Landscape of germline pathogenic variants in patients with dual primary breast and lung cancer.

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.

Whole-exome sequencing of BRCA-negative breast cancer patients and case-control analyses identify variants associated with breast cancer susceptibility.

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_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_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_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.

Harnessing the potential of machine learning for advancing "Quality by Design" in biomanufacturing.

Ensuring consistent high yields and product quality are key challenges in biomanufacturing. Even minor deviations in critical process parameters (CPPs) such as media and feed compositions can significantly affect product critical quality attributes (CQAs). To identify CPPs and their interdependencies with product yield and CQAs, design of experiments, and multivariate statistical approaches are typically used in industry. Although these models can predict the effect of CPPs on product yield, there is room to improve CQA prediction performance by capturing the complex relationships in high-dimensional data. In this regard, machine learning (ML) approaches offer immense potential in handling non-linear datasets and thus are able to identify new CPPs that could effectively predict the CQAs. ML techniques can also be synergized with mechanistic models as a 'hybrid ML' or 'white box ML' to identify how CPPs affect the product yield and quality mechanistically, thus enabling rational design and control of the bioprocess. In this review, we describe the role of statistical modeling in Quality by Design (QbD) for biomanufacturing, and provide a generic outline on how relevant ML can be used to meaningfully analyze bioprocessing datasets. We then offer our perspectives on how relevant use of ML can accelerate the implementation of systematic QbD within the biopharma 4.0 paradigm.

Germline Variants Associated with Nasopharyngeal Carcinoma Predisposition Identified through Whole-Exome Sequencing.

The current understanding of genetic susceptibility factors for nasopharyngeal carcinoma (NPC) is still incomplete. To identify novel germline variants associated with NPC predisposition, we analysed whole-exome sequencing data from 119 NPC patients from Singapore with a family history of NPC and/or with early-onset NPC, together with 1337 Singaporean participants without NPC. Variants were prioritised and filtered by selecting variants with minor allele frequencies of <1% in both local control (n = 1337) and gnomAD non-cancer (EAS) (n = 9626) cohorts and a high pathogenicity prediction (CADD score > 20). Using single-variant testing, we identified 17 rare pathogenic variants in 17 genes that were associated with NPC. Consistent evidence of enrichment in NPC patients was observed for five of these variants (in JAK2, PRDM16, LRP1B, NIN, and NKX2-1) from an independent case-control comparison of 156 NPC patients and 9770 unaffected individuals. In a family with five siblings, a FANCE variant (p. P445S) was detected in two affected members, but not in three unaffected members. Gene-based burden testing recapitulated variants in NKX2-1 and FANCE as being associated with NPC risk. Using pathway analysis, endocytosis and immune-modulating pathways were found to be enriched for mutation burden. This study has identified NPC-predisposing variants and genes which could shed new insights into the genetic predisposition of NPC.