Search Results (715)

Progress in establishing environmental risk factors and, consequently, prophylactic measures for glial tumors, particularly for glioblastomas, is of utmost importance, considering the dismal prognosis and limited treatment options. This report surveyed updates on established and recently identified factors that can predispose a patient to glioma formation while highlighting possible mechanistic links and further research directions. In addition to established factors that increase the risk of glioma, i.e., brain irradiation and several genetic syndromes, another group consists of likely factors contributing to such risks, such as the use of tobacco and those yielding ambiguous results (e.g., UV exposure). Oxidative stress is a common denominator for several types of exposure, and a mechanistic background for other factors remains elusive. Nevertheless, the analysis of clinical and basic research strongly suggests that, apart from the effect of environmental stressors on DNA alterations and mutation burden, the impact of modifying the tumor microenvironment should be considered. Identifying the involvement of environmental hazards in gliomagenesis and glial tumor progression would lower overall risk by modifying clinical practice, patient management, and lifestyle choices. Further verifying the environmental hazards in glioma formation and progression would have far-reaching implications for neurologists, neurosurgeons, and patients. Full article

Background: Colorectal liver metastasis (CRLM) represents a major clinical challenge in oncology, affecting 25–50% of colorectal cancer patients and significantly impacting survival. While multimodal therapies—including surgical resection, systemic chemotherapy, and local ablative techniques—have improved outcomes, prognosis remains heterogeneous due to variations in tumor biology, patient factors, and institutional practices. Methods: This review synthesizes current evidence on prognostic factors influencing CRLM management, encompassing clinical (e.g., tumor burden, anatomic distribution, timing of metastases), biological (e.g., CEA levels, inflammatory markers), and molecular (e.g., RAS/BRAF mutations, MSI status, HER2 alterations) determinants. Results: Key findings highlight the critical role of molecular profiling in guiding therapeutic decisions, with RAS/BRAF mutations predicting resistance to anti-EGFR therapies and MSI-H status indicating potential responsiveness to immunotherapy. Emerging tools like circulating tumor DNA (ctDNA) and radiomics offer promise for dynamic risk stratification and early recurrence detection, while the gut microbiome is increasingly recognized as a modulator of treatment response. Conclusions: Despite advancements, challenges persist in standardizing resectability criteria and integrating multidisciplinary approaches. Current guidelines (NCCN, ESMO, ASCO) emphasize personalized strategies but lack granularity in terms of incorporating novel biomarkers. This exhaustive review underscores the imperative for the development of a unified, biomarker-integrated framework to refine CRLM management and improve long-term outcomes. Full article

Background/Objectives: The RTK-RAS signaling cascade is a central axis in colorectal cancer (CRC) pathogenesis, governing cellular proliferation, survival, and therapeutic resistance. Somatic alterations in key pathway genes—including KRAS, NRAS, BRAF, and EGFR—are pivotal to clinical decision-making in precision oncology. However, the integration of these genomic events with clinical and demographic data remains hindered by fragmented resources and a lack of accessible analytical frameworks. To address this challenge, we developed AI-HOPE-RTK-RAS, a domain-specialized conversational artificial intelligence (AI) system designed to enable natural language-based, integrative analysis of RTK-RAS pathway alterations in CRC. Methods: AI-HOPE-RTK-RAS employs a modular architecture combining large language models (LLMs), a natural language-to-code translation engine, and a backend analytics pipeline operating on harmonized multi-dimensional datasets from cBioPortal. Unlike general-purpose AI platforms, this system is purpose-built for real-time exploration of RTK-RAS biology within CRC cohorts. The platform supports mutation frequency profiling, odds ratio testing, survival modeling, and stratified analyses across clinical, genomic, and demographic parameters. Validation included reproduction of known mutation trends and exploratory evaluation of co-alterations, therapy response, and ancestry-specific mutation patterns. Results: AI-HOPE-RTK-RAS enabled rapid, dialogue-driven interrogation of CRC datasets, confirming established patterns and revealing novel associations with translational relevance. Among early-onset CRC (EOCRC) patients, the prevalence of RTK-RAS alterations was significantly lower compared to late-onset disease (67.97% vs. 79.9%; OR = 0.534, p = 0.014), suggesting the involvement of alternative oncogenic drivers. In KRAS-mutant patients receiving Bevacizumab, early-stage disease (Stages I–III) was associated with superior overall survival relative to Stage IV (p = 0.0004). In contrast, BRAF-mutant tumors with microsatellite-stable (MSS) status displayed poorer prognosis despite higher chemotherapy exposure (OR = 7.226, p < 0.001; p = 0.0000). Among EOCRC patients treated with FOLFOX, RTK-RAS alterations were linked to worse outcomes (p = 0.0262). The system also identified ancestry-enriched noncanonical mutations—including CBL, MAPK3, and NF1—with NF1 mutations significantly associated with improved prognosis (p = 1 × 10⁻⁵). Conclusions: AI-HOPE-RTK-RAS exemplifies a new class of conversational AI platforms tailored to precision oncology, enabling integrative, real-time analysis of clinically and biologically complex questions. Its ability to uncover both canonical and ancestry-specific patterns in RTK-RAS dysregulation—especially in EOCRC and populations with disproportionate health burdens—underscores its utility in advancing equitable, personalized cancer care. This work demonstrates the translational potential of domain-optimized AI tools to accelerate biomarker discovery, support therapeutic stratification, and democratize access to multi-omic analysis. Full article

