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Updated: Jun 23, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Study designs in genetic epidemiology.

Michele L Cote¹

¹Department of Epidemiology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA. cotem@med.wayne.edu

Methods in Molecular Biology (Clifton, N.J.)

|April 22, 2009

Summary

This summary is machine-generated.

Identifying germline mutations is key to understanding cancer risk. This research explores methods to detect rare, high-risk mutations and common variants that influence cancer development, aiding personalized risk assessment.

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Area of Science:

Genetics
Oncology
Molecular Biology

Background:

Germline mutations in genes like p53 and BRCA1 significantly increase inherited cancer risk.
These high-penetrance mutations are rare but account for a small percentage of overall cancer diagnoses.
Research is actively seeking common genetic variants associated with modest cancer risk increases.

Purpose of the Study:

To describe methods for identifying genetic contributions to cancer risk.
To outline strategies for pinpointing chromosomal regions linked to rare, high-penetrance mutations.
To detail approaches for discovering common mutations that modulate cancer development.

Main Methods:

Utilizing advancements post-Human Genome Project to identify cancer-associated genes and variants.
Employing techniques to establish evidence for a genetic component in disease risk.
Applying methods for detecting both rare, highly penetrant mutations and common risk-modulating variants.

Main Results:

Established methodologies exist for identifying germline mutations influencing cancer predisposition.
The study details approaches to locate specific chromosomal regions harboring significant genetic variants.
Methods cover the spectrum from rare, high-impact mutations to common, low-impact variants.

Conclusions:

Germline mutations play a crucial role in inherited cancer susceptibility.
A range of genetic analysis methods are available to identify cancer risk factors.
Continued research into common variants is essential for comprehensive cancer risk prediction.