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PubMed2026

Chinese expert consensus on precision testing and molecular diagnosis of pancreatic cancer (2025).

This consensus by the CSCO Pancreatic Cancer Expert Committee establishes evidence-based guidelines for molecular testing in pancreatic ductal adenocarcinoma. It details recommendations for biomarkers (e.g., KRAS, BRCA, MSI), liquid biopsy, and precision imaging to direct targeted therapies and immunotherapy, aiming to standardize diagnosis and optimize individualized patient care. Pancreatic ductal adenocarcinoma (PDAC) is the most common pathological type of primary pancreatic malignancy, accounting for ~95% of cases and generally referred to as pancreatic cancer [1]. Its prognosis is extremely poor and its incidence continues to rise [2]. According to the most recent global cancer statistics, the incidence of pancreatic cancer ranks 12th among all cancers, and its mortality ranks 6th, making it one of the deadliest malignancies worldwide [3]. Approximately 57% of patients have metastatic disease at diagnosis and require systemic therapy, for which chemotherapy remains the standard first-line option [1]. However, the overall response rate to currently available systemic regimens is low, and the 5-year survival rate for patients with metastatic disease remains below 5% [3]. Although most pancreatic cancers harbor canonical driver mutations, they exhibit marked heterogeneity at the molecular level. Whole-genome sequencing (WGS) and integrative genomic analyses have identified molecular subtypes of PDAC with potential clinical relevance [4-9]. With the increasing implementation of precision oncology, the Chinese Society of Clinical Oncology (CSCO) Guidelines for the Diagnosis and Treatment of Pancreatic Cancer give a level 1 recommendation to perform genetic and other molecular testing on tissue or cytologic specimens as part of the pathological diagnostic work-up, in order to guide individualized treatment, including targeted therapy and immunotherapy [10]. To further promote the use of genetic and molecular testing in the precision treatment of pancreatic cancer, the CSCO Pancreatic Cancer Expert Committee convened a multidisciplinary panel to develop the present Chinese Expert Consensus on Precision Testing and Molecular Diagnosis of Pancreatic Cancer (2025), aiming to provide clinicians with an authoritative reference for precision diagnostics and treatment decision-making.

Humans↗

PubMed2026

Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.

Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of normal tissue references, leading to potential confounding of tumor-specific and tissue-of-origin signals. To address these limitations, a hierarchical classification (HC) framework is presented in which CLs are aligned with patient tumors across biological resolutions, from organ to molecular subtype. Gene expression profiles from 802 CLs, 5,612 tumors from The Cancer Genome Atlas (TCGA) , and 8,939 non-cancerous tissues were integrated to separate oncogenic signals from tissue-specific signals. Node-specific features were selected using maximum relevance minimum redundancy, and balanced accuracies of 89% in cross-validation and 75%, and 80% on external datasets were achieved. Through the framework, 43 CLs were reassigned, and clinically relevant underrepresented subtypes were identified.

cancer cell lines↗

PubMed2026

Identification and expression validation of key genes of Xiaozhengtongluo formula in the treatment of diabetic nephropathy by Mendelian randomization.

Xiaozhengtongluo formula (XZTL) has a positive effect on the treatment of diabetic nephropathy (DN), but its mechanism is not fully understood. Therefore, it is important to explore the key genes of XZTL in the treatment of DN. Differentially expressed genes (DEGs) between DN and control obtained from GSE96804, drug target genes of XZTL, and disease target genes of DN obtained from public databases were intersected. Genes of intersection were defined as candidate genes. Next, Mendelian randomization (MR) analysis was used to ascertain the causal associations between candidate genes and DN. Afterwards, key genes were confirmed through receiver operating characteristic (ROC) curve analysis and expression validation. Subsequently, enrichment analysis, molecular regulatory network analysis, and molecular docking were conducted. Finally, experimental verification of the expression levels of key genes was performed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Altogether, 29 candidate genes were screened via MR analysis, identifying APOD, IGFBP3, and LPL as significantly associated with DN. IGFBP3 and APOD were risk factors, whereas LPL was protective. Consistent expression trends across training and validation datasets defined them as key genes. All three were co-enriched in 26 pathways, including oxidative phosphorylation. Regulatory networks showed MIR497HG/hsa-miR-19a-3p regulated IGFBP3, and NEAT1/hsa-miR-29a-3p regulated LPL; IGFBP3 and LPL were co-targeted by SP3 and SP1. Molecular docking revealed APOD-baicalein, LPL-oleic acid, and IGFBP3-quercetin binding, suggesting therapeutic potential. RT-qPCR confirmed aberrant expression of these genes in DN, which was normalized by XZTL intervention. In this study, three key genes (APOD, IGFBP3, and LPL) of XZTL in the treatment of DN were finally obtained, providing mechanistic clues for understanding XZTL's multi-target mechanism and providing experimentally tractable candidate targets for DN molecular subtyping, targeted therapeutic development, and precision medicine approaches in TCM.