Background: Tyrosine kinase inhibitors (TKIs) have significantly improved outcomes in non-small cell lung cancer (NSCLC), especially among patients with actionable genetic mutations. However, the influence of family and personal medical history (FPMH) on clinical and treatment outcomes with TKI therapy remains underexplored. Methods: We conducted a retrospective cohort study involving 136 NSCLC patients receiving TKIs, categorized into two groups based on the presence or absence of documented FPMH. Clinical variables assessed included demographic data, comorbidities, Eastern Cooperative Oncology Group (ECOG) performance status, tumor characteristics, genetic mutations (EGFR, ALK, ROS1), treatment responses, toxicity profiles, and survival outcomes. Statistical analyses included Chi-square tests, t-tests, Mann–Whitney U tests, Spearman correlation, and univariate logistic regression (p < 0.05 threshold for significance). Results: Patients with FPMH (n = 34) had a significantly higher burden of chronic diseases (58.8% vs. 15.7%), poorer ECOG scores (≥3: 8.8% vs. 1.0%), increased recurrence (41.2% vs. 20.6%), and greater chemotherapy-related toxicity (50.0% vs. 28.4%) compared to those without FPMH (n = 102). However, there were no significant differences in survival duration or mutation status between the two groups. Conclusions: FPMH may be a predictive factor for treatment complications and recurrence in NSCLC patients receiving TKIs, although it does not appear to influence survival or genetic mutation status. These findings support the need for personalized clinical monitoring strategies based on medical history. Full article

Microsatellite instability (MSI) is a clinically important biomarker for predicting responses to immune checkpoint inhibitors and identifying individuals with Lynch syndrome. Although MSI detection has been incorporated into Illumina’s next-generation tumor sequencing workflows, interpretation of the results remains challenging due to the absence of standardized thresholds and reporting criteria. In this retrospective study, we assessed the performance of MSI detection using Illumina’s targeted NGS panels—TruSight Tumor 170 and TruSight Oncology 500. The NGS-based MSI results were compared to those obtained by the reference method, MSI-PCR, across multiple tumor types in a real-world cohort of 331 cancer patients. The NGS method demonstrated high concordance overall (AUC = 0.922), though sensitivity was lower in colorectal cancers (AUC = 0.867) due to broader score variability and overlapping distributions. Our findings support the clinical utility of Illumina’s NGS-derived MSI scores for identifying MSI-H tumors, with a recommended MSI score cut-off value of ≥13.8%. Additionally, a borderline group was introduced, defined by an MSI score ranging from ≥8.7% to <13.8%. Within this range, the integration of TMB into the MSI classification workflow significantly improves diagnostic accuracy. For samples that remain inconclusive, orthogonal confirmation using MSI-PCR is advised to ensure accurate MSI classification. Full article

Sporadic colorectal cancer (CRC), the third leading cause of cancer-related death globally, arises through a continuum from normal tissue to adenomas, progressing from low-grade (LGD) to high-grade dysplasia (HGD); yet, the early epigenetic drivers of this transition remain unclear. To investigate these events, we profiled LGD and HGD adenomas using EM-seq, and identified a consensus differential methylation signature (DMS) of 626 regions through two independent bioinformatics pipelines. This signature effectively distinguished LGD from HGD in both tissue and plasma-derived cell-free DNA (cfDNA), highlighting specific methylation patterns. Functional annotation indicated enrichment for regulatory elements associated with transcription factor activity and cell signaling. Applying the DMS to the TCGA CRC dataset revealed three tumor subtypes with increasing hypermethylation and one normal cluster. The most hypermethylated subtype exhibited poor survival, high mutation burden, and disrupted transcriptional networks. While overlapping with classical CpG Island Methylator Phenotype (CIMP) categories, the DMS captured a broader spectrum of methylation alterations. These findings suggest that the DMS captures functionally relevant, antecedent epigenetic alterations in CRC progression, enabling the robust stratification of dysplasia severity and tumor subtypes. This signature holds promise for enhancing preclinical detection and molecular classification, and warrants further evaluation in larger prospective cohorts. Full article

