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A Multiomics Signature Highlights Alterations Underlying Homologous Recombination Deficiency in Triple-Negative Breast Cancer

  • Translational Research
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Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

Homologous recombination (HR) is a key pathway in DNA double-strand damage repair. HR deficiency (HRD) occurs more commonly in triple-negative breast cancers (TNBCs) than in other breast cancer subtypes. Several clinical trials have demonstrated the value of HRD in stratifying breast cancer patients into distinct groups based on their responses to poly(ADP ribose) polymerase inhibitors and chemotherapy.

Methods

We retrospectively collected TNBC samples to establish a multiomics cohort (n = 343) and explored the biological and phenotypic mechanisms underlying the better prognosis of patients with high HRD scores. Gene set enrichment analysis was conducted to elucidate the underlying pathways in patients with low HRD scores, and a radiomics model was established to predict the HRD score via a noninvasive method.

Results

Multivariable Cox analysis revealed the independent prognostic value of a low HRD score (hazard ratio 2.20, 95% confidence interval 1.05–4.59; p = 0.04). Furthermore, amino acid and lipid metabolism pathways were highly enriched in tumors from patients with low HRD scores, which was also demonstrated by differential abundant metabolite analysis. A noninvasive radiomics method was developed to predict the HRD status and it performed well in the independent validation cohort (support vector machine model: area under the curve [AUC] 0.739, sensitivity 0.571, and specificity 0.824; logistic regression model: AUC 0.695, sensitivity 0.571, and specificity 0.882).

Conclusions

We revealed the prognostic value of the HRD score, predicted the HRD status with noninvasive radiomics features, and preliminarily explored druggable targets for TNBC patients with low HRD scores.

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Acknowledgments

The authors thank the staff of the Radiology Department of Fudan University Shanghai Cancer Center for their assistance with the breast MRI collection. In addition, they thank the staff of the Institute of Science and Technology for Brain-Inspired Intelligence of Fudan University for their contribution to radiomics feature extraction.

Funding

This project was supported by grants from the National Natural Science Foundation of China (81901703, 82071878, 91959207 and 92159301), Cancer Research Program of National Cancer Center (NCC201909B06), Youth Medical Talents-Clinical Imaging Practitioner Program [SHWRS(2020)_087] and Clinical Research Plan of SHDC (SHDC2020CR2008A).

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Authors and Affiliations

  1. Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China

    Guan-Hua Su PhD, Lin Jiang MD, Yi **ao MD, Yi-Zhou Jiang MD & Zhi-Ming Shao MD

  2. Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 201203, China

    Ren-Cheng Zheng PhD & He Wang PhD

  3. Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China

    Wei-Jun Peng MD, Ya-Jia Gu MD & Chao You MD

Authors
  1. Guan-Hua Su PhD
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Contributions

All authors fundamentally contributed to this study, participated sufficiently, and take public responsibility for the content. CY designed the study; CY and GHS performed the literature review; and Guan-Hua Su drafted the manuscript. CY, GHS and LJ collected the data. CY and GHS were responsible for quality control and interpretation of the data. LJ and GHS were involved in the statistical analysis and interpreted the results. RCZ and HW were involved in the MR radiomics extraction. CY, GHS, YX and YZJ interpreted the results and edited the manuscript. WJP and ZMS edited the manuscript. CY and YJG edited and finalized the manuscript. The publication was approved by all authors.

Corresponding authors

Correspondence to Ya-Jia Gu MD or Chao You MD.

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Conflict of interest

Guan-Hua Su, Lin Jiang, Yi **ao, Ren-Cheng Zheng, He Wang, Yi-Zhou Jiang, Wei-Jun Peng, Zhi-Ming Shao, Ya-Jia Gu, and Chao You declare no competing financial or nonfinancial interests.

Availability of data and materials

The accession number for raw LC-MS data, microarray data and sequence data reported in this paper is NODE: OEP000155. All data can be viewed in The National Omics Data Encyclopedia (NODE) (http://www.biosino.org/node) by pasting the accession (OEP000155) into the text search box or through the URL: http://www.biosino.org/node/project/detail/OEP000155.

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The Institutional Review Board approved this study.

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Written informed consent was obtained from all subjects (patients) in this study.

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Su, GH., Jiang, L., **ao, Y. et al. A Multiomics Signature Highlights Alterations Underlying Homologous Recombination Deficiency in Triple-Negative Breast Cancer. Ann Surg Oncol 29, 7165–7175 (2022). https://doi.org/10.1245/s10434-022-11958-7

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