Search Results (345)

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

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

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

Background: The N⁶-methyladenosine (m⁶A) modification of eukaryotic mRNA is the most prevalent of such epigenetic modifications and has recently been identified as a potential player in the pathogenesis and progression of hepatocellular carcinoma (HCC). With the increasing emergence of immunotherapy in the treatment of HCC, we have evaluated the potential of m⁶A-related genes in predicting overall survival and the therapeutic efficacy of immunotherapy in HCC patients. Methods: We employed transcriptomic data from TCGA-LIHC and GSE76427, comprising a total of 485 HCC patients, as the training set. Based on 23 recognized m⁶A regulators, we performed clustering analysis on HCC patients. The intersecting differentially expressed genes (DEGs) among subtypes were used in least absolute shrinkage and selection operator (LASSO) Cox and multivariate Cox regression analyses to construct the risk model. For the quantification of a risk model of HCC patients, a risk score was developed and correlated with clinical and immunological parameters. Furthermore, a single-cell transcriptomic atlas was used to analyze the relationship between model genes and immune cell subpopulations. Mechanistic studies included in vitro assays to validate the association between the m⁶A-related gene ANLN and the progression of HCC. Results: Internal (TCGA and GEO) and external validation (ICGC) suggested that an 8-gene risk score provides an accurate and stable prognostic assessment for HCC. Furthermore, the high-risk score, characterized by elevated TP53 mutation frequency, tumor mutation burden (TMB), and tumor stem cell characteristics indicated a poor prognosis. The prognostic signature was associated with immune cell infiltration in HCC. Those patients with a high-risk score had lower immune tolerance with a better prediction of the efficacy of immunotherapy. The risk model helps to assess and predict the response and prognosis of HCC patients to immune checkpoint inhibitors (ICIs). Additionally, single-cell RNA sequencing data revealed that the high-risk group had a higher proportion of T cells and fewer immunosuppressive T cells, potentially correlating with a better response to immunotherapy. Finally, in vitro experiments showed that ANLN, an m⁶A-related gene, promoted the proliferation and migration of HCC cells. Conclusions: In this study, we identified and validated an m⁶A gene signature consisting of eight genes that can be used to predict prognosis and immunotherapy efficacy in HCC patients. Full article

Lactylation and PANoptosis are emerging modes of tumor progression regulation; however, their interplay and effect on the prognosis for lung adenocarcinoma (LUAD) remain unclear. This research analyzed both bulk and single-cell transcriptomic profiles of LUAD and identified 506 potential markers related to lactylation and PANoptosis. Employing 117 machine learning approaches and 5 LUAD datasets, lactylation and PANoptosis-related signatures (LAPRS) and further predictive nomograms were constructed with 85 prognostic genes. The performance of LAPRS was validated with multifaceted validation, including Kaplan–Meier analysis, time-dependent ROC curves and comparison with 55 existing LUAD models. LAPRS enabled the stratification of LUAD patients into high- and low-risk subgroups. Through additional investigation, high-risk individuals showed elevated genomic alterations, reduced immune infiltration, and poorer immunotherapy response, while low-risk individuals showed better drug sensitivity and a higher tumor mutation burden. Further analysis via 18 models and experimental validation revealed APOL1 as a poor prognostic factor, potentially interacting with the lactylation-related gene VIM through TNF signaling. This research clarifies the mechanistic roles of lactylation and PANoptosis in LUAD and proposes APOL1 as a novel prognostic marker, offering insights for therapeutic stratification. Full article

In the era of precision oncology, comprehensive molecular profiling is critical for guiding targeted and immunotherapy strategies. This study presents the analytical and clinical validation of a 1021-gene next-generation sequencing (NGS) panel, designed for use with both formalin-fixed paraffin-embedded (FFPE) tissue- and liquid-biopsy specimens. Analytical validation confirmed the assay’s high sensitivity and specificity across variant types—including SNVs (Single Nucleotide Variations), indels, CNVs (Copy Number Variations), and fusions—down to a 0.5% variant allele frequency. The assay also accurately identified microsatellite instability (MSI) and tumor mutational burden (TMB), essential biomarkers for immunotherapy. Clinical validation was performed on over 1300 solid tumor samples from diverse histologies, revealing actionable alterations in over 50% of cases. The panel detected on-label treatment biomarkers in 12.57% of patients, increasing to 20.15% when immunotherapy markers were included. Additionally, the assay demonstrated strong concordance with orthogonal methods and was effective in detecting variants in plasma-derived circulating tumor DNA in 70% of evaluable cases. These findings support the robust performance and broad clinical applicability of the 1021-gene panel for comprehensive genomic profiling in both tissue and liquid biopsies, offering a valuable tool for personalized cancer treatment. Full article

