A novel prognostic signature and potential therapeutic drugs based on tumor immune microenvironment characterization in breast cancer

Abstract

Tumor microenvironment (TME) is closely correlated to the occurrence and progression of breast cancer, however its potentiality in assisting diagnosis and therapeutic decision remains unclear. Therefore, the major aim of this study is to explore the prognostic value of TME related gene in breast cancer. Expression matrices and clinical data of breast cancer obtained from public databases were divided into TME relevant clusters according to immune characterization. A 12-gene molecular classifier was generated through the utilization of differentially expressed genes identified between distinct Tumor Microenvironment (TME) clusters, coupled with correlative regression analysis. The performance of this TME-driven prognostic signature (TPS) were examined across both the training and validation cohorts. Furthermore, our study revealed that breast cancer cases classified as high-risk based on the TPS exhibited the phenotype with elevated immune cell infiltration, higher tumor mutational burden, and a notably worse overall prognostic outcome. To conclude, the novel TME-based TPS was able to serve as a superior prognosis indicator for breast cancer, alone or jointly with other clinical factors. Also, breast cancer patients belong to different risk subgroups of TPS were found potentially suitable for distinguished therapeutic agents, which might improve personalized treatment for breast cancer in the future.

Keywords: Breast cancer; Immune landscape; Potential drugs; Prognostic signature; Tumor microenvironment.

Fig. 1

Scheme of the study.

Fig. 2

The characteristics of TME clusters in BC. (A) Cellular interactions among TME risk subtypes were displayed with color-coded cell types. (B) Top DEGs between TME related cluster combing with annotation of major clinicopathological factors in TCGA-BRCA cohort. (C) Bar plot illustrating biological changes observed between TME clusters. (D) Alterations in immune cell infiltration between TME clusters (CIBERSORT score). Asterisk symbols reflect significant differences among groups. One asterisk (*), two asterisks (**), three asterisks (***) represents the P value less than 0.05, 0.01 and 0.001, respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

Assessment of TPS as a prognosis indicator. (A) Correlative distribution of TPS risk score and patient counts, vital status and elemental genes in the training group. (B) Correlative distribution of TPS risk score and patient counts, vital status and elemental genes in the testing group. (C) Correlative distribution of TPS risk score and patient counts, vital status and elemental genes in the whole group. (D) Kaplan-Meier survival compared OS in different risk subgroups of the training cohort. (E) Kaplan-Meier survival compared OS in different risk subgroups of the testing cohort. (F) Kaplan-Meier survival compared OS in different risk subgroups of the whole cohort. (G) The ROC of TPS in the training cohort. (H) The ROC of TPS in the testing cohort. (I) The ROC of TPS in the whole cohort.

Fig. 4

Gene set enrichment shows biological characteristics alterations between TPS risk subgroups. (A) GSEA reveals distinct KEGG signaling pathways. (B) GSEA highlights divergent biological processes. (C) GSEA identifies disparities in hallmark gene sets. (D) The immune landscape is depicted through ssGSEA between groups. Asterisk symbols reflect significant differences among groups. One asterisk (*), two asterisks (**), three asterisks (***) represents the P value less than 0.05, 0.01 and 0.001, respectively.

Fig. 5

Assessment of tumor purity and potential responsiveness to immunotherapy across TPS-risk subgroups. (A) ESTIMATE score comparison. (B) Immune scores comparison. (C) Stromal scores comparison. (D) Tumor purity comparison analysis. (E) TIDE score comparison. (F) Assessment of immune dysfunction score. (G) Assessment of immune exclusion score. Asterisk symbols reflect significant differences among groups. One asterisk (*), two asterisks (**), three asterisks (***) represents the P value less than 0.05, 0.01 and 0.001, respectively.

Fig. 6

Gene mutation status analysis between TPS risk subgroups. (A) Top somatic mutation genes in TPS risk subgroups. (B) Tumor mutation burden comparison. (C) tumor mutation burden and TPS risk score’ correlation.

Fig. 7

Identification of Potential Drug Candidates Tailored for Distinct TPS Risk Patient Subgroups. (A) Candidate drugs identified within the CTRP database. (B) Candidate drugs identified within the GDSC database.