Benefits of Targeted Molecular Therapy to Immune Infiltration and Immune-Related Genes Predicting Signature in Breast Cancer - Chen, Fahai; Fang, Jianmin (Frontiers in Oncology, 2022)
Background: This study aimed to investigate the tumor-related infiltrating lymphocytes affecting the response of trastuzumab and identify potential biomarkers based on immune-related genes to improve prognosis and clinical outcomes of targeted therapies in breast cancer. Methods: Estimation of Stromal and Immune cells in MAligant Tumours using Expression data (ESTIMATE) was adopted to infer the fraction of stromal and immune cells through utilizing gene expression signatures in breast tumor samples. Cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was applied to characterize cell composition of 22 lymphocytes from breast cancer tissues by their gene expression profiles. Immune-related genes were collected from the Immunology Database and Analysis (ImmPort). Univariate and multivariate cox regression were performed to identify the significant independent risk factors associated with the poor overall survival (OS) of breast cancer patients. Hub genes were identified based on the Protein-Protein interaction (PPI) network analysis. Results: Based on the ESTIMATE algorithm, a significant reduction of stromal scores was observed in tumor tissues and pre-treated tumor tissues compared with non-tumor and post-treated tumor tissues, respectively, while immune scores failed to present notably statistical differences between both groups. However, from the results of univariate Cox regression, the immune score was identified to be remarkably associated with the poor overall survival (OS) for breast cancer patients. Subsequently, the top five infiltrating lymphocytes were evaluated in tumor tissues based on the CIBERSORT algorithm. Furthermore, Significance analysis identified 1244 Differentially Expression Genes (DEGs) from the GSE114082 dataset, and then 91 overlapping immune-related DEGs were screened between GSE114082 and ImmPort datasets. Subsequently, 10 top hub genes were identified and five (IGF1, ADIPOQ, CREB1, LEP, and NR3C1) of them were correlated with worse overall survival on response to trastuzumab in breast cancer patients. Conclusions: This study provided an insight into the immune score based on the tumor-related infiltrating lymphocytes in breast cancer tissues and demonstrates the benefits of immune infiltration on the treatment of trastuzumab. Meanwhile, the study established a novel five-immune-related-gene signature to predict the overall survival of breast cancer treated by trastuzumab.