Cancer Informatics最新文献

{"title":"Integration of Multi-Omics Data Identifies the Role of the Selenium-Related Gene PNPO and Pre-exhausted CD127^- CD8⁺ T Cells in Laryngeal Carcinoma.","authors":"Lin Xiang, Lin Chen, Cheng Gong, Yao Tang","doi":"10.1177/11769351261438477","DOIUrl":"https://doi.org/10.1177/11769351261438477","url":null,"abstract":"<p><strong>Objective: </strong>To elucidate mechanistic links among selenium measures, selenium-related genes, and immune traits in laryngeal carcinoma (LC) by integrating Mendelian randomization, bulk transcriptomic, and single-cell analyses.</p><p><strong>Methods: </strong>Two-sample Mendelian randomization (MR) was used to evaluate the causal effects of selenium measures and genetically predicted expression of selenium-related genes instrumented by eQTLs on LC risk, and immune traits were screened as candidate mediators via a directionality-based filter. We then examined PNPO expression in relation to pathway activity and immune infiltration in the TCGA and GEO cohorts. Single-cell RNA sequencing was further analyzed to characterize PNPO-associated programs in malignant epithelial and immune cells. The scPagwas and deconvolution algorithms were applied to prioritize disease-relevant T-cell subsets, and hdWGCNA was used to identify phenotype-associated gene modules. Intercellular communication, signaling activity, developmental trajectories, and transcription factor programs were evaluated in complementary analyses. The reporting of this study conforms to the STROBE-MR guideline for Mendelian randomization studies.</p><p><strong>Results: </strong>Genetically predicted selenium measures showed no evidence of a causal association with LC risk. In contrast, PNPO showed evidence consistent with involvement in LC susceptibility, potentially involving CD127^- CD8⁺ T cells. In bulk transcriptomic cohorts, tumors with low PNPO expression were enriched for oncogenic pathways and were associated with poorer survival. PNPO expression correlated positively with inferred CD8⁺ T-cell infiltration. At single-cell resolution, PNPO^- malignant epithelial cells displayed transcriptional features consistent with stemness, drug resistance, and immune-evasion programs. We further identified a pre-exhausted CD127^- CD8⁺ T-cell subset with distinct molecular and functional characteristics.</p><p><strong>Conclusion: </strong>These analyses implicate PNPO-linked vitamin B6 metabolism and a pre-exhausted CD127^- CD8⁺ T-cell state in LC, highlighting candidates for mechanistic validation and potential therapeutic exploration.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351261438477"},"PeriodicalIF":2.5,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13100444/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In Silico Analysis of the Dual Role of Tumor Microenvironment on Colon Cancer Subtypes.","authors":"Christianah Kehinde, Michelle Livesey, Yeuko Manganyi, Hocine Bendou","doi":"10.1177/11769351261431245","DOIUrl":"10.1177/11769351261431245","url":null,"abstract":"<p><strong>Background: </strong>Colon cancer is a highly heterogeneous disease, marked by substantial intra- and inter-tumor variability. Investigating transcriptomic profiles can offer deeper insight into this heterogeneity. However, most genome-transcriptome studies on colon cancer have primarily focused on examining primary tumors and matched normal tissues, often neglecting the multi-stage disease progression.</p><p><strong>Objective: </strong>To establish unique molecular colon subtypes based on the progression in transcriptomic profiles. Additionally, to investigate the implicated factors, such as mutations and the tumor microenvironment (TME), that affect colon cancer progression and their implications for therapy.</p><p><strong>Methods: </strong>RNA-sequencing data from The Cancer Genome Atlas Colon Cancer (TCGA-COAD) cohort were obtained from the UCSC Xena database, including 47 early and 39 late-stage tumor samples. Heterogeneity was exposed by tracking cancer progression through the multi-stages of cancer development. Hierarchical clustering revealed colon subtypes with varying progression, and differentially expressed genes (DEGs) were identified between these subtypes. The DEGs were subjected to Recursive Feature Elimination and mutational analyses to reveal driver genes. The TME and biological pathways were analyzed. The study was validated with an independent GEO dataset.</p><p><strong>Results: </strong>Two novel colon subtypes were identified. Significant enrichment pathways and varied mutations in cancer driver genes were found in both subtypes. Interestingly, concurrent downregulation of oncogenes and tumor suppressor genes was observed in one of the subtypes, suggesting a link to the dual functionality of CD4 and CD8 T-cells in the TME.