Diabetic Nephropathies↗

PubMed2026

Integrated Genomic and Proteomic Analysis Reveals T-B Lymphocyte Signatures in the MYCN Driven "Immune Desert" of Specific Neuroblastoma Subtypes.

AIMS: This study aims to systematically dissect how MYCN amplification shapes the immunosuppressive tumor microenvironment (TME) in high-risk neuroblastoma, elucidating key mechanisms underlying immune evasion. METHODS: We performed an integrated multi-omics analysis of bulk RNA-seq (n = 721), single-cell RNA-seq (n = 9), proteomic data (n = 49) and spatial transcriptomics (Visium, with external validation in melanoma). Analyses included unsupervised clustering, cell-cell communication inference, transcriptional regulatory network reconstruction, and spatial proximity assessment to map the immune landscape. RESULTS: A distinct molecular subtype (Class C), defined by MYCN amplification and poor prognosis, exhibited a comprehensive "immune desert" phenotype characterized by low immune scores and minimal leukocyte infiltration. Single-cell analysis confirmed significant depletion of T and B lymphocytes within the Class C TME. Dysregulated transcriptional networks were identified, including upregulation of REL and EOMES in T cells-with EOMES potentially driving exhaustion via regulation of Transient Receptor Potential (TRP) genes, and REL inhibition enhancing cytotoxic function in vitro. A unique immunosuppressive B-cell subset (B7) engaged in enhanced crosstalk with exhausted T cells and harbored a MYC-centered network linked to cell cycle dysregulation and poor survival. Spatial transcriptomics revealed significant proximity between B7-active regions and Treg/exhaustion-enriched areas, externally validated in melanoma. Proteomic data validated elevated REL expression in MYCN-amplified tumors. CONCLUSION: This work delineates the immunosuppressive architecture of MYCN-driven neuroblastoma, revealing novel regulatory nodes within specific lymphocyte compartments. Integrating single-cell, spatial, and proteomic evidence, we propose REL inhibition as a therapeutic candidate, the EOMES/TRP axis as a bioinformatically supported hypothesis, and the B7/MYC hub as a hypothesis supported by transcriptomic and spatial evidence.

Humans↗

PubMed2026

Integration of multi-omics data uncovers novel germline susceptibility candidates in early-onset colorectal cancer.

Colorectal cancer (CRC) is increasingly diagnosed in individuals under 50 years of age, yet the underlying genetic predisposition remains largely unexplained, particularly in mismatch repair (MMR)-proficient cases. This study aimed to identify novel hereditary CRC susceptibility genes by integrating germline and tumour whole-exome sequencing (WES) with transcriptomic profiling across a cohort of early-onset CRC (EOCRC) patients. Tumours were categorised using Consensus Molecular Subtypes (CMS) classification and analysed for mutational signature and burden. We used a novel 'All vs One' multi-omic integration approach to identify loss-of-function rare germline variants with concordant gene expression alterations in tumour tissue. Five candidate genes (ADCY4, NOXO1, CDHR2, ARHGAP10, EEF2K) were prioritised based on this approach and potential biological relevance in CRC. These findings highlight the molecular heterogeneity of EOCRC and demonstrate the utility of multi-omic approaches in refining germline variant interpretation. Integrating tumour transcriptomics enhances gene discovery efforts and supports a more comprehensive understanding of CRC heritability in younger individuals.

Humans↗

PubMed2026

Machine learning and multi-omics clustering to map cellular rewiring and immune evasion in ccRCC.

