, I.K. Current Perspective on the Role of the Circadian Clock and Extracellular Matrix in Chronic Lung Diseases. Int. J. Environ. Res. Public Health 2023, 20, 2455. [Google Scholar] [CrossRef]
  11. Chen, W.-H.; Huang, Q.-Y.; Wang, Z.-Y.; Zhuang, X.-X.; Lin, S.; Shi, Q.-Y. Therapeutic potential of exosomes/miRNAs in polycystic ovary syndrome induced by the alteration of circadian rhythms. Front. Endocrinol. 2022, 13, 918805. [Google Scholar] [CrossRef]
  12. Sulli, G.; Lam, M.T.Y.; Panda, S. Interplay between Circadian Clock and Cancer: New Frontiers for Cancer Treatment. Trends Cancer 2019, 5, 475–494. [Google Scholar] [CrossRef]
  13. Altman, B.J.; Hsieh, A.L.; Sengupta, A.; Krishnanaiah, S.Y.; Stine, Z.E.; Walton, Z.E.; Gouw, A.M.; Venkataraman, A.; Li, B.; Goraksha-Hicks, P.; et al. MYC Disrupts the Circadian Clock and Metabolism in Cancer Cells. Cell Metab. 2015, 22, 1009–1019. [Google Scholar] [CrossRef]
  14. Fekry, B.; Eckel-Mahan, K. The circadian clock and cancer: Links between circadian disruption and disease Pathology. J. Biochem. 2022, 171, 477–486. [Google Scholar] [CrossRef]
  15. Verlande, A.; Masri, S. Circadian Clocks and Cancer: Timekeeping Governs Cellular Metabolism. Trends Endocrinol. Metab. 2019, 30, 445–458. [Google Scholar] [CrossRef]
  16. Fekry, B.; Ribas-Latre, A.; Baumgartner, C.; Mohamed, A.M.T.; Kolonin, M.G.; Sladek, F.M.; Younes, M.; Eckel-Mahan, K.L. HNF4α-Deficient Fatty Liver Provides a Permissive Environment for Sex-Independent Hepatocellular Carcinoma. Cancer Res. 2019, 79, 5860–5873. [Google Scholar] [CrossRef]
  17. Dong, P.; Wang, Y.; Liu, Y.; Zhu, C.; Lin, J.; Qian, R.; Hua, L.; Lu, C. BMAL1 induces colorectal cancer metastasis by stimulating exosome secretion. Mol. Biol. Rep. 2022, 49, 373–384. [Google Scholar] [CrossRef]
  18. Ortega-Campos, S.M.; Verdugo-Sivianes, E.M.; Amiama-Roig, A.; Blanco, J.R.; Carnero, A. Interactions of circadian clock genes with the hallmarks of cancer. Biochim. Biophys. Acta BBA Rev. Cancer 2023, 1878, 188900. [Google Scholar] [CrossRef]
  19. Duffy, M.J. Tumor markers in clinical practice: A review focusing on common solid cancers. Med. Princ. Pr. 2012, 22, 4–11. [Google Scholar] [CrossRef]
  20. Locker, G.Y.; Hamilton, S.; Harris, J.; Jessup, J.M.; Kemeny, N.; Macdonald, J.S.; Somerfield, M.R.; Hayes, D.F.; Bast, R.C., Jr. ASCO 2006 update of recommendations for the use of tumor markers in gastrointestinal cancer. J. Clin. Oncol. 2006, 24, 5313–5327. [Google Scholar] [CrossRef]
  21. He, C.-Z.; Zhang, K.-H.; Li, Q.; Liu, X.-H.; Hong, Y.; Lv, N.-H. Combined use of AFP, CEA, CA125 and CAl9-9 improves the sensitivity for the diagnosis of gastric cancer. BMC Gastroenterol. 2013, 13, 87. [Google Scholar] [CrossRef]
  22. Gupta, D.; Lis, C.G. Role of CA125 in predicting ovarian cancer survival—A review of the epidemiological literature. J. Ovarian Res. 2009, 2, 13. [Google Scholar] [CrossRef]
  23. Wong, C.H.; Chen, Y.C. Clinical significance of exosomes as potential biomarkers in cancer. World J. Clin. Cases 2019, 7, 171–190. [Google Scholar] [CrossRef]
  24. Kalluri, R.; LeBleu, V.S. The biology, function, and biomedical applications of exosomes. Science 2020, 367, eaau6977. [Google Scholar] [CrossRef]
  25. Krishnan, A.; Bhattacharya, B.; Mandal, D.; Dhar, R.; Muthu, S. Salivary exosomes: A theranostics secret of oral cancer—Correspondence. Int. J. Surg. 2022, 108, 106990. [Google Scholar] [CrossRef]
  26. Wang, X.; Tian, L.; Lu, J.; Ng, I.O. Exosomes and cancer—Diagnostic and prognostic biomarkers and therapeutic vehicle. Oncogenesis 2022, 11, 54. [Google Scholar] [CrossRef]
  27. Makler, A.; Asghar, W. Exosomal biomarkers for cancer diagnosis and patient monitoring. Expert. Rev. Mol. Diagn. 2020, 20, 387–400. [Google Scholar] [CrossRef]
  28. Hanjani, N.A.; Esmaelizad, N.; Zanganeh, S.; Gharavi, A.T.; Heidarizadeh, P.; Radfar, M.; Omidi, F.; MacLoughlin, R.; Doroudian, M. Emerging role of exosomes as biomarkers in cancer treatment and diagnosis. Crit. Rev. Oncol. Hematol. 2022, 169, 103565. [Google Scholar] [CrossRef]
  29. Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef]
  30. Anwanwan, D.; Singh, S.K.; Singh, S.; Saikam, V.; Singh, R. Challenges in liver cancer and possible treatment approaches. Biochim. Biophys. Acta BBA Rev. Cancer 2020, 1873, 188314. [Google Scholar] [CrossRef]
  31. National Comprehensive Cancer Nwtwork. NCCN Clinical Practice Guidelines in Oncology: Hepatobiliary Cancers; Version 1.2023; National Comprehensive Cancer Network: Plymouth Meeting, PA, USA, 2023; Available online: https://www.nccn.org/guidelines/guidelines-detail?category=1&id=1438.2023 (accessed on 10 June 2024).
  32. Singal, A.G.; Llovet, J.M.; Yarchoan, M.; Mehta, N.; Heimbach, J.K.; Dawson, L.A.; Jou, J.H.; Kulik, L.M.; Agopian, V.G.; Marrero, J.A.; et al. AASLD Practice Guidance on prevention, diagnosis, and treatment of hepatocellular carcinoma. Hepatology 2023, 78, 1922–1965. [Google Scholar] [CrossRef]
  33. Choi, D.T.; Kum, H.C.; Park, S.; Ohsfeldt, R.L.; Shen, Y.; Parikh, N.D.; Singal, A.G. Hepatocellular Carcinoma Screening Is Associated with Increased Survival of Patients with Cirrhosis. Clin. Gastroenterol. Hepatol. 2019, 17, 976–987.e4. [Google Scholar] [CrossRef]
  34. Yang, J.D.; Hainaut, P.; Gores, G.J.; Amadou, A.; Plymoth, A.; Roberts, L.R. A global view of hepatocellular carcinoma: Trends, risk, prevention and management. Nat. Rev. Gastroenterol. Hepatol. 2019, 16, 589–604. [Google Scholar] [CrossRef]
  35. Lok, A.S.; Sterling, R.K.; Everhart, J.E.; Wright, E.C.; Hoefs, J.C.; Di Bisceglie, A.M.; Morgan, T.R.; Kim, H.; Lee, W.M.; Bonkovsky, H.L.; et al. Des-γ-carboxy prothrombin and α-fetoprotein as biomarkers for the early detection of hepatocellular carcinoma. Gastroenterology 2010, 138, 493–502. [Google Scholar] [CrossRef]
  36. Pinyol, R.; Montal, R.; Bassaganyas, L.; Sia, D.; Takayama, T.; Chau, G.-Y.; Mazzaferro, V.; Roayaie, S.; Lee, H.C.; Kokudo, N.; et al. Molecular predictors of prevention of recurrence in HCC with sorafenib as adjuvant treatment and prognostic factors in the phase 3 STORM trial. Gut 2019, 68, 1065–1075. [Google Scholar] [CrossRef]
  37. Parikh, N.D.; Mehta, A.S.; Singal, A.G.; Block, T.; Marrero, J.A.; Lok, A.S. Biomarkers for the Early Detection of Hepatocellular Carcinoma. Cancer Epidemiol. Biomark. Prev. 2020, 29, 2495–2503. [Google Scholar] [CrossRef]
  38. Chen, W.; Mao, Y.; Liu, C.; Wu, H.; Chen, S. Exosome in Hepatocellular Carcinoma: An update. J. Cancer 2021, 12, 2526–2536. [Google Scholar] [CrossRef]
  39. Szabo, G.; Momen-Heravi, F. Extracellular vesicles in liver disease and potential as biomarkers and therapeutic targets. Nat. Rev. Gastroenterol. Hepatol. 2017, 14, 455–466. [Google Scholar] [CrossRef]
  40. Théry, C.; Zitvogel, L.; Amigorena, S. Exosomes: Composition, biogenesis and function. Nat. Rev. Immunol. 2002, 2, 569–579. [Google Scholar] [CrossRef]
  41. Edwards, K.A.; Leete, J.J.; Smith, E.G.; Quick, A.; Modica, C.M.; Wassermann, E.M.; Polejaeva, E.; Dell, K.C.; LoPresti, M.; Walker, P.; et al. Elevations in Tumor Necrosis Factor Alpha and Interleukin 6 from Neuronal-Derived Extracellular Vesicles in Repeated Low-Level Blast Exposed Personnel. Front. Neurol. 2022, 13, 723923. [Google Scholar] [CrossRef]
  42. Raposo, G.; Stoorvogel, W. Extracellular vesicles: Exosomes, microvesicles, and friends. J. Cell Biol. 2013, 200, 373–383. [Google Scholar] [CrossRef]
  43. Sheta, M.; Taha, E.A.; Lu, Y.; Eguchi, T. Extracellular Vesicles: New Classification and Tumor Immunosuppression. Biology 2023, 12, 110. [Google Scholar] [CrossRef]
  44. Pan, B.T.; Johnstone, R.M. Fate of the transferrin receptor during maturation of sheep reticulocytes in vitro: Selective externalization of the receptor. Cell 1983, 33, 967–978. [Google Scholar] [CrossRef]
  45. Gurung, S.; Perocheau, D.; Touramanidou, L.; Baruteau, J. The exosome journey: From biogenesis to uptake and intracellular signalling. Cell Commun. Signal. 2021, 19, 47. [Google Scholar] [CrossRef]
  46. Mulcahy, L.A.; Pink, R.C.; Carter, D.R. Routes and mechanisms of extracellular vesicle uptake. J. Extracell. Vesicles 2014, 3, 24641. [Google Scholar] [CrossRef]
  47. Mathieu, M.; Martin-Jaular, L.; Lavieu, G.; Théry, C. Specificities of secretion and uptake of exosomes and other extracellular vesicles for cell-to-cell communication. Nat. Cell Biol. 2019, 21, 9–17. [Google Scholar] [CrossRef]
  48. Paskeh, M.D.A.; Entezari, M.; Mirzaei, S.; Zabolian, A.; Saleki, H.; Naghdi, M.J.; Sabet, S.; Khoshbakht, M.A.; Hashemi, M.; Hushmandi, K.; et al. Emerging role of exosomes in cancer progression and tumor microenvironment remodeling. J. Hematol. Oncol. 2022, 15, 83. [Google Scholar] [CrossRef]
  49. Colombo, M.; Raposo, G.; Théry, C. Biogenesis, secretion, and intercellular interactions of exosomes and other extracellular vesicles. Annu. Rev. Cell Dev. Biol. 2014, 30, 255–289. [Google Scholar] [CrossRef]
  50. Lötvall, J.; Hill, A.F.; Hochberg, F.; Buzás, E.I.; Di Vizio, D.; Gardiner, C.; Gho, Y.S.; Kurochkin, I.V.; Mathivanan, S.; Quesenberry, P.; et al. Minimal experimental requirements for definition of extracellular vesicles and their functions: A position statement from the International Society for Extracellular Vesicles. J. Extracell. Vesicles 2014, 3, 26913. [Google Scholar] [CrossRef]
  51. Wang, X.; Huang, J.; Chen, W.; Li, G.; Li, Z.; Lei, J. The updated role of exosomal proteins in the diagnosis, prognosis, and treatment of cancer. Exp. Mol. Med. 2022, 54, 1390–1400. [Google Scholar] [CrossRef]
  52. Smolarz, M.; Pietrowska, M.; Matysiak, N.; Mielańczyk, Ł.; Widłak, P. Proteome profiling of exosomes purified from a small amount of human serum: The problem of co-purified serum components. Proteomes 2019, 7, 18. [Google Scholar] [CrossRef]
  53. Liang, Y.; Lehrich, B.M.; Zheng, S.; Lu, M. Emerging methods in biomarker identification for extracellular vesicle-based liquid biopsy. J. Extracell. Vesicles 2021, 10, e12090. [Google Scholar] [CrossRef]
  54. Wang, N.; Song, X.; Liu, L.; Niu, L.; Wang, X.; Song, X.; Xie, L. Circulating exosomes contain protein biomarkers of metastatic non-small-cell lung cancer. Cancer Sci. 2018, 109, 1701–1709. [Google Scholar] [CrossRef]
  55. Mazurov, D.; Barbashova, L.; Filatov, A. Tetraspanin protein CD 9 interacts with metalloprotease CD 10 and enhances its release via exosomes. FEBS J. 2013, 280, 1200–1213. [Google Scholar] [CrossRef]
