CELL INTELLIGENCE · 肿瘤细胞治疗研究

Triple-negative breast cancer (TNBC) is one of the most aggressive molecular subtypes of breast cancer and immune-checkpoint blockade therapy has markedly changed the treatment landscape for this malignancy. Tumour-infiltrating lymphocytes (TILs) and tumour mutational burden (TMB) predict patient response to treatment with immune checkpoint inhibitors and reflect patient outcomes.

The present study aimed to develop a TIL-based prognostic model, create a list of immune-related genes (IRGs) to inform clinicians of possible outcome predictions and generate a clinically relevant estimate of potential benefit from immunotherapy in TNBC.

The present study included a cohort of 130 patients that were classified into two groups, namely TMB high /CD8 + T-cell-rich and TMB low /CD8 + T-cell-poor. Differential expression analysis using the 'edgeR' package identified IRGs associated with survival. The identified IRGs were included in a univariate Cox analysis to derive a prognostic signature.

In addition, the present study examined how the signature genes were associated with immune cell infiltration using the Tumour IMmune Estimation Resource database. The final four-gene signature, C-X-C motif chemokine ligand 13 (CXCL13), latent TGF- binding protein 2, placental growth factor and transporter associated with antigen processing binding protein-like (TAPBPL), stratified risk robustly: Patients in the high-risk group had significantly worse overall survival compared with low-risk patients in both prognostic and validation models. Compared with high-risk patients, low-risk patients had greater infiltration of CD8 + T cells, M1 macrophages, resting dendritic cells and activated CD4 + T cells and less infiltration of both M0 and M2 macrophages.

Higher CXCL13 and TAPBPL expression levels were significantly associated with higher CD8 + T-cell counts and inversely associated with M0 and M2 macrophage counts. The overall risk score and CXCL13 expressions were all positively correlated with multiple immune checkpoint genes, while TAPBPL expression correlated positively with CTLA4, TIM3 and TIGIT.

In summary, the present study provided a TMB- and T-cell infiltration-based IRG signature that is prognostic and may potentially support the prediction of immunotherapy responsiveness in TNBC in the future.