Immune checkpoint blockade (ICB) efficacy in clear cell renal cell carcinoma (ccRCC) is limited by tumor microenvironment (TME) heterogeneity. Because traditional bulk-derived models lack spatial resolution, we developed an integrated framework connecting macroscopic survival risks to microscopic TME structures. We applied ten algorithms to establish multi-omics subtypes and evaluated 101 machine-learning combinations across three independent cohorts to generate a Consensus Machine Learning-driven Signature (CMLS). The signature's spatial and cellular origins were decoded using spatial transcriptomics (ST) and a 140,000-cell scRNA-seq atlas. Expression of key genes was experimentally validated via RT-qPCR in 17 paired ccRCC clinical tissues. We identified two molecular subtypes with distinct clinical and epigenetic profiles. SuperPC optimization yielded a 24-gene CMLS serving as an independent prognostic factor. scRNA-seq and ST deconvolution revealed these signals predominantly originate from cancer-associated fibroblasts (CAFs) and malignant epithelial cells, which collaborate to drive spatial immune exclusion. RT-qPCR confirmed significant overexpression of five core CMLS genes in ccRCC versus adjacent normal tissues. Low CMLS scores correlated with enhanced ICB responsiveness, whereas high-CMLS tumors demonstrated specific vulnerability to dasatinib and dabrafenib. The CMLS translates spatial immune-exclusion dynamics into a quantifiable metric, outperforming tumor mutational burden in predicting ICB benefits, providing a robust tool for patient stratification in ccRCC.

Humans↗

PubMed2026

SWI/SNF Alterations Define a Chromatin-Dependent Subtype of Urothelial Carcinoma.

PURPOSE: SWI/SNF (BAF) chromatin remodeling complex alterations are common in urothelial carcinoma, yet no biomarker-directed therapeutic strategies have been established for this population. We investigated whether BAF alterations delineate a biologically distinct, therapeutically actionable urothelial carcinoma subtype. EXPERIMENTAL DESIGN: We performed integrative genomic and transcriptomic analyses of 792 urothelial carcinoma tumors from the Oncology Research Information Exchange Network (ORIEN) and validated findings in the TCGA-BLCA cohort. Mechanistic studies incorporated RNA sequencing and ATAC-seq following histone deacetylase (HDAC) inhibition. Functional dependencies were assessed using patient-derived xenograft organoids and cell line models. Clinical relevance was explored in a biomarker-enriched investigator-initiated trial. RESULTS: Approximately half of urothelial carcinoma tumors exhibited BAF alterations, defining a previously unrecognized chromatin-altered molecular subtype characterized by activation of proliferative programs, loss of lineage identity, and altered metabolic signaling. This subtype was enriched for transcriptomic programs associated with HDAC inhibitor sensitivity and depleted of HDAC inhibitor resistance signatures. Mechanistically, HDAC inhibition induced widespread chromatin remodeling with reduced accessibility at AP-1 and TEAD-associated regions, and downregulation of E2F- and MYC-driven transcriptional networks. Functional studies confirmed enhanced HDAC inhibition sensitivity in ARID1A -mutated cell lines and a patient-derived organoid model. Early clinical observations demonstrated a durable responder treated with HDAC inhibitors and immunotherapy. CONCLUSIONS: BAF alterations define a chromatin-dependent tumor state in urothelial carcinoma that is selectively vulnerable to HDAC inhibition. Integrating genomic, epigenomic, functional, and early clinical evidence, these findings provide a rationale for biomarker-enriched clinical trials and HDAC inhibitor-based combination strategies in urothelial carcinoma.