  56. Malla, R.R.; Pandrangi, S.; Kumari, S.; Gavara, M.M.; Badana, A.K. Exosomal tetraspanins as regulators of cancer progression and metastasis and novel diagnostic markers. Asia Pac. J. Clin. Oncol. 2018, 14, 383–391. [Google Scholar] [CrossRef]
  57. Mashouri, L.; Yousefi, H.; Aref, A.R.; Ahadi, A.M.; Molaei, F.; Alahari, S.K. Exosomes: Composition, biogenesis, and mechanisms in cancer metastasis and drug resistance. Mol. Cancer 2019, 18, 75. [Google Scholar] [CrossRef]
  58. Nolte-’t Hoen, E.N.; Buermans, H.P.; Waasdorp, M.; Stoorvogel, W.; Wauben, M.H.; ’t Hoen, P.A. Deep sequencing of RNA from immune cell-derived vesicles uncovers the selective incorporation of small non-coding RNA biotypes with potential regulatory functions. Nucleic Acids Res. 2012, 40, 9272–9285. [Google Scholar] [CrossRef]
  59. Doyle, L.M.; Wang, M.Z. Overview of Extracellular Vesicles, Their Origin, Composition, Purpose, and Methods for Exosome Isolation and Analysis. Cells 2019, 8, 727. [Google Scholar] [CrossRef]
  60. Zhang, Y.; Liu, Y.; Liu, H.; Tang, W.H. Exosomes: Biogenesis, biologic function and clinical potential. Cell Biosci. 2019, 9, 19. [Google Scholar] [CrossRef]
  61. Ge, L.; Zhang, N.; Li, D.; Wu, Y.; Wang, H.; Wang, J. Circulating exosomal small RNAs are promising non-invasive diagnostic biomarkers for gastric cancer. J. Cell Mol. Med. 2020, 24, 14502–14513. [Google Scholar] [CrossRef]
  62. Li, X.; Chen, R.; Kemper, S.; Brigstock, D.R. Dynamic changes in function and proteomic composition of extracellular vesicles from hepatic stellate cells during cellular activation. Cells 2020, 9, 290. [Google Scholar] [CrossRef]
  63. Malhi, H. Emerging role of extracellular vesicles in liver diseases. Am. J. Physiol. Gastrointest. Liver Physiol. 2019, 317, G739–G749. [Google Scholar] [CrossRef]
  64. Kostallari, E.; Hirsova, P.; Prasnicka, A.; Verma, V.K.; Yaqoob, U.; Wongjarupong, N.; Roberts, L.R.; Shah, V.H. Hepatic stellate cell–derived platelet-derived growth factor receptor-alpha-enriched extracellular vesicles promote liver fibrosis in mice through SHP2. Hepatology 2018, 68, 333–348. [Google Scholar] [CrossRef]
  65. Dasgupta, D.; Nakao, Y.; Mauer, A.S.; Thompson, J.M.; Sehrawat, T.S.; Liao, C.-Y.; Krishnan, A.; Lucien, F.; Guo, Q.; Liu, M.; et al. IRE1A stimulates hepatocyte-derived extracellular vesicles that promote inflammation in mice with steatohepatitis. Gastroenterology 2020, 159, 1487–1503.e17. [Google Scholar] [CrossRef]
  66. Kalluri, R. The biology and function of exosomes in cancer. J. Clin. Investig. 2016, 126, 1208–1215. [Google Scholar] [CrossRef]
  67. Bebelman, M.P.; Smit, M.J.; Pegtel, D.M.; Baglio, S.R. Biogenesis and function of extracellular vesicles in cancer. Pharmacol. Ther. 2018, 188, 1–11. [Google Scholar] [CrossRef]
  68. Osaki, M.; Okada, F. Exosomes and their role in cancer progression. Yonago Acta Medica 2019, 62, 182–190. [Google Scholar] [CrossRef]
  69. Zhong, Y.; Li, H.; Li, P.; Chen, Y.; Zhang, M.; Yuan, Z.; Zhang, Y.; Xu, Z.; Luo, G.; Fang, Y.; et al. Exosomes: A New Pathway for Cancer Drug Resistance. Front. Oncol. 2021, 11, 743556. [Google Scholar] [CrossRef]
  70. Ogata-Kawata, H.; Izumiya, M.; Kurioka, D.; Honma, Y.; Yamada, Y.; Furuta, K.; Gunji, T.; Ohta, H.; Okamoto, H.; Sonoda, H.; et al. Circulating exosomal microRNAs as biomarkers of colon cancer. PLoS ONE 2014, 9, e92921. [Google Scholar] [CrossRef] [PubMed]
  71. Liu, T.; Liu, D.; Guan, S.; Dong, M. Diagnostic role of circulating MiR-21 in colorectal cancer: A update meta-analysis. Ann. Med. 2021, 53, 87–102. [Google Scholar] [CrossRef]
  72. Zhou, W.; Fong, M.Y.; Min, Y.; Somlo, G.; Liu, L.; Palomares, M.R.; Yu, Y.; Chow, A.; O’Connor, S.T.F.; Chin, A.R.; et al. Cancer-secreted miR-105 destroys vascular endothelial barriers to promote metastasis. Cancer Cell 2014, 25, 501–515. [Google Scholar] [CrossRef]
  73. Thind, A.; Wilson, C. Exosomal miRNAs as cancer biomarkers and therapeutic targets. J. Extracell. Vesicles 2016, 5, 31292. [Google Scholar] [CrossRef] [PubMed]
  74. Eichelser, C.; Stückrath, I.; Müller, V.; Milde-Langosch, K.; Wikman, H.; Pantel, K.; Schwarzenbach, H. Increased serum levels of circulating exosomal microRNA-373 in receptor-negative breast cancer patients. Oncotarget 2014, 5, 9650–9663. [Google Scholar] [CrossRef] [PubMed]
  75. Que, R.; Ding, G.; Chen, J.; Cao, L. Analysis of serum exosomal microRNAs and clinicopathologic features of patients with pancreatic adenocarcinoma. World J. Surg. Oncol. 2013, 11, 219. [Google Scholar] [CrossRef] [PubMed]
  76. Wang, J.; Chen, J.; Chang, P.; LeBlanc, A.; Li, D.; Abbruzzesse, J.L.; Frazier, M.L.; Killary, A.M.; Sen, S. MicroRNAs in Plasma of Pancreatic Ductal Adenocarcinoma Patients as Novel Blood-Based Biomarkers of Disease. Cancer Prev. Res. 2009, 2, 807–813. [Google Scholar] [CrossRef] [PubMed]
  77. Wong, T.-S.; Liu, X.-B.; Wong, B.Y.-H.; Ng, R.W.-M.; Yuen, A.P.-W.; Wei, W.I. Mature miR-184 as Potential Oncogenic microRNA of Squamous Cell Carcinoma of Tongue. Clin. Cancer Res. 2008, 14, 2588–2592. [Google Scholar] [CrossRef]
  78. Yamamoto, Y.; Kosaka, N.; Tanaka, M.; Koizumi, F.; Kanai, Y.; Mizutani, T.; Murakami, Y.; Kuroda, M.; Miyajima, A.; Kato, T.; et al. MicroRNA-500 as a potential diagnostic marker for hepatocellular carcinoma. Biomarkers 2009, 14, 529–538. [Google Scholar] [CrossRef] [PubMed]
  79. Yang, J.; Dong, W.; Zhang, H.; Zhao, H.; Zeng, Z.; Zhang, F.; Li, Q.; Duan, X.; Hu, Y.; Xiao, W. Exosomal microRNA panel as a diagnostic biomarker in patients with hepatocellular carcinoma. Front. Cell Dev. Biol. 2022, 10, 927251. [Google Scholar] [CrossRef] [PubMed]
  80. Qu, Z.; Wu, J.; Wu, J.; Ji, A.; Qiang, G.; Jiang, Y.; Jiang, C.; Ding, Y. Exosomal miR-665 as a novel minimally invasive biomarker for hepatocellular carcinoma diagnosis and prognosis. Oncotarget 2017, 8, 80666. [Google Scholar] [CrossRef]
  81. Sohn, W.; Kim, J.; Kang, S.H.; Yang, S.R.; Cho, J.-Y.; Cho, H.C.; Shim, S.G.; Paik, Y.-H. Serum exosomal microRNAs as novel biomarkers for hepatocellular carcinoma. Exp. Mol. Med. 2015, 47, e184. [Google Scholar] [CrossRef]
  82. Tomimaru, Y.; Eguchi, H.; Nagano, H.; Wada, H.; Kobayashi, S.; Marubashi, S.; Tanemura, M.; Tomokuni, A.; Takemasa, I.; Umeshita, K.; et al. Circulating microRNA-21 as a novel biomarker for hepatocellular carcinoma. J. Hepatol. 2012, 56, 167–175. [Google Scholar] [CrossRef]
  83. Park, N.J.; Zhou, H.; Elashoff, D.; Henson, B.S.; Kastratovic, D.A.; Abemayor, E.; Wong, D.T. Salivary microRNA: Discovery, Characterization, and Clinical Utility for Oral Cancer Detection. Clin. Cancer Res. 2009, 15, 5473–5477. [Google Scholar] [CrossRef] [PubMed]
  84. Zhang, P.-F.; Gao, C.; Huang, X.-Y.; Lu, J.-C.; Guo, X.-J.; Shi, G.-M.; Cai, J.-B.; Ke, A.-W. Cancer cell-derived exosomal circUHRF1 induces natural killer cell exhaustion and may cause resistance to anti-PD1 therapy in hepatocellular carcinoma. Mol. Cancer 2020, 19, 110. [Google Scholar] [CrossRef] [PubMed]
  85. Zhang, P.-F.; Wei, C.-Y.; Huang, X.-Y.; Peng, R.; Yang, X.; Lu, J.-C.; Zhang, C.; Gao, C.; Cai, J.-B.; Gao, P.-T.; et al. Circular RNA circTRIM33–12 acts as the sponge of MicroRNA-191 to suppress hepatocellular carcinoma progression. Mol. Cancer 2019, 18, 1–15. [Google Scholar] [CrossRef] [PubMed]
  86. Huang, X.-Y.; Huang, Z.-L.; Huang, J.; Xu, B.; Huang, X.-Y.; Xu, Y.-H.; Zhou, J.; Tang, Z.-Y. Exosomal circRNA-100338 promotes hepatocellular carcinoma metastasis via enhancing invasiveness and angiogenesis. J. Exp. Clin. Cancer Res. 2020, 39, 20. [Google Scholar] [CrossRef]
  87. Chen, W.; Quan, Y.; Fan, S.; Wang, H.; Liang, J.; Huang, L.; Chen, L.; Liu, Q.; He, P.; Ye, Y. Exosome-transmitted circular RNA hsa_circ_0051443 suppresses hepatocellular carcinoma progression. Cancer Lett. 2020, 475, 119–128. [Google Scholar] [CrossRef]
  88. Xian, J.; Su, W.; Liu, L.; Rao, B.; Lin, M.; Feng, Y.; Qiu, F.; Chen, J.; Zhou, Q.; Zhao, Z.; et al. Identification of three circular RNA cargoes in serum exosomes as diagnostic biomarkers of non–small-cell lung cancer in the Chinese population. J. Mol. Diagn. 2020, 22, 1096–1108. [Google Scholar] [CrossRef]
  89. Kang, Y.; You, J.; Gan, Y.; Chen, Q.; Huang, C.; Chen, F.; Xu, X.; Chen, L. Serum and serum exosomal CircRNAs hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896 as diagnostic biomarkers for lung adenocarcinoma. Front. Oncol. 2022, 12, 912246. [Google Scholar] [CrossRef]
  90. Luo, Y.; Ma, J.; Liu, F.; Guo, J.; Gui, R. Diagnostic value of exosomal circMYC in radioresistant nasopharyngeal carcinoma. Head. Neck 2020, 42, 3702–3711. [Google Scholar] [CrossRef]
  91. Xia, D.; Gu, X. Plasmatic exosome-derived circRNAs panel act as fingerprint for glioblastoma. Aging 2021, 13, 19575–19586. [Google Scholar] [CrossRef]
  92. He, Y.-D.; Tao, W.; He, T.; Wang, B.-Y.; Tang, X.-M.; Zhang, L.-M.; Wu, Z.-Q.; Deng, W.-M.; Zhang, L.-X.; Shao, C.-K.; et al. A urine extracellular vesicle circRNA classifier for detection of high-grade prostate cancer in patients with prostate-specific antigen 2–10 ng/mL at initial biopsy. Mol. Cancer 2021, 20, 96. [Google Scholar] [CrossRef] [PubMed]
  93. Royo, F.; Moreno, L.; Mleczko, J.; Palomo, L.; Gonzalez, E.; Cabrera, D.; Cogolludo, A.; Vizcaino, F.P.; Van-Liempd, S.; Falcon-Perez, J.M. Hepatocyte-secreted extracellular vesicles modify blood metabolome and endothelial function by an arginase-dependent mechanism. Sci. Rep. 2017, 7, 42798. [Google Scholar] [CrossRef] [PubMed]
  94. Nojima, H.; Freeman, C.M.; Schuster, R.M.; Japtok, L.; Kleuser, B.; Edwards, M.J.; Gulbins, E.; Lentsch, A.B. Hepatocyte exosomes mediate liver repair and regeneration via sphingosine-1-phosphate. J. Hepatol. 2016, 64, 60–68. [Google Scholar] [CrossRef] [PubMed]
  95. Wang, R.; Ding, Q.; Yaqoob, U.; de Assuncao, T.M.; Verma, V.K.; Hirsova, P.; Cao, S.; Mukhopadhyay, D.; Huebert, R.C.; Shah, V.H. Exosome adherence and internalization by hepatic stellate cells triggers sphingosine 1-phosphate-dependent migration. J. Biol. Chem. 2015, 290, 30684–30696. [Google Scholar] [CrossRef] [PubMed]
  96. Chen, L.; Charrier, A.; Zhou, Y.; Chen, R.; Yu, B.; Agarwal, K.; Tsukamoto, H.; Lee, L.J.; Paulaitis, M.E.; Brigstock, D.R. Epigenetic regulation of connective tissue growth factor by MicroRNA-214 delivery in exosomes from mouse or human hepatic stellate cells. Hepatology 2014, 59, 1118–1129. [Google Scholar] [CrossRef] [PubMed]
  97. Chen, L.; Chen, R.; Velazquez, V.M.; Brigstock, D.R. Fibrogenic signaling is suppressed in hepatic stellate cells through targeting of connective tissue growth factor (CCN2) by cellular or exosomal microRNA-199a-5p. Am. J. Pathol. 2016, 186, 2921–2933. [Google Scholar] [CrossRef] [PubMed]
