Identification of a novel inflammation-related gene signature for predicting inflammatory breast cancer survival

Abstract

Breast cancer is the most common cancer type and ranks the second in cancer-related deaths in women. However, the relationship between inflammation-related gene signatures and the prognosis of breast cancer remains elusive. Here, we show that breast invasive carcinoma (BRCA) can be classified into high-risk and low-risk groups based on the level of inflammation. These groups have different tumor immune microenvironments, prognoses, and drug sensitivities. In general, breast cancer patients in high-risk groups have higher macrophage abundance, higher tumor mutation burden (TMB), and the signaling pathways related to the inflammatory response and immune response are activated. Our study demonstrates that the high-risk group of breast cancer patients exhibit a high prevalence of M2 macrophages, as well as a high incidence of tumor mutations in conjunction with an inflammatory response. Furthermore, our analysis indicates that PD.0332991 and ROSCOVITINE exhibit greater efficacy in the treatment of low-risk inflammatory breast cancer, while Bicalutamide and Imatinib demonstrate greater efficacy in the treatment of high-risk patients. In sum, our model exhibited numerous advantages. It not only overcame the challenge posed by the heterogeneity of cancer to clinical diagnosis, but also accurately predicted the prognosis of subtypes of breast cancer patients. This provides valuable reference for clinical practitioners and assists patients in obtaining the best chemotherapy regimen.

Funding

National Natural Science Foundation of China(32260167); Major Science and Technology Projects in Yunnan Province(Grant No. 202102AA310055); Key Laboratory of Tumor Immunological Prevention and Treatment in Yunnan Province, Yan'an Hospital Affiliated to Kunming Medical University(Grant No. KLTIPT-2023-02); Yunnan University(ZC-22223104)