Journal Article↗

PubMed2026

Integrative subtyping by bile acid metabolism identifies CLCA1/UGT2A3/ZG16 as markers of immune dysfunction and poor prognosis in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the primary driver of cancer-related death and illness across the world. Despite the full-scale shift of the treatment approach for some colorectal cancer patients due to the use of immune checkpoint inhibitors (ICIs), primary resistance still poses a huge challenge to clinicians. Bile acid metabolism is involved in the pathogenesis of CRC. However, its particular function in shaping the tumor immune microenvironment (TIME) and its effect on prognosis and immune treatment response remain unclear. METHODS: Based on the transcriptome and clinical data from The Cancer Genome Atlas-Colon Adenocarcinoma (TCGA-COAD) cohort, we performed unsupervised consensus clustering and classified patients into different molecular subtypes according to bile acid metabolism. We subsequently compared overall survival (OS), immune cell infiltration levels, and differentially expressed genes among the subtypes. In addition, protein-protein interaction (PPI) network and Cox proportional hazards regression were used to identify key hub genes. Finally, the expression of these crucial hub genes was validated in the Gene Expression Omnibus (GEO) cohort and independent clinical patients. RESULTS: The bile-low group showed a significant reduction in OS time (p = 0.0049). The infiltration levels of CD8+ T cells (p < 0.05) and M1 macrophages (p < 0.01) were significantly higher in the bile-low group than in the bile-high group. We identified three key genes-CLCA1, UGT2A3, and ZG16-and found that they all were downregulated in tumor tissues across the TCGA-COAD and GEO datasets, as well as in independent clinical samples. Survival analysis showed that high CLCA1 expression was significantly associated with favorable overall survival (p < 0.001), whereas UGT2A3 (p = 0.23) and ZG16 (p = 0.17) did not reach statistical significance. The three hub genes were negatively correlated with the (TIDE) score (CLCA1: R = - 0.24, p < 0.001; UGT2A3: R = - 0.15, p = 0.0022; ZG16: R = - 0.14, p = 0.0039). CONCLUSION: Our findings suggest that bile acid metabolism could shape the TIME via key genes CLCA1, UGT2A3, and ZG16, and subsequently modify CRC prognosis and immunotherapy responses. These genes may serve as potential prognostic indicators and mechanistic mediators linking bile acid metabolism to T-cell dysfunction, offering insights for future combination strategies targeting the metabolism-barrier-immunity axis.

CLCA1↗

PubMed2026

Proteogenomic features define subtypes of mantle cell lymphoma.

Mantle cell lymphoma (MCL) is a biologically heterogeneous B-cell malignancy. Although genomics and transcriptomics have delineated parts of the MCL disease spectrum, proteomics remains largely unexplored. Here, we conducted a comprehensive proteogenomic analysis integrating genomics, transcriptomics, and proteomics on peripheral blood samples from 27 patients with MCL and 4 healthy donors to investigate the translational and posttranslational dimensions of MCL. Our study identified 1296 downregulated and 468 upregulated proteins in MCL cells. The splicing pathways were significantly upregulated at both the mRNA and protein levels, suggesting a critical role for aberrant RNA splicing in MCL pathogenesis. Integration of proteomic data with genetic aberrations revealed immunoglobulin heavy chain variable mutational status and CCND1 mutation are associated with distinctive transcriptomic and proteomic profiles, which correspond to significant differences in clinical outcomes. A multiomics molecular stratification model incorporating proteomic data showed superior predictive power for patient survival compared with single-omics models (concordance index, 0.83 vs 0.74). This study provides, to our knowledge, the first comprehensive proteogenomic profile of MCL, offering novel insights into its molecular mechanisms and clinical behavior. The identification of molecular subtypes and prognostic protein signatures underscores the potential of proteomics to guide precision medicine strategies for MCL.

Humans↗

PubMed2026

Yes-Associated Protein (YAP)1 and β-Catenin Immunohistochemistry as a Surrogate Marker for GTF2I-Mutant Type A/AB Thymomas.