  98. Zhang, X.; Chen, F.; Huang, P.; Wang, X.; Zhou, K.; Zhou, C.; Yu, L.; Peng, Y.; Fan, J.; Zhou, J.; et al. Exosome-depleted MiR-148a-3p derived from Hepatic Stellate Cells Promotes Tumor Progression via ITGA5/PI3K/Akt Axis in Hepatocellular Carcinoma. Int. J. Biol. Sci. 2022, 18, 2249–2260. [Google Scholar] [CrossRef] [PubMed]
  99. Li, X.; Liu, R.; Huang, Z.; Gurley, E.C.; Wang, X.; Wang, J.; He, H.; Yang, H.; Lai, G.; Zhang, L.; et al. Cholangiocyte-derived exosomal long noncoding RNA H19 promotes cholestatic liver injury in mouse and humans. Hepatology 2018, 68, 599–615. [Google Scholar] [CrossRef] [PubMed]
  100. Witek, R.P.; Yang, L.; Liu, R.; Jung, Y.; Omenetti, A.; Syn, W.K.; Choi, S.S.; Cheong, Y.; Fearing, C.M.; Agboola, K.M.; et al. Liver cell–derived microparticles activate hedgehog signaling and alter gene expression in hepatic endothelial cells. Gastroenterology 2009, 136, 320–330.e2. [Google Scholar] [CrossRef] [PubMed]
  101. Newman, L.A.; Muller, K.; Rowland, A. Circulating cell-specific extracellular vesicles as biomarkers for the diagnosis and monitoring of chronic liver diseases. Cell Mol. Life Sci. 2022, 79, 232. [Google Scholar] [CrossRef]
  102. Sung, S.; Kim, J.; Jung, Y. Liver-derived exosomes and their implications in liver pathobiology. Int. J. Mol. Sci. 2018, 19, 3715. [Google Scholar] [CrossRef] [PubMed]
  103. Wang, X.; Rao, H.; Liu, F.; Wei, L.; Li, H.; Wu, C. Recent Advances in Adipose Tissue Dysfunction and Its Role in the Pathogenesis of Non-Alcoholic Fatty Liver Disease. Cells 2021, 10, 3300. [Google Scholar] [CrossRef] [PubMed]
  104. Pan, X.; Zhang, Y. Hepatocyte nuclear factor 4α in the pathogenesis of non-alcoholic fatty liver disease. Chin. Med. J. 2022, 135, 1172–1181. [Google Scholar] [CrossRef] [PubMed]
  105. Eguchi, A.; Yan, R.; Pan, S.Q.; Wu, R.; Kim, J.; Chen, Y.; Ansong, C.; Smith, R.D.; Tempaku, M.; Ohno-Machado, L.; et al. Comprehensive characterization of hepatocyte-derived extracellular vesicles identifies direct miRNA-based regulation of hepatic stellate cells and DAMP-based hepatic macrophage IL-1β and IL-17 upregulation in alcoholic hepatitis mice. J. Mol. Med. 2020, 98, 1021–1034. [Google Scholar] [CrossRef] [PubMed]
  106. Keinicke, H.; Sun, G.; Mentzel, C.M.J.; Fredholm, M.; John, L.M.; Andersen, B.; Raun, K.; Kjaergaard, M. FGF21 regulates hepatic metabolic pathways to improve steatosis and inflammation. Endocr. Connect. 2020, 9, 755–768. [Google Scholar] [CrossRef]
  107. Julich-Haertel, H.; Urban, S.K.; Krawczyk, M.; Willms, A.; Jankowski, K.; Patkowski, W.; Kruk, B.; Krasnodębski, M.; Ligocka, J.; Schwab, R.; et al. Cancer-associated circulating large extracellular vesicles in cholangiocarcinoma and hepatocellular carcinoma. J. Hepatol. 2017, 67, 282–292. [Google Scholar] [CrossRef] [PubMed]
  108. Arbelaiz, A.; Azkargorta, M.; Krawczyk, M.; Santos-Laso, A.; Lapitz, A.; Perugorria, M.J.; Erice, O.; Gonzalez, E.; Jimenez-Agüero, R.; La Casta, A.; et al. Serum extracellular vesicles contain protein biomarkers for primary sclerosing cholangitis and cholangiocarcinoma. Hepatology 2017, 66, 1125–1143. [Google Scholar] [CrossRef]
  109. Chen, L.; Guo, P.; He, Y.; Chen, Z.; Chen, L.; Luo, Y.; Qi, L.; Liu, Y.; Wu, Q.; Cui, Y.; et al. HCC-derived exosomes elicit HCC progression and recurrence by epithelial-mesenchymal transition through MAPK/ERK signalling pathway. Cell Death Dis. 2018, 9, 513. [Google Scholar] [CrossRef] [PubMed]
  110. Cao, L.-q.; Yang, X.-w.; Chen, Y.-b.; Zhang, D.-w.; Jiang, X.-F.; Xue, P. Exosomal miR-21 regulates the TETs/PTENp1/PTEN pathway to promote hepatocellular carcinoma growth. Mol. Cancer 2019, 18, 1–14. [Google Scholar] [CrossRef]
  111. Xue, X.; Wang, X.; Zhao, Y.; Hu, R.; Qin, L. Exosomal miR-93 promotes proliferation and invasion in hepatocellular carcinoma by directly inhibiting TIMP2/TP53INP1/CDKN1A. Biochem. Biophys. Res. Commun. 2018, 502, 515–521. [Google Scholar] [CrossRef]
  112. Verma, V.K.; Li, H.; Wang, R.; Hirsova, P.; Mushref, M.; Liu, Y.; Cao, S.; Contreras, P.C.; Malhi, H.; Kamath, P.S.; et al. Alcohol stimulates macrophage activation through caspase-dependent hepatocyte derived release of CD40L containing extracellular vesicles. J. Hepatol. 2016, 64, 651–660. [Google Scholar] [CrossRef]
  113. Liu, D.; Kang, H.; Gao, M.; Jin, L.; Zhang, F.; Chen, D.; Li, M.; Xiao, L. Exosome-transmitted circ_MMP2 promotes hepatocellular carcinoma metastasis by upregulating MMP2. Mol. Oncol. 2020, 14, 1365–1380. [Google Scholar] [CrossRef]
  114. Zhu, C.; Su, Y.; Liu, L.; Wang, S.; Liu, Y.; Wu, J. Circular RNA hsa_circ_0004277 Stimulates Malignant Phenotype of Hepatocellular Carcinoma and Epithelial-Mesenchymal Transition of Peripheral Cells. Front. Cell Dev. Biol. 2020, 8, 585565. [Google Scholar] [CrossRef]
  115. Chen, C.; Luo, F.; Liu, X.; Lu, L.; Xu, H.; Yang, Q.; Xue, J.; Shi, L.; Li, J.; Zhang, A.; et al. NF-kB-regulated exosomal miR-155 promotes the inflammation associated with arsenite carcinogenesis. Cancer Lett. 2017, 388, 21–33. [Google Scholar] [CrossRef]
  116. Wu, Q.; Zhou, L.; Lv, D.; Zhu, X.; Tang, H. Exosome-mediated communication in the tumor microenvironment contributes to hepatocellular carcinoma development and progression. J. Hematol. Oncol. 2019, 12, 53. [Google Scholar] [CrossRef]
  117. Gai, X.; Tang, B.; Liu, F.; Wu, Y.; Wang, F.; Jing, Y.; Huang, F.; Jin, D.; Wang, L.; Zhang, H. mTOR/miR-145-regulated exosomal GOLM1 promotes hepatocellular carcinoma through augmented GSK-3β/MMPs. J. Genet. Genom. 2019, 46, 235–245. [Google Scholar] [CrossRef]
  118. Leonardi, G.C.; Candido, S.; Cervello, M.; Nicolosi, D.; Raiti, F.; Travali, S.; Spandidos, D.A.; Libra, M. The tumor microenvironment in hepatocellular carcinoma. Int. J. Oncol. 2012, 40, 1733–1747. [Google Scholar]
  119. Tian, Y.; Li, S.; Song, J.; Ji, T.; Zhu, M.; Anderson, G.J.; Wei, J.; Nie, G. A doxorubicin delivery platform using engineered natural membrane vesicle exosomes for targeted tumor therapy. Biomaterials 2014, 35, 2383–2390. [Google Scholar] [CrossRef]
  120. Conigliaro, A.; Costa, V.; Lo Dico, A.; Saieva, L.; Buccheri, S.; Dieli, F.; Manno, M.; Raccosta, S.; Mancone, C.; Tripodi, M.; et al. CD90+ liver cancer cells modulate endothelial cell phenotype through the release of exosomes containing H19 lncRNA. Mol. Cancer 2015, 14, 155. [Google Scholar] [CrossRef]
  121. Huang, A.; Dong, J.; Li, S.; Wang, C.; Ding, H.; Li, H.; Su, X.; Ge, X.; Sun, L.; Bai, C.; et al. Exosomal transfer of vasorin expressed in hepatocellular carcinoma cells promotes migration of human umbilical vein endothelial cells. Int. J. Biol. Sci. 2015, 11, 961–969. [Google Scholar] [CrossRef]
  122. Moh-Moh-Aung, A.; Fujisawa, M.; Ito, S.; Katayama, H.; Ohara, T.; Ota, Y.; Yoshimura, T.; Matsukawa, A. Decreased miR-200b-3p in cancer cells leads to angiogenesis in HCC by enhancing endothelial ERG expression. Sci. Rep. 2020, 10, 10418. [Google Scholar] [CrossRef] [PubMed]
  123. Ye, L.; Zhang, Q.; Cheng, Y.; Chen, X.; Wang, G.; Shi, M.; Zhang, T.; Cao, Y.; Pan, H.; Zhang, L.; et al. Tumor-derived exosomal HMGB1 fosters hepatocellular carcinoma immune evasion by promoting TIM-1(+) regulatory B cell expansion. J. Immunother. Cancer 2018, 6, 145. [Google Scholar] [CrossRef]
  124. Robey, R.W.; Pluchino, K.M.; Hall, M.D.; Fojo, A.T.; Bates, S.E.; Gottesman, M.M. Revisiting the role of ABC transporters in multidrug-resistant cancer. Nat. Rev. Cancer 2018, 18, 452–464. [Google Scholar] [CrossRef] [PubMed]
  125. Sun, N.; Lee, Y.-T.; Zhang, R.Y.; Kao, R.; Teng, P.-C.; Yang, Y.; Yang, P.; Wang, J.J.; Smalley, M.; Chen, P.-J.; et al. Purification of HCC-specific extracellular vesicles on nanosubstrates for early HCC detection by digital scoring. Nat. Commun. 2020, 11, 4489. [Google Scholar] [CrossRef]
  126. Kooijmans, S.A.; Vader, P.; van Dommelen, S.M.; van Solinge, W.W.; Schiffelers, R.M. Exosome mimetics: A novel class of drug delivery systems. Int. J. Nanomed. 2012, 7, 1525–1541. [Google Scholar]
  127. Khamisipour, G.; Jadidi-Niaragh, F.; Jahromi, A.S.; Zandi, K.; Hojjat-Farsangi, M. Mechanisms of tumor cell resistance to the current targeted-therapy agents. Tumor Biol. 2016, 37, 10021–10039. [Google Scholar] [CrossRef]
  128. Xue, D.; Han, J.; Liu, Y.; Tuo, H.; Peng, Y. Current perspectives on exosomes in the diagnosis and treatment of hepatocellular carcinoma (review). Cancer Biol. Ther. 2021, 22, 279–290. [Google Scholar] [CrossRef]
  129. Liu, G.; Ouyang, X.; Sun, Y.; Xiao, Y.; You, B.; Gao, Y.; Yeh, S.; Li, Y.; Chang, C. The miR-92a-2-5p in exosomes from macrophages increases liver cancer cells invasion via altering the AR/PHLPP/p-AKT/β-catenin signaling. Cell Death Differ. 2020, 27, 3258–3272. [Google Scholar] [CrossRef]
  130. Wang, Y.; Wang, B.; Xiao, S.; Li, Y.; Chen, Q. miR-125a/b inhibits tumor-associated macrophages mediated in cancer stem cells of hepatocellular carcinoma by targeting CD90. J Cell Biochem 2019, 120, 3046–3055. [Google Scholar] [CrossRef]
  131. Wang, G.; Luo, G.; Zhao, M.; Miao, H. Significance of exosomes in hepatocellular carcinoma. Front. Oncol. 2022, 12, 1056379. [Google Scholar] [CrossRef]
  132. Tian, X.-P.; Wang, C.-Y.; Jin, X.-H.; Li, M.; Wang, F.-W.; Huang, W.-J.; Yun, J.-P.; Xu, R.-H.; Cai, Q.-Q.; Xie, D. Acidic microenvironment up-regulates exosomal miR-21 and miR-10b in early-stage hepatocellular carcinoma to promote cancer cell proliferation and metastasis. Theranostics 2019, 9, 1965–1979. [Google Scholar] [CrossRef] [PubMed]
  133. Vaupel, P.; Schmidberger, H.; Mayer, A. The Warburg effect: Essential part of metabolic reprogramming and central contributor to cancer progression. Int. J. Radiat. Biol. 2019, 95, 912–919. [Google Scholar] [CrossRef] [PubMed]
  134. Qian, D.; Xie, Y.; Huang, M.; Gu, J. Tumor-derived exosomes in hypoxic microenvironment: Release mechanism, biological function and clinical application. J. Cancer 2022, 13, 1685–1694. [Google Scholar] [CrossRef] [PubMed]
  135. Fang, T.; Lv, H.; Lv, G.; Li, T.; Wang, C.; Han, Q.; Yu, L.; Su, B.; Guo, L.; Huang, S.; et al. Tumor-derived exosomal miR-1247-3p induces cancer-associated fibroblast activation to foster lung metastasis of liver cancer. Nat. Commun. 2018, 9, 191. [Google Scholar] [CrossRef]
  136. Yugawa, K.; Yoshizumi, T.; Mano, Y.; Itoh, S.; Harada, N.; Ikegami, T.; Kohashi, K.; Oda, Y.; Mori, M. Cancer-associated fibroblasts promote hepatocellular carcinoma progression through downregulation of exosomal miR-150-3p. Eur. J. Surg. Oncol. 2021, 47, 384–393. [Google Scholar] [CrossRef]
