RNA-Based Classification of Homologous Recombination Deficiency in Racially Diverse Patients with Breast Cancer

Author:

Walens Andrea12ORCID,Van Alsten Sarah C.2ORCID,Olsson Linnea T.2ORCID,Smith Markia A.3ORCID,Lockhart Alex4ORCID,Gao Xiaohua12ORCID,Hamilton Alina M.3ORCID,Kirk Erin L.2ORCID,Love Michael I.45ORCID,Gupta Gaorav P.1ORCID,Perou Charles M.15ORCID,Vaziri Cyrus3ORCID,Hoadley Katherine A.15ORCID,Troester Melissa A.123ORCID

Affiliation:

1. 1Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina.

2. 2Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina.

3. 3Department of Pathology and Laboratory Medicine, School of Medicine, University of North Carolina, Chapel Hill, North Carolina.

4. 4Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.

5. 5Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.

Abstract

Abstract Background: Aberrant expression of DNA repair pathways such as homologous recombination (HR) can lead to DNA repair imbalance, genomic instability, and altered chemotherapy response. DNA repair imbalance may predict prognosis, but variation in DNA repair in diverse cohorts of breast cancer patients is understudied. Methods: To identify RNA-based patterns of DNA repair expression, we performed unsupervised clustering on 51 DNA repair-related genes in the Cancer Genome Atlas Breast Cancer [TCGA BRCA (n = 1,094)] and Carolina Breast Cancer Study [CBCS (n = 1,461)]. Using published DNA-based HR deficiency (HRD) scores (high-HRD ≥ 42) from TCGA, we trained an RNA-based supervised classifier. Unsupervised and supervised HRD classifiers were evaluated in association with demographics, tumor characteristics, and clinical outcomes. Results : Unsupervised clustering on DNA repair genes identified four clusters of breast tumors, with one group having high expression of HR genes. Approximately 39.7% of CBCS and 29.3% of TCGA breast tumors had this unsupervised high-HRD (U-HRD) profile. A supervised HRD classifier (S-HRD) trained on TCGA had 84% sensitivity and 73% specificity to detect HRD-high samples. Both U-HRD and S-HRD tumors in CBCS had higher frequency of TP53 mutant-like status (45% and 41% enrichment) and basal-like subtype (63% and 58% enrichment). S-HRD high was more common among black patients. Among chemotherapy-treated participants, recurrence was associated with S-HRD high (HR: 2.38, 95% confidence interval = 1.50–3.78). Conclusions: HRD is associated with poor prognosis and enriched in the tumors of black women. Impact: RNA-level indicators of HRD are predictive of breast cancer outcomes in diverse populations.

Funder

Susan G. Komen

National Cancer Institute

Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill

Publisher

American Association for Cancer Research (AACR)

Subject

Oncology,Epidemiology

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