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Identification and validation of a novel necroptosis-related molecular signature to evaluate prognosis and immune features in breast cancer

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Abstract

Necroptosis has been shown to play an important role in the development of tumors. However, the characteristics of the necroptosis-related subtypes and the associated immune cell infiltration in the tumor microenvironment (TME) of breast cancer (BRCA) remain unclear. In this study, we identified three clusters related to necroptosis using the expression patterns of necroptosis-relevant genes (NRGs), and found that these three clusters had different clinicopathological features, prognosis and immune cell infiltration in the TME. Cluster 2 was characterized by less infiltration of immune cells in the TME and was associated with a worse prognosis. Then, a necroptosis risk score (NRS) composed of 14 NRGs was constructed using the least absolute shrinkage and selection operator regression (LASSO) Cox regression method. Based on NRS, all BRCA patients in the TCGA datasets were classified into a low-risk group and a high-risk group. Patients in the low-risk group were characterized by longer overall survival (OS), lower mutation burden, and higher infiltration level of immune cells in the TME. Moreover, the NRS was significantly associated with chemotherapeutic drug sensitivity. Finally, the knockdown of VDAC1 reduced the proliferation and migration of BRCA cells, and promoted cell death induced by necroptosis inducer. This study identified a novel necroptosis-related subtype of BRCA, and a comprehensive analysis of NRGs in BRCA revealed its potential roles in prognosis, clinicopathological features, TME, chemotherapy, tumor proliferation, and tumor necroptosis. These results may improve our understanding of NRGs in BRCA and provide a reference for developing individualized therapeutic strategies.

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Data Availability

The datasets used in this study can be found in the online repositories. The name of the repository has been written in the section of the materials and methods of the article.

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Acknowledgements

The authors appreciate everyone who has participated in this research work. And we thank Dr. Shizhang Ling for proof correction and discussion, Dr. Jianming Zeng (University of Macau), and all the members of his bioinformatics team, biotrainee, for generously sharing their experience and codes. The Use of the biorstudio high performance computing cluster (https://biorstudio.cloud) at Biotrainee and The shanghai HS Biotech Co., Ltd for conducting the research reported in this paper. We also thank all members of The Translational Research Institute for Neurological Disorders, Department of Neurosurgery, the First Affiliated Hospital (Yijishan Hospital), Wannan Medical College.

Funding

This study was supported by the National Natural Science Foundation of China and The Recruitment Program of Overseas High-Level Young Talents; Key Scientific Research Project of Jiangsu Provincial Health Commission (ZD2021019); Beijing Xisike Clinical Oncology Research Foundation (Y-tongshu2021/ms-0294), and the start-up funding of the Zhongda Hospital, School of Medicine & Advanced Institute for Life and Health, Southeast University.

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Authors and Affiliations

  1. School of Chemistry and Chemical Engineering & Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, 210009, China

    Fan Zhang, Zhipeng Yao & Hongping Xia

  2. School of Basic Medical Sciences & Key Laboratory of Antibody Technique of National Health Commission & Jiangsu Antibody Drug Engineering Research Center, Nanjing Medical University, Nanjing, 211166, China

    Fan Zhang, Haojun Xu & Hongping Xia

  3. Department of Gynecologic Oncology, Cancer Hospital of Shantou University Medical College, Shantou, 515041, China

    Chenxue Qi, Congzhu Li & Hongping Xia

  4. Jiangsu Cancer Hospital, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Institute of Cancer Research, Nanjing, 210009, China

    Guoren Zhou

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Contributions

FZ conceived and designed the study. FZ, CXQ, ZPY and HJX participated in data acquisition, discussion, analysis and interpretation of data, cell assay, writing, reviewing, and revision of the manuscript. GRZ, CZL and HPX supervised and monitored the data and participated in funding acquisition, reviewing and revision of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Guoren Zhou, Congzhu Li or Hongping Xia.

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Zhang, F., Qi, C., Yao, Z. et al. Identification and validation of a novel necroptosis-related molecular signature to evaluate prognosis and immune features in breast cancer. Apoptosis 28, 1628–1645 (2023). https://doi.org/10.1007/s10495-023-01887-5

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