Abstract
BackgroundIncreasing evdence supports the suggestion that the immune cell infiltration (ICI) patterns play a pivotal role in tumor progression in breast cancer (BRCA). Nonetheless, there has been no comprehensive analysis of the ICI patterns effects on the clinical outcomes and immunotherapy.MethodsMultiomic data for BRCA samples were downloaded from TCGA. ESTIMATE algorithm, ssGSEA method, and CIBERSORT analysis were used to uncover the landscape of the tumor immune microenvironment (TIME). BRCA subtypes based on the ICI pattern were identified by consensus clustering and principal-component analysis was performed to obtain the ICI scores to quantify the ICI patterns in individual tumors. Their prognostic value was validated by the Kaplan-Meier survival curves. Gene set enrichment analysis (GSEA) was applied for functional annotation. Immunophenoscore (IPS) was employed to explore the immunotherapeutic role of the ICI scores. Finally, the mutation data was analyzed by using the “maftools” R package.ResultsThree different immune infiltration patterns with a distinct prognosis and biological signature were recognized among 1,198 BRCA samples. The characteristics of TIME under these three patterns were highly consistent with three known immune profiles: immune- excluded, immune-desert, and immune-inflamed phenotypes, respectively. The identification of the ICI patterns within individual tumors based on the ICI score, developed under the ICI-related signature genes, contributed into dissecting biological processes, clinical outcome, immune cells infiltration, immunotherapeutic effect, and genetic variation. High ICI score subtype, characterized with a suppression of immunity, suggested an immune-exhausted phenotype. Abundant effective immune cells were discovered in the low ICI score patients, which corresponded to an immune-activated phenotype and might present an immunotherapeutic advantage. Immunophenoscore was implemented as a surrogate of immunotherapeutic outcome, low-ICI scores samples obtained a significantly higher immunophenoscore. Enrichment of the JAK/STAT and VEGF signal pathways were activated in the ICI low-score subgroup. Finally, the synergistic effect between the ICI score and the tumor mutation burden (TMB) was confirmed.ConclusionThis work comprehensively elucidated that the ICI patterns served as an indispensable player in complexity and diversity of TIME. Quantitative identification of the ICI patterns in individual tumor will contribute into mapping the landscape of TIME further optimizing precision immunotherapy.
Highlights
Breast cancer (BRCA) is one of the most frequently diagnosed malignant tumors and is the first leading cause of tumor-related death in females [1,2,3]
According to similarities exhibited in the immune cell infiltration (ICI) profiles, we found that k = 3 had an optimal clustering stability
Kaplan-Meier survival analysis of three distinct ICI patterns indicated that ICI cluster A exhibited a prominent advantage of median survival time, whereas ICI cluster B presented with the worst prognosis (Figure 1B, P = 0.021)
Summary
Breast cancer (BRCA) is one of the most frequently diagnosed malignant tumors and is the first leading cause of tumor-related death in females [1,2,3]. Cancer immunotherapy harnesses an anti-tumor immune response to recognize and eliminate tumor cells by activating the host immune system. T cell-related immune responses induce anti-tumor responses by increasing immune checkpoint inhibitors, only a minority of cancer patients benefit from them [5]. Accumulating evidences supported that immune infiltration in the tumor immune microenvironment (TIME) functioned as decisive players for predicting the prognosis of BRCA [8]. Increasing evdence supports the suggestion that the immune cell infiltration (ICI) patterns play a pivotal role in tumor progression in breast cancer (BRCA). There has been no comprehensive analysis of the ICI patterns effects on the clinical outcomes and immunotherapy
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