Search Results (4,739)

Hepatic cancer is a world health concern due to its high lethality. The main risk factor worldwide is having hepatic cirrhosis. The etiology of hepatic cirrhosis has changed in recent years, with metabolic-associated steatotic liver disease (MASLD) becoming the leading cause, displacing hepatitis C and B viruses and alcoholic liver disease. It is of the utmost importance to develop screening programs in at-risk populations for early detection. The survival rate of HCC, as determined by a group of specialists or an interdisciplinary committee, is a challenge we have taken on in a public health hospital in Ecuador. This retrospective study identified 71 patients diagnosed with hepatocellular carcinoma, mostly middle-aged men with a history of liver cirrhosis. No significant association was found between the presence of cirrhosis, laboratory abnormalities, and survival. However, the identification by imaging vascular invasion and extrahepatic extension were associated. This study highlights that patients with liver lesions identified through HCC screening have a higher survival rate over a one-year follow-up period. Full article

Oral cancer remains a critical global health challenge, with delayed diagnosis driving high morbidity and mortality. Despite progress in artificial intelligence, computer vision, and medical imaging, early detection tools that are accessible, explainable, and designed for patient engagement remain limited. This study presents a novel system that combines a patient-centred chatbot with a deep learning framework to support early diagnosis, symptom triage, and health education. The system integrates convolutional neural networks, class activation mapping, and natural language processing within a conversational interface. Five deep learning models were evaluated (CNN, DenseNet121, DenseNet169, DenseNet201, and InceptionV3) using two balanced public datasets. Model performance was assessed using accuracy, sensitivity, specificity, diagnostic odds ratio (DOR), and Cohen’s Kappa. InceptionV3 consistently outperformed the other models across these metrics, achieving the highest diagnostic accuracy (77.6%) and DOR (20.67), and was selected as the core engine of the chatbot’s diagnostic module. The deployed chatbot provides real-time image assessments and personalised conversational support via multilingual web and mobile platforms. By combining automated image interpretation with interactive guidance, the system promotes timely consultation and informed decision-making. It offers a prototype for a chatbot, which is scalable and serves as a low-cost solution for underserved populations and demonstrates strong potential for integration into digital health pathways. Importantly, the system is not intended to function as a formal screening tool or replace clinical diagnosis; rather, it provides preliminary guidance to encourage early medical consultation and informed health decisions. Full article

Cytoskeleton-associated protein 4 (CKAP4) has emerged as a critical player in gastrointestinal (GI) cancer progression, diagnosis, and therapy. This comprehensive review synthesizes current knowledge on CKAP4′s multifaceted roles across GI malignancies, providing novel insights into its mechanisms of action and clinical potential. Its interaction with DKK1 and subsequent activation of the PI3K/AKT pathway underscores its role in promoting tumor growth. This review also highlights novel insights into CKAP4′s mechanisms of action beyond the well-established DKK1-CKAP4 axis, including its interaction with integrin β1 and involvement in angiogenesis through the FMNL2/EGFL6/CKAP4/ERK pathway. CKAP4′s impact on tumor microenvironment and immune evasion is elucidated, offering a new perspective on its contribution to cancer progression. In addition, CKAP4 arises as a promising serum biomarker for early detection and prognosis across multiple GI cancers, emphasizing its potential superiority over traditional markers. The therapeutic potential of targeting CKAP4 is extensively explored, including novel approaches like anti-CKAP4 antibodies and aptamers, and their synergistic effects with existing treatments. By integrating findings from esophageal, gastric, pancreatic, and colorectal cancers, this review provides a unique, comprehensive overview of CKAP4 in GI oncology, underscoring CKAP4′s potential to revolutionize GI cancer diagnosis and treatment and paving the way for future translational research. Full article

