Integrative analysis identifies two molecular and clinical subsets in Luminal B breast cancer

Huina Wang; Bo Liu; Junqi Long; Jiangyong Yu; Xinchan Ji; Jinmeng Li; Nian Zhu; Xujie Zhuang; Lujia Li; Yuhaoran Chen; Zhidong Liu; Shu Wang; Shuangtao Zhao

doi:10.1016/j.isci.2023.107466

Integrative analysis identifies two molecular and clinical subsets in Luminal B breast cancer

iScience. 2023 Jul 26;26(9):107466. doi: 10.1016/j.isci.2023.107466. eCollection 2023 Sep 15.

Authors

Huina Wang¹, Bo Liu², Junqi Long¹, Jiangyong Yu³, Xinchan Ji¹, Jinmeng Li¹, Nian Zhu¹, Xujie Zhuang¹, Lujia Li¹, Yuhaoran Chen¹, Zhidong Liu⁴, Shu Wang⁵, Shuangtao Zhao⁴

Affiliations

¹ School of Software Engineering, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.
² School of Mathematical and Computational Sciences, Massey University, Palmerston North 4472, New Zealand.
³ Department of Medical Oncology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China.
⁴ Department of Thoracic Surgery, Beijing Tuberculosis and Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
⁵ Breast Disease Center, Peking University People's Hospital, Peking University, Beijing 100044, China.

Abstract

Comprehensive multiplatform analysis of Luminal B breast cancer (LBBC) specimens identifies two molecularly distinct, clinically relevant subtypes: Cluster A associated with cell cycle and metabolic signaling and Cluster B with predominant epithelial mesenchymal transition (EMT) and immune response pathways. Whole-exome sequencing identified significantly mutated genes including TP53, PIK3CA, ERBB2, and GATA3 with recurrent somatic mutations. Alterations in DNA methylation or transcriptomic regulation in genes (FN1, ESR1, CCND1, and YAP1) result in tumor microenvironment reprogramming. Integrated analysis revealed enriched biological pathways and unexplored druggable targets (cancer-testis antigens, metabolic enzymes, kinases, and transcription regulators). A systematic comparison between mRNA and protein displayed emerging expression patterns of key therapeutic targets (CD274, YAP1, AKT1, and CDH1). A potential ceRNA network was developed with a significantly different prognosis between the two subtypes. This integrated analysis reveals a complex molecular landscape of LBBC and provides the utility of targets and signaling pathways for precision medicine.

Keywords: Bioinformatics; Cancer systems biology; Microenvironment.