Thymomas are rare thymic epithelial tumors classified by the World Health Organization into type A/AB thymomas, which commonly harbor GTF2I mutations and behave indolently, and type B thymomas and thymic carcinomas, in which these mutations are less common. Type A and AB thymomas are uniquely enriched for a recurrent somatic hotspot mutation in GTF2I p. L424H; yet, this gene is rarely included in clinical sequencing panels, limiting its diagnostic utility. Yes-associated protein (YAP)1, the principal effector of the Hippo signaling pathway, and β-catenin, the central transcriptional effector of the Wnt pathway, have emerging roles in thymoma biology; however, their relationship to GTF2I mutation status and histologic subtype has not been systematically characterized. We analyzed The Cancer Genome Atlas thymoma data set and an institutional cohort of 38 thymic epithelial tumors to evaluate YAP1 and β-catenin immunohistochemistry (IHC) as surrogate markers for GTF2I mutation status and histologic classification. In The Cancer Genome Atlas data set, YAP1 and CTNNB1 mRNA expression were markedly elevated in type A/AB thymomas relative to type B and carcinoma subtypes, and GTF2I-mutant tumors exhibited significantly higher YAP1 mRNA expression than GTF2I-wildtype tumors. Targeted next-generation sequencing of our institutional cohort confirmed enrichment of the canonical GTF2I p. L424H hotspot in indolent subtypes. By IHC, both nuclear YAP1 positivity and cytoplasmic β-catenin localization were significantly more frequent in indolent thymomas. Cytoplasmic β-catenin demonstrated high specificity (94%) for indolent histology, supporting its use in diagnostically challenging cases such as type A versus type B3 distinction on small biopsies. YAP1 IHC showed a high negative predictive value for GTF2I mutations, such that a YAP1-negative result reliably excludes a GTF2I-mutant tumor. These findings implicate crosstalk between Hippo and Wnt signaling in GTF2I-mutant thymomas and position YAP1 and β-catenin IHC as accessible, cost-effective surrogates for molecular subtyping in a tumor where standard sequencing panels have limited coverage.

GTF2I↗

PubMed2026

[BRCA1 Gene's Mutations And Hereditary Breast Cancer: Genetic, Biological, And Clinical Aspects].

INTRODUCTION: Hereditary breast cancer accounts for approximately 5 to 10% of all breast cancer cases. Mutations in the BRCA1 gene, which plays a central role in DNA repair and cell cycle regulation, are the main cause of these familial forms and are strongly associated with aggressive subtypes, particularly triple-negative breast cancer. METHODS: A narrative literature review was conducted using biomedical databases (PubMed, Scopus, Web of Science, Google Scholar) between January 2024 and June 2025. Eligible publications addressed the genetic, biological, epidemiological, and clinical aspects of BRCA1 in hereditary breast cancer. RESULTS: BRCA1 ensures genomic stability through its roles in DNA repair, cell cycle checkpoints, and transcriptional regulation. Most mutations are truncating or missense variants, with some reported as founder mutations (e.g., c.68_69delAG, c.5266dupC, 943ins10). Women carrying germline BRCA1 mutations have an estimated lifetime risk of 56-87% of developing breast cancer, with a strong association with aggressive molecular subtypes, especially triple-negative breast cancer. CONCLUSION: A comprehensive understanding of BRCA1 mutations is crucial to enhance prevention, screening, and personalized management of hereditary breast cancer. In low-resource settings, the integration of genetic testing and counseling remains a major challenge and a public health priority to reduce disparities in cancer care.

Humans↗

PubMed2026

An oxidative stress - and immunotherapy-related six-gene signature defines immune subtypes and predicts prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Oxidative stress and the tumor immune microenvironment jointly shape hepatocellular carcinoma (HCC) progression and response to immunotherapy, yet integrated biomarkers linking these processes are lacking. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify oxidative stress- and immunotherapyrelated differentially expressed genes (OSIRDEGs). Functional enrichment, weighted gene co-expression network analysis (WGCNA) and LASSO-Cox regression were used to construct a prognostic signature. Consensus clustering, TIDE, CIBERSORT and ssGSEA characterized immune phenotypes. Somatic mutation, copy-number and drug-response data were integrated to assess genomic alterations and drug sensitivity. Expression of model genes was validated by qRT-PCR and western blotting in HCC cell lines. RESULTS: We identified 24 OSIRDEGs enriched in cell-cycle and mitotic pathways. WGCNA intersection yielded 18 module genes, from which a six-gene signature (BUB1B, CDKN2A, CENPE, HMMR, PTTG1, SPP1) was derived. The signature robustly stratified patients into high- and low-risk groups with significantly different progression-free and disease-free survival in both TCGA-LIHC and GSE14520. Based on signature expression, two molecular subtypes were defined, exhibiting distinct survival, immune landscapes and predicted immunotherapy responsiveness. Model genes harbored recurrent alterations and showed significant correlations with anticancer agents. All six genes were upregulated at mRNA and protein levels in metastatic HCC cell lines versus normal hepatocytes. CONCLUSIONS: We systematically explored the landscape of OSIRDEGs in HCC, and proposed a validated six-gene signature that refines prognostic stratification, delineates immunerelevant HCC subtypes and highlights candidate biomarkers for therapeutic selection and mechanistic investigation.