Background/Objectives: Family physicians are key stakeholders in the implementation of cancer prevention strategies, including risk factor assessment, lifestyle counseling, and early detection. Despite this, integration of personalized prevention into routine practice remains limited. This study aimed to explore family physicians’ perspectives on barriers, training needs, and collaboration opportunities in cancer prevention. Methods: A mixed-methods study was conducted using an exploratory sequential design. The qualitative phase involved semi-structured interviews with 12 family physicians from the North-West Region of Romania. Thematic analysis was employed to identify main challenges and opportunities. Findings informed the development of a structured online survey completed by 50 family physicians. Descriptive and comparative statistical analyses were applied to assess trends and subgroup differences. Results: Interviews and survey data revealed multiple barriers to cancer prevention in primary care: insufficient consultation time, limited access to diagnostic tools, administrative workload, and low patient health literacy. Physicians reported moderate familiarity with personalized prevention but expressed strong interest in further training, particularly through flexible and interactive learning formats. Collaboration with cancer centers was considered suboptimal; participants emphasized the need for streamlined referral pathways and improved communication. Conclusions: The study highlights systemic and educational gaps affecting cancer prevention efforts in family medicine. Tailored training programs, digital integration with cancer centers, and targeted policy adjustments are needed to enhance prevention capacity within primary care. Full article

Human papillomavirus (HPV) infection is a primary driver of cervical cancer. Integration of HPV into the human genome causes persistent expression of viral oncogenes E6 and E7, which promote carcinogenesis and disrupt host genomic function. However, the impact of integration on host gene expression remains incompletely understood. We used multimodal RNA sequencing, combining total RNA-seq and Cap Analysis of Gene Expression (CAGE), to clarify virus–host interactions after HPV integration. HPV-derived transcripts were detected in 17 of 20 clinical samples. In most specimens, transcriptional start sites (TSSs) showed predominant early promoter usage, and transcript patterns differed with detectable E4 RNA region. Notably, the high RNA expressions of E4 region and viral-human chimeric RNAs were mutually exclusive. Chimeric RNAs were identified in 13 of 17 samples, revealing 16 viral integration sites (ISs). CAGE data revealed two patterns of TSS upregulation centered on the ISs: a two-sided pattern (43.8%) and a one-sided pattern (31.3%). Total RNA-seq showed upregulation of 12 putative cancer-related genes near ISs, including MAGI1-AS1, HAS3, CASC8, BIRC2, and MMP12. These findings indicate that HPV integration drives transcriptional activation near ISs, enhancing expression of adjacent oncogenes. Our study deepens understanding of HPV-induced carcinogenesis and informs precision medicine strategies for cervical cancer. Full article

Breast cancer (BC) is one of the most common malignancies among women worldwide. Despite advances in early detection and treatment, prognosis remains highly variable. Molecular biomarkers, such as microRNAs (miRNAs), have emerged as promising tools to refine prognostic assessment. Among them, miR-21 is consistently overexpressed in solid tumors and implicated in key oncogenic pathways. This systematic review and meta-analysis aimed to clarify the prognostic significance of miR-21 in BC and explore its molecular mechanisms through bioinformatic analyses. A systematic search of PubMed, Scopus, and Web of Science up to April 2025 identified 18 eligible observational studies. Pooled analyses showed that high miR-21 expression was significantly associated with poorer overall survival (OS) (HR = 2.37, 95% CI: 1.42–3.98) and recurrence-related outcomes (DFS/RFS) (HR = 2.10, 95% CI: 1.32–3.34). Subgroup analyses confirmed robust associations across different cut-off definitions and revealed particularly strong effects in triple-negative BC (HR = 5.69) and mixed subtypes (HR = 2.55), but no significant association in HER2-positive BC. Bioinformatic analysis identified target genes such as PTEN, BCL2, STAT3, and MYC, involved in apoptosis regulation, proliferation, NF-κB signaling, and immune modulation. These findings provide consistent evidence that miR-21 is a promising minimally invasive prognostic biomarker in BC, particularly in aggressive subtypes, and support its integration into future multimodal prognostic models. Full article

