Evidence map›Paper›PMID 35962742›Full record

ArticleThe oncologist2023

Concordance Between Genomic Alterations Detected by Tumor and Germline Sequencing: Results from a Tertiary Care Academic Center Molecular Tumor Board.

Michelle F Green, Catherine H Watson, Sarah Tait, Jie He, Dean C Pavlick, Garrett Frampton, Jinny Riedel, Jennifer K Plichta, Andrew J Armstrong, Rebecca A Previs and 5 more

Open access · goldAbstract read
In one paragraph

Article in The oncologist, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

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  9. Clinical genetics in breast cancer.Journal of surgical oncology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 3 institutions in 1 country.

Michelle F GreenDepartment of Pathology, Duke University Medical Center, Durham, NC, USA.ORCID 0000-0002-6055-4342
Catherine H WatsonDepartment of Obstetrics and Gynecology, Duke University, Durham, NC, USA.
Sarah TaitDuke University, School of Medicine, Durham, NC, USA.
Jie HeFoundation Medicine, Inc., Cambridge, MA, USA.
Dean C PavlickFoundation Medicine, Inc., Cambridge, MA, USA.
Garrett FramptonFoundation Medicine, Inc., Cambridge, MA, USA.
Jinny RiedelDuke Cancer Institute, Duke University Medical Center, Durham, NC, USA.
Jennifer K PlichtaDepartment of Surgery, Duke University Medical Center, Durham, NC, USA.
Andrew J ArmstrongDuke Cancer Institute Center for Prostate and Urologic Cancers, Duke University, Durham NCUSA.
Rebecca A PrevisDepartment of Obstetrics and Gynecology, Duke University, Durham, NC, USA.
Noah KauffDuke Cancer Institute, Duke University Medical Center, Durham, NC, USA.
John H StricklerDuke Cancer Institute, Duke University Medical Center, Durham, NC, USA.
Michael B DattoDepartment of Pathology, Duke University Medical Center, Durham, NC, USA.
Andrew BerchuckDepartment of Obstetrics and Gynecology, Duke University, Durham, NC, USA.
Carolyn S MenendezDepartment of Surgery, Duke University Medical Center, Durham, NC, USA.
Duke Medical Center · USDuke University · USFoundation Medicine (United States)

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe majority of tumor sequencing currently performed on cancer patients does not include a matched normal control, and in cases where germline testing is performed, it is usually run independently of tumor testing. The rates of concordance between variants identified via germline and tumor testing in this context are poorly understood. We compared tumor and germline sequencing results in patients with breast, ovarian, pancreatic, and prostate cancer who were found to harbor alterations in genes associated with homologous recombination deficiency (HRD) and increased hereditary cancer risk. We then evaluated the potential for a computational somatic-germline-zygosity (SGZ) modeling algorithm to predict germline status based on tumor-only comprehensive genomic profiling (CGP) results.

methodsA retrospective chart review was performed using an academic cancer center's databases of somatic and germline sequencing tests, and concordance between tumor and germline results was assessed. SGZ modeling from tumor-only CGP was compared to germline results to assess this method's accuracy in determining germline mutation status.

resultsA total of 115 patients with 146 total alterations were identified. Concordance rates between somatic and germline alterations ranged from 0% to 85.7% depending on the gene and variant classification. After correcting for differences in variant classification and filtering practices, SGZ modeling was found to have 97.2% sensitivity and 90.3% specificity for the prediction of somatic versus germline origin.

conclusionsMutations in HRD genes identified by tumor-only sequencing are frequently germline. Providers should be aware that technical differences related to assay design, variant filtering, and variant classification can contribute to discordance between tumor-only and germline sequencing test results. In addition, SGZ modeling had high predictive power to distinguish between mutations of somatic and germline origin without the need for a matched normal control, and could potentially be considered to inform clinical decision-making.

Indexed as

NeoplasmsGenomicsGerm-Line MutationHumansMaleMutationRetrospective StudiesTertiary Health Care

Identifiers

PMID35962742
PMCPMC9847540
OpenAlexW4291209206

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.