Humans↗

PubMed2026

Evaluation of the clinical and mechanistic role of MCM2 expression in the prediction of meningioma recurrence after radiotherapy.

OBJECTIVE: Postoperative radiotherapy is an effective treatment for meningiomas; however, treatment response varies among patients. In addition, practical methods for predicting tumor recurrence after radiotherapy have not been well established. Minichromosome maintenance protein 2 (MCM2), a key regulator of DNA replication licensing, was recently implicated in highly proliferative molecular subtypes of meningioma. In this study, the authors evaluated whether MCM2 immunohistochemical expression predicts response to radiotherapy in patients with meningiomas. METHODS: The authors retrospectively analyzed the records of patients with WHO grade 1-3 meningiomas treated with resection followed by radiotherapy at a single institution between July 2003 and November 2023. The MCM2 labeling index was assessed immunohistochemically, and patients were stratified into MCM2-high and -low groups using a cutoff of 35%. Progression-free survival (PFS) was defined as the interval from the completion of radiation therapy to postoperative radiological tumor recurrence or regrowth. Patients who showed no progression were censored at their last follow-up. PFS was estimated using Kaplan-Meier analysis and subsequently evaluated with Cox proportional hazards models. To further investigate the biological mechanisms associated with MCM2 expression, comprehensive transcriptomic analyses, including gene set enrichment analysis, was performed to elucidate the molecular processes that occur within MCM2-high tumors. RESULTS: The study population included 15 men (42%) and 21 women (58%), with a mean age of 63 years. Ten tumors (28%) were classified as MCM2-high meningiomas and 26 (72%) as MCM2-low meningiomas. High MCM2 expression was significantly associated with WHO grades 2-3 histology and higher Ki-67 labeling indices. During a median follow-up of 2.52 years, tumor progression after radiotherapy occurred in 47% of the patients. High MCM2 expression (HR 8.34, p = 0.03) was significantly associated with shorter PFS and remained an independent predictor of recurrence after adjustment for WHO grade, tumor size, and Ki-67 labeling index. Transcriptomic analyses of MCM2-high tumors revealed upregulation of cell proliferation-related pathways, accompanied by increased signaling through the E2F8-CHEK1 axis associated with radiation resistance and suppression of the TNF-α signaling pathway implicated in radiosensitivity. CONCLUSIONS: In meningiomas, high MCM2 expression is associated with early recurrence following radiotherapy. The study findings suggest that this association is driven by diverse biological mechanisms related to cell cycle regulation and radioresistance. Immunohistochemical assessment of MCM2 expression may serve as a practical and accessible biomarker for risk stratification and may support the future development of individualized postoperative radiotherapy strategies.

Humans↗

PubMed2026

Bibliometric analysis of retinoblastoma research over the past decade.

BACKGROUND: Retinoblastoma (RB), the most prevalent primary intraocular malignancy in children, has emerged as a model disease for exploring the molecular underpinnings of pediatric cancer. Over the past decade, research in this field has accelerated, propelled by advances in genomics, diagnostic imaging, targeted therapies, and global scientific collaboration. METHODS: This study systematically retrieved RB-related publications from 2015 to 2024 using the Web of Science Core Collection. A total of 4990 articles were included. CiteSpace and VOSviewer were employed to perform bibliometric and visual analyses across multiple dimensions, including countries, institutions, authors, journals, and thematic evolution. RESULTS: The United States and China were identified as the leading contributors, jointly accounting for over 40.55% of all publications. US-based journals led in both publication volume and citation impact, underscoring their global influence. Cluster analysis revealed 4 major research domains: clinical diagnosis, treatment, and prognosis; molecular mechanisms and signaling pathways; gene and protein function studies; and research methodologies and experimental models. CONCLUSION: RB research is transitioning into an era of precision oncology, characterized by molecular subtyping, novel therapeutic targets, and individualized treatment approaches. While diagnostic and therapeutic outcomes have markedly improved in high-income countries, significant disparities persist in low- and middle-income regions due to limited access to early detection and comprehensive care. Future priorities should include the refinement of preclinical models, investigation of drug resistance mechanisms, and promotion of international collaboration to standardize diagnostic and therapeutic strategies. These efforts are critical to improving global outcomes for children with RB.

