Abstract
PURPOSE: Young age at breast cancer diagnosis correlates with unfavorable clinicopathologic features and worse outcomes compared to older women. Understanding biological differences between breast tumors in young versus older women may lead to better therapeutic approaches for younger patients.
EXPERIMENTAL DESIGN: We identified 100 patients {less than or equal to}35 years old at non-metastatic breast cancer diagnosis who participated in the prospective Young Women's Breast Cancer Study cohort. Tumors were assigned a surrogate intrinsic subtype based on receptor status and grade. Whole exome sequencing of tumor and germline samples was performed. Genomic alterations were compared to older women ({greater than or equal to}45 years old) in The Cancer Genome Atlas, according to intrinsic subtype.
RESULTS: 93 tumors from 92 patients were successfully sequenced. Median age was 32.5 years. 52.7% of tumors were hormone receptor-positive/HER2-negative, 28.0% HER2-positive, and 16.1% triple-negative. Comparison of young to older women (median age 61 years) with luminal A tumors (N=28 young women) revealed three significant differences: PIK3CA alterations were more common in older patients, while GATA3 and ARID1A alterations were more common in young patients. No significant genomic differences were found comparing age groups in other intrinsic subtypes. 22 patients (23.9%) in the Young Women's Study cohort carried a pathogenic germline variant, most commonly (13 patients, 14.1%) in BRCA1/2. Conclusions: Somatic alterations in three genes (PIK3CA, GATA3, and ARID1A) occur at different frequencies in young versus older women with luminal A breast cancer. Additional investigation of these genes and associated pathways could delineate biological susceptibilities and improve treatment options for young breast cancer patients.
Original language | English |
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Pages (from-to) | 2339-2348 |
Number of pages | 10 |
Journal | Clinical Cancer Research |
Volume | 28 |
Issue number | 11 |
Early online date | 31 Jan 2022 |
DOIs | |
Publication status | Published - 1 Jun 2022 |
Keywords
- AGE
- ALIGNMENT
- DIAGNOSIS
- LARGE COHORT
- MOLECULAR PHENOTYPE
- MUTATION
- PATTERNS
- PREGNANCY
- SUSCEPTIBILITY