  137. Li, S.; Qi, Y.; Huang, Y.; Guo, Y.; Huang, T.; Jia, L. Exosome-derived SNHG16 sponging miR-4500 activates HUVEC angiogenesis by targeting GALNT1 via PI3K/Akt/mTOR pathway in hepatocellular carcinoma. J. Physiol. Biochem. 2021, 77, 667–682. [Google Scholar] [CrossRef]
  138. Dai, W.; Wang, Y.; Yang, T.; Wang, J.; Wu, W.; Gu, J. Downregulation of exosomal CLEC3B in hepatocellular carcinoma promotes metastasis and angiogenesis via AMPK and VEGF signals. Cell Commun. Signal. 2019, 17, 1–17. [Google Scholar] [CrossRef]
  139. Wang, W.; Wei, C. Advances in the early diagnosis of hepatocellular carcinoma. Genes Dis. 2020, 7, 308–319. [Google Scholar] [CrossRef] [PubMed]
  140. Manea, I.; Iacob, R.; Iacob, S.; Cerban, R.; Dima, S.; Oniscu, G.; Popescu, I.; Gheorghe, L. Liquid biopsy for early detection of hepatocellular carcinoma. Front. Med. 2023, 10, 1218705. [Google Scholar] [CrossRef]
  141. Wang, Y.; Zhang, C.; Zhang, P.; Guo, G.; Jiang, T.; Zhao, X.; Jiang, J.; Huang, X.; Tong, H.; Tian, Y. Serum exosomal microRNAs combined with alpha-fetoprotein as diagnostic markers of hepatocellular carcinoma. Cancer Med. 2018, 7, 1670–1679. [Google Scholar] [CrossRef]
  142. Chen, S.; Zhang, Y.; Wu, X.; Zhang, C.; Li, G. Diagnostic Value of lncRNAs as Biomarker in Hepatocellular Carcinoma: An Updated Meta-Analysis. Can. J. Gastroenterol. Hepatol. 2018, 2018, 8410195. [Google Scholar] [CrossRef]
  143. Xu, H.; Chen, Y.; Dong, X.; Wang, X. Serum Exosomal Long Noncoding RNAs ENSG00000258332.1 and LINC00635 for the Diagnosis and Prognosis of Hepatocellular Carcinoma. Cancer Epidemiol. Biomark. Prev. 2018, 27, 710–716. [Google Scholar] [CrossRef] [PubMed]
  144. Fornari, F.; Ferracin, M.; Trerè, D.; Milazzo, M.; Marinelli, S.; Galassi, M.; Venerandi, L.; Pollutri, D.; Patrizi, C.; Borghi, A.; et al. Circulating microRNAs, miR-939, miR-595, miR-519d and miR-494, Identify Cirrhotic Patients with HCC. PLoS ONE 2015, 10, e0141448. [Google Scholar] [CrossRef]
  145. Yu, D.; Li, Y.; Wang, M.; Gu, J.; Xu, W.; Cai, H.; Fang, X.; Zhang, X. Exosomes as a new frontier of cancer liquid biopsy. Mol. Cancer 2022, 21, 56. [Google Scholar] [CrossRef]
  146. Weber, J.A.; Baxter, D.H.; Zhang, S.; Huang, D.Y.; Huang, K.H.; Lee, M.J.; Galas, D.J.; Wang, K. The microRNA spectrum in 12 body fluids. Clin. Chem. 2010, 56, 1733–1741. [Google Scholar] [CrossRef]
  147. Yoshioka, Y.; Konishi, Y.; Kosaka, N.; Katsuda, T.; Kato, T.; Ochiya, T. Comparative marker analysis of extracellular vesicles in different human cancer types. J. Extracell. Vesicles 2013, 2, 20424. [Google Scholar] [CrossRef] [PubMed]
  148. Wang, Z.; Chen, J.-Q.; Liu, J.-L.; Tian, L. Exosomes in tumor microenvironment: Novel transporters and biomarkers. J. Transl. Med. 2016, 14, 1–9. [Google Scholar] [CrossRef]
  149. Larssen, P.; Wik, L.; Czarnewski, P.; Eldh, M.; Löf, L.; Ronquist, K.G.; Dubois, L.; Freyhult, E.; Gallant, C.J.; Oelrich, J.; et al. Tracing cellular origin of human exosomes using multiplex proximity extension assays. Mol. Cell. Proteom. 2017, 16, 502–511. [Google Scholar] [CrossRef] [PubMed]
  150. Goetzl, L.; Darbinian, N.; Goetzl, E.J. Novel window on early human neurodevelopment via fetal exosomes in maternal blood. Ann. Clin. Transl. Neurol. 2016, 3, 381–385. [Google Scholar] [CrossRef]
  151. Goetzl, L.; Darbinian, N.; Merabova, N. Noninvasive assessment of fetal central nervous system insult: Potential application to prenatal diagnosis. Prenat. Diagn. 2019, 39, 609–615. [Google Scholar] [CrossRef]
  152. Goetzl, L.; Merabova, N.; Darbinian, N.; Martirosyan, D.; Poletto, E.; Fugarolas, K.; Menkiti, O. Diagnostic Potential of Neural Exosome Cargo as Biomarkers for Acute Brain Injury. Ann. Clin. Transl. Neurol. 2018, 5, 4–10. [Google Scholar] [CrossRef] [PubMed]
  153. Goetzl, E.J.; Boxer, A.; Schwartz, J.B.; Abner, E.L.; Petersen, R.C.; Miller, B.L.; Kapogiannis, D. Altered lysosomal proteins in neural-derived plasma exosomes in preclinical Alzheimer disease. Neurology 2015, 85, 40–47. [Google Scholar] [CrossRef] [PubMed]
  154. Newman, L.A.; Useckaite, Z.; Johnson, J.; Sorich, M.J.; Hopkins, A.M.; Rowland, A. Selective Isolation of Liver-Derived Extracellular Vesicles Redefines Performance of miRNA Biomarkers for Non-Alcoholic Fatty Liver Disease. Biomedicines 2022, 10, 195. [Google Scholar] [CrossRef] [PubMed]
  155. Zeng, Y.; Hu, S.; Luo, Y.; He, K. Exosome Cargos as Biomarkers for Diagnosis and Prognosis of Hepatocellular Carcinoma. Pharmaceutics 2023, 15, 2365. [Google Scholar] [CrossRef] [PubMed]
  156. Wang, S.; Xu, M.; Li, X.; Su, X.; Xiao, X.; Keating, A.; Zhao, R.C. Exosomes released by hepatocarcinoma cells endow adipocytes with tumor-promoting properties. J. Hematol. Oncol. 2018, 11, 82. [Google Scholar] [CrossRef]
  157. Liu, W.-h.; Ren, L.-n.; Wang, X.; Wang, T.; Zhang, N.; Gao, Y.; Luo, H.; Navarro-Alvarez, N.; Tang, L.-J. Combination of exosomes and circulating microRNAs may serve as a promising tumor marker complementary to alpha-fetoprotein for early-stage hepatocellular carcinoma diagnosis in rats. J. Cancer Res. Clin. Oncol. 2015, 141, 1767–1778. [Google Scholar] [CrossRef] [PubMed]
  158. Li, X.; Li, C.; Zhang, L.; Wu, M.; Cao, K.; Jiang, F.; Chen, D.; Li, N.; Li, W. The significance of exosomes in the development and treatment of hepatocellular carcinoma. Mol. Cancer 2020, 19, 1. [Google Scholar] [CrossRef] [PubMed]
  159. Chapuy-Regaud, S.; Dubois, M.; Plisson-Chastang, C.; Bonnefois, T.; Lhomme, S.; Bertrand-Michel, J.; You, B.; Simoneau, S.; Gleizes, P.-E.; Flan, B.; et al. Characterization of the lipid envelope of exosome encapsulated HEV particles protected from the immune response. Biochimie 2017, 141, 70–79. [Google Scholar] [CrossRef] [PubMed]
  160. Haraszti, R.A.; Didiot, M.-C.; Sapp, E.; Leszyk, J.; Shaffer, S.A.; Rockwell, H.E.; Gao, F.; Narain, N.R.; DiFiglia, M.; Kiebish, M.A.; et al. High-resolution proteomic and lipidomic analysis of exosomes and microvesicles from different cell sources. J. Extracell. Vesicles 2016, 5, 32570. [Google Scholar] [CrossRef]
  161. Llorente, A.; Skotland, T.; Sylvänne, T.; Kauhanen, D.; Róg, T.; Orłowski, A.; Vattulainen, I.; Ekroos, K.; Sandvig, K. Molecular lipidomics of exosomes released by PC-3 prostate cancer cells. Biochim. Biophys. Acta 2013, 1831, 1302–1309. [Google Scholar] [CrossRef]
  162. Trajkovic, K.; Hsu, C.; Chiantia, S.; Rajendran, L.; Wenzel, D.; Wieland, F.; Schwille, P.; Brügger, B.; Simons, M. Ceramide triggers budding of exosome vesicles into multivesicular endosomes. Science 2008, 319, 1244–1247. [Google Scholar] [CrossRef] [PubMed]
  163. Subra, C.; Laulagnier, K.; Perret, B.; Record, M. Exosome lipidomics unravels lipid sorting at the level of multivesicular bodies. Biochimie 2007, 89, 205–212. [Google Scholar] [CrossRef] [PubMed]
  164. Sanchez, J.I.; Jiao, J.; Kwan, S.Y.; Veillon, L.; Warmoes, M.O.; Tan, L.; Odewole, M.; Rich, N.E.; Wei, P.; Lorenzi, P.L.; et al. Lipidomic Profiles of Plasma Exosomes Identify Candidate Biomarkers for Early Detection of Hepatocellular Carcinoma in Patients with Cirrhosis. Cancer Prev. Res. 2021, 14, 955–962. [Google Scholar] [CrossRef] [PubMed]
  165. Van Niel, G.; d’Angelo, G.; Raposo, G. Shedding light on the cell biology of extracellular vesicles. Nat. Rev. Mol. Cell Biol. 2018, 19, 213–228. [Google Scholar] [CrossRef] [PubMed]
  166. Xie, J.X.; Fan, X.; Drummond, C.A.; Majumder, R.; Xie, Y.; Chen, T.; Liu, L.; Haller, S.T.; Brewster, P.S.; Dworkin, L.D.; et al. MicroRNA profiling in kidney disease: Plasma versus plasma-derived exosomes. Gene 2017, 627, 1–8. [Google Scholar] [CrossRef] [PubMed]
  167. Zhang, Q.; Li, H.; Liu, Y.; Li, J.; Wu, C.; Tang, H. Exosomal Non-Coding RNAs: New Insights into the Biology of Hepatocellular Carcinoma. Curr. Oncol. 2022, 29, 5383–5406. [Google Scholar] [CrossRef]
  168. Cho, H.J.; Eun, J.W.; Baek, G.O.; Seo, C.W.; Ahn, H.R.; Kim, S.S.; Cho, S.W.; Cheong, J.Y. Serum exosomal microRNA, miR-10b-5p, as a potential diagnostic biomarker for early-stage hepatocellular carcinoma. J. Clin. Med. 2020, 9, 281. [Google Scholar] [CrossRef] [PubMed]
  169. Cho, H.J.; Baek, G.O.; Seo, C.W.; Ahn, H.R.; Sung, S.; Son, J.A.; Kim, S.S.; Cho, S.W.; Jang, J.W.; Nam, S.W.; et al. Exosomal microRNA-4661-5p–based serum panel as a potential diagnostic biomarker for early-stage hepatocellular carcinoma. Cancer Med. 2020, 9, 5459–5472. [Google Scholar] [CrossRef] [PubMed]
  170. Shi, M.; Jiang, Y.; Yang, L.; Yan, S.; Wang, Y.G.; Lu, X.J. Decreased levels of serum exosomal miR-638 predict poor prognosis in hepatocellular carcinoma. J. Cell. Biochem. 2018, 119, 4711–4716. [Google Scholar] [CrossRef]
  171. Li, W.; Ding, X.; Wang, S.; Xu, L.; Yin, T.; Han, S.; Geng, J.; Sun, W. Downregulation of serum exosomal miR-320d predicts poor prognosis in hepatocellular carcinoma. J. Clin. Lab. Anal. 2020, 34, e23239. [Google Scholar] [CrossRef]
  172. Yan, L.; Chen, Y.; Zhou, J.; Zhao, H.; Zhang, H.; Wang, G. Diagnostic value of circulating cell-free DNA levels for hepatocellular carcinoma. Int. J. Infect. Dis. 2018, 67, 92–97. [Google Scholar] [CrossRef] [PubMed]
  173. Tian, B.W.; Han, C.L.; Dong, Z.R.; Tan, S.Y.; Wang, D.X.; Li, T. Role of Exosomes in Immunotherapy of Hepatocellular Carcinoma. Cancers 2022, 14, 4036. [Google Scholar] [CrossRef] [PubMed]
  174. Poggio, M.; Hu, T.; Pai, C.-C.; Chu, B.; Belair, C.D.; Chang, A.; Montabana, E.; Lang, U.E.; Fu, Q.; Fong, L.; et al. Suppression of exosomal PD-L1 induces systemic anti-tumor immunity and memory. Cell 2019, 177, 414–427.e13. [Google Scholar] [CrossRef] [PubMed]
  175. Kar, R.; Dhar, R.; Mukherjee, S.; Nag, S.; Gorai, S.; Mukerjee, N.; Mukherjee, D.; Vatsa, R.; Jadhav, M.C.; Ghosh, A.; et al. Exosome-Based Smart Drug Delivery Tool for Cancer Theranostics. ACS Biomater. Sci. Eng. 2023, 9, 577–594. [Google Scholar] [CrossRef] [PubMed]
  176. Kim, M.S.; Haney, M.J.; Zhao, Y.; Mahajan, V.; Deygen, I.; Klyachko, N.L.; Inskoe, E.; Piroyan, A.; Sokolsky, M.; Okolie, O.; et al. Development of exosome-encapsulated paclitaxel to overcome MDR in cancer cells. Nanomed. Nanotechnol. Biol. Med. 2016, 12, 655–664. [Google Scholar] [CrossRef] [PubMed]
  177. Kowal, J.; Tkach, M.; Théry, C. Biogenesis and secretion of exosomes. Curr. Opin. Cell Biol. 2014, 29, 116–125. [Google Scholar] [CrossRef] [PubMed]
