Evidence map›Paper›PMID 34117742›Full record

ArticleBriefings in bioinformatics2021

A new method to accurately identify single nucleotide variants using small FFPE breast samples.

Angelo Fortunato, Diego Mallo, Shawn M Rupp, Lorraine M King, Timothy Hardman, Joseph Y Lo, Allison Hall, Jeffrey R Marks, E Shelley Hwang, Carlo C Maley

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

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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

10 authors.

Angelo FortunatoArizona Cancer Evolution Center, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA.ORCID 0000-0001-7363-0423
Diego MalloArizona Cancer Evolution Center, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA.
Shawn M RuppArizona Cancer Evolution Center, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA.
Lorraine M KingDepartment of Surgery, Duke University, Durham, NC, USA.
Timothy HardmanDepartment of Surgery, Duke University, Durham, NC, USA.
Joseph Y LoDepartment of Radiology, Duke University, Durham, NC, USA.
Allison HallDepartment of Pathology, Duke University, Durham, NC, USA.
Jeffrey R MarksDepartment of Surgery, Duke University, Durham, NC, USA.
E Shelley HwangDepartment of Surgery, Duke University, Durham, NC, USA.
Carlo C MaleyArizona Cancer Evolution Center, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA.

Funding

Women's Cancer Research ProgramP30CA014236 · NCI · DUKE UNIVERSITY · PI DONNA NIEDZWIECKI · 1985 to 2026
$174.8M
PHYLOGENIES of Barrett's Esophagus LineagesP01CA091955 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI GRADY, WILLIAM MALLORY · 2002 to 2019
$35.9M
Molecular, Cellular and Tissue Characterization UnitU2CCA233254 · NCI · DUKE UNIVERSITY · PI HWANG, E.SHELLEY · 2018 to 2023
$11.4M
The Role of the Microbiome in Cancer Suppression and Susceptibility Across SpeciesU54CA217376 · NCI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MALEY, CARLO · 2018 to 2022
$8.6M
Modeling Neoplastic Progression in Barrett's Esophagus - Renewal -2R01CA140657 · NCI · WISTAR INSTITUTE · PI Carlo Maley · 2009 to 2026
$5.0M
Application of Evolutionary Principles to Maintain Cancer Control (PQ21)R01CA170595 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI GATENBY, ROBERT A · 2012 to 2015
$2.1M
(PQC3) Genomic Diversity and Microenvironment as Drivers of Metastasis in DCISR01CA185138 · NCI · DUKE UNIVERSITY · PI HWANG, E.SHELLEY, MALEY, CARLO · 2014 to 2017
$2.0M
NCI NIH HHS P30 CA014236NCI NIH HHS R01 CA140657NCI NIH HHS R01 CA170595NCI NIH HHS R01 CA185138NCI NIH HHS U2C CA233254NCI NIH HHS U54 CA217376
6 · The paper itself

Abstract

Most tissue collections of neoplasms are composed of formalin-fixed and paraffin-embedded (FFPE) excised tumor samples used for routine diagnostics. DNA sequencing is becoming increasingly important in cancer research and clinical management; however it is difficult to accurately sequence DNA from FFPE samples. We developed and validated a new bioinformatic pipeline to use existing variant-calling strategies to robustly identify somatic single nucleotide variants (SNVs) from whole exome sequencing using small amounts of DNA extracted from archival FFPE samples of breast cancers. We optimized this strategy using 28 pairs of technical replicates. After optimization, the mean similarity between replicates increased 5-fold, reaching 88% (range 0-100%), with a mean of 21.4 SNVs (range 1-68) per sample, representing a markedly superior performance to existing tools. We found that the SNV-identification accuracy declined when there was less than 40 ng of DNA available and that insertion-deletion variant calls are less reliable than single base substitutions. As the first application of the new algorithm, we compared samples of ductal carcinoma in situ of the breast to their adjacent invasive ductal carcinoma samples. We observed an increased number of mutations (paired-samples sign test, P < 0.05), and a higher genetic divergence in the invasive samples (paired-samples sign test, P < 0.01). Our method provides a significant improvement in detecting SNVs in FFPE samples over previous approaches.

Indexed as

Biomarkers, TumorPolymorphism, Single NucleotideBreast NeoplasmsComputational BiologyDNA, NeoplasmFemaleGenetic HeterogeneityGenetic TestingHigh-Throughput Nucleotide SequencingHumansMutationWorkflowBiomarkers, TumorDNA, NeoplasmDCISexomeheterogeneityNGS

Identifiers

PMID34117742
PMCPMC8574974

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.