Background: Thyroid neoplasms exhibit a diverse molecular landscape, and the 2022 WHO classification emphasizes the critical role of molecular profiling in thyroid cancer management; however, comprehensive mutational data from fine-needle aspiration cytology (FNAC) samples using targeted next-generation sequencing (NGS) are still limited, necessitating further investigation to guide clinical practice. Purpose: To characterize the mutational landscape of thyroid neoplasms using targeted NGS of FNAC samples and to assess the clinical implications of molecular profiling. Materials and Methods: This retrospective study included 952 patients with thyroid carcinomaneoplasms who underwent surgery at Sun Yat-sen Memorial Hospital from 2021 to 2023. Preoperative ultrasound, FNAC, and targeted NGS were performed. NGS panels covering 18, 88, and pan-cancer genes were used to analyze FNAC samples. Molecular alterations were correlated with clinical and pathological features. Results: The most frequent mutation was BRAF^V600E (84.45%), followed by RET (6.41%), BRCA1/2 (4.41%) and RAS (4.41%). Patients were categorized into BRAF-like (830 cases), RAS-like (36 cases), high-risk mutations (25 cases), and other mutations (28 cases). High-risk mutations were associated with older age and larger tumor size. BRAF-like tumors had a higher lymph node metastasis rate (58.77%) compared to RAS-like tumors (33.33%). Tumor mutation burden varied significantly among different thyroid neoplasm subtypes. Conclusions: Molecular profiling using targeted NGS of FNAC samples provides valuable insights into the genetic landscape of thyroid neoplasms and has significant clinical implications for diagnosis and personalized treatment strategies. Further validation with paired tumor and plasma samples is warranted. Full article

Endometrial carcinoma (EC) is the most common gynaecological malignancy in developed nations, exhibiting significant molecular heterogeneity that impacts prognosis and treatment response, particularly in advanced or recurrent settings. Traditional classification is increasingly supplemented by molecular subtyping (POLE-ultramutated, MSI-high/dMMR, NSMP, p53-mutated/CNH), which provides crucial prognostic information and predicts benefit from immunotherapy. This review summarizes the landscape of predictive biomarkers for immune checkpoint inhibitor (ICI) therapy in EC, emphasizing a new therapeutic scenario for advanced and recurrent EC. Mismatch repair deficiency (dMMR) or high microsatellite instability (MSI-H), leading to high tumor mutational burden (TMB) and increased neoantigen production, is the most established predictor, resulting in FDA approvals for pembrolizumab and dostarlimab in this subgroup. POLE mutations also confer hypermutation and high immunogenicity, predicting a favorable ICI response. Other biomarkers, including PD-L1 expression and TMB, show variable correlation with response and require further standardization. The tumor immune microenvironment, including tumor-infiltrating lymphocytes (TILs), also influences treatment outcomes. Clinical trials have demonstrated significant survival benefits for ICIs combined with chemotherapy (e.g., dostarlimab/pembrolizumab + carboplatin/paclitaxel) in first-line settings, especially for dMMR/MSI-H EC, and for ICI combinations with targeted agents (e.g., lenvatinib + pembrolizumab) in previously treated patients. Integrating molecular classification and validated biomarkers is essential for optimizing patient selection and developing personalized immunotherapy strategies for EC. Full article

Oral squamous cell carcinoma (OSCC) remains one of the most common malignancies in the head and neck region, often preceded by a spectrum of oral potentially malignant disorders (OPMDs). Despite advances in diagnostic methods, reliable and non-invasive biomarkers for early detection and prognostic stratification are still lacking. In recent years, circulating cell-free DNA (cfDNA) has emerged as a promising liquid biopsy tool in several solid tumors, offering insights into tumor burden, heterogeneity, and molecular dynamics. However, its application in oral oncology remains underexplored. This study aims to review and discuss the current evidence on cfDNA quantification and mutation analysis (including TP53, NOTCH1, and EGFR) in patients with OPMDs and OSCC. Particular attention is given to cfDNA fragmentation patterns, methylation signatures, and tumor-specific mutations as prognostic and predictive biomarkers. Moreover, we highlight the challenges in standardizing pre-analytical and analytical workflows in oral cancer patients and explore the potential role of cfDNA in monitoring oral carcinogenesis. Understanding cfDNA dynamics in the oral cavity might offer a novel, minimally invasive strategy to improve early diagnosis, risk assessment, and treatment decision-making in oral oncology. Full article

