Long-term survival varies among hormone receptor-positive (HR+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancer patients and is seriously impaired by metastasis. Chromosomal instability (CIN) was one of the key drivers of breast cancer metastasis. Here we evaluate CIN and 10-year invasive disease-free survival (iDFS) and overall survival (OS) in HR+/HER2-- breast cancer. In this large-scale, multiple-site, retrospective study, 354 HR+/HER2- breast cancer patients were recruited. Of these, 204 patients were used for internal training, 70 for external validation, and 80 for cross-validation. All medical records were carefully reviewed to obtain the disease recurrence information. Formalin-fixed paraffin-embedded tissue samples were collected, followed by low-pass whole-genome sequencing with a median genome coverage of 1.86X using minimal 1 ng DNA input. CIN was then assessed using a customized bioinformatics workflow. Three or more instances of CIN per sample was defined as high CIN and the frequency was 42.2% (86/204) in the internal cohort. High CIN correlated significantly with increased lymph node metastasis, vascular invasion, progesterone receptor negative status, HER2 low, worse pathological type, and performed as an independent prognostic factor for HR+/- breast cancer. Patients with high CIN had shorter iDFS and OS than those with low CIN [10-year iDFS 11.1% versus 82.2%, hazard ratio (HR) = 11.12, p < 0.01; 10-year OS 45.7% versus 94.3%, HR = 14.17, p < 0.01]. These findings were validated in two external cohorts with 70 breast cancer patients. Moreover, high CIN could predict the prognosis more accurately than Adjuvant! Online score (10-year iDFS 11.1% versus 48.6%, HR = 2.71, p < 0.01). Cross-validation analysis found that high consistency (83.8%) was observed between CIN and MammaPrint score, while only 45% between CIN and Adjuvant! Online score. In conclusion, high CIN is an independent prognostic indicator for HR+/HER2- breast cancer with shorter iDFS and OS and holds promise for predicting recurrence and metastasis.
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