Evidence map›Paper›PMID 31352405›Full record

ArticleG3 (Bethesda, Md.)2019

FERMI: A Novel Method for Sensitive Detection of Rare Mutations in Somatic Tissue.

L Alexander Liggett, Anchal Sharma, Subhajyoti De, James DeGregori

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  5. Review
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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

4 authors.

L Alexander LiggettDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO 80045.
Anchal SharmaRutgers Cancer Institute, New Brunswick, NJ 08901.
Subhajyoti DeRutgers Cancer Institute, New Brunswick, NJ 08901.
James DeGregoriDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO 80045 james.degregori@ucdenver.edu.

Funding

University of Colorado Cancer Center Support Grant - Lung Cancer Patient-Derived Xenografts with Autologous Human Immune SystemsP30CA046934 · NCI · UNIVERSITY OF COLORADO DENVER · PI James V Degregori · 1988 to 2026
$117.0M
TRANSCRIPTIONAL PROFILINGP30CA072720 · NCI · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI Tracie Saunders · 1997 to 2026
$94.5M
Colorado Clinical and Translational Sciences InstituteUL1TR001082 · NCATS · UNIVERSITY OF COLORADO DENVER · PI SOKOL, RONALD J. · 2013 to 2017
$48.0M
Aging-associated alterations in adaptive landscapes and the evolution of leukemiaR01CA180175 · NCI · UNIVERSITY OF COLORADO DENVER · PI DEGREGORI, JAMES V · 2013 to 2018
$1.8M
Computational approaches for identifying epigenomic contexts of somatic mutationsR01GM129066 · NIGMS · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI DE, SUBHAJYOTI · 2019 to 2023
$1.7M
The Role of Trisomy 21 in Hematopoiesis and LeukemogenesisF31CA196231 · NCI · UNIVERSITY OF COLORADO DENVER · PI LIGGETT, LUTHER ALEXANDER · 2015 to 2018
$121k
NCATS NIH HHS UL1 TR001082NCI NIH HHS F31 CA196231NCI NIH HHS P30 CA046934NCI NIH HHS P30 CA072720NCI NIH HHS R01 CA180175NIGMS NIH HHS R01 GM129066
6 · The paper itself

Abstract

With growing interest in monitoring mutational processes in normal tissues, tumor heterogeneity, and cancer evolution under therapy, the ability to accurately and economically detect ultra-rare mutations is becoming increasingly important. However, this capability has often been compromised by significant sequencing, PCR and DNA preparation error rates. Here, we describe FERMI (Fast Extremely Rare Mutation Identification) - a novel method designed to eliminate the majority of these sequencing and library-preparation errors in order to significantly improve rare somatic mutation detection. This method leverages barcoded targeting probes to capture and sequence DNA of interest with single copy resolution. The variant calls from the barcoded sequencing data are then further filtered in a position-dependent fashion against an adaptive, context-aware null model in order to distinguish true variants. As a proof of principle, we employ FERMI to probe bone marrow biopsies from leukemia patients, and show that rare mutations and clonal evolution can be tracked throughout cancer treatment, including during historically intractable periods like minimum residual disease. Importantly, FERMI is able to accurately detect nascent clonal expansions within leukemias in a manner that may facilitate the early detection and characterization of cancer relapse.

Indexed as

AlgorithmsBiopsyBone MarrowDNA Mutational AnalysisFalse Positive ReactionsGene LibraryHumansJanus Kinase 2LeukemiaLeukocytesMutationNeoplasm, ResidualPolymerase Chain ReactionPolymorphism, Single NucleotideSensitivity and SpecificitySingle Molecule ImagingJAK2 protein, humanJanus Kinase 2CancerGeneticsSequencing

Identifiers

PMID31352405
PMCPMC6723130

What OpenQuestion holds

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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.