Retinoblastoma↗

PubMed2025

A comparative genomic analysis of left- and right-sided colon cancer using real-world data from the AACR project GENIE BPC dataset.

Left- and Right-sided colon cancers (LCC and RCC) are increasingly recognized as distinct clinicopathological and molecular subtypes with divergent prognoses and therapeutic responses. Leveraging a large, multi-institutional cohort from the AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) Biopharma Collaborative (BPC) (n = 750; LCC: 363 vs. RCC: 387), we conducted a comprehensive analysis of mutational profiles, tumor mutation burden (TMB), and survival outcomes. Our findings revealed a markedly higher TMB in RCC compared to LCC (6.65 ± 11.3 vs. 3.17 ± 4.35; adjusted P = 3.12×10-32), suggesting greater genomic instability in RCC. After applying functional annotation filters (PolyPhen > 0.85, SIFT < 0.05), RCC tumors were significantly enriched for mutations in BRAF (23.1% vs. 6.7%), KMT2D (8.6% vs. 3.2%), and SMAD4 (13.1% vs. 7.3%), while TP53 mutations predominated in LCC (40.6% vs. 31.8%). Multivariate Cox regression analysis identified RCC as an independent predictor of poorer overall survival (OS) relative to LCC (HR: 1.30, 95% CI: 1.02-1.66, P = 0.033). Notably, KRAS mutations were associated with significantly worse OS in LCC (HR: 1.68, 95% CI: 1.06-2.70, P = 0.027), while BRAF mutations predicted adverse outcomes in RCC (HR: 1.58, 95% CI: 1.05-2.37, P = 0.028). These results underscore the prognostic value of tumor sidedness and specific genetic alterations in colon adenocarcinoma. Our study highlights the need for sidedness-specific molecular profiling to inform precision oncology strategies in colon cancer management.

BRAF↗

PubMed2026

Methylation-Associated Differentiation Features Define Biological and Prognostic Heterogeneity in CMS4 Colorectal Cancer.

Consensus molecular subtype 4 (CMS4) colorectal cancer (CRC) is associated with an aggressive clinical course and poor survival, yet the biological basis of heterogeneity within this subtype remains incompletely understood. DNA methylation is an epigenetic mechanism involved in transcriptional regulation, cellular differentiation, and colorectal tumorigenesis. Here, we integrated single-cell RNA sequencing (scRNA-seq), bulk data, and promoter DNA methylation data to characterize CMS4-associated cancer cell states and methylation-related features. Using the scAB algorithm, we integrated scRNA-seq with bulk CMS4 data and identified CMS4-related cells distributed across multiple patients. Single-cell analyses of cell-cell communication and transcriptional regulation revealed a CMS4-related cancer cell population characterized by macrophage migration inhibitory factor (MIF)-centered intercellular communication, enhanced caudal type homeobox 1 (CDX1) and Kruppel-like factor 5 (KLF5) regulon activity, and gene modules enriched in differentiation-related pathways. CytoTRACE analysis further stratified CMS4 cancer cells into poorly and well-differentiated states, yielding 802 differentially expressed genes (DEGs). Linking these differentiation-associated DEGs with bulk expression and promoter methylation data identified 218 methylation-associated DEGs showing significant inverse methylation expression correlations, suggesting a link between differentiation-related heterogeneity and promoter methylation. Univariable Cox regression followed by LASSO regression further prioritized eight genes for construction of the methylation and differentiation-related prognostic model (MeDiff-PM). MeDiff-PM consistently stratified overall survival in the TCGA CMS4 cohort and two independent validation cohorts, with cutoff-independent continuous Cox analyses further supporting its prognostic association across cohorts. And MeDiff-PM remained prognostically significant after adjustment for available clinical variables. High MeDiff-PM risk scores were associated with activation of P53, WNT, and ubiquitin-mediated proteolysis pathways and with consistent predicted drug response differences for compounds across three CMS4 cohorts. While individual in silico knockout analysis suggested links between MeDiff-PM genes and metallothionein-related and immune-associated transcriptional responses. Collectively, these findings indicate that methylation-associated differentiation features represent a molecular dimension of intra-CMS4 heterogeneity and provide a biologically informed framework for prognostic stratification within CMS4 CRC.

