Breast cancer (BC) is a heterogeneous disease, and triple-negative breast cancer (TNBC) is the most aggressive and immunogenic subtype. A significant proportion of TNBC cases are linked to hereditary cancer syndromes involving pathogenic germline variants, most commonly in BRCA1/2. However, few studies have compared hereditary and sporadic TNBC in admixed populations. In this study, molecular and immunological features were analyzed through the analysis of 62 Colombian TNBC samples (20 hereditary and 42 sporadic cases) by RNA sequencing to identify molecular and immune differences. We used an external validation cohort of 16 TCGA TNBC cases (8 BRCA-mutated and 8 non-mutated) to replicate our findings. Results: We found a set of 921 differentially expressed genes (DEGs) between hereditary and sporadic TNBC. Hereditary tumors were enriched for pathways related to extracellular matrix (ECM) remodeling, structural components, and DNA damage response and exhibited a more immunologically active tumor microenvironment compared to sporadic tumors. LASSO logistic regression identified 23 genes with discriminatory potential, showing that hereditary tumors are characterized by complex immune regulation, inflammatory processes, and activation of key oncogenic pathways. Conclusions: Hereditary TNBC is characterized by molecular and biological functions linked to ECM remodeling and its constituents and an active immune microenvironment. This integrated molecular–immune profile provides insight into the distinct biology of hereditary tumors in admixed populations.

Uveal melanoma (UVM) is an aggressive cancer with a poor prognosis, particularly in metastatic cases. This study aimed to develop and validate a novel extracellular matrix (ECM) gene expression signature to predict prognosis and stratify patients by risk. ECM-related genes were identified and used to construct a prognostic model through Lasso–Cox regression analysis, leveraging RNA sequencing data from 80 UVM patients in The Cancer Genome Atlas (TCGA). The model was validated using an independent cohort of 63 UVM patients. Survival analyses, immune infiltration profiling, and functional enrichment analyses were conducted to evaluate the biological significance and clinical utility of the signature. The ECM signature stratified patients into high- and low-risk groups with significant differences in survival outcomes. High-risk patients showed elevated expression of MMP1 and MMP12, which are associated with ECM remodeling and immune modulation, alongside increased infiltration of immunosuppressive cells, such as M2 macrophages. Validation confirmed the prognostic value of the signature across cohorts. Functional analyses highlighted the involvement of ECM-related pathways, epithelial–mesenchymal transition, and immune system interactions in tumor progression. This ECM gene expression signature is a robust prognostic tool for UVM, offering insights into tumor biology and immune microenvironment interactions. It holds promise for improving patient stratification and guiding personalized therapeutic strategies. Further research is warranted to explore the functional roles of these genes in UVM progression.

Background: High-grade serous ovarian cancer (HGSOC) is a highly aggressive malignancy with poor prognosis due to late-stage diagnosis and limited treatments. Identifying differentially expressed genes (DEGs), and immune cell infiltration patterns may improve prognostic assessment and therapeutic strategies. Methods: We conducted a meta-analysis of gene expression data from the GEO (Gene Expression Omnibus, NCBI). DEGs were identified, functionally enriched, and analyzed for protein-protein interactions. Overlaps with oncogenes and tumor suppressor genes were examined. Cox survival analysis and a gene expression-based risk stratification model were developed. Immune infiltration differences were assessed using deconvolution methods. Results: A total of 11 studies (291 HGSOC, 96 controls) identified 892 DEGs, mainly involved in mitochondrial function, vesicle trafficking, and immune regulation. Key oncogenes (EZH2, PDK1, ERBB2) and tumor suppressor genes (BRCA1, DUSP22) were identified. Survival analysis associated the expression of SEC24B, TGOLN2, TRAK1, and CAST with poor prognosis. Low-risk patients had higher activated dendritic cells and CD4+ memory T cells while high-risk patients were enriched in common lymphoid progenitors and megakaryocyte-erythroid progenitors. Conclusions: This study identifies key DEGs in HGSOC progression and presents a risk stratification model predicting patient outcomes.