GRIN2A has previously been identified as frequently mutated in tumor samples, leading to a hypothesized involvement of GRIN2A in tumorigenesis. Pathogenic GRIN2A germline variants, on the other hand lead, to neurodevelopmental disorders, with no evidence for tumor burden. Thus, we aimed for an independent assessment of somatic and germline variation in GRIN2A, hypothesizing that a distinct distribution of somatic variation indicates a tumorigenic effect. All publicly available GRIN2A variants were obtained from ClinVar, gnomAD and Cosmic to account for germline variation in affected individuals and the general population, as well as somatic variation. Functional consequences, mutational hotspots and gene expression were assessed for each dataset to draw conclusions on the potential pathomechanisms of tumorigenesis. Pathogenic germline variants in GRIN2A expose a clear genotype–phenotype association and are predominantly present in functionally relevant domains, while somatic GRIN2A variants exhibit a uniform distribution and no high abundance in functionally relevant domains. The expression of GRIN2A is lower in tumor samples compared to in non-diseased tissues. Given the non-uniform distribution and domain clustering, our results suggest that specific domains of GRIN2A are highly intolerant towards germline variation, while a lack of somatic mutational clustering and functional relevance refutes the previously hypothesized major role of GRIN2A in tumorigenesis. Full article

Luminal B breast cancer (LBBC) represents an aggressive, high-grade ER+ disease, associated with a high proliferation rate, higher mutation burden, and higher probability of eliciting the immune response. Clinical and pathological data from 89 patients of stage II-III, triple-negative (TN), and luminal B-like BC (LB-like BC) were included in the analysis. All patients were submitted to neoadjuvant chemotherapy (NACT). Quantitative and qualitative evaluations of TILs (Tumor-Infiltrating Lymphocytes) were performed on tissue microarrays constructed from pretreatment core-needle biopsy tumor specimens. The proportion of stromal TILs, CD8, CD4, and PD-L1 positive (+) immune cells (IC), as well as the number of FOXP3, CTLA4, and HSP-70+ IC, was observed concerning tumor immunophenotype, traditional clinicopathological prognostic factors, and tumor response to NACT. There was no statistically significant difference in the proportion of stromal TILs between the LB-like and TNBC (p = 0.344) cohorts. However, a higher CD4/CD8 ratio was associated with the TNBC biology (p = 0.018) and within the LB-like BC cohort with a high proliferation index and metastatic nodal involvement (p = 0.045, p = 0.015). Within the LB-like BC cohort, a higher expression of PD-L1 and HSP70+ IC was associated with a high proliferation index of tumor cells (p = 0.018, p = 0.040), massive metastatic nodal involvement (p = 0.002, p = 0.026), and higher stages of disease (p = 0.004, p = 0.042). Better response to NACT was associated with higher numbers of HSP70+ IC and higher proportions of CD8+ cells within the LB-like BC cohort (p = 0.045, p = 0.012). Routine evaluation of immune markers and HSP70 may help identify high-risk patients of LB-like breast cancer who would have a better response to NACT. Full article

Pancreatic cancer (PC) is highly aggressive, with a 5-year survival rate of 12.8%, making early detection vital. However, non-specific symptoms and precursor lesions complicate diagnosis. Existing tools for the early detection of PC are limited. CAFs are crucial in cancer progression, invasion, and metastasis, yet their role in PC is poorly understood. This study analyzes mRNA data from PC samples to identify CAF-related genes and drugs for PC treatment using algorithms like EPIC, xCell, MCP-counter, and TIDE to quantify CAF infiltration. Weighted gene co-expression network analysis (WGCNA) identified 26 hub genes. Our analyses revealed eight prognostic genes, leading to establishing a six-gene model for assessing prognosis. Correlation analysis showed that the CAF risk score correlates with CAF infiltration and related markers. We also identified six potential drugs, observing significant differences between high-CAF and low-CAF risk groups. High CAF risk scores were associated with lower responses to immunotherapy and higher tumor mutation burdens. GSEA indicated that these scores are enriched in tumor microenvironment pathways. In summary, these six model genes can predict overall survival and responses to chemotherapy and immunotherapy for pancreatic cancer, offering valuable insights for future clinical strategies. Full article

