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      Germline variation in BRCA1/ 2 is highly ethnic‐specific: Evidence from over 30,000 Chinese hereditary breast and ovarian cancer patients

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          Abstract

          BRCA1 and BRCA2 play essential roles in maintaining the genome stability. Pathogenic germline mutations in these two genes disrupt their function, lead to genome instability and increase the risk of developing breast and ovarian cancers. BRCA mutations have been extensively screened in Caucasian populations, and the resulting information are used globally as the standard reference in clinical diagnosis, treatment and prevention of BRCA‐related cancers. Recent studies suggest that BRCA mutations can be ethnic‐specific, raising the question whether a Caucasian‐based BRCA mutation information can be used as a universal standard worldwide, or whether an ethnicity‐based BRCA mutation information system need to be developed for the corresponding ethnic populations. In this study, we used Chinese population as a model to test ethnicity‐specific BRCA mutations considering that China has one of the latest numbers of breast cancer patients therefore BRCA mutation carriers. Through comprehensive data mining, standardization and annotation, we collected 1,088 distinct BRCA variants derived from over 30,000 Chinese individuals, one of the largest BRCA data set from a non‐Caucasian population covering nearly all known BRCA variants in the Chinese population ( https://dbBRCA-Chinese.fhs.umac.mo). Using this data, we performed multi‐layered analyses to determine the similarities and differences of BRCA variation between Chinese and non‐Chinese ethnic populations. The results show the substantial differences of BRCA data between Chinese and non‐Chinese ethnicities. Our study indicates that the current Caucasian population‐based BRCA data is not adequate to represent the BRCA status in non‐Caucasian populations. Therefore, ethnic‐based BRCA standards need to be established to serve for the non‐Caucasian populations.

          Abstract

          What's new?

          Currently, Caucasian population‐based BRCA mutation data are used worldwide as the standard reference for diagnosis, treatment, and prevention of BRCA‐associated cancers. Recent studies however suggest that BRCA variation can be ethnic specific. Here, the authors carried out a comprehensive comparison of BRCA mutation data between the Chinese and worldwide non‐Chinese populations and found substantial differences. The study suggests that BRCA mutations are highly ethnic specific and that the current Caucasian population‐based BRCA data is not adequate to represent the BRCA status in non‐Caucasian populations. Developing new standard references using ethnic‐based BRCA mutation data is needed to better serve non‐Caucasian ethnic populations.

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          Most cited references30

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          A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1.

          A strong candidate for the 17q-linked BRCA1 gene, which influences susceptibility to breast and ovarian cancer, has been identified by positional cloning methods. Probable predisposing mutations have been detected in five of eight kindreds presumed to segregate BRCA1 susceptibility alleles. The mutations include an 11-base pair deletion, a 1-base pair insertion, a stop codon, a missense substitution, and an inferred regulatory mutation. The BRCA1 gene is expressed in numerous tissues, including breast and ovary, and encodes a predicted protein of 1863 amino acids. This protein contains a zinc finger domain in its amino-terminal region, but is otherwise unrelated to previously described proteins. Identification of BRCA1 should facilitate early diagnosis of breast and ovarian cancer susceptibility in some individuals as well as a better understanding of breast cancer biology.
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            dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs.

            The purpose of the dbNSFP is to provide a one-stop resource for functional predictions and annotations for human nonsynonymous single-nucleotide variants (nsSNVs) and splice-site variants (ssSNVs), and to facilitate the steps of filtering and prioritizing SNVs from a large list of SNVs discovered in an exome-sequencing study. A list of all potential nsSNVs and ssSNVs based on the human reference sequence were created and functional predictions and annotations were curated and compiled for each SNV. Here, we report a recent major update of the database to version 3.0. The SNV list has been rebuilt based on GENCODE 22 and currently the database includes 82,832,027 nsSNVs and ssSNVs. An attached database dbscSNV, which compiled all potential human SNVs within splicing consensus regions and their deleteriousness predictions, add another 15,030,459 potentially functional SNVs. Eleven prediction scores (MetaSVM, MetaLR, CADD, VEST3, PROVEAN, 4× fitCons, fathmm-MKL, and DANN) and allele frequencies from the UK10K cohorts and the Exome Aggregation Consortium (ExAC), among others, have been added. The original seven prediction scores in v2.0 (SIFT, 2× Polyphen2, LRT, MutationTaster, MutationAssessor, and FATHMM) as well as many SNV and gene functional annotations have been updated. dbNSFP v3.0 is freely available at http://sites.google.com/site/jpopgen/dbNSFP.
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              InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines.

              In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published updated standards and guidelines for the clinical interpretation of sequence variants with respect to human diseases on the basis of 28 criteria. However, variability between individual interpreters can be extensive because of reasons such as the different understandings of these guidelines and the lack of standard algorithms for implementing them, yet computational tools for semi-automated variant interpretation are not available. To address these problems, we propose a suite of methods for implementing these criteria and have developed a tool called InterVar to help human reviewers interpret the clinical significance of variants. InterVar can take a pre-annotated or VCF file as input and generate automated interpretation on 18 criteria. Furthermore, we have developed a companion web server, wInterVar, to enable user-friendly variant interpretation with an automated interpretation step and a manual adjustment step. These tools are especially useful for addressing severe congenital or very early-onset developmental disorders with high penetrance. Using results from a few published sequencing studies, we demonstrate the utility of InterVar in significantly reducing the time to interpret the clinical significance of sequence variants.
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                Author and article information

                Contributors
                sanmingwang@umac.mo
                Journal
                Int J Cancer
                Int. J. Cancer
                10.1002/(ISSN)1097-0215
                IJC
                International Journal of Cancer
                John Wiley & Sons, Inc. (Hoboken, USA )
                0020-7136
                1097-0215
                13 February 2019
                15 August 2019
                : 145
                : 4 ( doiID: 10.1002/ijc.v145.4 )
                : 962-973
                Affiliations
                [ 1 ] Cancer Centre and Institute of Translational Medicine, Faculty of Health Sciences University of Macau Macau China
                [ 2 ] Eppley Cancer Institute University of Nebraska Medical Center Omaha NE
                Author notes
                [*] [* ] Correspondence to: San Ming Wang, MD, Faculty of Health Sciences, University of Macau, Taipa, Macau, China, Tel.: 853‐882‐24836, E‐mail: sanmingwang@ 123456umac.mo
                [†]

                S.P.B., K.C. and H.G. contributed equally to this work

                Author information
                https://orcid.org/0000-0002-2172-1320
                Article
                IJC32176
                10.1002/ijc.32176
                6617753
                30702160
                f7bd790f-95d5-409c-b28d-13720bdf9516
                © 2019 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 29 November 2018
                : 14 January 2019
                : 25 January 2019
                Page count
                Figures: 1, Tables: 4, Pages: 12, Words: 7947
                Funding
                Funded by: The Faculty of Health Sciences, University of Macau
                Funded by: The University of Macau
                Award ID: SRG2017‐00097‐FHS
                Categories
                Cancer Genetics and Epigenetics
                Cancer Genetics and Epigenetics
                Custom metadata
                2.0
                ijc32176
                15 August 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.5 mode:remove_FC converted:10.07.2019

                Oncology & Radiotherapy
                breast cancer,brca1,brca2,ethnic‐specific,population,mutation,chinese
                Oncology & Radiotherapy
                breast cancer, brca1, brca2, ethnic‐specific, population, mutation, chinese

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