  178. Hadla, M.; Palazzolo, S.; Corona, G.; Caligiuri, I.; Canzonieri, V.; Toffoli, G.; Rizzolio, F. Exosomes increase the therapeutic index of doxorubicin in breast and ovarian cancer mouse models. Nanomedicine 2016, 11, 2431–2441. [Google Scholar] [CrossRef]
  179. Wei, H.; Chen, J.; Wang, S.; Fu, F.; Zhu, X.; Wu, C.; Liu, Z.; Zhong, G.; Lin, J. A nanodrug consisting of doxorubicin and exosome derived from mesenchymal stem cells for osteosarcoma treatment in vitro. Int. J. Nanomed. 2019, 14, 8603–8610. [Google Scholar] [CrossRef]
  180. Najafi, S.; Majidpoor, J.; Mortezaee, K. Extracellular vesicle-based drug delivery in cancer immunotherapy. Drug Deliv. Transl. Res. 2023, 13, 2790–2806. [Google Scholar] [CrossRef]
  181. Morad, G.; Helmink, B.A.; Sharma, P.; Wargo, J.A. Hallmarks of response, resistance, and toxicity to immune checkpoint blockade. Cell 2021, 184, 5309–5337. [Google Scholar] [CrossRef]
  182. Seo, N.; Akiyoshi, K.; Shiku, H. Exosome-mediated regulation of tumor immunology. Cancer Sci. 2018, 109, 2998–3004. [Google Scholar] [CrossRef] [PubMed]
  183. Fan, M.; Liu, H.; Yan, H.; Che, R.; Jin, Y.; Yang, X.; Zhou, X.; Yang, H.; Ge, K.; Liang, X.-J.; et al. A CAR T-inspiring platform based on antibody-engineered exosomes from antigen-feeding dendritic cells for precise solid tumor therapy. Biomaterials 2022, 282, 121424. [Google Scholar] [CrossRef] [PubMed]
  184. Liu, X.; Wei, Q.; Lu, L.; Cui, S.; Ma, K.; Zhang, W.; Ma, F.; Li, H.; Fu, X.; Zhang, C. Immunomodulatory potential of mesenchymal stem cell-derived extracellular vesicles: Targeting immune cells. Front. Immunol. 2023, 14, 1094685. [Google Scholar] [CrossRef] [PubMed]
  185. Fu, W.; Lei, C.; Liu, S.; Cui, Y.; Wang, C.; Qian, K.; Li, T.; Shen, Y.; Fan, X.; Lin, F.; et al. CAR exosomes derived from effector CAR-T cells have potent antitumour effects and low toxicity. Nat. Commun. 2019, 10, 4355. [Google Scholar] [CrossRef] [PubMed]
  186. Taghikhani, A.; Farzaneh, F.; Sharifzad, F.; Mardpour, S.; Ebrahimi, M.; Hassan, Z.M. Engineered Tumor-Derived Extracellular Vesicles: Potentials in Cancer Immunotherapy. Front. Immunol. 2020, 11, 221. [Google Scholar] [CrossRef] [PubMed]
  187. Yan, R.; Chen, H.; Selaru, F.M. Extracellular Vesicles in Hepatocellular Carcinoma: Progress and Challenges in the Translation from the Laboratory to Clinic. Medicina 2023, 59, 1599. [Google Scholar] [CrossRef] [PubMed]
  188. Jesus, S.; Soares, E.; Cruz, M.T.; Borges, O. Exosomes as adjuvants for the recombinant hepatitis B antigen: First report. Eur. J. Pharm. Biopharm. 2018, 133, 1–11. [Google Scholar] [CrossRef] [PubMed]
  189. Jang, S.C.; Economides, K.D.; Moniz, R.J.; Sia, C.L.; Lewis, N.; McCoy, C.; Zi, T.; Zhang, K.; Harrison, R.A.; Lim, J.; et al. ExoSTING, an extracellular vesicle loaded with STING agonists, promotes tumor immune surveillance. Commun. Biol. 2021, 4, 497. [Google Scholar] [CrossRef] [PubMed]
  190. Xu, J.; Ji, L.; Liang, Y.; Wan, Z.; Zheng, W.; Song, X.; Gorshkov, K.; Sun, Q.; Lin, H.; Zheng, X.; et al. CircRNA-SORE mediates sorafenib resistance in hepatocellular carcinoma by stabilizing YBX1. Signal Transduct. Target. Ther. 2020, 5, 298. [Google Scholar] [CrossRef] [PubMed]
  191. Lu, J.C.; Zhang, P.F.; Huang, X.Y.; Guo, X.J.; Gao, C.; Zeng, H.Y.; Zheng, Y.M.; Wang, S.W.; Cai, J.B.; Sun, Q.M.; et al. Amplification of spatially isolated adenosine pathway by tumor-macrophage interaction induces anti-PD1 resistance in hepatocellular carcinoma. J. Hematol. Oncol. 2021, 14, 200. [Google Scholar] [CrossRef]
  192. Wang, J.; Yang, Y.; Lu, J.; Wang, X. The role of exosomes in therapeutic resistance of hepatocellular carcinoma. Hepatoma Res. 2023, 9, 46. [Google Scholar] [CrossRef]
  193. He, C.; Dong, X.; Zhai, B.; Jiang, X.; Dong, D.; Li, B.; Jiang, H.; Xu, S.; Sun, X. MiR-21 mediates sorafenib resistance of hepatocellular carcinoma cells by inhibiting autophagy via the PTEN/Akt pathway. Oncotarget 2015, 6, 28867–28881. [Google Scholar] [CrossRef] [PubMed]
  194. Lou, G.; Song, X.; Yang, F.; Wu, S.; Wang, J.; Chen, Z.; Liu, Y. Exosomes derived from miR-122-modified adipose tissue-derived MSCs increase chemosensitivity of hepatocellular carcinoma. J. Hematol. Oncol. 2015, 8, 122. [Google Scholar] [CrossRef] [PubMed]
  195. Gao, Y.; Yin, Z.; Qi, Y.; Peng, H.; Ma, W.; Wang, R.; Li, W. Golgi phosphoprotein 3 promotes angiogenesis and sorafenib resistance in hepatocellular carcinoma via upregulating exosomal miR-494-3p. Cancer Cell Int. 2022, 22, 35. [Google Scholar] [CrossRef] [PubMed]
  196. Escudier, B.; Dorval, T.; Chaput, N.; André, F.; Caby, M.-P.; Novault, S.; Flament, C.; Leboulaire, C.; Borg, C.; Amigorena, S.; et al. Vaccination of metastatic melanoma patients with autologous dendritic cell (DC) derived-exosomes: Results of thefirst phase I clinical trial. J. Transl. Med. 2005, 3, 10. [Google Scholar] [CrossRef] [PubMed]
  197. Besse, B.; Charrier, M.; Lapierre, V.; Dansin, E.; Lantz, O.; Planchard, D.; Le Chevalier, T.; Livartoski, A.; Barlesi, F.; Laplanche, A.; et al. Dendritic cell-derived exosomes as maintenance immunotherapy after first line chemotherapy in NSCLC. Oncoimmunology 2016, 5, e1071008. [Google Scholar] [CrossRef] [PubMed]
  198. Gehrmann, U.; Näslund, T.I.; Hiltbrunner, S.; Larssen, P.; Gabrielsson, S. (Eds.) Harnessing the exosome-induced immune response for cancer immunotherapy. In Seminars in Cancer Biology; Elsevier: Amsterdam, The Netherlands, 2014. [Google Scholar]
  199. Katzenstein, H.M.; Langham, M.R.; Malogolowkin, M.H.; Krailo, M.D.; Towbin, A.J.; McCarville, M.B.; Finegold, M.J.; Ranganathan, S.; Dunn, S.; McGahren, E.D.; et al. Minimal adjuvant chemotherapy for children with hepatoblastoma resected at diagnosis (AHEP0731): A Children’s Oncology Group, multicentre, phase 3 trial. Lancet Oncol. 2019, 20, 719–727. [Google Scholar] [CrossRef] [PubMed]
  200. Yeung, C.C.; Dondelinger, F.; Schoof, E.M.; Georg, B.; Lu, Y.; Zheng, Z.; Zhang, J.; Hannibal, J.; Fahrenkrug, J.; Kjaer, M. Circadian regulation of protein cargo in extracellular vesicles. Sci. Adv. 2022, 8, eabc9061. [Google Scholar] [CrossRef] [PubMed]
  201. Partch, C.L.; Green, C.B.; Takahashi, J.S. Molecular architecture of the mammalian circadian clock. Trends Cell Biol. 2014, 24, 90–99. [Google Scholar] [CrossRef]
  202. Patke, A.; Young, M.W.; Axelrod, S. Molecular mechanisms and physiological importance of circadian rhythms. Nat. Rev. Mol. Cell Biol. 2020, 21, 67–84. [Google Scholar] [CrossRef]
  203. Takahashi, J.S. Transcriptional architecture of the mammalian circadian clock. Nat. Rev. Genet. 2017, 18, 164–179. [Google Scholar] [CrossRef] [PubMed]
  204. Shafi, A.A.; Knudsen, K.E. Cancer and the circadian clock. Cancer Res. 2019, 79, 3806–3814. [Google Scholar] [CrossRef] [PubMed]
  205. Sancar, A.; Van Gelder, R.N. Clocks, cancer, and chronochemotherapy. Science 2021, 371, eabb0738. [Google Scholar] [CrossRef] [PubMed]
  206. Buhr, E.D.; Takahashi, J.S. Molecular components of the Mammalian circadian clock. Handb. Exp. Pharmacol. 2013, 217, 3–27. [Google Scholar]
  207. Panda, S.; Hogenesch, J.B.; Kay, S.A. Circadian rhythms from flies to human. Nature 2002, 417, 329–335. [Google Scholar] [CrossRef] [PubMed]
  208. Bass, J.; Takahashi, J.S. Circadian integration of metabolism and energetics. Science 2010, 330, 1349–1354. [Google Scholar] [CrossRef]
  209. Battaglin, F.; Chan, P.; Pan, Y.; Soni, S.; Qu, M.; Spiller, E.R.; Castanon, S.; Torres, E.T.R.; Mumenthaler, S.M.; Kay, S.A.; et al. Clocking cancer: The circadian clock as a target in cancer therapy. Oncogene 2021, 40, 3187–3200. [Google Scholar] [CrossRef] [PubMed]
  210. Chen, L.; Zhao, J.; Tang, Q.; Li, H.; Zhang, C.; Yu, R.; Zhao, Y.; Huo, Y.; Wu, C. PFKFB3 control of cancer growth by responding to circadian clock outputs. Sci. Rep. 2016, 6, 24324. [Google Scholar] [CrossRef]
  211. Tang, Q.; Cheng, B.; Xie, M.; Chen, Y.; Zhao, J.; Zhou, X.; Chen, L. Circadian clock gene Bmal1 inhibits tumorigenesis and increases paclitaxel sensitivity in tongue squamous cell carcinoma. Cancer Res. 2017, 77, 532–544. [Google Scholar] [CrossRef]
  212. Lucassen, E.A.; Coomans, C.P.; van Putten, M.; de Kreij, S.R.; van Genugten, J.H.; Sutorius, R.P.; de Rooij, K.E.; van der Velde, M.; Verhoeve, S.L.; Smit, J.W.; et al. Environmental 24-hr cycles are essential for health. Curr. Biol. 2016, 26, 1843–1853. [Google Scholar] [CrossRef]
  213. Pan, A.; Schernhammer, E.S.; Sun, Q.; Hu, F.B. Rotating night shift work and risk of type 2 diabetes: Two prospective cohort studies in women. PLoS Med. 2011, 8, e1001141. [Google Scholar] [CrossRef] [PubMed]
  214. Logan, R.W.; McClung, C.A. Rhythms of life: Circadian disruption and brain disorders across the lifespan. Nat. Rev. Neurosci. 2019, 20, 49–65. [Google Scholar] [CrossRef] [PubMed]
  215. Dooner, M.S.; Stewart, C.; Deng, Y.; Papa, E.; Pereira, M.; Del Tatto, M.; Johnson, S.; Wen, S.; Amaral, A.; Aliotta, J.; et al. Daily rhythms influence the ability of lung-derived extracellular vesicles to modulate bone marrow cell phenotype. PLoS ONE 2018, 13, e0207444. [Google Scholar] [CrossRef] [PubMed]
  216. Khalyfa, A.; Gaddameedhi, S.; Crooks, E.; Zhang, C.; Li, Y.; Qiao, Z.; Trzepizur, W.; Kay, S.A.; Andrade, J.; Satterfield, B.C.; et al. Circulating Exosomal miRNAs Signal Circadian Misalignment to Peripheral Metabolic Tissues. Int. J. Mol. Sci. 2020, 21, 6396. [Google Scholar] [CrossRef] [PubMed]
  217. Danielson, K.M.; Estanislau, J.; Tigges, J.; Toxavidis, V.; Camacho, V.; Felton, E.J.; Khoory, J.; Kreimer, S.; Ivanov, A.R.; Mantel, Y.; et al. Diurnal Variations of Circulating Extracellular Vesicles Measured by Nano Flow Cytometry. PLoS ONE 2016, 11, e0144678. [Google Scholar] [CrossRef] [PubMed]
  218. Kumar, A.; Sundaram, K.; Mu, J.; Dryden, G.W.; Sriwastva, M.K.; Lei, C.; Zhang, L.; Qiu, X.; Xu, F.; Yan, J.; et al. High-fat diet-induced upregulation of exosomal phosphatidylcholine contributes to insulin resistance. Nat. Commun. 2021, 12, 213. [Google Scholar] [CrossRef]
  219. Noh, J. The Effect of Circadian and Sleep Disruptions on Obesity Risk. J. Obes. Metab. Syndr. 2018, 27, 78–83. [Google Scholar] [CrossRef] [PubMed]
  220. Chaput, J.-P.; McHill, A.W.; Cox, R.C.; Broussard, J.L.; Dutil, C.; da Costa, B.G.G.; Sampasa-Kanyinga, H.; Wright, K.P. The role of insufficient sleep and circadian misalignment in obesity. Nat. Rev. Endocrinol. 2023, 19, 82–97. [Google Scholar] [CrossRef] [PubMed]
