Evidence map›Paper›PMID 32066500›Full record

ArticleGenome medicine2020

The pan-cancer landscape of prognostic germline variants in 10,582 patients.

Ajay Chatrath, Roza Przanowska, Shashi Kiran, Zhangli Su, Shekhar Saha, Briana Wilson, Takaaki Tsunematsu, Ji-Hye Ahn, Kyung Yong Lee, Teressa Paulsen and 7 more

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

31 citing papers in PubMed, 42 citations in OpenAlex.

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  14. TGFβ in Pancreas and Colorectal Cancer: Opportunities to Overcome Therapeutic Resistance.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    Review
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  18. Research Silos in Cancer Disparities: Obstacles to Improving Clinical Outcomes for Underserved Patient Populations.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023
    Article
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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

17 authors at 2 institutions in 2 countries.

Ajay ChatrathDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Roza PrzanowskaDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Shashi KiranDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Zhangli SuDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Shekhar SahaDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Briana WilsonDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Takaaki TsunematsuDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Ji-Hye AhnDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Kyung Yong LeeDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Teressa PaulsenDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Ewelina SobierajskaDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Manjari KiranDepartment of Systems and Computational Biology, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana, India.
Xiwei TangDepartment of Statistics, University of Virginia, Charlottesville, VA, USA.
Tianxi LiDepartment of Statistics, University of Virginia, Charlottesville, VA, USA.
Pankaj KumarDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA.
Aakrosh RatanCenter for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
Anindya DuttaDepartment of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1240 Pinn Hall, Charlottesville, VA, 22908, USA. ad8q@virginia.edu.ORCID 0000-0002-4319-0073
University of Virginia · USUniversity of Hyderabad · IN

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007267 · NIGMS · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI GARCIA-BLANCO, MARIANO A. · 1985 to 2024
$13.4M
The role of MCM8-9 in genomic instability of cancersR01CA060499 · NCI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Anindya Dutta · 1994 to 2026
$8.6M
Summer Research Experience in Cancer(SuRE-C)R25CA206972 · NCI · UNIVERSITY OF VIRGINIA · PI ADRIAN J HALME, Hui Zong · 2017 to 2026
$2.0M
Effect of anti-S phase agents on human chromosomesR01CA166054 · NCI · UNIVERSITY OF VIRGINIA · PI DUTTA, ANINDYA · 2013 to 2017
$1.6M
American Heart Association-American Stroke Association 18PRE33990261NCI NIH HHS HHSN261201400008CNCI NIH HHS HHSN261201500003CNCI NIH HHS HHSN261201500003INCI NIH HHS R01 CA060499NCI NIH HHS R01 CA166054NIGMS NIH HHS T32 GM007267NIH HHS R01 CA166054NIH HHS R01 CA60499NIH HHS T32 GM007267
6 · The paper itself

Abstract

backgroundWhile clinical factors such as age, grade, stage, and histological subtype provide physicians with information about patient prognosis, genomic data can further improve these predictions. Previous studies have shown that germline variants in known cancer driver genes are predictive of patient outcome, but no study has systematically analyzed multiple cancers in an unbiased way to identify genetic loci that can improve patient outcome predictions made using clinical factors.

methodsWe analyzed sequencing data from the over 10,000 cancer patients available through The Cancer Genome Atlas to identify germline variants associated with patient outcome using multivariate Cox regression models.

resultsWe identified 79 prognostic germline variants in individual cancers and 112 prognostic germline variants in groups of cancers. The germline variants identified in individual cancers provide additional predictive power about patient outcomes beyond clinical information currently in use and may therefore augment clinical decisions based on expected tumor aggressiveness. Molecularly, at least 12 of the germline variants are likely associated with patient outcome through perturbation of protein structure and at least five through association with gene expression differences. Almost half of these germline variants are in previously reported tumor suppressors, oncogenes or cancer driver genes with the other half pointing to genomic loci that should be further investigated for their roles in cancers.

conclusionsGermline variants are predictive of outcome in cancer patients and specific germline variants can improve patient outcome predictions beyond predictions made using clinical factors alone. The germline variants also implicate new means by which known oncogenes, tumor suppressor genes, and driver genes are perturbed in cancer and suggest roles in cancer for other genes that have not been extensively studied in oncology. Further studies in other cancer cohorts are necessary to confirm that germline variation is associated with outcome in cancer patients as this is a proof-of-principle study.

Indexed as

Germ-Line MutationBiomarkers, TumorGenetic TestingHumansNeoplasmsOncogene ProteinsPolymorphism, Single NucleotideQuantitative Trait LociTumor Suppressor ProteinsBiomarkers, TumorOncogene ProteinsTumor Suppressor ProteinsCancer biologyDriver geneeQTLGermline variantsNon-synonymous mutationOncogenePan-cancerSingle nucleotide polymorphismSurvival analysisTumor suppressor

Identifiers

PMID32066500
PMCPMC7027124
OpenAlexW3011051319

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Registered trials

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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.