Background/Objectives: Response to immune checkpoint inhibitors (ICIs) is associated with several biological pathways, including tumor immunogenicity and antitumor immunity. Identifying host factors involved in these pathways may guide personalized ICI treatment. Methods: We describe the application of chromatin conformation assays to blood from patients with advanced urothelial carcinoma from the phase 3 JAVELIN Bladder 100 trial (NCT02603432). This trial demonstrated a significant survival benefit with avelumab maintenance plus best supportive care (BSC) vs. BSC alone following non-progression with platinum-based chemotherapy as first-line therapy. Blood-based chromatin conformation markers (CCMs) were screened for associations with high/low immune effector gene expression in tumors and for interactions with outcomes and tumor mutation burden. Results: Candidate CCMs included genes involved in several immune response pathways, such as POU2F2, which encodes a transcription factor that regulates B-cell maturation. Conclusions: Our findings suggest that polygenic host factors may affect response to ICIs and support further investigation of chromatin conformation assays. Full article

Immunotherapy has emerged as a transformative approach in gastrointestinal (GI) cancers, addressing historically poor survival rates in advanced-stage disease. Immune checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 axis demonstrate remarkable efficacy in colorectal cancer with deficient mismatch repair (dMMR) or high microsatellite instability (MSI-H), exemplified by trials like NICHE-2 achieving exceptional pathological response rates. However, significant limitations persist, including resistance in some dMMR/MSI-H tumors, minimal efficacy in proficient mismatch repair (pMMR) tumors, and low overall response rates across most GI malignancies due to tumor heterogeneity and immune evasion mechanisms. Predictive biomarkers such as tumor mutational burden (TMB) and PD-L1 expression are crucial for optimizing patient selection, while hypermutated pMMR tumors with POLE mutations represent emerging therapeutic opportunities. In pancreatic adenocarcinoma, where survival remains dismal, combination strategies with chemotherapy and novel approaches like cancer vaccines show promise but lack transformative breakthroughs. Esophagogastric cancers benefit from ICIs combined with chemotherapy, particularly in MSI-H and HER2-positive tumors, while hepatocellular carcinoma has achieved significant progress with combinations like atezolizumab–bevacizumab and durvalumab–tremelimumab surpassing traditional therapies. Biliary tract cancers show modest improvements with durvalumab–chemotherapy combinations. Despite these advances, immunotherapy faces substantial challenges including immune-related adverse events, acquired resistance through cancer immunoediting, and the need for biomarker-driven approaches to overcome tumor microenvironment barriers. This review discusses key clinical trials, therapeutic progress, and emerging modalities including CAR T-cell therapies and combination strategies, emphasizing the critical need to address resistance mechanisms and refine precision medicine approaches to fully realize immunotherapy’s potential in GI malignancies. Full article

Immune checkpoints such as PD-1/PD-L1, CTLA-4, LAG-3, TIM-3, and TIGIT play critical roles in regulating anti-tumor immunity and are exploited by hematological malignancies to evade immune surveillance. While classic Hodgkin lymphoma (HL) demonstrates notable responsiveness to immune checkpoint inhibitors (ICIs), which is attributed to genetic alterations like chromosome 9p24.1 amplification, the responsiveness of non-Hodgkin lymphoma (NHL), acute myeloid leukemia (AML), and multiple myeloma (MM) remain inconsistent and generally modest. In NHL, the heterogeneous immune microenvironment, particularly variations in tumor-infiltrating lymphocytes and PD-L1 expression, drives differential ICI outcomes. AML shows limited responsiveness to monotherapy, but the combination of monotherapy with hypomethylating agents yield encouraging results, particularly in selected patient subsets. Conversely, MM trials have largely failed, potentially due to genetic polymorphisms influencing checkpoint signaling pathways and the inherently immunosuppressive bone marrow microenvironment. Both intrinsic tumor factors (low tumor mutational burden, impaired antigen presentation, IFN-γ pathway alterations) and extrinsic factors (immunosuppressive cells and alternative checkpoint upregulation) contribute significantly to primary and acquired resistance mechanisms. Future strategies to overcome resistance emphasize combination therapies, such as dual checkpoint blockade, epigenetic modulation, and reprogramming the tumor microenvironment, as well as biomarker-driven patient selection, aiming for precision-based, tailored immunotherapy across hematological malignancies. Full article