</p><p><strong>Conclusion: </strong>Overall, our study demonstrates a complex relationship between TME and gene expression of driver genes. The presence of immune cell fractions with dual functions suggests a balanced early-to-late-stage progression. The findings provide insights into the disease progression that potentially contribute to the development of targeted therapies.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351261431245"},"PeriodicalIF":2.5,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13033067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147582381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"hsa-miR-1246 is Consistently Overexpressed in Spheroid-Derived Cancer Stem Cells From Multiple Tumor Types.","authors":"Ángela Y García Fonseca, Yeimy González-Giraldo, Natalia Vargas Rondón, Andrés F Aristizábal-Pachón","doi":"10.1177/11769351251414086","DOIUrl":"10.1177/11769351251414086","url":null,"abstract":"<p><p>Tumors consist of various cell types, including a small population of cancer stem cells (CSCs), which are linked to metastasis, drug resistance, and recurrence. Maintaining the CSC phenotype requires regulation of molecules, including miRNAs; they are small non-coding RNAs involved in processes such as proliferation, differentiation, invasion, and apoptosis. However, miRNAs involved in CSC generation and maintenance remain largely unidentified. In this study, we aimed to identify miRNAs associated with CSC populations by studying the miRNA profiles in Spheroids-Derived cancer stem cells (SDCSCs) from different cancer cell lines. Firstly, we used small RNA sequencing by Illumina to identify differentially expressed miRNAs from SDCSCs compared with adherent cells from lung cancer cell line. MiRNAs with <i>P</i> < .05 and fold change >1.0 were considered significant. Next, we conducted a meta-analysis to integrate expression data from studies performed under same conditions from several tumor cell lines such as ovarium, breast, colorectal cancer cell lines. We reanalyzed microarrays and RNA sequencing data. For integration we employed the Robust Rank Aggregation approach. We identified only one upregulated miRNA, the hsa-miR-1246 with a <i>P</i>-value 1.6356^-5. hsa-miR-1246 showed consistent overexpression in CSC-enriched spheroids, with fold changes ranging from 2.4 to 3.8 (<i>P</i> < .05) across studies. Bioinformatics analysis revealed that hsa-miR-1246 interacts with cyclins, GSK3B, and other experimentally validated targets, which were related to the cell cycle (FDR 8,40E-03) and the regulation of transcription from RNA polymerase II (FDR 8,30E-03). Our results provide the first integrative study showing that hsa-miR-1246 is consistently overexpressed from cancer stem cells in different tumor cell lines, suggesting a direct link between its oncogenic activity and the CSC phenotype. Since our analysis demonstrates that miR-1246 overexpression is highly specific to CSCs rather than differentiated tumor cells, its detection in patients could serve as an indirect indicator of CSC abundance and tumor aggressiveness. This provides new biological insight into the cellular origin of this miRNA and supports its potential use as a biomarker of stemness and therapeutic target in cancer. Additional studies using in vivo models and functional knockdown experiments will be important to validate these findings and better define the role of hsa-miR-1246 in CSC regulation.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351251414086"},"PeriodicalIF":2.5,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13009628/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Depower: An R Package for Simulation-Based Power Analysis of Differential Expression Studies.","authors":"Brett Klamer, Lianbo Yu","doi":"10.1177/11769351261431247","DOIUrl":"https://doi.org/10.1177/11769351261431247","url":null,"abstract":"<p><p>Sample size calculations and power analyses are essential components of experimental design in modern biomedical research. Designs that account for sample correlation, multiple testing, and other sources of variability inherent to specific studies are routinely employed for identifying differential expressions. Despite recent advances in methodologies and software tools for power analysis, there remains a lack of statistical packages capable of accommodating these complex designs in differential expression studies. To fill this gap, we provide the R package depower, which implements the simulation-based framework presented in our recent publications. This unified framework covers both independent and dependent group comparisons and controls false positive rates by employing a simulation-based approach to calculate the empirical null distribution of test statistics.