Dataset Information

Prevalence of pathogenic/likely pathogenic variants in the 24 cancer genes of the ACMG Secondary Findings v2.0 list in a large cancer cohort and ethnicity-matched controls.

ABSTRACT:

Background

Prior research has established that the prevalence of pathogenic/likely pathogenic (P/LP) variants across all of the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes is approximately 0.8-5%. We investigated the prevalence of P/LP variants in the 24 ACMG SF v2.0 cancer genes in a family-based cancer research cohort (n?=?1173) and in cancer-free ethnicity-matched controls (n?=?982).

Methods

We used InterVar to classify variants and subsequently conducted a manual review to further examine variants of unknown significance (VUS).

Results

In the 24 genes on the ACMG SF v2.0 list associated with a cancer phenotype, we observed 8 P/LP unique variants (8 individuals; 0.8%) in controls and 11 P/LP unique variants (14 individuals; 1.2%) in cases, a non-significant difference. We reviewed 115 VUS. The median estimated per-variant review time required was 30?min; the first variant within a gene took significantly (p?=?0.0009) longer to review (median = 60?min) compared with subsequent variants (median = 30?min). The concordance rate was 83.3% for the variants examined by two reviewers.

Conclusion

The 115 VUS required database and literature review, a time- and labor-intensive process hampered by the difficulty in interpreting conflicting P/LP determinations. By rigorously investigating the 24 ACMG SF v2.0 cancer genes, our work establishes a benchmark P/LP variant prevalence rate in a familial cancer cohort and controls.

SUBMITTER: Kim J

PROVIDER: S-EPMC6305568 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prevalence of pathogenic/likely pathogenic variants in the 24 cancer genes of the ACMG Secondary Findings v2.0 list in a large cancer cohort and ethnicity-matched controls.

Kim Jung J Luo Wen W Wang Mingyi M Wegman-Ostrosky Talia T Frone Megan N MN Johnston Jennifer J JJ Nickerson Michael L ML Rotunno Melissa M Li Shengchao A SA Achatz Maria I MI Brodie Seth A SA Dean Michael M de Andrade Kelvin C KC Fortes Fernanda P FP Gianferante Matthew M Khincha Payal P McMaster Mary L ML McReynolds Lisa J LJ Pemov Alexander A Pinheiro Maisa M Santiago Karina M KM Alter Blanche P BP Caporaso Neil E NE Gadalla Shahinaz M SM Goldin Lynn R LR Greene Mark H MH Loud Jennifer J Yang Xiaohong R XR Freedman Neal D ND Gapstur Susan M SM Gaudet Mia M MM Calista Donato D Ghiorzo Paola P Fargnoli Maria Concetta MC Nagore Eduardo E Peris Ketty K Puig Susana S Landi Maria Teresa MT Hicks Belynda B Zhu Bin B Liu Jia J Sampson Joshua N JN Chanock Stephen J SJ Mirabello Lisa J LJ Morton Lindsay M LM Biesecker Leslie G LG Tucker Margaret A MA Savage Sharon A SA Goldstein Alisa M AM Stewart Douglas R DR

Genome medicine 20181224 1

<h4>Background</h4>Prior research has established that the prevalence of pathogenic/likely pathogenic (P/LP) variants across all of the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes is approximately 0.8-5%. We investigated the prevalence of P/LP variants in the 24 ACMG SF v2.0 cancer genes in a family-based cancer research cohort (n = 1173) and in cancer-free ethnicity-matched controls (n = 982).<h4>Methods</h4>We used InterVar to classify variants and subsequently co ...[more]

PMID: 30583724

Similar Datasets

Project description:BackgroundGermline risk assessment is increasing as part of cancer care; however, disparities in subsequent genetic counseling are unknown.MethodsPan-cancer patients were prospectively consented to tumor-normal sequencing via custom next generation sequencing panel (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets) inclusive of germline analysis of ≥76 genes from January 2015 through December 2019 (97.5% research nonbillable) with protocol for genetics referral. Rates of pathogenic/likely pathogenic germline variants (PVs) and downstream counseling were compared across ancestry groups (mutually exclusive groups based on self-reported race/ethnicity and Ashkenazi Jewish [AJ] heritage) using nonparametric tests and multivariable logistic regression models.ResultsAmong 15,775 patients (59.6%, non-Hispanic [NH]-White; 15.7%, AJ; 20.5%, non-White [6.9%, Asian; 6.8%, Black/African American (AA); 6.7%, Hispanic; 0.1%, Other], and 4.2%, unknown), 2663 (17%) had a PV. Non-White patients had a lower PV rate (n = 433, 13.4%) compared to NH-Whites (n = 1451, 15.4%) and AJ patients (n = 683, 27.6%), p < .01, with differences in mostly moderate and low/recessive/uncertain penetrance variants. Among 2239 patients with new PV, 1652 (73.8%) completed recommended genetic counseling. Non-White patients had lower rates of genetic counseling (67.7%) than NH-White (73.7%) and AJ patients (78.8%), p < .01, with lower rates occurring in Black/AA (63%) compared to NH-White patients, even after adjustment for confounders (odds ratio, 0.60; 95% confidence interval, 0.37-0.97; p = .036). Non-White, particularly Black/AA and Asian, probands had a trend toward lower rates and numbers of at-risk family members being seen for counseling/genetic testing.ConclusionsDespite minimizing barriers to genetic testing, non-White patients were less likely to receive recommended cancer genetics follow-up, with potential implications for oncologic care, cancer risk reduction, and at-risk family members.Lay summaryGenetic testing is becoming an important part of cancer care, and we wanted to see if genetics care was different between individuals of different backgrounds. We studied 15,775 diverse patients with cancer who had genetic testing using a test called MSK-IMPACT that was covered by research funding. Clinically important genetic findings were high in all groups. However, Black patients were less likely to get recommended counseling compared to White patients. Even after removing many roadblocks, non-White and especially Black patients were less likely to get recommended genetics care, which may affect their cancer treatments and families.

Dataset Information

Prevalence of pathogenic/likely pathogenic variants in the 24 cancer genes of the ACMG Secondary Findings v2.0 list in a large cancer cohort and ethnicity-matched controls.

Background

Methods

Results

Conclusion

Publications

Prevalence of pathogenic/likely pathogenic variants in the 24 cancer genes of the ACMG Secondary Findings v2.0 list in a large cancer cohort and ethnicity-matched controls.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets