Search Results (11,387)

Background: Lung cancer is the leading cause of cancer-related mortality globally, with late-stage diagnoses contributing to poor survival rates. While lung cancer screening with low-dose computed tomography (LDCT) has proven effective in reducing mortality among heavy smokers, its limitations, including high false-positive rates and resource intensiveness, restrict widespread use. Liquid biopsy, particularly using microRNA (miRNA) biomarkers, offers a promising adjunct to current screening strategies. This study aimed to evaluate the predictive power of a panel of serum miRNA biomarkers for lung cancer detection. Patients and Methods: A case-control study was conducted at two tertiary hospitals, enrolling 82 lung cancer cases and 123 controls. We performed an extensive literature review to shortlist 25 candidate miRNAs, of which 16 showed a significant two-fold increase in expression compared to the controls. Machine learning techniques, including Random Forest, K-Nearest Neighbors, Neural Networks, and Support Vector Machines, were employed to identify the top six miRNAs. We then evaluated predictive models, incorporating these biomarkers with lung nodule characteristics on LDCT. Results: A prediction model utilising six miRNA biomarkers (mir-196a, mir-1268, mir-130b, mir-1290, mir-106b and mir-1246) alone achieved area under the curve (AUC) values ranging from 0.78 to 0.86, with sensitivities of 70–78% and specificities of 73–85%. Incorporating lung nodule size significantly improved model performance, yielding AUC values between 0.96 and 0.99, with sensitivities of 92–98% and specificities of 93–98%. Conclusions: A prediction model combining serum miRNA biomarkers and nodule size showed high predictive power for lung cancer. Integration of the prediction model into current lung cancer screening protocols may improve patient outcomes. Full article

Smilax glabra flavonoids (SGF), the active components of Smilax glabra Roxb., have been demonstrated to exhibit antioxidant activity and metabolic benefits in obesity, leading us to further explore their antitumor effects in obesity-related colorectal cancer (CRC). This study investigated the antiproliferative effects of SGF on obesity-related CRC by using a murine colon adenocarcinoma MC38 cell line. The underlying mechanisms were further explored via RNA-Seq and bioinformatics analysis in combination with experimental validation. SGF was proven to possess cytotoxic effects against MC38 cells, indicated by the inhibition of proliferation and migration, especially in an adipocyte-rich environment. In line with this, SGF exhibited much stronger antiproliferative effects on MC38-transplanted tumors in obese mice. Transcriptomics analysis showed that the cytotoxic effects of SGF might be related to the AMPK pathway and ferroptosis. On this basis, SGF was confirmed to induce ferroptosis and dictate ferroptosis sensitivity in a high-fat context mimicked by a two-step conditioned medium (CM) transfer experiment or a Transwell coculture system. The results of Western blotting validated that SGF suppressed the phosphorylation of AMPK, accompanied by alterations in the biomarkers of ferroptosis. These results demonstrate that SGF exerts in vitro and in vivo antiproliferative effects in obesity-associated CRC through inhibiting AMPK activation, thereby driving ferroptosis. Full article

Exosomes have emerged as pivotal players in precision oncology, offering innovative solutions to longstanding challenges such as metastasis, therapeutic resistance, and immune evasion. These nanoscale extracellular vesicles facilitate intercellular communication by transferring bioactive molecules that mirror the biological state of their parent cells, positioning them as transformative tools for cancer diagnostics and therapeutics. Recent advancements in exosome engineering, artificial intelligence (AI)-driven analytics, and isolation technologies are breaking barriers in scalability, reproducibility, and clinical application. Bioengineered exosomes are being leveraged for CRISPR-Cas9 delivery, while AI models are enhancing biomarker discovery and liquid biopsy accuracy. Despite these advancements, key obstacles such as heterogeneity in exosome populations and the lack of standardized isolation protocols persist. This review synthesizes pioneering research on exosome biology, molecular engineering, and clinical translation, emphasizing their dual roles as both mediators of tumor progression and tools for intervention. It also explores emerging areas, including microbiome–exosome interactions and the integration of machine learning in exosome-based precision medicine. By bridging innovation with translational strategies, this work charts a forward-looking path for integrating exosomes into next-generation cancer care, setting it apart as a comprehensive guide to overcoming clinical and technological hurdles in this rapidly evolving field. Full article