Liquid biopsy through the analysis of circulating tumor DNA (ctDNA) is emerging as a powerful and non-invasive tool complementing tissue biopsy in lymphoma management. Whilst tissue biopsy remains the diagnostic gold standard, it fails to detect the molecular heterogeneity of the tumor’s multiple compartments and poses challenges for sequential disease monitoring. In diffuse large-B-cell lymphoma (DLBCL), ctDNA facilitates non-invasive genotyping by identifying hallmark mutations (e.g., MYD88, CD79B, EZH2), enabling molecular cluster classification. Dynamic changes in ctDNA levels during DLBCL treatment correlate strongly with progression-free survival and overall survival, underscoring its value as a predictive and prognostic biomarker. In Hodgkin’s lymphoma, characterized by a scarcity of malignant cells in tissue biopsies, ctDNA provides reliable molecular insights into tumor biology, response to therapy, and relapse risk. In primary central nervous system lymphoma, the detection of MYD88 L265P in ctDNA offers a highly sensitive, specific, and minimally invasive diagnostic option. Likewise, in aggressive T-cell lymphomas, ctDNA supports molecular profiling, aligns with tumor burden, and shows high concordance with tissue-based results. Ongoing and future clinical trials will be critical for validating and standardizing ctDNA applications, ultimately integrating liquid biopsy into routine clinical practice and enabling more personalized and dynamic lymphoma care. Full article

Background: Long non-coding RNAs (lncRNAs) are crucial factors affecting the occurrence, progression, and prognosis of gastric carcinoma (GC). The accumulation of disulfide bonds to excessive levels in cells expressing high SLC7A11 triggers disulfidptosis, which functions as a regulated form of cellular death. Research has demonstrated that upregulated SLC7A11 is common in human cancers, but the effect of disulfidptosis on GC remains unclear. Identifying lncRNAs associated with disulfidptosis (drlncRNAs) and establishing a prognostic risk profile holds considerable importance for advancing GC research and treatment. Methods: Clinical records and transcriptomic datasets from individuals with GC were acquired from The Cancer Genome Atlas (TCGA) repository. A three-drlncRNA risk model was built using three common regression analysis methods. Then we used receiver operating characteristic (ROC) curves, independent prognostic analysis, and additional statistical approaches to assess the precision of the model. This investigation additionally encompassed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, immune cell infiltration evaluation, and pharmacological sensitivity predictions. To further investigate immunotherapy response disparities between patient cohorts with elevated- and reduced-risk scores, analyses of tumor mutational burden (TMB), tumor immune dysfunction and exclusion (TIDE), and microsatellite instability (MSI) were implemented. Results: We constructed a unique model composed of three drlncRNAs (AC107021.2, AC016394.2, and AC129507.1). Its independent prognostic capability for GC patients was validated through both single-variable and multivariable Cox regression analyses. GO and KEGG pathway assessments revealed predominant enrichment within the elevated-risk cohort, particularly in pathways involving sulfur compound interactions, traditional Wnt signaling mechanisms, cell-substrate adherens junctions, and cAMP signaling cascades, among others. Tumor microenvironment (TME) evaluation demonstrated elevated ImmuneScores, StromalScores, and ESTIMATEScores within the high-risk patient population. Concurrently, this elevated-risk cohort exhibited enhanced immune cell infiltration patterns, whereas the reduced-risk group displayed superior expression of immune checkpoints (ICPs). Additional investigations revealed that patients categorized into the reduced-risk classification possessed greater tumor mutational burden, increased MSI-high proportions, and diminished tumor immune dysfunction and exclusion scores compared to their high-risk counterparts. Pharmacological sensitivity assessments confirmed the superior efficacy of several therapeutic agents, including gemcitabine and veliparib (ABT.888), in patients with lower risk classifications. Conclusions: Our established risk stratification system demonstrates independent prognostic predictive capacity while offering personalized clinical intervention guidance for individuals diagnosed with GC. Full article