Search PubMedSearch

SEARCH · Search PubMed

Results for “Immune contexture”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

2 recordsLinked to original sources

HLA class I expression and tumor immune infiltration together shape colon cancer immune contexture.

BACKGROUND: The relative contribution of HLA class I molecules-including classical HLA class Ia (HLA-A, -B, -C) and non-classical HLA class Ib (HLA-E, -F, -G)-to shaping the tumor immune microenvironment in colon cancer remains insufficiently defined. We investigated how their expression patterns relate to immune infiltration and clinical outcome. METHODS: In a retrospective cohort of 280 colon cancers, we assessed HLA class Ia and class Ib expression and quantified CD45-positive immune cell infiltration by immunohistochemistry. These features were correlated with clinicopathological variables, microsatellite instability (MSI) status, and previously established genomic immune signatures. RESULTS: High HLA class Ia expression and increased CD45-positive cell infiltration were each associated with improved overall, disease-specific, and progression-free survival. CD45-positive density correlated strongly with Immunologic Constant of Rejection scores. HLA class Ia loss was more frequent in advanced stages and in MSI-H tumors. Among HLA class Ib molecules, only HLA-E expression was associated with favorable disease-specific and progression-free survival. Integrative analysis identified three immune phenotypes with distinct prognostic profiles; tumors characterized by high HLA class Ia expression, low HLA class Ib expression, and high CD45-positive infiltration had the best outcomes. CONCLUSION: Colon cancer immunogenicity is shaped by coordinated patterns of HLA class I expression and immune infiltration. Integrating HLA class Ia/Ib expression with immune cell density provides a refined stratification of tumor immune phenotypes and may support personalized immunotherapeutic decision-making.

Antigen presentation

Lymphangiogenesis-related gene signature-based risk model for prognostic assessment of cervical cancer: immune-metabolic characterization and molecular subtype analysis.

BACKGROUND: Lymphangiogenesis promotes tumor dissemination and may shape the immune contexture of cervical cancer, yet lymphangiogenesis-related prognostic stratification and its immunometabolic implications remain insufficiently defined in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). METHODS: TCGA-CESC transcriptomes and clinical data were obtained from UCSC Xena and integrated with normal cervix tissues from the Genotype-Tissue Expression Project after batch correction. Prognostic LYMRGs were first identified from the differentially expressed set using univariable Cox proportional hazards analysis. Candidate genes were then reduced using an L1-regularized Cox model (Least Absolute Shrinkage and Selection Operator), and the remaining markers were entered into a multivariable Cox regression to obtain the final coefficients and compute an individualized risk score. The model's prognostic value was further assessed in an independent Gene Expression Omnibus dataset. In addition, expression patterns of the signature genes were leveraged for molecular subtyping of TCGA samples via non-negative matrix factorization (NMF). Immune infiltration and immunotherapy-associated characteristics were interrogated through a multi-algorithm strategy (single-sample gene set enrichment analysis, CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore . Additional analyses included pathway enrichment (GSEA/GO/KEGG), drug sensitivity prediction (pRRophetic/CellMiner), and ceRNA network analysis. RESULTS: A six-gene LYMRG signature robustly stratified survival. High-risk patients had significantly worse overall survival in The Cancer Genome Atlas with AUCs of 0.819/0.801/0.801 at 1/3/5 years, and in GSE52903 (P = 0.001) with AUCs of 0.733/0.719/0.725. NMF identified two subtypes with distinct prognosis (P = 0.01) and divergent immune landscapes. Risk groups and subtypes exhibited consistent differences in immune infiltration, checkpoint expression, TIDE/IPS patterns, and pathway enrichment. Predicted chemosensitivity differed by risk group, and the ceRNA network suggested candidate upstream lncRNA regulators of the signature. CONCLUSION: A lymphangiogenesis-related six-gene model enables clinically meaningful prognostic stratification of CESC and links lymphangiogenesis programs to distinct tumor immune phenotypes and therapeutic vulnerabilities.

cancer