ArticleJournal of cancer research and clinical oncology2024
PIK3CA mutation-driven immune signature as a prognostic marker for evaluating the tumor immune microenvironment and therapeutic response in breast cancer.
Article in Journal of cancer research and clinical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- OncogenicJournal for immunotherapy of cancer · 2026Article
- Circulating T-cell receptor repertoire and clinicopathological correlations in breast cancer patients: immune repertoire analysis from the VGH-TAYLOR study.Breast cancer research : BCR · 2025Article
- Hormone Receptor Positive/HER2 Negative Breast Carcinoma: Association ofInternational journal of molecular sciences · 2025Article
- A novel PIK3CA hot-spot mutation in breast cancer patients detected by HRM-COLD-PCR analysis.Breast disease · 2024Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
purposeGene mutations drive tumor immune microenvironment (TIME) heterogeneity, in turn affecting prognosis and immunotherapy efficacy. PIK3CA is the most frequently mutated gene in breast cancer (BC), yet its relevance to BC prognosis remains controversial. Herein, we sought to determine the impact of PIK3CA mutation-driven immune genes (PDIGs) on BC prognosis in relation to TIME heterogeneity.
methodsPIK3CA mutation characteristics were compared and verified between the TCGA-BRCA dataset and a patient cohort from our hospital. PIK3CA mutation-driven differentially expressed genes were identified for consensus clustering and weighted gene co-expression network analysis to select the modules most relevant to the immune subtype. Thereafter, the two were intersected to obtain PDIGs. Univariate Cox, LASSO, and multivariate Cox regression analyses were sequentially performed on PDIGs to obtain a PIK3CA mutation-driven immune signature (PDIS), which was then validated using the Gene Expression Omnibus (GEO) database. Differences in functional enrichment, mutation landscape, immune infiltration, checkpoint gene expression, and drug response were compared between different risk groups.
resultsPIK3CA mutation frequencies in the TCGA and validation cohorts were 34.49% and 40.83%, respectively. PIK3CA mutants were significantly associated with ER, PR, and molecular BC subtypes in our hospital cohort. The PDIS allowed for effective risk stratification and exhibited prognostic power in TCGA and GEO sets. The low-risk patients exhibited greater immune infiltration, higher expression of common immune checkpoint factors, and lower scores for tumor immune dysfunction and exclusion.
conclusionThe PDIS can be used as an effective prognostic model for predicting immunotherapy response to guide clinical decision-making.
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