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351261431247"},"PeriodicalIF":2.5,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12988263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147469308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Prognostic 9-Gene Signature Linked to Autophagy-Dependent Cell Death in Hepatocellular Carcinoma.","authors":"Jin Zhang, Linze Xu, Hao Wang, Dandan Wu, Huikai Li, Yueguo Li, Yang Liu","doi":"10.1177/11769351261426577","DOIUrl":"https://doi.org/10.1177/11769351261426577","url":null,"abstract":"<p><strong>Objectives: </strong>Autophagy-dependent cell death (ADCD) plays a pivotal role in solid tumors, ultimately influencing immunotherapeutic efficacy and cancer prognosis. However, its significance in hepatocellular carcinoma (HCC) remains underexplored.</p><p><strong>Methods: </strong>Through integrated analysis of single-cell and bulk transcriptomic data, this research systematically identified ADCD-associated genes in LIHC. This was achieved by applying AddModuleScore, ssGSEA, and WGCNA for robust gene screening. A prognostic model was developed for LIHC grounded in The Cancer Genome Atlas (TCGA) dataset. Its validity was confirmed through internal validation with an independent TCGA cohort and external validation using GEO datasets. Immune characteristics were assessed by adopting CIBERSORT and ESTIMATE algorithms. Through LASSO-Cox regression analysis, this research established a 9-gene ADCD signature and derived the ADCD-related risk score system (ADCDRS).</p><p><strong>Results: </strong>The ADCDRS demonstrated superior prognostic performance. Aside from that, this unique system was significantly associated with clinical features, immune infiltration patterns, and the tumor's local environment. To improve clinical applicability, this research constructed a nomogram incorporating the ADCDRS. Additionally, potential therapeutic agents targeting specific risk subgroups were identified.</p><p><strong>Conclusion: </strong>This study highlights the prognostic and therapeutic potential of ADCD-related biomarkers in LIHC.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351261426577"},"PeriodicalIF":2.5,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12988277/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147469370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Clinical Trial Selection for Cancer Patients Using Large Language Models.","authors":"Lisa Gandy, Frank Tilli","doi":"10.1177/11769351251399641","DOIUrl":"https://doi.org/10.1177/11769351251399641","url":null,"abstract":"<p><strong>Purpose: </strong>Identifying appropriate clinical trials for cancer patients with specific gene mutations remains a significant challenge, largely due to limitations in current search tools like ClinicalTrials.gov, which at times return irrelevant or misleading results. This diagnostic accuracy study investigates the efficacy of 2 large language models (LLMs), GPT-4.0 and Gemini 2.0, in evaluating the eligibility of patients with specific cancer-related gene mutations for clinical trials.</p><p><strong>Methods: </strong>The study prompts GPT 4.0 and Gemini 2.0 with trial details from ClinicalTrials.gov and a particular cancer mutation. We then assess model performance against physician-curated benchmarks across 6 gene mutations (ALK, BRAF, EGFR, ERBB2, KIT, and KRAS).</p><p><strong>Results: </strong>The results demonstrate good <i>F</i>1-scores for both LLMs-averaging 64% for GPT-4.0 and 70% for Gemini 2.0-highlighting their potential to streamline clinical trial matching. Furthermore, decision trees provided interpretability by identifying key textual indicators that LLMs use.</p><p><strong>Conclusion: </strong>This work demonstrates the feasibility of using proprietary LLMs such as GPT 4.0 and Gemini 2.0 \"off the shelf\" with both limited LLM fine-tuning and limited patient information to evaluate clinical trial eligibility.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351251399641"},"PeriodicalIF":2.5,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12929875/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147310682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resilient Sinkhorn-Based Optimal Transport Late Fusion Framework for Breast Cancer Diagnosis.","authors":"Michael Asiedu Asare, Isaac Acquah, Benjamin Appiah Yeboah, Emmanuel Owusu","doi":"10.1177/11769351261420789","DOIUrl":"https://doi.org/10.1177/11769351261420789","url":null,"abstract":"<p><strong>Objective: </strong>This research aims to develop and evaluate a clinically deployable multimodal deep learning framework for breast cancer diagnosis that maintains robustness, even when clinical data are asynchronous, unpaired, or incomplete, effectively addressing real-world challenges related to data heterogeneity and fragmented clinical workflows.