Background: Breast cancer-related lymphedema (BCRL) is a common and debilitating treatment-related adverse event that can profoundly impact quality of life and financial well-being. Although prospective surveillance and early intervention for BCRL have been shown to reduce the incidence and severity of this chronic condition, diagnostic accuracy of screening, programmatic utilization and efficacy vary widely. We describe the protocol for the BCRL Prospective Surveillance Model (PSM) and Early Intervention Program at the Dana-Farber Brigham Cancer Center that aims to address these issues by augmenting arm measurements (standard of care) with use of patient-reported outcome metrics (PROMs). Methods: Women with newly diagnosed stage I-III breast cancer at high risk for developing BCRL based on tumor and treatment characteristics are eligible for inclusion in our PSM care pathway, which uses both the Breast Cancer and Lymphedema Symptom Experience Index PROMs and arm measurements for screening. Screening begins prior to the initiation of neoadjuvant therapy and continues at regular intervals postoperatively. A positive screen, defined as new patient-reported arm swelling/heaviness and/or relative volume change (RVC) ≥ 5% in the affected limb, triggers consideration for multidisciplinary early intervention. Analysis: The BCRL detection rate will be compared to years previous to protocol development. PSM feasibility will be determined according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Efficacy of the PSM will be gauged by comparing change in patient-reported outcomes of interest and arm volume measurement pre and post early intervention. Feasibility will be determined by calculating the percentage of PSM-eligible individuals who complete all PSM activities in a 1-year span. Characteristics of participants versus non-participants in the target population will be compared. Furthermore, 1:1 semi-structured interviews with enrolled patients will be performed to understand facilitators and barriers to implementation. Conclusions: The findings from this study will be used to develop a standardized approach to PSM and early intervention that can be adapted to both resource-modest and resource-abundant healthcare infrastructures. Full article

Pancreatic ductal adenocarcinoma (PDAC) represents a malignancy characterized by one of the lowest survival rates; furthermore, at the time of diagnosis, the majority of tumors are deemed unresectable. Consequently, there exists a pressing need to investigate early signs and symptoms, as well as to implement screening protocols for patients at risk of developing PDAC. By doing so, we may enhance the potential for improved treatment outcomes in light of the typically poor prognosis associated with PDAC. A review of recent literature focused on symptoms that manifest prior to the diagnosis of PDAC has been conducted, emphasizing the underlying biological mechanisms and potential screening applications, alongside data pertaining to the influence of these symptoms on prognosis and treatment. Additionally, the roles of pre-existing pain, depression, diabetes mellitus, and paraneoplastic syndromes in treatment and outcomes were scrutinized to ascertain the feasibility of integrating these factors into clinical practice. Full article

Fusobacterium nucleatum (Fn) has been increasingly recognized as a crucial mediator of colorectal cancer (CRC) biology, particularly in microsatellite-stable (MSS) tumors, where immune checkpoint inhibitors (ICIs) have shown limited efficacy. Rather than representing a passive microbial passenger, Fn actively shapes tumor behavior by adhering to epithelial cells, activating oncogenic signaling, and promoting epithelial–mesenchymal transition (EMT). At the same time, it remodels the tumor microenvironment, driving immune suppression through inhibitory receptor engagement, accumulation of myeloid-derived cells, and metabolic reprogramming of tumor-associated macrophages. These mechanisms converge to impair cytotoxic immunity and contribute to both intrinsic and acquired resistance to ICIs. Beyond immune escape, Fn interferes with conventional chemotherapy by sustaining autophagy and blocking ferroptosis, thereby linking microbial colonization to multidrug resistance. Most of these mechanisms derive from preclinical in vitro and in vivo models, where causal relationships can be inferred. In contrast, human data are mainly observational and provide correlative evidence without proving causality. No interventional clinical studies directly targeting Fn have yet been conducted. Its enrichment across the adenoma–carcinoma sequence and consistent detection in both tumor and fecal samples highlight its potential as a biomarker for early detection and patient stratification. Importantly, multidimensional stool assays that integrate microbial, genetic, and epigenetic markers are emerging as promising non-invasive tools for CRC screening. Therapeutic strategies targeting Fn are also under exploration, ranging from antibiotics and bacteriophages to multifunctional nanodrugs, dietary modulation, and natural microbiota-derived products. These approaches may not only reduce microbial burden but also restore immune competence and enhance the efficacy of immunotherapy in MSS CRC. Altogether, current evidence positions Fn at the intersection of microbial dysbiosis, tumor progression, and therapy resistance. A deeper understanding of its pathogenic role may support the integration of microbial profiling into precision oncology frameworks, paving the way for innovative diagnostic and therapeutic strategies in CRC. Full article