Introduction: Endometrial cancer (EC) is one of the most common gynecologic cancers, with an increasing incidence due to variables such as aging and lifestyle changes. Current biomarkers exhibit limited prognostic value, despite advancements in understanding their molecular basis, underscoring the necessity for new molecular markers. Microtubule affinity-regulating kinase 3 (MARK3) has been identified as a potential candidate owing to its established prognostic significance in various cancers; however, its function in endometrial cancer (EC) is not yet well understood. Methods: This study investigates the function of MARK3 in endometrial cancer through the analysis of Ishikawa and HEC-1B cell lines. A series of assays were conducted, including colony formation, CCK-8 viability, EDU proliferation assays, scratch wound healing tests, and Transwell migration assays, to investigate the effects of MARK3 overexpression. We conducted RT-qPCR, Western blot, and immunofluorescence assays to evaluate the molecular mechanisms influencing cell proliferation and migration. Bioinformatics analysis utilized publicly available datasets to examine the gene enrichment and co-expression networks. Results: The overexpression of MARK3 markedly reduced colony formation in both Ishikawa (p = 0.0039) and HEC-1B (p = 0.0014) cell lines. Furthermore, the overexpression of MARK3 led to decreased cell viability, as demonstrated by the EDU assay results (Ishikawa-OE p = 0.0302; HEC-OE p = 0.0037). The molecular analysis supported these findings, indicating an increase in phosphorylated AKT (pAKT), thereby suggesting MARK3’s role in regulating cell survival pathways. Gene enrichment analysis revealed pathways associated with cell cycle regulation and apoptosis, whereas co-expression analysis pinpointed critical interacting genes that may play a role in EC progression. Conclusions: MARK3 is essential in the regulation of cell proliferation and migration in endometrial cancer, positioning it as a potential prognostic biomarker and therapeutic target. This study represents the inaugural investigation into the functional role of MARK3 in endothelial cell progression, thereby enhancing our comprehension of its mechanistic influence on cancer biology and its implications for personalized therapy. Bioinformatics analysis reinforces the relevance of MARK3 in endometrial cancer, offering new insights into its clinical significance. Full article

Background: The majority of head and neck cancers (HNCs) occur in the larynx. In clinical practice, adverse effects are frequently observed in laryngeal cancer (LC) patients undergoing radiotherapy (RT). Therefore, investigating markers that can predict these unfavorable events is of interest. Long non-coding RNAs (lncRNAs) have emerged as potential biomarkers for the early identification of patients susceptible to post-RT toxicity. MALAT1 and NEAT1 regulate various cellular processes, the inflammatory response, and resistance to anti-cancer treatments; however, their impact on the portability of post-RT adverse effects remains unknown. The aim of this study was to evaluate the clinical value of two plasma-circulating lncRNAs, MALAT1 and NEAT1, as predictive biomarkers for post-RT adverse effects in LC patients. Methods: The expression levels of the studied lncRNAs were determined using real-time quantitative reverse transcription PCR (qRT-PCR) in plasma samples obtained from 70 LC patients before the initiation of RT. These levels were then correlated with patient outcomes. Results: A low expression of MALAT1 was associated with a significantly higher probability of anemia, liver failure, and severe malnutrition (OR = 5.36; p = 0.040, OR = 6.07; p = 0.037, OR = 9.75; p < 0.001, respectively) after the completion of RT. Similarly, patients with low NEAT1 expression had a significantly higher risk of anemia, liver failure, and mild or severe malnutrition (OR = 5.26; p = 0.020, OR = 5.70; p = 0.016, OR = 13.09; p = 0.002, respectively). Simultaneous lower expression levels of both lncRNAs were significantly associated with shorter median overall survival (OS) in RT-treated LC patients (HR = 5.44; p = 0.001). Conclusions: The analysis of MALAT1 and NEAT1 expression indicates clinical utility in predicting toxic events induced by RT-based therapy. Full article