</p><p><strong>Methods: </strong>In this retrospective study, a multimodal deep learning architecture was developed that integrates histopathological images with structured clinical risk factors. Custom models were developed and independently trained for each modality, and late fusion was achieved via a dynamically reweighted Sinkhorn-based fusion layer. Model performance was evaluated using precision-recall Area Under Curve (PR-AUC), recall, <i>F</i>1 score, and Brier score under complete and partial modality availability scenarios. Robustness and clinical utility were further assessed through statistical significance testing and decision curve analysis (DCA). Additionally, we employed a Sinkhorn cost matrix to enhance interpretability.</p><p><strong>Results: </strong>The proposed Sinkhorn fusion model outperformed all baseline methods, achieving the highest recall (0.96), PR-AUC (0.775), <i>F</i>1 score (0.828), and the best calibration (Brier score ≈ 0.19). Notably, it maintained perfect recall (1.00) under a 50% simulated modality dropout, despite a significant drop in PR-AUC (20% vs 0%: <i>t</i> = -20.35, <i>P</i> < .0001; 50% vs 0%: <i>t</i> = 88.60, <i>P</i> < .0001), portraying a strong overall robustness to information missingness. Under internally controlled conditions, DCA demonstrated superior clinical utility across thresholds of 0.2 to 0.7.</p><p><strong>Conclusions: </strong>The model's ability to accommodate unpaired and incomplete clinical inputs while maintaining both calibration and sensitivity makes it particularly well-suited for deployment in asynchronous and resource-constrained settings. Its consistent performance under clinical uncertainty and minimal preprocessing requirements represents a significant advancement toward equitable, reliable, and scalable AI-assisted breast cancer screening. To our knowledge, this is the first paper to model breast cancer late fusion as an optimal transport problem.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351261420789"},"PeriodicalIF":2.5,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12929828/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147291301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Novel Hub Genes and Potential Signaling Pathways with the Pathogenesis of Oral Cavity Squamous Cell Carcinoma Based on Bioinformatics Analysis.","authors":"Mohammad Reza Eskandarion, Mojtaba Vand Rajabpour, Shahroo Etemad-Moghadam, Farrokh Heidari, Seyede FatemeMahmoudi Hashemi, Hadiseh Mohammadpour, Amir Mohammad Karimi, Ebrahim Karimi, Mojgan Alaeddini","doi":"10.1177/11769351261417703","DOIUrl":"10.1177/11769351261417703","url":null,"abstract":"<p><strong>Background & aim: </strong>Oral squamous cell carcinoma (OSCC) is a devastating disease with poor prognosis and low survival rates, despite advancements in diagnosis and treatment. Early detection and identification of molecular targets are crucial for improving patient outcomes. This study aims to identify differentially expressed genes (DEGs) and key molecular pathways involved in the OSCC. This study's findings will contribute to the development of effective targeted therapies, ultimately improving the prognosis and survival rates of OSCC patients.</p><p><strong>Materials & methods: </strong>Three gene expression profiles (GSE37991, GSE30784, and GSE107591) from the GEO database were analyzed for differentially expressed genes using EnrichR. Subsequent downstream analyses of the selected module genes were conducted using various bioinformatics tools including STRING, Cytoscape, GEPIA, cBioPortal, NetworkAnalyst, MirWalk, and a bipartite miRNA-mRNA correlation network.</p><p><strong>Result: </strong>The reanalysis indicated that the Toll-like receptor (TLR) signaling pathway plays a significant role in the development of oral SCC and CXCL8, CCL5, CXCL10, STAT1, IL1B, and TLR2 genes were up-regulated and enriched significantly in the signaling pathways' interactions in oral SCC. Genetic mutation analysis of hub genes in OSCC revealed that STAT1 have 2.5% mutation rate and 0% for other genes. It was revealed that the development and prediction of OSCC may be affected by hsa-mir-146a-5 and hsa-mir-155-5p.</p><p><strong>Conclusion: </strong>Novel potential biomarkers and signaling pathways associated with OSCC have been identified, which may be important in the transformation of OSCC adenocarcinoma and may serve as therapeutic targets for OSCC.