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Administration of PARP inhibitors against breast and ovarian cancers with BRCA1 and BRCA2 mutations has shown clinical benefits in patients. However, these agents are also toxic and have a narrow therapeutic index. In this work, we aimed to identify membrane proteins that are specifically upregulated in these cancers. We interrogated public datasets to analyze genes upregulated or downregulated when these mutations were present, compared with wild-type cancers. Surface protein expression and functional annotation analyses were also performed. In breast cancer, we identified 11 upregulated and 44 downregulated transcripts in BRCA1-mut, while 10 upregulated and 57 downregulated transcripts were identified in BRCA2-mut cancers. In ovarian cancer, 79 transcripts were upregulated and 123 were downregulated in BRCA1-mut cancers, while five were upregulated and seven were downregulated in BRCA2-mut tumors. Regarding the biological function related to these genes, in BRCA1-mutated ovarian cancers, the main functions of upregulated genes included MHC assembly or regulation of the interferon gamma pathway; in BRCA2-mut ovarian cancers, regulation of phosphorylation and signaling; in BRCA1-mut breast cancers, cell damage repair and angiogenesis; and finally, in BRCA2-mut breast cancers, cytokine production and T-cell migration. Genes expressed in the surface membrane or extracellular matrix and related to patient outcomes included B3GNT7 and CTSV in BRCA2-mut breast cancers, exhibiting detrimental prognoses. CD6, CXCL9, and CXCL13 were associated with favorable outcomes in BRCA1-mutant ovarian cancers. The last three genes were also correlated with the infiltration of effector T cells and dendritic cells in ovarian tumors. In summary, we identified deregulated candidate genes that could be used as therapeutic targets.
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http://dx.doi.org/10.3390/cancers17132208 | DOI Listing |
Int J Surg
September 2025
State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Introduction: Recent advancements in surgical techniques and perioperative care have improved cancer survival rates, yet postoperative comorbidity and mortality remain a critical concern. Despite progress in cancer control, systematic analyses of long-term mortality trends and competing risks in surgery-intervened cancer populations are lacking. This study aimed to quantify temporal patterns of postoperative mortality causes across 21 solid cancers and identify dominant non-cancer risk factors to inform survivorship care strategies.
View Article and Find Full Text PDFCancer Med
September 2025
Department of Computer Engineering, Social and Biological Network Analysis Laboratory, University of Kurdistan, Sanandaj, Iran.
Background: Ovarian cancer (OC) remains the most lethal gynecological malignancy, largely due to its late-stage diagnosis and nonspecific early symptoms. Advances in biomarker identification and machine learning offer promising avenues for improving early detection and prognosis. This review evaluates the role of biomarker-driven ML models in enhancing the early detection, risk stratification, and treatment planning of OC.
View Article and Find Full Text PDFNat Commun
September 2025
Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, 90033, California, USA.
J Int Med Res
September 2025
Obstetrics and Gynecology Department, Wuhan University Zhongnan Hospital, China.
ObjectiveThis study aimed to evaluate the efficacy and safety of hyperthermic intraperitoneal intraoperative chemotherapy (HIPEC) in patients with advanced ovarian cancer.MethodsA total of 200 patients with advanced ovarian cancer were enrolled in this retrospective study and randomly allocated to two groups (research registry number: 11353). On the first day after abdominal closure, routine treatment was performed in the non-HIPEC group, whereas HIPEC was performed in the HIPEC group.
View Article and Find Full Text PDFPLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
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