NDLI: Assessment of in silico protein sequence analysis in the clinical classification of variants in cancer risk genes

Please wait, while we are loading the content...

Breast cancer genetic counseling among Dutch patients from Turkish and Moroccan descent: participation determinants and perspectives of patients and healthcare professionals

Survey of family history taking and genetic testing in pediatric practice

Engaging Hmong adults in genomic and pharmacogenomic research: Toward reducing health disparities in genomic knowledge using a community-based participatory research approach

Frequency of single nucleotide platelet receptor gene polymorphism (P2Y12-i744T>C) in coronary artery disease patients among Tamilian population

Voluntary premarital screening to prevent sickle cell disease in Jamaica: does it work?

The effect of a celebrity health disclosure on demand for health care: trends in BRCA testing and subsequent health services use

Implementing genetic education in primary care: the Gen-Equip programme

Journal of Community Genetics : Volume 8, Issue 1, January 2017

Journal of Community Genetics : Volume 7

Journal of Community Genetics : Volume 6

Journal of Community Genetics : Volume 5

Journal of Community Genetics : Volume 4

Journal of Community Genetics : Volume 3

Journal of Community Genetics : Volume 2

Journal of Community Genetics : Volume 1

Assessment of in silico protein sequence analysis in the clinical classification of variants in cancer risk genes

Content Provider	Springer Nature Link
Author	Kerr, Iain D. Cox, Hannah C. Moyes, Kelsey Evans, Brent Burdett, Brianna C. Kan, Aric McElroy, Heather Vail, Paris J. Brown, Krystal L. Sumampong, Dechie B. Monteferrante, Nicholas J. Hardman, Kennedy L. Theisen, Aaron Mundt, Erin Wenstrup, Richard J. Eggington, Julie M.
Copyright Year	2016
Abstract	Missense variants represent a significant proportion of variants identified in clinical genetic testing. In the absence of strong clinical or functional evidence, the American College of Medical Genetics recommends that these findings be classified as variants of uncertain significance (VUS). VUSs may be reclassified to better inform patient care when new evidence is available. It is critical that the methods used for reclassification are robust in order to prevent inappropriate medical management strategies and unnecessary, life-altering surgeries. In an effort to provide evidence for classification, several in silico algorithms have been developed that attempt to predict the functional impact of missense variants through amino acid sequence conservation analysis. We report an analysis comparing internally derived, evidence-based classifications with the results obtained from six commonly used algorithms. We compiled a dataset of 1118 variants in BRCA1, BRCA2, MLH1, and MSH2 previously classified by our laboratory’s evidence-based variant classification program. We compared internally derived classifications with those obtained from the following in silico tools: Align-GVGD, CONDEL, Grantham Analysis, MAPP-MMR, PolyPhen-2, and SIFT. Despite being based on similar underlying principles, all algorithms displayed marked divergence in accuracy, specificity, and sensitivity. Overall, accuracy ranged from 58.7 to 90.8% while the Matthews Correlation Coefficient ranged from 0.26–0.65. CONDEL, a weighted average of multiple algorithms, did not perform significantly better than its individual components evaluated here. These results suggest that the in silico algorithms evaluated here do not provide reliable evidence regarding the clinical significance of missense variants in genes associated with hereditary cancer.
Starting Page	87
Ending Page	95
Page Count	9
File Format	PDF
ISSN	1868310X
Journal	Journal of Community Genetics
Volume Number	8
Issue Number	2
e-ISSN	18686001
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2017-01-03
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	HBOC Lynch syndrome Sequence conservation Missense mutation Variant classification Variants of uncertain significance Human Genetics Public Health Epidemiology Gene Therapy Gene Function
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health Epidemiology Genetics (clinical)

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Assessment of in silico protein sequence analysis in the clinical classification of variants in cancer risk genes

Microsatellite Instability Use in Mismatch Repair Gene Sequence Variant Classification

Comparison of locus-specific databases for BRCA1 and BRCA2 variants reveals disparity in variant classification within and among databases

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics

Gene variants of unknown clinical significance in Lynch syndrome. An introduction for clinicians

Colorectal tumour BRAF V600E and MLH1 promoter methylation status in the assessment of mismatch repair gene sequence variants of unknown clinical significance

The pathological significance of selected MLH1 missense mutations based on the theoretical in silico predictions.

Comparison of locus-specific databases for BRCA1 and BRCA2 variants reveals disparity in variant classification within and among databases

Classification of MSH6 Variants of Uncertain Significance Using Functional Assays

Assessment of in silico protein sequence analysis in the clinical classification of variants in cancer risk genes

Similar Documents

Assessment of in silico protein sequence analysis in the clinical classification of variants in cancer risk genes

Microsatellite Instability Use in Mismatch Repair Gene Sequence Variant Classification

Comparison of locus-specific databases for BRCA1 and BRCA2 variants reveals disparity in variant classification within and among databases

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics

Gene variants of unknown clinical significance in Lynch syndrome. An introduction for clinicians

Colorectal tumour BRAF V600E and MLH1 promoter methylation status in the assessment of mismatch repair gene sequence variants of unknown clinical significance

The pathological significance of selected MLH1 missense mutations based on the theoretical in silico predictions.

Comparison of locus-specific databases for BRCA1 and BRCA2 variants reveals disparity in variant classification within and among databases

Classification of MSH6 Variants of Uncertain Significance Using Functional Assays

Assessment of in silico protein sequence analysis in the clinical classification of variants in cancer risk genes