An immune cell infiltration-based immune score model predicts prognosis and chemotherapy effects in breast cancer

Abstract

Background: Immune cells have essential auxiliary functions and influence clinical outcomes in cancer, with high immune infiltration being associated with improved clinical outcomes and better response to treatment in breast cancer (BC). However, studies to date have not fully considered the tumor-infiltrating immune cell (TIIC) landscape in tumors. This study investigated potential biomarkers based on TIICs to improve prognosis and treatment effect in BC. Results: We enrolled 5112 patients for analysis and used cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT), a new computational algorithm, to quantify 22 TIICs in primary BC. From the results of univariate Cox regression, 12 immune cells were determined to be significantly related to the overall survival (OS) of BC patients. Furthermore, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were applied to construct an immune prognostic model based on six potential biomarkers. By dividing patients into low- and high-risk groups, a significant distinction in OS was found in the training cohort, with 20-year survival rates of 42.6% and 26.3%, respectively. Applying a similar protocol to validation and test cohorts, we found that OS was significantly shorter in the high-risk group than in the low-risk group, regardless of the molecular subtype of BC. Using the immune score model to predict the effect of BC patients to chemotherapy, the survival advantage for the low-risk group was evident among those who received chemotherapy, regardless of the chemotherapy regimen. In evaluating the predictive value of the nomogram, a decision curve showed better predictive accuracy than the standard tumor-node-metastasis (TNM) staging system. Conclusion: The immune cell infiltration-based immune score model can be effectively and efficiently used to predict the prognosis of BC patients as well as the effect of chemotherapy.

ATP2C2 Has Potential to Define Tumor Microenvironment in Breast Cancer

“…Considering the importance of immune cell infiltration in tumors (31)(32)(33), CIBERSORT was further applied to evaluate the abundance ratios of 22 types of immune cells in each BRCA specimen from GEO. Mounting evidence suggests that the interaction between the tumor and the microenvironment plays an important role in the progression of BRCA and immunotherapeutic efficacy.…”

A Novel Immune-Related Seventeen-Gene Signature for Predicting Early Stage Lung Squamous Cell Carcinoma Prognosis

“…It was reported that the proportion of immune cell infiltration in tumor microenvironment was closely related to patient's prognosis (53)(54)(55)(56)(57). For example, neutrophil infiltration in tumor environment was associated with a better prognosis (58).…”

Prognostic and predictive value of FCER1G in glioma outcomes and response to immunotherapy

“…Notably, patients with high FCER1G expression showed high levels of the therapeutic targets PDL1 and CTLA4, which indicated a hypothetic treatment as immune checkpoint. PDL1 is a key negative regulator for immune inhibitory axis signaling controlling T lymphocyte infiltration in solid tumors, which is widely expressed in glioma cell lines [ 48 , 49 ] and human specimens [ 50 , 51 ]. PD-L1 is recently served as a oncogenic gene.…”