CELL INTELLIGENCE · 肿瘤细胞治疗研究

BACKGROUND: Breast cancers (BRCs) can be classified into 6 molecular subtypes based on gene expression profiles. Previous research suggests that tumor-infiltrating lymphocytes are associated with metastasis-free survival (MFS) in triple-negative and HER2-overexpressing BRC. OBJECTIVES: Our study aims to investigate further how the immune response (IR) may impact MFS in different molecular subtypes of BRC. DESIGN: A single hospital-based retrospective cohort study. METHODS: A training series of 327 BRCs was used to identify 297 IR transcripts that were correlated with the T cell-associated CD3D transcript or the B cell-associated CD19 transcript. Using these IR transcripts, each of the 6 molecular subtypes was hierarchically clustered into high and low immune responders. An IR score based on the average of the 297 IR transcripts was determined for each BRC. Correlations between the IR score and 3 signatures for IR or response to immune checkpoint inhibition therapy (ICIT) were investigated. A series of 884 BRCs from public datasets was used for confirmation, and the other independent series of 988 BRCs was used for validation. RESULTS: For subtype I, high immune responders had a statistically significantly better MFS than low immune responders in all the training, confirmation, and validation series by Kaplan-Meier survival analysis ( P = .0039, .049, .039, log-rank test). The same trend was observed for subtype II ( P = .16, .052, .015) and subtype IV ( P = .0078, .0002, .12). Our IR scores were linearly correlated with the Teschendorff, the T-effector and IFNg, and the T-cell inflamed signatures for IR or ICIT. The IR scores were also linearly correlated with the expression of 6 different immune checkpoint genes. CONCLUSIONS: Tumor IR is a biomarker for MFS for BRCs of I, II, and IV subtypes. Our study supports the potential use of the IR score for identifying patients responsive to ICIT. Tumor-infiltrating lymphocytes (TILs) have been used as prognostic factors in several solid tumors, including breast cancer (BRC). The traditional approach is based on pathological evaluation of the extents of TILs, and the results are known to have significant inter-observer variations. Previously, we have classified BRC into 6 molecular subtypes. In the present study, we used genome-wide RNA expressing profiles to identify immune response (IR) transcripts and establish an IR score. We showed that IR scores were correlated with TILs, and a high IR score predicted a better metastasis-free survival (MFS) in subtype I (basal-cell triple negative), subtype II (ER-negative HER2-overexpressing), and subtype IV (luminal B-like) BRC. These results significantly confirm and extend previously published data on the significance of TILs in BRC. In addition, the IR score also correlated with known immune checkpoint inhibition therapy (ICIT) predictive signatures, implying potential use for ICIT.