In pancreatic cancer (PC), vascular endothelial growth factor (VEGF) and its primary receptor, vascular endothelial growth factor receptor (VEGFR)-2, are central drivers of angiogenesis and metastasis, with their overexpression strongly associated with poor prognosis. In some PC patients, VEGF levels correlate with disease stage, tumor burden, and survival outcomes. However, therapies targeting VEGF and VEGFR-2, including tyrosine kinase inhibitors (TKIs) and monoclonal antibodies, have demonstrated limited efficacy, partly due to the emergence of resistance mechanisms. Resistance appears to stem from the activation of alternative vascularization pathways. This review explores the multifaceted roles of VEGFRs in pancreatic cancer, including VEGFR-1 and VEGFR-3. Potential strategies to improve VEGFR-targeting therapies, such as combination treatments, the development of more selective inhibitors, and the use of biomarkers, are discussed as promising approaches to enhance treatment efficacy and outcomes. Full article

Non-coding RNAs (ncRNAs) play crucial roles in colorectal cancer (CRC) development and progression. Recent developments in single-cell transcriptome profiling methods have revealed surprising levels of expression variability among seemingly homogeneous cells, suggesting the existence of many more cell types than previously estimated. This review synthesizes recent advances in ncRNA research in CRC, emphasizing single-cell bioinformatics approaches for their analysis. We explore computational methods and tools used for ncRNA identification, characterization, and functional prediction in CRC, with a focus on single-cell RNA sequencing (scRNA-seq) data. The review highlights key bioinformatics strategies, including sequence-based and structure-based approaches, machine learning applications, and multi-omics data integration. We discuss how these computational techniques can be applied to analyze differential expression, perform functional enrichment, and construct regulatory networks involving ncRNAs in CRC. Additionally, we examine the role of bioinformatics in leveraging ncRNAs as diagnostic and prognostic biomarkers for CRC. We also discuss recent scRNA-seq studies revealing ncRNA heterogeneity in CRC. This review aims to provide a comprehensive overview of the current state of single-cell bioinformatics in ncRNA CRC research and outline future directions in this rapidly evolving field, emphasizing the integration of computational approaches with experimental validation to advance our understanding of ncRNA biology in CRC. Full article

Background: Depressive symptoms (DepS) are prevalent among patients with breast cancer. Offering an anti-inflammatory diet is a promising strategy for DepS management, but it is costly and difficult to scale up. Instead, anti-inflammatory dietary education is cost-effective and may be more conducive to the promotion of an anti-inflammatory diet strategy. Methods: A prospective, assessor-blinded, two-arm randomized controlled trial was designed to determine the effects of 12-week anti-inflammatory dietary education on DepS in breast cancer patients with depression. Adult female patients with depression and receiving adjuvant chemotherapy were recruited. Participants in the intervention group received anti-inflammatory dietary education, while the control group received routine nursing care. Outcomes included the Center for Epidemiologic Studies Depression Scale (CES-D) score, energy-adjusted dietary inflammatory index (E-DII), plasma inflammatory biomarkers, and quality of life (QoL), which were all assessed at baseline and after a 12-week follow-up. The robustness of the estimates was investigated through sensitivity analyses. A post hoc power analysis was conducted to establish the observed effect sizes for the primary outcomes. Results: A total of 88.6% (62/70) of the participants completed the entire 12-week follow-up. No statistically significant between-group differences were found in the baseline characteristics, including sociodemographic factors, disease-related characteristics, and lifestyle factors. After the intervention, both the CES-D score (p = 0.040) and E-DII (p < 0.001) in the intervention group were significantly lower than in the control group, while the QoL was significantly increased (p < 0.001). Compared with the baseline, the tumor necrosis factor-α (TNF-α) (p = 0.002) and C-reactive protein (CRP) (p = 0.045) levels were significantly lower in the intervention group but not in the control group. Conclusions: Anti-inflammatory dietary education may improve DepS and QoL in breast cancer patients with depression and undergoing chemotherapy by regulating inflammation. Given its acceptability and practicality, this strategy may be incorporated into routine cancer care. Full article

Reprogramming of metabolic pathways is crucial to guarantee the bioenergetic and biosynthetic demands of rapidly proliferating cancer cells and might be related to treatment resistance. We have previously demonstrated the deregulation of the succinate pathway in head and neck squamous cell carcinoma (HNSCC) and its potential as a diagnostic and prognostic marker. Now we aim to identify biomarkers of resistance to radiotherapy (RT) by analyzing the expression of genes related to the succinate pathway and nutrient flux across the cell membrane. We determined the transcriptional expression of succinate receptor 1 (SUCNR1), succinate dehydrogenase A (SDHA), and the solute carrier (SLC) superfamily transporters responsible for the influx or efflux of a wide variety of nutrients (SLC2A3 and SLC16A3) in tumoral tissue from 120 HNSCC patients treated with RT or chemoradiotherapy (CRT). Our results indicated that the transcriptional expression of the glucose transporter SLC2A3 together with SDHA had the best predictive capacity for local response after treatment with RT or CRT. High SLC2A3 and SDHA expression predicted poor outcomes after RT or CRT, with these patients having a 4.2 times higher risk of local recurrence compared to the rest of the patients. These results might indicate that tumors that shifted toward a higher glucose influx and a higher oxidation of succinate via mitochondrial complex II present an ideal environment for radioresistance development. Patients with a high transcriptional expression of both SLC2A3 and SDHA had a significantly higher risk of local recurrence after treatment with RT or CRT. Full article

Early diagnosis is critical for improving outcomes in cancer patients; however, the application of diagnostic markers derived from serum proteomic screening remains challenging. Artificial intelligence (AI), encompassing deep learning and machine learning (ML), has gained increasing prominence across various scientific disciplines. In this study, we utilized cervical cancer (CC) as a model to develop an AI-driven pipeline for the identification and validation of serum biomarkers for early cancer diagnosis, leveraging mass spectrometry-based proteomics data. By processing and normalizing serum polypeptide differential peaks from 240 patients, we employed eight distinct ML algorithms to classify and analyze these differential polypeptide peaks, subsequently constructing receiver operating characteristic (ROC) curves and confusion matrices. Key performance metrics, including accuracy, precision, recall, and F1 score, were systematically evaluated. Furthermore, by integrating feature importance values, Shapley values, and local interpretable model-agnostic explanation (LIME) values, we demonstrated that the diagnostic area under the curve (AUC) achieved by our multi-dimensional learning models approached 1, significantly outperforming the diagnostic AUC of single markers derived from the PRIDE database. These findings underscore the potential of proteomics-driven integrated machine learning as a robust strategy to enhance early cancer diagnosis, offering a promising avenue for clinical translation. Full article

Background/Objectives: Laryngeal squamous cell carcinoma represents one of the most common head and neck cancers with a five-year survival rate that, despite diagnostic and therapeutic advances, has not shown any significant improvement in recent decades. Oxidative stress, generated by an imbalance between reactive oxygen species and cellular antioxidant systems, is considered a central mechanism in the carcinogenesis of laryngeal squamous cell carcinoma, causing DNA damage and genomic alterations. Methods: This prospective observational paired case–control study focused on the evaluation of antioxidant proteins, such as superoxide dismutase, catalase, heme-oxygenase 1, vimentin, metallothionein, and nuclear factor erythroid 2-related factor 2, in cancer tissues from fifteen patients with laryngeal squamous cell carcinoma, using adjacent healthy tissues as controls. Results: The results show a statistically significant overexpression of all proteins analyzed in cancer tissues compared to controls, with relevant correlations between specific biomarkers and clinical characteristics, age, sex, smoking habits, and degree of tumor differentiation. Conclusions: These preliminary studies, while limited by sample size and the complexity of molecular regulation, indicate that the overexpression of antioxidant enzymes in laryngeal squamous cell carcinoma tissues, along with their correlations with key clinical parameters, underscores a context-dependent role of oxidative stress in tumor progression. A deeper understanding of oxidative stress mechanisms could contribute to advance personalized management strategies for laryngeal squamous cell carcinoma, potentially improving treatment outcomes and patient prognosis. Full article

Background and Objectives: Neurotrophic receptor tyrosine kinase 3 (NTRK3) is a member of the tropomyosin receptor kinase family of receptor tyrosine kinases, which play a crucial role in neural development. However, owing to the limited number of studies about NTRK3 and cancer, we aimed to investigate NTRK3 as a potential prognostic marker for breast cancer (BC). Materials and Methods: We conducted a comprehensive analysis of NTRK3 expression in BC using the Tumor Immune Estimation Resource, Gene Expression Profiling Interactive Analysis 2, and Kaplan–Meier Plotter databases. We also explored the association between NTRK3 expression and tumor-infiltrating immune cells. Results: Low NTRK3 expression showed poorer prognosis in BC, as well as with T stage, pathology, and the Luminal subtype. In BC (BRCA), NTRK3 was positively correlated with CD4+ T cell, CD8+ T cell, macrophage, and neutrophil infiltration. Conclusions: These results suggest that NTRK3 may serve as a prognostic biomarker and provide novel insights into tumor immunology in BC. Therefore, NTRK3 represents a potential diagnostic and therapeutic target for BC treatment. Full article

