Genomic features of rapid versus late relapse in triple negative breast cancer
Yiqing Zhang,
Sarah Asad,
Zachary Weber,
David Tallman,
William Nock,
Meghan Wyse,
Jerome F. Bey,
Kristin L. Dean,
Elizabeth J. Adams,
Sinclair Stockard,
Jasneet Singh,
Eric P. Winer,
Nancy U. Lin,
Yi-Zhou Jiang,
Ding Ma,
Peng Wang,
Leming Shi,
Wei Huang,
Zhi-Ming Shao,
Mathew Cherian,
Maryam B. Lustberg,
Bhuvaneswari Ramaswamy,
Sagar Sardesai,
Jeffrey VanDeusen,
Nicole Williams,
Robert Wesolowski,
Samilia Obeng-Gyasi,
Gina M. Sizemore,
Steven T. Sizemore,
Claire Verschraegen,
Daniel G. Stover
Affiliations
Yiqing Zhang
Ohio State University College of Medicine
Sarah Asad
Ohio State University College of Medicine
Zachary Weber
Department of Biomedical Informatics, The Ohio State University
David Tallman
Ohio State University College of Medicine
William Nock
Ohio State University College of Medicine
Meghan Wyse
Division of Medical Oncology, Ohio State University Comprehensive Cancer Center
Jerome F. Bey
Ohio State University College of Medicine
Kristin L. Dean
Ohio State University College of Medicine
Elizabeth J. Adams
Ohio State University College of Medicine
Sinclair Stockard
Ohio State University College of Medicine
Jasneet Singh
Ohio State University College of Medicine
Eric P. Winer
Department of Medical Oncology, Susan F. Smith Center for Women’s Cancers, Dana-Farber Cancer Institute
Nancy U. Lin
Department of Medical Oncology, Susan F. Smith Center for Women’s Cancers, Dana-Farber Cancer Institute
Yi-Zhou Jiang
Department of Breast Surgery, Precision Cancer Medicine Center, Fudan University Shanghai Cancer Center
Ding Ma
Department of Breast Surgery, Precision Cancer Medicine Center, Fudan University Shanghai Cancer Center
Peng Wang
Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences
Leming Shi
State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University
Wei Huang
Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Industrial Technology Institute (SITI)
Zhi-Ming Shao
Department of Breast Surgery, Precision Cancer Medicine Center, Fudan University Shanghai Cancer Center
Abstract Background Triple-negative breast cancer (TNBC) is a heterogeneous disease and we have previously shown that rapid relapse of TNBC is associated with distinct sociodemographic features. We hypothesized that rapid versus late relapse in TNBC is also defined by distinct clinical and genomic features of primary tumors. Methods Using three publicly-available datasets, we identified 453 patients diagnosed with primary TNBC with adequate follow-up to be characterized as ‘rapid relapse’ (rrTNBC; distant relapse or death ≤2 years of diagnosis), ‘late relapse’ (lrTNBC; > 2 years) or ‘no relapse’ (nrTNBC: > 5 years no relapse/death). We explored basic clinical and primary tumor multi-omic data, including whole transcriptome (n = 453), and whole genome copy number and mutation data for 171 cancer-related genes (n = 317). Association of rapid relapse with clinical and genomic features were assessed using Pearson chi-squared tests, t-tests, ANOVA, and Fisher exact tests. We evaluated logistic regression models of clinical features with subtype versus two models that integrated significant genomic features. Results Relative to nrTNBC, both rrTNBC and lrTNBC had significantly lower immune signatures and immune signatures were highly correlated to anti-tumor CD8 T-cell, M1 macrophage, and gamma-delta T-cell CIBERSORT inferred immune subsets. Intriguingly, lrTNBCs were enriched for luminal signatures. There was no difference in tumor mutation burden or percent genome altered across groups. Logistic regression mModels that incorporate genomic features significantly outperformed standard clinical/subtype models in training (n = 63 patients), testing (n = 63) and independent validation (n = 34) cohorts, although performance of all models were overall modest. Conclusions We identify clinical and genomic features associated with rapid relapse TNBC for further study of this aggressive TNBC subset.