  221. Koritzinsky, E.H.; Street, J.M.; Chari, R.R.; Glispie, D.M.; Bellomo, T.R.; Aponte, A.M.; Star, R.A.; Yuen, P.S.T. Circadian variation in the release of small extracellular vesicles can be normalized by vesicle number or TSG101. Am. J. Physiol. Physiol. 2019, 317, F1098–F1110. [Google Scholar] [CrossRef]
  222. Eckel-Mahan, K.L.; Patel, V.R.; De Mateo, S.; Orozco-Solis, R.; Ceglia, N.J.; Sahar, S.; Dilag-Penilla, S.A.; Dyar, K.A.; Baldi, P.; Sassone-Corsi, P. Reprogramming of the circadian clock by nutritional challenge. Cell 2013, 155, 1464–1478. [Google Scholar] [CrossRef]
  223. Vollmers, C.; Gill, S.; DiTacchio, L.; Pulivarthy, S.R.; Le, H.D.; Panda, S. Time of feeding and the intrinsic circadian clock drive rhythms in hepatic gene expression. Proc. Natl. Acad. Sci. USA 2009, 106, 21453–21458. [Google Scholar] [CrossRef] [PubMed]
  224. Watanabe, M.; Tuccinardi, D.; Ernesti, I.; Basciani, S.; Mariani, S.; Genco, A.; Manfrini, S.; Lubrano, C.; Gnessi, L. Scientific evidence underlying contraindications to the ketogenic diet: An update. Obes. Rev. 2020, 21, e13053. [Google Scholar] [CrossRef] [PubMed]
  225. Tognini, P.; Murakami, M.; Liu, Y.; Eckel-Mahan, K.L.; Newman, J.C.; Verdin, E.; Baldi, P.; Sassone-Corsi, P. Distinct circadian signatures in liver and gut clocks revealed by ketogenic diet. Cell Metab. 2017, 26, 523–538.e5. [Google Scholar] [CrossRef] [PubMed]
  226. Ribas-Latre, A.; Fekry, B.; Kwok, C.; Baumgartner, C.; Shivshankar, S.; Sun, K.; Chen, Z.; Eckel-Mahan, K. Rosiglitazone reverses high fat diet-induced changes in BMAL1 function in muscle, fat, and liver tissue in mice. Int. J. Obes. 2019, 43, 567–580. [Google Scholar] [CrossRef] [PubMed]
  227. Lamia, K.A.; Storch, K.-F.; Weitz, C.J. Physiological significance of a peripheral tissue circadian clock. Proc. Natl. Acad. Sci. USA 2008, 105, 15172–15177. [Google Scholar] [CrossRef] [PubMed]
  228. Zhang, E.E.; Liu, Y.; Dentin, R.; Pongsawakul, P.Y.; Liu, A.C.; Hirota, T.; Nusinow, D.A.; Sun, X.; Landais, S.; Kodama, Y.; et al. Cryptochrome mediates circadian regulation of cAMP signaling and hepatic gluconeogenesis. Nat. Med. 2010, 16, 1152–1156. [Google Scholar] [CrossRef]
  229. Erren, T.C.; Falaturi, P.; Morfeld, P.; Knauth, P.; Reiter, R.J.; Piekarski, C. Shift work and cancer: The evidence and the challenge. Dtsch. Arztebl. Int. 2010, 107, 657–662. [Google Scholar] [PubMed]
  230. Erren, T.C.; Morfeld, P.; Groß, J.V.; Wild, U.; Lewis, P. “Night shift work” is probably carcinogenic: What about disturbed chronobiology in all walks of life? J. Occup. Med. Toxicol. 2019, 14, 29. [Google Scholar] [CrossRef] [PubMed]
  231. Kinouchi, K.; Sassone-Corsi, P. Metabolic rivalry: Circadian homeostasis and tumorigenesis. Nat. Rev. Cancer 2020, 20, 645–661. [Google Scholar] [CrossRef]
  232. Koritala, B.S.; Porter, K.I.; Arshad, O.A.; Gajula, R.P.; Mitchell, H.D.; Arman, T.; Manjanatha, M.G.; Teeguarden, J.; Van Dongen, H.P.A.; McDermott, J.E.; et al. Night shift schedule causes circadian dysregulation of DNA repair genes and elevated DNA damage in humans. J. Pineal Res. 2021, 70, e12726. [Google Scholar] [CrossRef]
  233. Chen, W.-D.; Wen, M.-S.; Shie, S.-S.; Lo, Y.-L.; Wo, H.-T.; Wang, C.-C.; Hsieh, I.C.; Lee, T.H.; Wang, C.Y. The circadian rhythm controls telomeres and telomerase activity. Biochem. Biophys. Res. Commun. 2014, 451, 408–414. [Google Scholar] [CrossRef] [PubMed]
  234. Ruan, W.; Yuan, X.; Eltzschig, H.K. Circadian rhythm as a therapeutic target. Nat. Rev. Drug Discov. 2021, 20, 287–307. [Google Scholar] [CrossRef] [PubMed]
  235. Huang, C.; Zhang, C.; Cao, Y.; Li, J.; Bi, F. Major roles of the circadian clock in cancer. Cancer Biol. Med. 2023, 20, 1–24. [Google Scholar] [CrossRef] [PubMed]
  236. Kettner, N.M.; Voicu, H.; Finegold, M.J.; Coarfa, C.; Sreekumar, A.; Putluri, N.; Katchy, C.A.; Lee, C.; Moore, D.D.; Fu, L. Circadian homeostasis of liver metabolism suppresses hepatocarcinogenesis. Cancer Cell 2016, 30, 909–924. [Google Scholar] [CrossRef] [PubMed]
  237. Ye, Y.; Xiang, Y.; Ozguc, F.M.; Kim, Y.; Liu, C.-J.; Park, P.K.; Hu, Q.; Diao, L.; Lou, Y.; Lin, C.; et al. The genomic landscape and pharmacogenomic interactions of clock genes in cancer chronotherapy. Cell Syst. 2018, 6, 314–328.e2. [Google Scholar] [CrossRef] [PubMed]
  238. Dong, Z.; Zhang, G.; Qu, M.; Gimple, R.C.; Wu, Q.; Qiu, Z.; Prager, B.C.; Wang, X.; Kim, L.J.; Morton, A.R.; et al. Targeting Glioblastoma Stem Cells through Disruption of the Circadian Clock. Cancer Discov. 2019, 9, 1556–1573. [Google Scholar] [CrossRef] [PubMed]
  239. Chen, P.; Hsu, W.-H.; Chang, A.; Tan, Z.; Lan, Z.; Zhou, A.; Spring, D.J.; Lang, F.F.; Wang, Y.A.; DePinho, R.A. Circadian regulator CLOCK recruits immune-suppressive microglia into the GBM tumor microenvironment. Cancer Discov. 2020, 10, 371–381. [Google Scholar] [CrossRef] [PubMed]
  240. Papagiannakopoulos, T.; Bauer, M.R.; Davidson, S.M.; Heimann, M.; Subbaraj, L.; Bhutkar, A.; Bartlebaugh, J.; Heiden, M.G.V.; Jacks, T. Circadian rhythm disruption promotes lung tumorigenesis. Cell Metab. 2016, 24, 324–331. [Google Scholar] [CrossRef]
  241. Qu, M.; Zhang, G.; Qu, H.; Vu, A.; Wu, R.; Tsukamoto, H.; Jia, Z.; Huang, W.; Lenz, H.-J.; Rich, J.N.; et al. Circadian regulator BMAL1::CLOCK promotes cell proliferation in hepatocellular carcinoma by controlling apoptosis and cell cycle. Proc. Natl. Acad. Sci. USA 2023, 120, e2214829120. [Google Scholar] [CrossRef]
  242. Fekry, B.; Ribas-Latre, A.; Drunen, R.V.; Santos, R.B.; Shivshankar, S.; Dai, Y.; Zhao, Z.; Yoo, S.; Chen, Z.; Sun, K.; et al. Hepatic circadian and differentiation factors control liver susceptibility for fatty liver disease and tumorigenesis. Faseb J. 2022, 36, e22482. [Google Scholar] [CrossRef]
  243. Crespo, M.; Leiva, M.; Sabio, G. Circadian Clock and Liver Cancer. Cancers 2021, 13, 3631. [Google Scholar] [CrossRef] [PubMed]
  244. Fekry, B.; Ribas-Latre, A.; Baumgartner, C.; Deans, J.R.; Kwok, C.; Patel, P.; Fu, L.; Berdeaux, R.; Sun, K.; Kolonin, M.G.; et al. Incompatibility of the circadian protein BMAL1 and HNF4α in hepatocellular carcinoma. Nat. Commun. 2018, 9, 4349. [Google Scholar] [CrossRef] [PubMed]
  245. Zisapel, N. New perspectives on the role of melatonin in human sleep, circadian rhythms and their regulation. Br. J. Pharmacol. 2018, 175, 3190–3199. [Google Scholar] [CrossRef] [PubMed]
  246. Talib, W.H.; Alsayed, A.R.; Abuawad, A.; Daoud, S.; Mahmod, A.I. Melatonin in Cancer Treatment: Current Knowledge and Future Opportunities. Molecules 2021, 26, 2506. [Google Scholar] [CrossRef]
  247. Cheng, L.; Liu, J.; Liu, Q.; Liu, Y.; Fan, L.; Wang, F.; Yu, H.; Li, Y.; Bu, L.; Li, X.; et al. Exosomes from melatonin treated hepatocellularcarcinoma cells alter the immunosupression status through STAT3 pathway in macrophages. Int. J. Biol. Sci. 2017, 13, 723. [Google Scholar] [CrossRef] [PubMed]
  248. Zhang, X.; Pant, S.M.; Ritch, C.C.; Tang, H.-Y.; Shao, H.; Dweep, H.; Gong, Y.-Y.; Brooks, R.; Brafford, P.; Wolpaw, A.J.; et al. Cell state dependent effects of Bmal1 on melanoma immunity and tumorigenicity. Nat. Commun. 2024, 15, 633. [Google Scholar] [CrossRef] [PubMed]
  249. Schibler, U.; Sassone-Corsi, P. A web of circadian pacemakers. Cell 2002, 111, 919–922. [Google Scholar] [CrossRef] [PubMed]
  250. Ray, S.; Valekunja, U.K.; Stangherlin, A.; Howell, S.A.; Snijders, A.P.; Damodaran, G.; Reddy, A.B. Circadian rhythms in the absence of the clock gene Bmal1. Science 2020, 367, 800–806. [Google Scholar] [CrossRef]
  251. Khalyfa, A.; Poroyko, V.A.; Qiao, Z.; Gileles-Hillel, A.; Khalyfa, A.A.; Akbarpour, M.; Farré, R.; Gozal, D. Exosomes and metabolic function in mice exposed to alternating dark-light cycles mimicking night shift work schedules. Front. Physiol. 2017, 8, 311175. [Google Scholar] [CrossRef]
  252. Chang, H.C.; Guarente, L. SIRT1 mediates central circadian control in the SCN by a mechanism that decays with aging. Cell 2013, 153, 1448–1460. [Google Scholar] [CrossRef]
  253. Asher, G.; Gatfield, D.; Stratmann, M.; Reinke, H.; Dibner, C.; Kreppel, F.; Mostoslavsky, R.; Alt, F.W.; Schibler, U. SIRT1 regulates circadian clock gene expression through PER2 deacetylation. Cell 2008, 134, 317–328. [Google Scholar] [CrossRef] [PubMed]
  254. Forterre, A.; Jalabert, A.; Chikh, K.; Pesenti, S.; Euthine, V.; Granjon, A.; Errazuriz, E.; Lefai, E.; Vidal, H.; Rome, S. Myotube-derived exosomal miRNAs downregulate Sirtuin1 in myoblasts during muscle cell differentiation. Cell Cycle 2014, 13, 78–89. [Google Scholar] [CrossRef]
  255. Shi, X.-F.; Wang, H.; Kong, F.-X.; Xu, Q.-Q.; Xiao, F.-J.; Yang, Y.-F.; Ge, R.-L.; Wang, L.-S. Exosomal miR-486 regulates hypoxia-induced erythroid differentiation of erythroleukemia cells through targeting Sirt1. Exp. Cell Res. 2017, 351, 74–81. [Google Scholar] [CrossRef]
  256. Ding, L.; Li, Z.-l.; Zhou, Y.; Liu, N.-c.; Liu, S.-s.; Zhang, X.-j.; Liu, C.-C.; Zhang, D.-J.; Wang, G.-H.; Ma, R.-X. Loss of Sirt1 promotes exosome secretion from podocytes by inhibiting lysosomal acidification in diabetic nephropathy. Mol. Cell. Endocrinol. 2023, 568–569, 111913. [Google Scholar] [CrossRef] [PubMed]
  257. Wang, Z.; Guo, W.; Yi, F.; Zhou, T.; Li, X.; Feng, Y.; Guo, Q.; Xu, H.; Song, X.; Cao, L. The Regulatory Effect of SIRT1 on Extracellular Microenvironment Remodeling. Int. J. Biol. Sci. 2021, 17, 89–96. [Google Scholar] [CrossRef] [PubMed]
  258. McAndrews, K.M.; LeBleu, V.S.; Kalluri, R. SIRT1 Regulates Lysosome Function and Exosome Secretion. Dev. Cell 2019, 49, 302–303. [Google Scholar] [CrossRef] [PubMed]
  259. Roy, S.; Das, A.; Vernekar, M.; Mandal, S.; Chatterjee, N. Understanding the Correlation between Metabolic Regulator SIRT1 and Exosomes with CA-125 in Ovarian Cancer: A Clinicopathological Study. BioMed Res. Int. 2022, 2022, 5346091. [Google Scholar] [CrossRef]
  260. Liu, L.; Jin, X.; Hu, C.-F.; Li, R.; Zhou, Z.; Shen, C.-X. Exosomes derived from mesenchymal stem cells rescue myocardial ischaemia/reperfusion injury by inducing cardiomyocyte autophagy via AMPK and Akt pathways. Cell. Physiol. Biochem. 2017, 43, 52–68. [Google Scholar] [CrossRef]
  261. Liu, F.; Bu, Z.; Zhao, F.; Xiao, D. Increased T-helper 17 cell differentiation mediated by exosome-mediated micro RNA-451 redistribution in gastric cancer infiltrated T cells. Cancer Sci. 2018, 109, 65–73. [Google Scholar] [CrossRef]
  262. Arslan, F.; Lai, R.C.; Smeets, M.B.; Akeroyd, L.; Choo, A.; Aguor, E.N.; Timmers, L.; Van Rijen, H.V.; Doevendans, P.A.; Pasterkamp, G.; et al. Mesenchymal stem cell-derived exosomes increase ATP levels, decrease oxidative stress and activate PI3K/Akt pathway to enhance myocardial viability and prevent adverse remodeling after myocardial ischemia/reperfusion injury. Stem Cell Res. 2013, 10, 301–312. [Google Scholar] [CrossRef]