Introduction: Liquid biopsies provide a less-invasive option to tissue biopsies for the early diagnosis, prognosis, and tailored therapy of colorectal cancer (CRC). CRC is a major cause of cancer-related death, and early identification is essential for improving patient outcomes. Review: Conventional diagnostic techniques, including colonoscopy and tissue biopsy, may be enhanced by liquid biopsies that examine circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), and other indicators present in body fluids. These markers provide significant insights into tumor biology, heterogeneity, and therapeutic response. CTCs detected in early-stage CRC have prognostic significance for disease recurrence and survival, while ctDNA investigation may uncover genetic mutations, epigenetic alterations, and tumor development. The identification of ctDNA in minimal residual disease (MRD) postsurgery correlates with an elevated risk of recurrence and unfavorable prognosis, underscoring its use in assessing treatment effectiveness. Furthermore, non-coding RNAs (ncRNAs) contained inside EVs provide potential prospective biomarkers and therapeutic targets, facilitating diagnosis and treatment assessment. Notwithstanding the potential of liquid biopsies, obstacles persist in assay standardization, sensitivity enhancement, and the management of tumor heterogeneity. Additional extensive research is required to determine their function in clinical practice. Conclusion: Overall, liquid biopsies serve as a potential instrument for real-time monitoring, evaluating therapy responses, and directing individualized therapeutic strategies in CRC patients. Full article

Treatment of resectable advanced-stage melanoma with neoadjuvant immunotherapy is rapidly becoming the new standard of care due to significant improvements in event-free survival (EFS) compared to surgery first followed by immunotherapy. The level of responsiveness seen in patients receiving immune checkpoint inhibitors (ICIs) must be mechanistically understood not only for the standardization of treatment but also to advance the novel concept of personalized cancer immunotherapy. This review aims to elucidate markers of the tumor microenvironment (TME) and blood that can predict treatment outcome. Interestingly, the canonical proteins involved in the molecular interactions that immunotherapies aim to disrupt have not been consistent indicators of treatment response, which amplifies the necessity for further research on the predictive model. Other major discussions surrounding neoadjuvant therapy involve the higher-level investigation of ICI efficacy due to the ability to examine a post-treatment tumor molecularly and pathologically, which this review will also cover. As neoadjuvant ICI becomes the standard of care in advanced melanoma treatment, further research aiming to identify more predictive biomarkers of treatment response to advance medical decision-making and patient care should continue to be sought after. Full article

Background: Cervical cancer, primarily driven by persistent high-risk human papillomavirus (HPV) infections, remains a significant global health challenge. Systemic inflammatory markers, such as neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and lymphocyte/monocyte ratio (LMR), may reflect disease progression. This study examines the association between these markers and p16 positivity in cervical intraepithelial neoplasia (CIN) cases. Methods: This retrospective analysis included 395 patients undergoing LEEP conization. Data on HPV status, p16 immunostaining, and hematological parameters were collected. Statistical analyses, including Mann–Whitney U and chi-square tests, assessed relationships between markers and outcomes, with significance set at p < 0.05. Results: Elevated NLR was significantly associated with p16 positivity (p = 0.011) and HPV DNA positivity (p = 0.04). HPV-positive individuals showed higher mean NLR (2.15) compared to HPV-negative individuals (1.61). Receiver operating characteristic (ROC) analysis demonstrated moderate diagnostic accuracy for NLR (AUC = 0.610), highlighting its potential as a biomarker. No significant associations were observed for PLR or LMR with p16 positivity. These findings suggest systemic inflammation, indicated by NLR, contributes to HPV persistence and CIN progression. Conclusions: NLR is a valuable prognostic biomarker for HPV-related cervical disease, correlating with both p16 and HPV DNA positivity. Incorporating hematological and immunohistochemical markers may enhance personalized cervical cancer management. Full article