Humans↗

PubMed2025

Distinct immune-metabolic phenotypes underlie poor coronary collateral circulation.

BACKGROUND: Coronary collateral circulation (CCC) significantly impacts myocardial perfusion and clinical outcomes in coronary artery disease patients, yet the underlying molecular heterogeneity remains inadequately characterized. OBJECTIVE: To identify distinct molecular phenotypes in patients with poor CCC, validate these phenotypes using clinical parameters, and evaluate their prognostic implications. METHODS: This study enrolled 149 patients (80 with good CCC and 69 with poor CCC) for high-throughput proteomic profiling. Unsupervised consensus clustering identified molecular subtypes within poor CCC patients, followed by differential expression analysis and KEGG pathway enrichment. Boruta feature selection was implemented, and multiple machine learning algorithms were tested on clinical data, with XGBoost optimization (accuracy 80.0%, F1-score 80.31%) and SHAP value interpretation. External validation was performed using the MIMIC database. Kaplan-Meier analysis and Cox regression models assessed major adverse cardiovascular events (MACE). RESULTS: Two distinct phenotypes emerged among poor CCC patients: Cluster 1 (n = 39, Complement-Driven Vascular Remodeling [CDVR]) and Cluster 2 (n = 30, Immuno-Thrombotic Myocardial Dysfunction [ITMD]). An XGBoost model incorporating fasting glucose, eosinophil percentage, and HbA1c achieved excellent discrimination (AUC > 0.91). External validation confirmed the phenotype-specific clinical patterns. Notably, Cluster 2 demonstrated significantly higher MACE incidence compared to Cluster 1 (Log-rank p < 0.05), with KEGG analysis revealing significant upregulation of platelet activation, diabetic cardiomyopathy, and metabolic pathways in the ITMD phenotype. CONCLUSION: Poor CCC encompasses distinct immune-metabolic phenotypes that can be accurately classified using integrated proteomic-clinical modeling. This classification enables more precise risk stratification and may guide personalized therapeutic strategies for coronary artery disease patients with inadequate collateralization.

Humans↗

PubMed2026

Translational Gap in Biomarker Discovery: Tumor Surface Markers Rarely Mirror Circulating Levels.

BACKGROUND: Tumor-associated cell surface proteins are frequently proposed as circulating biomarkers for colorectal cancer (CRC) based on their high tumor expression. However, many candidates identified through tissue-based analyses fail to translate into clinically useful biomarkers. We investigated the translational gap between tissue-level expression and circulating detectability in CRC, focusing on molecular subtypes defined by caudal-type homeobox 2 (CDX2) expression. METHODS: Transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to identify cell surface markers differentially expressed between CDX2-Low and CDX2-High CRCs. A clinical cohort of right-sided CRC patients was evaluated using paired tumor tissue and preoperative plasma samples. CDX2 expression was assessed by immunohistochemistry, and circulating concentrations of selected cell surface proteins were quantified using a multiplex ELISA platform. RESULTS: Several tumor-associated cell surface markers exhibited marked CDX2-dependent differences in tissue expression. However, for most markers, circulating plasma levels did not mirror tissue-level patterns. CEACAM1 was the sole marker demonstrating concordant CDX2-dependent differences in both tumor tissue and plasma, with significantly lower levels in CDX2-Low CRCs. In contrast, CEACAM5 showed a dissociation between tissue expression and circulating levels, despite analytical validation against serum carcinoembryonic antigen (CEA). CONCLUSIONS: Our findings demonstrate that tumor overexpression of cell surface markers does not necessarily translate into detectable circulating biomarkers. This translational disconnect underscores limitations of biomarker selection strategies based solely on tissue expression and highlights the importance of integrating systemic biology into biomarker development. While some tumor-associated proteins may lack utility as circulating biomarkers, they may still represent viable therapeutic targets in CRC.

CDX2↗