  263. Mukherji, A.; Bailey, S.M.; Staels, B.; Baumert, T.F. The circadian clock and liver function in health and disease. J. Hepatol. 2019, 71, 200–211. [Google Scholar] [CrossRef] [PubMed]
  264. Li, X.; Guan, J.; Jiang, Z.; Cheng, S.; Hou, W.; Yao, J.; Wang, Z. Microglial Exosome miR-7239-3p Promotes Glioma Progression by Regulating Circadian Genes. Neurosci. Bull. 2021, 37, 497–510. [Google Scholar] [CrossRef] [PubMed]
  265. Qu, M.; Qu, H.; Jia, Z.; Kay, S.A. HNF4A defines tissue-specific circadian rhythms by beaconing BMAL1::CLOCK chromatin binding and shaping the rhythmic chromatin landscape. Nat. Commun. 2021, 12, 6350. [Google Scholar] [CrossRef] [PubMed]
  266. Deans, J.R.; Deol, P.; Titova, N.; Radi, S.H.; Vuong, L.M.; Evans, J.R.; Pan, S.; Fahrmann, J.; Yang, J.; Hammock, B.D.; et al. HNF4α isoforms regulate the circadian balance between carbohydrate and lipid metabolism in the liver. Front. Endocrinol. 2023, 14, 1266527. [Google Scholar] [CrossRef] [PubMed]
  267. Zhang, H.; Zhang, X.; Wang, S.; Zheng, L.; Guo, H.; Ren, Y.; Qiao, B.; Wu, J.; Zhao, D.; Xu, L.; et al. Adipocyte-derived exosomal miR-22-3p modulated by circadian rhythm disruption regulates insulin sensitivity in skeletal muscle cells. J. Biol. Chem. 2023, 299, 105476. [Google Scholar] [CrossRef] [PubMed]
  268. Pusic, A.D.; Kraig, R.P. Youth and environmental enrichment generate serum exosomes containing miR-219 that promote CNS myelination. Glia 2014, 62, 284–299. [Google Scholar] [CrossRef] [PubMed]
  269. Tao, S.C.; Guo, S.C. Extracellular Vesicles: Potential Participants in Circadian Rhythm Synchronization. Int. J. Biol. Sci. 2018, 14, 1610–1620. [Google Scholar] [CrossRef] [PubMed]
  270. Shende, V.R.; Goldrick, M.M.; Ramani, S.; Earnest, D.J. Expression and rhythmic modulation of circulating microRNAs targeting the clock gene Bmal1 in mice. PLoS ONE 2011, 6, e22586. [Google Scholar] [CrossRef] [PubMed]
  271. Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13, 2498–2504. [Google Scholar] [CrossRef]
  272. Warde-Farley, D.; Donaldson, S.L.; Comes, O.; Zuberi, K.; Badrawi, R.; Chao, P.; Franz, M.; Grouios, C.; Kazi, F.; Lopes, C.T.; et al. The GeneMANIA prediction server: Biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010, 38 (Suppl. S2), W214–W220. [Google Scholar] [CrossRef]
  273. Liu, W.; Yu, M.; Xie, D.; Wang, L.; Ye, C.; Zhu, Q.; Liu, F.; Yang, L. Melatonin-stimulated MSC-derived exosomes improve diabetic wound healing through regulating macrophage M1 and M2 polarization by targeting the PTEN/AKT pathway. Stem Cell Res. Ther. 2020, 11, 1–15. [Google Scholar] [CrossRef] [PubMed]
  274. Yoon, Y.M.; Lee, J.H.; Song, K.H.; Noh, H.; Lee, S.H. Melatonin-stimulated exosomes enhance the regenerative potential of chronic kidney disease-derived mesenchymal stem/stromal cells via cellular prion proteins. J. Pineal Res. 2020, 68, e12632. [Google Scholar] [CrossRef] [PubMed]
  275. Zhou, Z.; Wang, R.; Wang, J.; Hao, Y.; Xie, Q.; Wang, L.; Wang, X. Melatonin pretreatment on exosomes: Heterogeneity, therapeutic effects, and usage. Front. Immunol. 2022, 13, 933736. [Google Scholar] [CrossRef] [PubMed]
  276. Wei, J.X.; Lv, L.H.; Wan, Y.L.; Cao, Y.; Li, G.L.; Lin, H.M.; Zhou, R.; Shang, C.Z.; Cao, J.; He, H.; et al. Vps4A functions as a tumor suppressor by regulating the secretion and uptake of exosomal microRNAs in human hepatoma cells. Hepatology 2015, 61, 1284–1294. [Google Scholar] [CrossRef] [PubMed]
  277. Qiu, Y.; Li, P.; Zhang, Z.; Wu, M. Insights into Exosomal Non-Coding RNAs Sorting Mechanism and Clinical Application. Front. Oncol. 2021, 11, 664904. [Google Scholar]
  278. Lee, Y.J.; Shin, K.J.; Chae, Y.C. Regulation of cargo selection in exosome biogenesis and its biomedical applications in cancer. Exp. Mol. Med. 2024, 56, 877–889. [Google Scholar] [CrossRef] [PubMed]
  279. Garcia-Martin, R.; Brandao, B.B.; Thomou, T.; Altindis, E.; Kahn, C.R. Tissue differences in the exosomal/small extracellular vesicle proteome and their potential as indicators of altered tissue metabolism. Cell Rep. 2022, 38, 110277. [Google Scholar] [CrossRef] [PubMed]
  280. Liu, W.-Z.; Ma, Z.-J.; Kang, X.-W. Current status and outlook of advances in exosome isolation. Anal. Bioanal. Chem. 2022, 414, 7123–7141. [Google Scholar] [CrossRef]
  281. Gao, J.; Li, A.; Hu, J.; Feng, L.; Liu, L.; Shen, Z. Recent developments in isolating methods for exosomes. Front. Bioeng. Biotechnol. 2022, 10, 1100892. [Google Scholar] [CrossRef]
  282. Jin, X.; Zhang, J.; Zhang, Y.; He, J.; Wang, M.; Hei, Y.; Guo, S.; Xu, X.; Liu, Y. Different origin-derived exosomes and their clinical advantages in cancer therapy. Front. Immunol. 2024, 15, 1401852. [Google Scholar] [CrossRef]
  283. Li, X.; Corbett, A.L.; Taatizadeh, E.; Tasnim, N.; Little, J.P.; Garnis, C.; Daugaard, M.; Guns, E.; Hoorfar, M.; Li, I.T.S. Challenges and opportunities in exosome research-Perspectives from biology, engineering, and cancer therapy. APL Bioeng. 2019, 3, 011503. [Google Scholar] [CrossRef] [PubMed]
  284. Mathivanan, S.; Ji, H.; Simpson, R.J. Exosomes: Extracellular organelles important in intercellular communication. J. Proteom. 2010, 73, 1907–1920. [Google Scholar] [CrossRef] [PubMed]
  285. Innominato, P.F.; Roche, V.P.; Palesh, O.G.; Ulusakarya, A.; Spiegel, D.; Lévi, F.A. The circadian timing system in clinical oncology. Ann. Med. 2014, 46, 191–207. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Exosome biogenesis. The primary pathway of exosome biogenesis involves the creation of multivesicular bodies (MVBs) within endosomes, leading to exosome secretion. During endocytosis, early endosomes transform into MVBs, generating intraluminal vesicles (ILVs) through the inward budding of their membranes. These MVBs may either merge with lysosomes for degradation or move to the cell surface to release exosomes. This release process is facilitated by RAB GTPases and SNARE complexes. Once exosomes are released, extracellular vesicles (ECVs) can interact with target cells through ligand–receptor binding, endocytosis, or membrane fusion, allowing the delivery of their cargo into the cytoplasm of the recipient cell. The molecular content of ECVs plays a crucial role in regulating various functions in target cells, including intracellular signaling, gene regulation, and metabolism, and can also be directly released into biological fluids. Created with BioRender.com.
Figure 1. Exosome biogenesis. The primary pathway of exosome biogenesis involves the creation of multivesicular bodies (MVBs) within endosomes, leading to exosome secretion. During endocytosis, early endosomes transform into MVBs, generating intraluminal vesicles (ILVs) through the inward budding of their membranes. These MVBs may either merge with lysosomes for degradation or move to the cell surface to release exosomes. This release process is facilitated by RAB GTPases and SNARE complexes. Once exosomes are released, extracellular vesicles (ECVs) can interact with target cells through ligand–receptor binding, endocytosis, or membrane fusion, allowing the delivery of their cargo into the cytoplasm of the recipient cell. The molecular content of ECVs plays a crucial role in regulating various functions in target cells, including intracellular signaling, gene regulation, and metabolism, and can also be directly released into biological fluids. Created with BioRender.com.
Cancers 16 02552 g001
Figure 2. Impact of extracellular vesicles (ECVs) in the hepatocellular carcinoma (HCC) tumor microenvironment. ECVs are released by both tumor cells and other surrounding cells into the tumor microenvironment and the circulatory system. These ECVs transport a variety of bioactive molecules that contribute to tumor growth, metastasis, and intercellular communication. By mediating these exchanges, ECVs play a key role in shaping the tumor microenvironment, potentially influencing the progression of cancer and the behavior of distant cells through the molecules that they carry. ECVs, extracellular vesicles; HSCs, hepatic stellate cells; ECM, extracellular matrix. Created with BioRender.com.
Figure 2. Impact of extracellular vesicles (ECVs) in the hepatocellular carcinoma (HCC) tumor microenvironment. ECVs are released by both tumor cells and other surrounding cells into the tumor microenvironment and the circulatory system. These ECVs transport a variety of bioactive molecules that contribute to tumor growth, metastasis, and intercellular communication. By mediating these exchanges, ECVs play a key role in shaping the tumor microenvironment, potentially influencing the progression of cancer and the behavior of distant cells through the molecules that they carry. ECVs, extracellular vesicles; HSCs, hepatic stellate cells; ECM, extracellular matrix. Created with BioRender.com.
Cancers 16 02552 g002
Figure 3. Roles of exosomes in HCC. This diagram demonstrates the multiple functions of exosomes in HCC, highlighting their roles in facilitating immune escape, promoting angiogenesis, driving metastasis, and supporting tumor invasion. Exosomes from other sources, like stem cells and macrophages, can also influence HCC by conferring drug resistance and modulating responses to immunotherapy. These exosomes have additional potential as biomarkers for detecting and monitoring HCC, shedding light on disease progression and offering new pathways for treatment. The ability of exosomes to mediate intercellular communication within the tumor microenvironment emphasizes their relevance to targeted therapies and personalized medical approaches. Created with BioRender.com.
Figure 3. Roles of exosomes in HCC. This diagram demonstrates the multiple functions of exosomes in HCC, highlighting their roles in facilitating immune escape, promoting angiogenesis, driving metastasis, and supporting tumor invasion. Exosomes from other sources, like stem cells and macrophages, can also influence HCC by conferring drug resistance and modulating responses to immunotherapy. These exosomes have additional potential as biomarkers for detecting and monitoring HCC, shedding light on disease progression and offering new pathways for treatment. The ability of exosomes to mediate intercellular communication within the tumor microenvironment emphasizes their relevance to targeted therapies and personalized medical approaches. Created with BioRender.com.
