Globally, breast cancer as the most frequently diagnosed form of cancer is the primary cause of death due to cancer in women in most countries. The heterogeneity of BRCA exists from the tumor microenvironment to the phenotypes and genotypes of cancer cells, leading to patients with the identical pathological period possess various responsiveness to clinical treatments and clinical outcomes. As the only predictive indicator utilized routinely in clinical application to forecast the survival and guide clinical management, the TNM staging fails to forecast the clinical outcome for patients with the same clinical stage. Thus, there is urgent need to exploit the novel and effective biomarkers for early diagnosis, treatment option, and survival evaluation to improve the prognosis for BRCA. In the past decades, more and more studies provided evidences to support that lncRNAs might play key roles in tumorigenesis, progression and invasion in breast cancer[15, 35]. According to previous researches, lncRNAs were reported as crucial regulators in regulating cancer immunity. A recent research from Mineo Marco et al reported that INCR1 knockdown can improve CAR T cell therapy via sensitizing tumor cells to cytotoxic T cell-mediated clearing . Another research showed encouraging potentiality for new clinical management decisions on the basis of epigenetic regulation targeting LncMALAT1, which can coordinate with the immune system. More and more evidences has strongly supported that immune-related lncRNAs may be novel disease biomolecules for cancer clinic treatment and possess valuable prognostic significance for survival[38, 39]. Several immune‐related lncRNA signatures have been explored in some tumors, such as bladder cancer, breast cancer, and colon cancer[40–42]. Nevertheless, the latent role of immune-correlated lncRNAs risk score model as a helpful predictive indicator needs further validated in cancer immune checkpoint therapy, especially in BRCA.
Here, our study assembled an immune-associated lncRNA signature and explored its predictive performance, as well as its role in immune cell infiltration and the assessment of responsiveness to immune checkpoint blockade treatment for BRCA patients. In our research, immune-associated lncRNAs were systematically identified through employing univariate Cox regression model as well as the biostatistics method. Subsequently, we employed LASSO algorithm analysis in lncRNA files derived from TCGA database, and final 13 significant immune-related lncRNAs were recognized. These 13 lncRNAs were included into developing the predictive risk score model. Subsequently, Kaplan–Meier curves, the timedependent ROC curves, and Cox regression analysis were employed to confirm the predictive performance of this immune-correlated lncRNAs risk score model, which can serve as an independent biomolecular indicator to forecast BRCA survival. Further validation was analyzed in both the internal testing group and combined cohort.
Subsequently, our pathway enrichment results suggested the latent impact of our immune-related lncRNA risk model on BRCA tumorigenesis and progression via endoderm development, endoderm formation, endoderm cell differentiation, laminin binding and so forth. Our results provide new evidence for strongly supporting that lncRNAs whose functions was still unclear may be novel biomarkers for predicting clinical outcomes in BRCA. Nonetheless, these findings require to be confirmed in further researches.
With the rise of immunotherapy, immune checkpoint blockade (ICB) treatment has markedly transformed anti-tumor immunopathological treatment. Patients with breast cancer administrated monotherapy of ICB has obtained objective benefit, however, the prognosis of BRCA patients in the use of ICB as monotherapy was not better than traditional chemotherapy regimens. Such biomolecules as immune checkpoint gene and tumor mutational burden cannot accurately forecast clinical outcomes from ICB treatment. Thus, exploiting biomolecular markers that can precisely forecast responsiveness to ICB is crucial to further advance precision immunotherapy[28, 44]. Several studies reported that lncRNAs associated with immune reaction could forecast responsiveness to clinical treatment[45, 46]. In this study, the association analyses shown that PDCD1, CD274, PDCD1LG2, CTLA-4, HAVCR2, and IDO1 were coexpressed. Besides, this immune‐correlated lncRNA risk score was significantly correlated with the ICB treatment target genes (i.e., PDCD1). These findings indicated that this immune-related lncRNA risk score model may serve as a key part to measure the responsiveness to ICB treatment of BRCA patients. Recently, accumulating evidences have supported that numerous lncRNAs possess key roles in regulating immunity, such as immune cell infiltration, antigen presentation and so on[11, 12]. Here, our results shown that this immune‐correlated lncRNAs risk model was markedly correlated with immune cell infiltration (i.e., B cells, CD4 + T cells, CD8 + T cells, dendritic cells and neutrophils etc.,) in BRCA, which indicated that as-constructed immune‐correlated lncRNA risk score model might serve as a key role in immune cell infiltration in BRCA.
Compared with published researches that investigated the lncRNA prognostic performance in BRCA, the superiority of our research is that, as far as we know, this research is the first to exploit immune-related lncRNAs signature which may precisely predict responsiveness to ICB in BRCA.