2020
DOI: 10.1007/s10549-020-05643-0
|View full text |Cite
|
Sign up to set email alerts
|

Evaluation of pathogenetic mutations in breast cancer predisposition genes in population-based studies conducted among Chinese women

Abstract: Purpose Limited studies have been conducted to evaluate pathogenetic mutations in breast cancer predisposition genes among Chinese women. To fully characterize germline mutations of these genes in this population, we used the whole-exome sequencing data in a population-based case-control study conducted in Shanghai, China. Methods We evaluated exonic, splicing, and copy number variants in 11 established and 14 candidate breast cancer predisposition genes in 831 invasive breast cancer cases and 839 controls. We… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
10
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
9

Relationship

0
9

Authors

Journals

citations
Cited by 18 publications
(12 citation statements)
references
References 50 publications
2
10
0
Order By: Relevance
“…This however is not unlike other genomics testing methods including the classic techniques such as MLPA 5 and copy number microarrays as well as other NGS-based CNV detection algorithms (Park and Mori, 2010;Zhao et al, 2013). This study has identified pathogenic (ACMG 1 and ACMG 2) CNVs in 32 of 2870 (1.1%) patients, or 32 of 431 (7.4%) of all PVs identified, a proportion roughly in line with few previous reports (Mancini-DiNardo et al, 2019;Tsaousis et al, 2019;Zeng et al, 2020). A significant subset of these CNVs have been identified in some of the less well characterized cancer predisposition genes and adds to the spectrum of variants 5 www.mrcholland.com reported in these genes (Table 2).…”
Section: Copy Number Variants (Cnvs)supporting
confidence: 87%
“…This however is not unlike other genomics testing methods including the classic techniques such as MLPA 5 and copy number microarrays as well as other NGS-based CNV detection algorithms (Park and Mori, 2010;Zhao et al, 2013). This study has identified pathogenic (ACMG 1 and ACMG 2) CNVs in 32 of 2870 (1.1%) patients, or 32 of 431 (7.4%) of all PVs identified, a proportion roughly in line with few previous reports (Mancini-DiNardo et al, 2019;Tsaousis et al, 2019;Zeng et al, 2020). A significant subset of these CNVs have been identified in some of the less well characterized cancer predisposition genes and adds to the spectrum of variants 5 www.mrcholland.com reported in these genes (Table 2).…”
Section: Copy Number Variants (Cnvs)supporting
confidence: 87%
“…It is worth emphasizing that we have performed a screening of CNVs in our cohort of HC patients, resulting in the identification of two large deletions (exons 7 to 8 and exons 7 to 11), accounting for 10.5% of the PVs. To our knowledge, only a small fraction of published studies have also performed this analysis and only seven CNVs have been identified so far: exon 1 deletion [33], exon 2 deletion [34], exon 1 to 6 deletion [35], exon 5 to 7 deletion [36], exon 8 to 11 deletion [37] and two whole-gene deletions [37,38]. While no CNVs were identified in the gnomAD SV control population dataset, analysis of BARD1 CNVs in HC cohorts is strongly recommended considering the significant contribution in our series of this kind of variant.…”
Section: Discussionmentioning
confidence: 99%
“…A panel NGS analysis involving 8085 Chinese breast cancer patients revealed only 18 (0.3%) carriers of pathogenic CHEK2 mutations [ 141 ]; eight of them carried the novel founder nonsense mutation c.C417A (p.Y139*) [ 142 ]. Only two carriers (0.24%) of CHEK2 mutations were identified in a recent analysis of 831 breast cancer patients from Shanghai [ 143 ]. Studies of breast and prostate cancer patients from Japan included analyses in control populations that revealed the presence of pathogenic CHEK2 germline mutations in 0.1% of both female and male noncancer controls [ 144 , 145 ].…”
Section: Germline Chek2 Variantsmentioning
confidence: 99%