Cancers 16 02552 g003
Figure 4. Circadian clock’s impact on ECV characteristics in cancer. In the molecular clock, CLOCK and BMAL1 rhythmically bind to E-boxes, activating clock-controlled genes and other clock components. Their activity is regulated by PER and CRY proteins, which inhibit CLOCK-BMAL1 upon entering the nucleus. A second feedback loop involves BMAL1 transcription, which is repressed by REV-ERB and activated by ROR. The circadian clock plays a crucial role in shaping the properties of ECVs, which are essential for cellular communication and metabolic regulation. Disruptions in circadian rhythms, resulting from factors such as genetic mutations in clock genes; environmental stresses like irregular eating times, jet lag, shift work, and constant light exposure; and pathological conditions like aging, diabetes, and obesity can drive cancer development and progression. These disturbances in circadian patterns significantly affect ECV characteristics, including size, concentration, and cargo composition, emphasizing the critical relationship among circadian rhythms, ECV biology, and cancer dynamics, whether through circulation or interactions with recipient cells. Created with BioRender.com.
Figure 4. Circadian clock’s impact on ECV characteristics in cancer. In the molecular clock, CLOCK and BMAL1 rhythmically bind to E-boxes, activating clock-controlled genes and other clock components. Their activity is regulated by PER and CRY proteins, which inhibit CLOCK-BMAL1 upon entering the nucleus. A second feedback loop involves BMAL1 transcription, which is repressed by REV-ERB and activated by ROR. The circadian clock plays a crucial role in shaping the properties of ECVs, which are essential for cellular communication and metabolic regulation. Disruptions in circadian rhythms, resulting from factors such as genetic mutations in clock genes; environmental stresses like irregular eating times, jet lag, shift work, and constant light exposure; and pathological conditions like aging, diabetes, and obesity can drive cancer development and progression. These disturbances in circadian patterns significantly affect ECV characteristics, including size, concentration, and cargo composition, emphasizing the critical relationship among circadian rhythms, ECV biology, and cancer dynamics, whether through circulation or interactions with recipient cells. Created with BioRender.com.
Cancers 16 02552 g004
Table 1. Exosomal ncRNAs as potential cancer biomarkers in diagnosis and progression.
Table 1. Exosomal ncRNAs as potential cancer biomarkers in diagnosis and progression.
Exosomal ncRNAType of DiseaseSource of ExosomeExpressionReferences
miRNA-21, miRNA-1224, miRNA-1229, miRNA-1246, miRNA-150, miRNA-21, miRNA-223, miRNA-23aColorectal
cancer
Blood↑, ↑, ↑, ↑, ↑, ↑, ↑, ↑[70,71]
miRNA-21, miRNA-105, miRNA-372Breast cancerBlood↑, ↑, ↑[72,73]
miRNA-373Triple-negative breast cancerBlood[74]
miRNA-21, miRNA-141, miRNA-200a, miRNA-200c, miRNA-200b, miRNA-203, miRNA-205, miRNA-214Ovarian cancerBlood↑, ↑, ↑, ↑, ↑, ↑, ↑, ↑
miRNA-17-5p, miRNA-21, miRNA-106a, miRNA-106bPancreatic cancerBlood↑, ↑, ↑, ↑[75,76]
miRNA-184Tongue cancerBlood[77]
miRNA-21, miRNA-500, mi-RNA-26a, mi-RNA-26c, miRNA-224, miRNA-665, miRNA-10b-5p, miRNA-18a-5p, miRNA-215-5p, miRNA-940mi-RNA-199a, miRNA-18a, miRNA-221, miRNA-222Hepatocellular carcinomaBlood↑, ↓, ↓, ↓, ↑, ↑, ↑, ↑, ↑, ↑, ↑, ↑, ↑[78,79,80,81,82]
miRNA-125a, miRNA-200aOral squamous cell carcinomaBlood[83]
circ-DB, circCUHRF1, circTMEM4A, circ-100338, circ-0051443Hepatocelluar carcinomaBlood↑, ↑, ↑, ↑, ↓, ↓[84,85,86,87]
circ_0047921, circ_0056285, circ_0007761Non-small cell lung cancerBlood↓, ↓, ↑[88]
circ_0001439, circ_0001492, circ_0000896Lung adenocarcinomaBlood↑, ↑, ↑[89]
circMYCNasopharyngeal carcinomaBlood[90]
circ_0047921, circ_0056285, circ_0007761Non-small cell lung cancerBlood↓, ↓, ↑[88]
hsa_circ_0055202, hsa_circ_0074920 hsa_circ_0043722GlioblastomaBlood↑, ↑, ↑[91]
circPDLIM5Prostate cancerUrine[92]
↑ up ↓ down.
Table 2. Role of ECVs in HCC carcinogenesis.
Table 2. Role of ECVs in HCC carcinogenesis.
Exosomal ComponentEffectMechanism of ImpactReferences
miRNA-93Tumor proliferationEnhances the growth of HCC cells[111,112]
PDGFRα, Hedgehog ligandsFibrogenesis, angiogenesisPromotes tissue remodeling and blood vessel formation[64]
miRNA-1247-3pLung metastasisConverts cells to cancer-associated fibroblasts and increases pro-inflammatory cytokines (IL-6, IL-8)[18]
Circ-0004277, miRNA-136-5pEMT, tissue invasionInduces epithelial-to-mesenchymal transition in surrounding cells[113,114]
miRNA-21, miRNA-10bTumor proliferation, metastasisRegulation of the tumor suppressor gene PTEN through modulation of Tet methylcytosine dioxygenase expression. Increases HIF-1α mRNA and promotes survival under hypoxia[110]
miRNA-155InflammationIntensifies IL-6 and IL-8 levels and enhances inflammatory response[115,116]
GOLM1Tumor occurrence, metastasisActivates GSK-3β/MMP signaling, a potential biomarker[38,117]
miRNA-320a, miRNA-451a Anti-tumorigenic effectsInhibits proliferation, migration, angiogenesis[118,119]
LncRNA H19Enhanced angiogenesisIncreases VEGF secretion and VEGF-R1 production[120]
miRNA-32AngiogenesisSuppresses PTEN and activates PI3K/Akt pathway[110]
VASNTumor development, angiogenesisStimulates endothelial cell proliferation and neovascularization[121]
miRNA-200b-3pAnti-angiogenicInhibits erythroblast transformation-related genes[122]
HMGB1Immune evasionExpands regulatory B cells, facilitating tumor survival[123]
Exosomal SMAD, Caveolin, MET, caveolins, S100, ITGαvβ5, OXL4, SDF-1α, IL-6, IL-8, AFP, and GGTHCC progressionCell adhesion, motility, invasive abilities, metastasis, angiogenesis, and cell proliferation[124,125,126,127,128]
miRNA-92a-2-5pPromotes metastasisEnhances cancer cell invasion via AR/PHLPP/p-AKT/β-catenin[129]
miRNA-125a/bImpedes tumor-associated macrophagesTargets CD90 in tumor-associated macrophages[130]
Table 3. ECVs in enhancing immunotherapy and managing therapy resistance.
Table 3. ECVs in enhancing immunotherapy and managing therapy resistance.
FunctionExampleDescriptionContext and Patient UseReference
ImmunomodulationPD-L1-enriched exosomesExosomes carrying PD-L1 inhibited T-cell activity, modulating the immune environment to favor tumor growth and impacting responses to immunotherapyOncology immunotherapy research—research phase[174]
Drug ResistanceExosomes carrying miRNA-1247-3pEnhanced resistance to sorafenib in HCC by altering gene expression related to drug metabolism and cellular survival pathwaysChemoresistance mechanisms study—research phase[135]
Chemotherapy DeliveryExosomes for Doxorubicin deliveryFacilitated targeted delivery of Doxorubicin, enhancing drug specificity and minimizing off-target effectsTargeted chemotherapy research—early clinical trials[178,179]
Gene TherapymiRNA-220a/220b/429 mimicsDelivered miRNAs that regulate oncogenic pathways, providing a method for precision gene therapyGene therapy innovation—research phase[174]
Chemoresistance MechanismsExosomes carrying circRNA-SORE and miRNAs in chemoresistanceStudied circRNAs and miRNAs that enhance cellular mechanisms of resistance to chemotherapy agentsMolecular oncology exploration—research phase[84,190,191,192,193,194,195]
Enhanced Immune SurveillanceExosomes carrying HMGB1Examined the role of HMGB1-bearing exosomes in modulating immune surveillance in HCCImmune surveillance enhancement—research phase[176]
Prognostic BiomarkersCirculating exosomal PD-L1 levelsDeveloped and validated exosomal PD-L1 as a biomarker for assessing responses to immunotherapyBiomarker development—early clinical trials[174]
Therapeutic Drug DeliveryExosomes in targeted drug deliveryEmployed engineered exosomes for specific drug conveyance to tumor sites, reducing systemic toxicityDrug delivery system development—early clinical trials[175,176,177,178,179]
Circadian Influence on TherapyVariability in exosome release by circadian rhythmsCircadian rhythms affect the secretion and composition of exosomes, influencing the responseChronotherapy research—research phase[8,200]
Table 4. Examples of circadian regulation of ECVs.
Table 4. Examples of circadian regulation of ECVs.
ExampleFindingReference
Circadian Variation in ECV QuantityECV quantity extracted from peripheral blood, bone marrow, and lungs of mice exhibited time-dependent changes[215]
Circadian Control of Exosomal CargoFlot1 regulated circadian control over MMP 14 in tendon fibroblast small ECVs[200]
Impact of Night Shift Work on ECV CargoNight shift work disrupted circadian rhythms and exosomal cargo, influencing metabolic health[216]
Circadian Variations in Plasma ECV CharacteristicsPlasma ECVs were larger at 10:00 compared to 22:00 in HIV patients[217]
Influence of Exosomal Cargo on Insulin ResistanceExosomes from obese mice or patients with type II diabetes could induce insulin resistance in lean mice[218,219,220]
Circadian Normalization Factor for Small ECV BiomarkersBiomarker TSG101 levels in urine showed a circadian correlation with small ECV excretion in healthy rats[221]
Table 5. Impact of circadian clock components on cancer progression via ECVs.
Table 5. Impact of circadian clock components on cancer progression via ECVs.
Impact of Circadian ClockDescriptionAssociated Conditions/ModelsReference
Circadian Component and Cancer Role
BMAL1 FunctionBMAL1 promotes metastasis in colorectal cancer through increased exosome secretionColorectal cancer
The link between circadian control and tumor progression
[17]
SIRT1 MechanismsSIRT1 interacts with CLOCK-BMAL1 to modulate PER2 stability, affecting exosome secretion and tumor environment interactionsFacilitates tumor microenvironment degradation
Breast cancer
[252,253,254,255]
SIRT1 MechanismsSIRT1 loss leads to enhanced exosome secretion, impacting breast cancer and diabetic nephropathyDiabetic nephropathy[256,257,258]
SIRT1 in CancerShift-work-related miRNA-22-3p uptake by nurses is linked to increased insulin resistance, highlighting its potential as a biomarker for diabetes preventionOvarian cancer[259]
Shift Work and its Effects
Shift-Work-Induced ChangesChronic shift work in mice alters intestinal flora and increases colonic permeability, affecting circadian gene expression via changes in plasma ECV componentsMouse model of chronic shift work[251]
Night Shift Exosomal ImpactNight shift conditions lead to reduced insulin sensitivity in adipocytes through alterations in exosome content, affecting core clock genesSimulated shift work study
Affects core clock genes and metabolic functions
[216]
Shift Work and Diabetes RiskShift-work-related miRNA-22-3p uptake by nurses is linked to increased insulin resistance, highlighting its potential as a biomarker for diabetes preventionShift nurses[267]
Exosomal miRNAs and Circadian GenesmiRNA-3614-5p as a messenger of circadian misalignment in night shift workersContributes to metabolic dysfunction[216]
Circadian Genes and miRNACirculating miRNAs like miRNA-219, miRNA-152, miRNA-494, and miRNA-142-3p regulate clock genesAffects BMAL1 and PER1 in circadian regulation[268,269,270,271,272]
Circadian Genes and miRNAExosomal miRNAs modulate peripheral circadian oscillators in various disease modelsHas impact on glioma progression and Parkinson’s disease[9,264]
Melatonin’s Therapeutic Role
Melatonin-Enhanced ExosomesMelatonin pre-treatment enhances anticancer and anti-inflammatory properties of exosomes, improving their therapeutic effectiveness in various clinical settingsCancer therapies, various models[273,274,275]
Anti-Inflammatory EffectsMelatonin-treated exosomes significantly reduce inflammatory markers and PD-L1 expression in macrophages, aiding in cancer therapy and reducing immune evasionHepatocellular carcinoma[247]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Fekry, B.; Ugartemendia, L.; Esnaola, N.F.; Goetzl, L. Extracellular Vesicles, Circadian Rhythms, and Cancer: A Comprehensive Review with Emphasis on Hepatocellular Carcinoma. Cancers 2024, 16, 2552. https://doi.org/10.3390/cancers16142552

AMA Style

Fekry B, Ugartemendia L, Esnaola NF, Goetzl L. Extracellular Vesicles, Circadian Rhythms, and Cancer: A Comprehensive Review with Emphasis on Hepatocellular Carcinoma. Cancers. 2024; 16(14):2552. https://doi.org/10.3390/cancers16142552

Chicago/Turabian Style

Fekry, Baharan, Lierni Ugartemendia, Nestor F. Esnaola, and Laura Goetzl. 2024. "Extracellular Vesicles, Circadian Rhythms, and Cancer: A Comprehensive Review with Emphasis on Hepatocellular Carcinoma" Cancers 16, no. 14: 2552. https://doi.org/10.3390/cancers16142552

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop