Literature DB >> 27633409

What's New in Genetic Testing for Cancer Susceptibility?

Jennifer K Plichta, Molly Griffin, Joseph Thakuria, Kevin S Hughes.   

Abstract

The advent of next-generation sequencing, and its transition further into the clinic with the US Food and Drug Administration approval of a cystic fibrosis assay in 2013, have increased the speed and reduced the cost of DNA sequencing. Coupled with a historic ruling by the Supreme Court of the United States that human genes are not patentable, these events have caused a seismic shift in genetic testing in clinical medicine. More labs are offering genetic testing services; more multigene panels are available for gene testing; more genes and gene mutations are being identified; and more variants of uncertain significance, which may or may not be clinically actionable, have been found. All these factors, taken together, are increasing the complexity of clinical management. While these developments have led to a greater interest in genetic testing, risk assessment, and large-scale population screening, they also present unique challenges. The dilemma for clinicians is how best to understand and manage this rapidly growing body of information to improve patient care. With millions of genetic variants of potential clinical significance and thousands of genes associated with rare but well-established genetic conditions, the complexities of genetic data management clearly will require improved computerized clinical decision support tools, as opposed to continued reliance on traditional rote, memory-based medicine.

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Year:  2016        PMID: 27633409

Source DB:  PubMed          Journal:  Oncology (Williston Park)        ISSN: 0890-9091            Impact factor:   2.990


  7 in total

1.  Efficient computation of the joint probability of multiple inherited risk alleles from pedigree data.

Authors:  Thomas Madsen; Danielle Braun; Gang Peng; Giovanni Parmigiani; Lorenzo Trippa
Journal:  Genet Epidemiol       Date:  2018-06-25       Impact factor: 2.135

2.  Molecular cancer screening: in search of evidence.

Authors:  Sana Raoof; Caleb J Kennedy; D A Wallach; Asaf Bitton; Robert C Green
Journal:  Nat Med       Date:  2021-07-01       Impact factor: 53.440

3.  A Clinical Decision Support Tool to Predict Cancer Risk for Commonly Tested Cancer-Related Germline Mutations.

Authors:  Danielle Braun; Jiabei Yang; Molly Griffin; Giovanni Parmigiani; Kevin S Hughes
Journal:  J Genet Couns       Date:  2018-03-02       Impact factor: 2.537

4.  Disease spectrum of gastric cancer susceptibility genes.

Authors:  Sophia K McKinley; Preeti Singh; Kanhua Yin; Jin Wang; Jingan Zhou; Yujia Bao; Menghua Wu; Kush Pathak; John T Mullen; Danielle Braun; Kevin S Hughes
Journal:  Med Oncol       Date:  2021-03-24       Impact factor: 3.064

5.  Statistical methods for Mendelian models with multiple genes and cancers.

Authors:  Jane W Liang; Gregory E Idos; Christine Hong; Stephen B Gruber; Giovanni Parmigiani; Danielle Braun
Journal:  Genet Epidemiol       Date:  2022-05-18       Impact factor: 2.344

6.  Assessment of tumor suppressor promoter methylation in healthy individuals.

Authors:  Deepak B Poduval; Elisabet Ognedal; Zuzana Sichmanova; Eivind Valen; Gjertrud T Iversen; Laura Minsaas; Per E Lønning; Stian Knappskog
Journal:  Clin Epigenetics       Date:  2020-08-28       Impact factor: 6.551

Review 7.  Genetic Predisposition to Breast and Ovarian Cancers: How Many and Which Genes to Test?

Authors:  Davide Angeli; Samanta Salvi; Gianluca Tedaldi
Journal:  Int J Mol Sci       Date:  2020-02-08       Impact factor: 5.923

  7 in total

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