Aberrant activation of Wnt/β-catenin signaling, frequently caused by oncogenic mutations, plays a crucial role in the development, progression, and therapy resistance of gastric, esophageal, hepatic, pancreatic, and colorectal cancers. Concurrently, circular RNAs (circRNAs), produced by back-splicing of precursor mRNAs (pre-mRNAs), have emerged as critical modulators of this pathway. Accumulating evidence indicates that specific circRNAs regulate Wnt/β-catenin signaling by sponging microRNAs, interacting with RNA-binding proteins, modulating protein function, and altering the expression of pathway components. Some circRNAs are also subject to feedback regulation by Wnt signaling itself. Clinically, tumor-associated circRNAs are present in body fluids and correlate with disease stage, metastatic burden, and patient survival, underscoring their potential as early and minimally invasive biomarkers. Moreover, targeting oncogenic circRNAs has shown promise in preclinical models of Wnt-driven gastrointestinal malignancies. In this review, we summarize the current understanding of the interplay between circRNAs and Wnt/β-catenin signaling in gastric and esophageal cancers. We discuss the translational challenges and emerging opportunities for biomarker development and targeted therapy. Full article

Ubiquitination is a dynamic and reversible post-translational modification mediated by ubiquitination regulators (UBRs), which plays an essential role in protein stability, cell differentiation and immunity. Dysregulation of UBRs can lead to destabilization of biological processes and may induce serious human diseases, including cancer. Many UBRs, such as E3 ubiquitin ligases and deubiquitinases (DUBs), have been identified as potential drug targets for cancer therapy. However, the potential clinical value of UBRs in lung adenocarcinoma (LUAD) remains to be elucidated. Here, we identified 17 hub UBRs from high-confidence protein–protein interaction networks of UBRs correlated with cancer hallmark-related pathways using four topological algorithms. The expression of hub UBRs is affected by copy number variation and post-transcriptional regulation, and their high expression is often detrimental to patient survival. Based on the expression profiles of hub UBRs, patients can be classified into two ubiquitination subtypes with different characteristics. These subtypes exhibit significant differences across multiple dimensions, including survival, expression level, mutation burden, female predominance, infiltration level, immune profile, and drug response. In addition, we established a scoring system for evaluating the ubiquitination status of individual LUAD patients, called the ubiquitination-related risk (UB_risk) score, and found that patients with low scores are more likely to gain advantages from immunotherapy. The results of this study emphasize the critical role of ubiquitination in the classification, tumor microenvironment and immunotherapy of LUAD. The construction of the UB_risk scoring system lays a research foundation for evaluating the ubiquitination status of individual LUAD patients and formulating precise treatment strategies from the ubiquitination level. Full article

The rising incidence of early-onset colorectal cancer (EOCRC), particularly among underrepresented populations, highlights the urgent need for tools that can uncover clinically meaningful, population-specific genomic alterations. The phosphoinositide 3-kinase (PI3K) pathway plays a key role in tumor progression, survival, and therapeutic resistance in colorectal cancer (CRC), yet its impact in EOCRC remains insufficiently explored. To address this gap, we developed AI-HOPE-PI3K, a conversational artificial intelligence platform that integrates harmonized clinical and genomic data for real-time, natural language-based analysis of PI3K pathway alterations. Built on a fine-tuned biomedical LLaMA 3 model, the system automates cohort generation, survival modeling, and mutation frequency comparisons using multi-institutional cBioPortal datasets annotated with clinical variables. AI-HOPE-PI3K replicated known associations and revealed new findings, including worse survival in colon versus rectal tumors harboring PI3K alterations, enrichment of INPP4B mutations in Hispanic/Latino EOCRC patients, and favorable survival outcomes associated with high tumor mutational burden in FOLFIRI-treated patients. The platform also enabled context-specific survival analyses stratified by age, tumor stage, and molecular alterations. These findings support the utility of AI-HOPE-PI3K as a scalable and accessible tool for integrative, pathway-specific analysis, demonstrating its potential to advance precision oncology and reduce disparities in EOCRC through data-driven discovery. Full article