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Background: Cancer predisposition is most often studied in the context of single cancers. However, inherited cancer predispositions can also give rise to multiple primary cancers. Yet, there is a paucity of studies on genetic predisposition in multiple primary cancers, especially those outside of well-defined cancer predisposition syndromes. This study aimed to identify germline variants associated with dual primary cancers of the breast and lung., Methods: Exome sequencing was performed on germline DNA from 55 Singapore patients (52 [95%] never-smokers) with dual primaries in the breast and lung, confirmed by histopathology. Using two large control cohorts: the local SG10K_Health (n = 9770) and gnomAD non-cancer East Asians (n = 9626); and two additional local case cohorts of early-onset or familial breast cancer (n = 290), and lung cancer (n = 209), variants were assessed for pathogenicity in accordance with ACMG/AMP guidelines. In particular, comparisons were made with known pathogenic or likely pathogenic variants in the ClinVar database, pathogenicity predictions were obtained from in silico prediction software, and case-control association analyses were performed., Results: Altogether, we identified 19 pathogenic or likely pathogenic variants from 16 genes, detected in 17 of 55 (31%) patients. Six of the 19 variants were identified using ClinVar, while 13 variants were classified pathogenic or likely pathogenic using ACMG/AMP guidelines. The 16 genes include well-known cancer predisposition genes such as BRCA2, TP53, and RAD51D; but also lesser known cancer genes EXT2, WWOX, GATA2, and GPC3. Most of these genes are involved in DNA damage repair, reaffirming the role of impaired DNA repair mechanisms in the development of multiple malignancies. These variants warrant further investigations in additional populations., Conclusions: We have identified both known and novel variants significantly enriched in patients with primary breast and lung malignancies, expanding the body of known cancer predisposition variants for both breast and lung cancer. These variants are mostly from genes involved in DNA repair, affirming the role of impaired DNA repair in the predisposition and development of multiple cancers., (© 2023. The Author(s).)

Background: For the majority of individuals with early-onset or familial breast cancer referred for genetic testing, the genetic basis of their familial breast cancer remains unexplained. To identify novel germline variants associated with breast cancer predisposition, whole-exome sequencing (WES) was performed., Methods: WES on 290 BRCA1/BRCA2-negative Singaporeans with early-onset breast cancer and/or a family history of breast cancer was done. Case-control analysis against the East-Asian subpopulation (EAS) from the Genome Aggregation Database (gnomAD) identified variants enriched in cases, which were further selected by occurrence in cancer gene databases. Variants were further evaluated in repeated case-control analyses using a second case cohort from the database of Genotypes and Phenotypes (dbGaP) comprising 466 early-onset breast cancer patients from the United States, and a Singapore SG10K&#95;Health control cohort., Results: Forty-nine breast cancer-associated germline pathogenic variants in 37 genes were identified in Singapore cases versus gnomAD (EAS). Compared against SG10K&#95;Health controls, 13 of 49 variants remain significantly enriched (False Discovery Rate (FDR)-adjusted p < 0.05). Comparing these 49 variants in dbGaP cases against gnomAD (EAS) and SG10K&#95;Health controls revealed 23 concordant variants that were significantly enriched (FDR-adjusted p < 0.05). Fourteen variants were consistently enriched in breast cancer cases across all comparisons (FDR-adjusted p < 0.05). Seven variants in GPRIN2, NRG1, MYO5A, CLIP1, CUX1, GNAS and MGA were confirmed by Sanger sequencing., Conclusions: In conclusion, we have identified pathogenic variants in genes associated with breast cancer predisposition. Importantly, many of these variants were significant in a second case cohort from dbGaP, suggesting that the strategy of using case-control analysis to select variants could potentially be utilized for identifying variants associated with cancer susceptibility., (© 2022. The Author(s).)