Evidence map›Paper›PMID 36575447›Full record

ArticleJournal of translational medicine2022

Accurate genome-wide genotyping from archival tissue to explore the contribution of common genetic variants to pre-cancer outcomes.

Daniela Nachmanson, Meghana Pagadala, Joseph Steward, Callie Cheung, Lauryn Keeler Bruce, Nicole Q Lee, Thomas J O'Keefe, Grace Y Lin, Farnaz Hasteh, Gerald P Morris and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 45% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
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

12 authors at 2 institutions in 1 country.

Daniela NachmansonBioinformatics and Systems Biology Graduate Program, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA.
Meghana PagadalaBiomedical Science Graduate Program, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA.
Joseph StewardMoores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA.
Callie CheungMoores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA.
Lauryn Keeler BruceBioinformatics and Systems Biology Graduate Program, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA.
Nicole Q LeeMoores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA.
Thomas J O'KeefeDepartment of Surgery, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA.
Grace Y LinDepartment of Pathology, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA.
Farnaz HastehDepartment of Pathology, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA.
Gerald P MorrisDepartment of Pathology, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA.
Hannah CarterMoores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA.
Olivier HarismendyMoores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA. oharismendy@ucsd.edu.ORCID 0000-0002-8098-9888
University of California San Diego · USUC San Diego Health System · US

Funding

VIRAL MALIGNANCYP30CA023100 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Jesse Nodora · 1985 to 2026
$124.9M
MEDICAL SCIENTIST TRAINING PROGRAMT32GM007198 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHI, NEIL C, INSEL, PAUL A · 1985 to 2024
$29.3M
Using Networks to Seed Hierarchical Whole-cell Models of CancerU54CA209891 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI IDEKER, TREY, KROGAN, NEVAN J · 2017 to 2021
$10.9M
San Diego Biomedical Informatics Education & Research (SABER)T15LM011271 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHAMIM NEMATI · 2012 to 2026
$9.7M
GRADUATE TRAINING PROGRAM IN BIONFORMATICST32GM008806 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAFNA, VINEET, REN, BING · 2001 to 2020
$6.2M
Elucidating the molecular and contextual basis for IDLE ultralow risk lesions and the tumor immune microenvironment of high risk in situ and invasive breast cancersU01CA196406 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BOROWSKY, ALEXANDER D, ESSERMAN, LAURA J · 2015 to 2020
$5.8M
Vermont Breast Cancer Molecular Characterization LaboratoryU01CA196383 · NCI · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SPRAGUE, BRIAN L, STEIN, JANET L · 2015 to 2020
$5.4M
NCI NIH HHS P30 CA023100NIGMS NIH HHS T32 GM007198NIH HHS P30CA023100NIH HHS T15LM011271NIH HHS T32GM008806NIH HHS U01CA196383NIH HHS U01CA196406NIH HHS U54CA209891
6 · The paper itself

Abstract

purposeThe contribution of common genetic variants to pre-cancer progression is understudied due to long follow-up time, rarity of poor outcomes and lack of available germline DNA collection. Alternatively, DNA from diagnostic archival tissue is available, but its somatic nature, limited quantity and suboptimal quality would require an accurate cost-effective genome-wide germline genotyping methodology. EXPERIMENTAL

designBlood and tissue DNA from 10 individuals were used to benchmark the accuracy of Single Nucleotide Polymorphisms (SNP) genotypes, Polygenic Risk Scores (PRS) or HLA haplotypes using low-coverage whole-genome sequencing (lc-WGS) and genotype imputation. Tissue-derived PRS were further evaluated for 36 breast cancer patients (11.7 years median follow-up time) diagnosed with DCIS and used to model the risk of Breast Cancer Subsequent Events (BCSE).

resultsTissue-derived germline DNA profiling resulted in accurate genotypes at common SNPs (blood correlation r

conclusionsArchival tissue DNA germline profiling using lc-WGS and imputation, represents a cost and resource-effective alternative in the retrospective design of long-term disease genetic studies. Initial results in breast cancer suggest that common risk variants contribute to pre-cancer progression.

Indexed as

Breast NeoplasmsCarcinoma, Intraductal, NoninfiltratingFemaleGenome-Wide Association StudyGenotypeHumansPolymorphism, Single NucleotideRetrospective StudiesBreast cancerDuctal carcinoma in situGenotypingLow-coverage whole-genome sequencingPolygenic risk scorePre-cancer

Identifiers

PMID36575447
PMCPMC9793518
OpenAlexW4313250888

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.