Background/Objectives: Colorectal cancer (CRC) is one of the most prevalent malignancies; this issue underlines the need for accurate molecular biomarkers for early detection and accurate prognosis. Circular RNAs (circRNAs) have recently emerged as very promising cancer biomarkers. The circular transcript of the chaperonin-containing TCP1 subunit 3 (CCT3) gene, namely circ-CCT3, is a significant oncogenic driver. In gastrointestinal malignancies, circ-CCT3 promotes tumor growth by sponging tumor-suppressor miRNAs. In this study, we examined whether circ-CCT3 expression can predict the prognosis of patients diagnosed with colorectal adenocarcinoma, the most frequent type of CRC. Methods: Total RNA was extracted from pulverized, fresh frozen colorectal tissues and reverse-transcribed. A previously developed, highly sensitive quantitative PCR (qPCR) assay was applied to determine circ-CCT3 expression in 216 primary colorectal adenocarcinoma tissue specimens and 86 paired normal colorectal tissues. Results: circ-CCT3 was significantly upregulated in colorectal adenocarcinoma tissues, in comparison to their non-cancerous tissue counterparts. Higher circ-CCT3 expression was associated with a poorer disease-free (DFS) and overall survival (OS) of colorectal adenocarcinoma patients. Interestingly, multivariate Cox regression showed that the prognostic value of circ-CCT3 expression regarding DFS was independent of other established prognosticators used in clinical practice, including TNM staging. Furthermore, the stratification of patients based on the TNM classification of the tumors revealed that increased circ-CCT3 levels predicted shorter DFS and OS intervals, especially in the subgroup of TNM stage II or III patients. Conclusions: Our study provides evidence that circ-CCT3 overexpression constitutes a promising molecular biomarker of poor prognosis in colorectal adenocarcinoma, independently predicting tumor recurrence. Full article

HPV-related head and neck cancers are increasing globally and although they constitute a major public health problem, there are currently no validated screening or early detection methods in widespread clinical use. This review discusses advances in clinical and molecular aspects of prevention, screening, and early detection of HPV-related head and neck cancers (HNCs), such as potential use of HPV blood or saliva seropositivity, RNA biomarkers, liquid biopsy, circulating tumor DNA, and proteomics. In addition to HPV vaccination, public education about vaccination, smoking, and safe sexual practices is warranted. Continued research is warranted to define optimal use and integration of approaches for prevention, screening, and early detection methods of HNCs. Full article

Lung cancer remains one of the most lethal cancers globally. Its early detection is vital to improving survival rates. In this work, we propose a hybrid computer-aided diagnosis (CAD) pipeline for lung cancer classification using Computed Tomography (CT) scan images. The proposed CAD pipeline integrates ten image preprocessing techniques and ten pretrained deep learning models for feature extraction including convolutional neural networks and transformer-based architectures, and four classical machine learning classifiers. Unlike traditional end-to-end deep learning systems, our approach decouples feature extraction from classification, enhancing interpretability and reducing the risk of overfitting. A total of 400 model configurations were evaluated to identify the optimal combination. The proposed approach was evaluated on the publicly available Lung Image Database Consortium and Image Database Resource Initiative dataset, which comprises 1018 thoracic CT scans annotated by four thoracic radiologists. For the classification task, the dataset included a total of 6568 images labeled as malignant and 4849 images labeled as benign. Experimental results show that the best performing pipeline, combining Contrast Limited Adaptive Histogram Equalization, Swin Transformer feature extraction, and eXtreme Gradient Boosting, achieved an accuracy of 95.8%. Full article