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351261417703"},"PeriodicalIF":2.5,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12905109/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146203098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"C1QBP Associated With Immune Infiltration Predicts Poor Prognosis in Lung Adenocarcinoma.","authors":"Minghang Zhang, Ying Wang, Fei Qi, Xiaomei Yang, Tongmei Zhang, Shaofa Xu","doi":"10.1177/11769351261415650","DOIUrl":"10.1177/11769351261415650","url":null,"abstract":"<p><strong>Objectives: </strong>C1QBP is a multi-compartmental protein implicated in diverse cellular processes. However, its clinical predictive value, particularly its association with immune cell infiltration, in lung adenocarcinoma (LUAD) remains unelucidated. Thus, the present study aimed to comprehensively evaluate C1QBP expression patterns, prognostic significance, and its correlation with the tumor immune microenvironment (TIME) in LUAD.</p><p><strong>Methods: </strong>We first assessed C1QBP expression levels and prognostic relevance in LUAD using multiple bioinformatics platforms. Subsequently, we analyzed the associations of C1QBP expression with immune cell infiltration and immunotherapeutic response, and identified signaling pathways linked to C1QBP expression via Gene Set Enrichment Analysis (GSEA). Finally, enzyme-linked immunosorbent assay (ELISA) was employed to validate the correlation between serum C1QBP concentration and prognosis in non-small cell lung cancer (NSCLC) patients receiving immunotherapy.</p><p><strong>Results: </strong>C1QBP was highly expressed in LUAD tissues, and this high expression was significantly associated with advanced tumor stage. Moreover, high C1QBP expression emerged as an independent risk factor for overall survival (OS) in LUAD patients. Bioinformatics analyses revealed that C1QBP expression was negatively correlated with the infiltration levels of multiple immune cell subsets (including T cells, B cells, and dendritic cells) in LUAD, while patients with low C1QBP expression exhibited higher Immunophenoscore (IPS). GSEA further demonstrated that high C1QBP expression was positively correlated with pathways regulating the tumor cell cycle, but negatively correlated with immune-related signaling pathways. Finally, in NSCLC patients treated with immune checkpoint inhibitors (ICIs), those with higher serum C1QBP concentrations had significantly shorter OS and progression-free survival (PFS).</p><p><strong>Conclusions: </strong>Our study identifies C1QBP as a potential oncogene that is closely associated with the TIME in LUAD. Collectively, these findings suggest that C1QBP holds promise as a novel indicator of poor prognosis in LUAD patients.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351261415650"},"PeriodicalIF":2.5,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12901909/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146203172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"THBS3 Functions as a Novel Biomarker for Prognosis and Immunotherapeutic Response in Colorectal Cancer: An Integrative Analysis and Validation of the Thrombospondin Gene Family.","authors":"Tao Jiang, Sichao Zhu, Hengyi Zhou, Ningning Zhang, Long Zhang, Changwen Zou, Hu Song","doi":"10.1177/11769351251412614","DOIUrl":"10.1177/11769351251412614","url":null,"abstract":"<p><strong>Background: </strong>The THBS gene family plays key functions in various diseases; however, its specific roles in colorectal cancer (CRC) have not been systematically characterized.</p><p><strong>Methods: </strong>Multi-omics data and online databases were used to analyze the mRNA expression levels of the THBS gene family in CRC and their correlations with clinicopathological features and survival. This analysis identified THBS3 as a potential oncogene closely linked with CRC progression. Then, the relationship between THBS3 expression and the immune landscape was assessed. Single-cell RNA sequencing analyzed THBS3 distribution in CRC subtypes. Additionally, GO, KEGG, and GSEA enrichment analyses investigated the mechanisms of THBS3 in CRC. Molecular docking identified anticancer compounds with high affinity for THBS3. Lastly, in vitro experiments examined THBS3's function in CRC.</p><p><strong>Results: </strong>THBS3 was significantly upregulated in CRC and correlated with poor prognosis. Elevated THBS3 correlated with increased infiltration of M2 macrophages and regulatory T cells (Treg cells), as well as higher expression of immune checkpoint molecules, suggesting its role in shaping an immunosuppressive microenvironment. THBS3 promoted CRC cell proliferation and metastasis, through activation of the PI3K-AKT and EMT pathways.</p><p><strong>Conclusion: </strong>THBS3 facilitates the progression of CRC and may serve as a novel prognostic biomarker and therapeutic target.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"25 ","pages":"11769351251412614"},"PeriodicalIF":2.5,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12847665/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146087384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}