Identification and validation of a combined hypoxia and immune index for triple-negative breast cancer

Shaoquan Zheng; Yutian Zou; Jie-Ying Liang; Weikai Xiao; Anli Yang; Tiebao Meng; Shilin Lu; Zhongbing Luo; Xiaoming Xie

doi:10.1002/1878-0261.12747

Identification and validation of a combined hypoxia and immune index for triple-negative breast cancer

Mol Oncol. 2020 Nov;14(11):2814-2833. doi: 10.1002/1878-0261.12747. Epub 2020 Jul 1.

Authors

Shaoquan Zheng^{1

2}, Yutian Zou^{1

2}, Jie-Ying Liang^{2

3}, Weikai Xiao⁴, Anli Yang^{1

2}, Tiebao Meng⁵, Shilin Lu⁶, Zhongbing Luo⁷, Xiaoming Xie^{1

2}

Affiliations

¹ Department of Breast Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
² State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangdong, China.
³ Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
⁴ Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
⁵ Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou, China.
⁶ Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.
⁷ Department of Breast Surgery, First Affiliated Hospital of Gannan Medical College, Ganzhou City, China.

Abstract

The interaction between hypoxia and immune status has been confirmed in various cancer settings, and corresponding treatments have been investigated. However, reliable biomarkers are needed for individual treatment, so we sought to develop a novel scoring system based on hypoxia and immune status. Prognostic hypoxia-immune status-related signatures of patients with triple-negative breast cancer (TNBC) were identified in The Cancer Genome Atlas (TCGA) (N = 158), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (N = 297), and GSE58812 (N = 107). LASSO Cox regression was used for model construction. Hypoxia and immune status expression profiles were analyzed, and infiltrating immune cells were compared. Quantitative real-time PCR (qRT-PCR) was used for validation in the Sun Yat-sen University Cancer Center (SYSUCC) cohort, and immunofluorescence was applied for the detection of hypoxia and immune markers in cancer tissues. Ten cross-cohort prognostic hypoxia-immune signatures were included to construct the comprehensive index of hypoxia and immune (CIHI) in the METABRIC cohort. Two subgroups of patients with distinct hypoxia-immune status conditions were identified using CIHI: hypoxia^high /immune^low and hypoxia^low /immune^high , with a significantly better overall survival (OS) rate in the latter (P < 0.01). The prognostic value of CIHI was further validated in the TCGA, GSE58812, and SYSUCC cohorts (P < 0.01). Hypoxia-immune signatures were significantly differentially expressed between the two groups, and more active immune responses were observed in the hypoxia^low /immune^high group. Cytotoxic lymphocytes were inversely correlated with CIHI in silico. Differentially expressed CA-IX and stromal PD-L1 were detected between subgroups of the SYSUCC cohort. A hypoxia-immune-based cross-cohort classifier for predicting prognosis was developed and validated, which may guide hypoxia modifier treatment and immunotherapy for TNBC.

Keywords: hypoxia; immune; immunotherapy; triple-negative breast cancer.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers, Tumor / analysis
Biomarkers, Tumor / genetics
Biomarkers, Tumor / immunology
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Humans
Hypoxia / diagnosis
Hypoxia / genetics
Hypoxia / immunology*
Prognosis
Triple Negative Breast Neoplasms / diagnosis
Triple Negative Breast Neoplasms / genetics
Triple Negative Breast Neoplasms / immunology*
Tumor Hypoxia*

Substances

Biomarkers, Tumor