The accurate classification of pancreatic cystic lesions remains clinically challenging due to overlapping imaging features and variable malignant potential. Mucinous cystic neoplasms, in particular, require early identification given their premalignant nature. RNA profiling presents a promising alternative to current diagnostic limitations—a molecular lens sharpened by AI-driven pattern recognition. This study aimed to evaluate the diagnostic potential of RNA signatures for differentiating pancreatic cyst subtypes and to clarify their roles in their pathophysiology. The study included 31 patients with pancreatic lesions who underwent endoscopic ultrasound-guided fine-needle aspiration. RNA was extracted from cyst fluid, tissue, and peripheral blood. Expression of 17 target genes was analyzed using qPCR. Gene expression patterns were compared across mucinous cystic neoplasms, serous cystic neoplasms, pseudocysts, adenocarcinoma, and chronic pancreatitis cohorts. Diagnostic accuracy was evaluated via ROC analysis. Mucinous cysts exhibited significant overexpression of MUC1, ITGA2, ELOVL6, and MUC5AC genes compared to serous cysts and pseudocysts. PKM gene expression correlated with increasing malignant potential. In blood plasma, only MUC1, MUC4, and PYGL were elevated in adenocarcinoma compared to mucinous neoplasms. We identified a distinct RNA signature that can distinguish mucinous cystic neoplasms from benign cystic lesions (serous cysts and pseudocysts), which could be useful for guiding patient management and improving clinical outcomes. Validation in broader cohorts is essential for clinical implementation. Full article

Background: Colonoscopy remains the gold standard for colorectal cancer screening. Deep learning systems with real-time computer-aided polyp detection (CADe) demonstrate high accuracy in controlled research settings and preliminary randomized controlled trials (RCTs) report favorable outcomes in clinical settings. This study aims to evaluate the efficacy of AI-assisted colonoscopy compared to standard colonoscopy focusing on Polyp Detection Rate (PDR) and Adenoma Detection Rate (ADR), and to explore their implications for clinical practice. Methods: A systematic search was conducted using multiple indexing databases for RCTs comparing AI-assisted to standard colonoscopy. Random-effect models were utilized to calculate pooled odds ratios (ORs) with 95% confidence intervals. The risk of bias was assessed using the Cochrane Risk of Bias Tool, and heterogeneity was quantified using I statistics. Results: From 22,762 studies, 12 RCTs (n = 11,267) met the inclusion criteria. AI-assisted colonoscopy significantly improved PDR (OR 1.31, 95% CI 1.08–1.59, p = 0.005), despite heterogeneity among studies (I² = 79%). While ADR showed improvement with AI-assisted colonoscopy (OR 1.24, 95% CI, 0.98–1.58, p = 0.08), the result was not statistically significant and had high heterogeneity (I² = 81%). Conclusions: AI-assisted colonoscopy significantly enhances PDR, highlighting its potential role in colorectal cancer screening programs. However, while an improvement in the ADR was observed, the results were not statistically significant and showed considerable variability. These findings highlight the promise of AI in improving diagnostic accuracy but also point to the need for further research to better understand its impact on meaningful clinical outcomes. Full article

Exhaled breath (EB) contains numerous volatile organic compounds (VOCs) that can reflect pathological metabolic processes, making breath analysis a promising non-invasive diagnostic approach. In particular, volatile aldehydes and ketones have been identified as disease biomarkers in EB. Gas sensors are expected to play a crucial role in the diagnosis of numerous diseases at an early stage. Among the various available approaches, sensors stand out as especially attractive tools for diagnosing diseases such as lung cancer (LC) and diabetes, due to their affordability and operational simplicity. There is an urgent need in the field of disease detection for the development of affordable, non-invasive, and user-friendly sensors capable of detecting various biomarkers. Devices of the new generation should also demonstrate high repeatability of measurements and extended operational stability of the employed sensors. Due to these demands, the past few years have seen significant advancements in the development and implementation of electronic noses (ENs), which are composed of an array of sensors for the determination of VOCs present in EB. To meet these requirements, the development and integration of advanced receptor coatings on sensor transducers is essential. These coatings include nanostructured materials, molecularly imprinted polymers, and bioreceptors, which collectively enhance selectivity, sensitivity, and operational stability. However, reliable biomarker detection in point-of-care (PoC) mode remains a significant challenge, constrained by several factors. This review provides a comprehensive and critical evaluation of recent studies demonstrating that the detection of VOCs using gas sensor platforms enables disease detection and can be implemented in PoC mode. Full article