Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer

Dongxu Feng; Wenbing Li; Wei Wu; Ulf Dietrich Kahlert; Pingfa Gao; Gangfeng Hu; Xia Huang; Wenjie Shi; Huichao Li

doi:10.1155/2023/2736932

Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer

J Oncol. 2023 Jan 30:2023:2736932. doi: 10.1155/2023/2736932. eCollection 2023.

Authors

Dongxu Feng¹, Wenbing Li¹, Wei Wu¹, Ulf Dietrich Kahlert², Pingfa Gao¹, Gangfeng Hu¹, Xia Huang¹, Wenjie Shi^{2

3}, Huichao Li⁴

Affiliations

¹ Department of General Surgery, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences, Chongming District, Shanghai 202150, China.
² University Clinic for General, Visceral, Vascular-and Transplantation Surgery, Faculty of Medicine, Otto-von-Guericke-University, Magdeburg 39120, Germany.
³ University Hospital for Gynaecology, Pius-Hospital, University Medicine Oldenburg, Oldenburg 26121, Germany.
⁴ Department of Thyroid Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266555, Shandong, China.

Abstract

Background: Many studies have found that chromatin regulators (CRs) are correlated with tumorigenesis and disease prognosis. Here, we attempted to build a new CR-related gene model to predict breast cancer (BC) survival status.

Methods: First, the CR-related differentially expressed genes (DEGs) were screened in normal and tumor breast tissues, and the potential mechanism of CR-related DEGs was determined by function analysis. Based on the prognostic DEGs, the Cox regression model was applied to build a signature for BC. Then, survival and receiver operating characteristic (ROC) curves were performed to validate the signature's efficacy and identify its independent prognostic value. The CIBERSORT and tumor immune dysfunction and exclusion (TIDE) algorithms were used to assess the immune cells infiltration and immunotherapy efficacy for this signature, respectively. Additionally, a novel nomogram was also built for clinical decisions.

Results: We identified 98 CR-related DEGs in breast tissues and constructed a novel 6 CR-related gene signature (ARID5A, ASCL1, IKZF3, KDM4B, PRDM11, and TFF1) to predict the outcome of BC patients. The prognostic value of this CR-related gene signature was validated with outstanding predictive performance. The TIDE analysis revealed that the high-risk group patients had a better response to immune checkpoint blockade (ICB) therapy.

Conclusion: A new CR-related gene signature was built, and this signature could provide the independent predictive capability of prognosis and immunotherapy efficacy for BC patients.