Evidence map›Paper›PMID 33288765›Full record

ArticleNature communications2020

Quantifying the influence of mutation detection on tumour subclonal reconstruction.

Lydia Y Liu, Vinayak Bhandari, Adriana Salcedo, Shadrielle M G Espiritu, Quaid D Morris, Thomas Kislinger, Paul C Boutros

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

14 citing papers in PubMed, 20 citations in OpenAlex.

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  6. Basket Trials: Past, Present, and Future.Annual review of cancer biology · 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

7 authors at 4 institutions in 2 countries.

Lydia Y LiuDepartment of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada.ORCID 0000-0001-6026-3169
Vinayak BhandariDepartment of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada.
Adriana SalcedoDepartment of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada.
Shadrielle M G EspirituOntario Institute for Cancer Research, Toronto, ON, M5G 0A3, Canada.
Quaid D MorrisVector Institute for Artificial Intelligence, Toronto, ON, M5G 1M1, Canada.ORCID 0000-0002-2760-6999
Thomas KislingerDepartment of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada.
Paul C BoutrosDepartment of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada. pboutros@mednet.ucla.edu.ORCID 0000-0003-0553-7520
Ontario Institute for Cancer Research · CAUniversity Health Network · CAUniversity of Toronto · CAUniversity of California, Los Angeles · US

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Samuel Wheeler French · 1985 to 2026
$134.5M
UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI David A. Nathanson · 2017 to 2026
$25.2M
Advancing method benchmarking and data sharing through crowd-sourced competitions in cancer researchU24CA248265 · NCI · SAGE BIONETWORKS · PI BOUTROS, PAUL CHRISTOPHER, VARMA, SUSHEEL · 2020 to 2024
$4.1M
The Evolution of Sarcoma Drug Sensitivity through Time and SpaceR01CA244729 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BOUTROS, PAUL CHRISTOPHER, SORAGNI, ALICE · 2020 to 2024
$3.4M
Development of Protein Biomarkers in Post-DRE Urine for use in Liquid Biopsy of Prostate CancerU01CA214194 · NCI · EASTERN VIRGINIA MEDICAL SCHOOL · PI BOUTROS, PAUL CHRISTOPHER, KISLINGER, THOMAS · 2016 to 2021
$2.5M
CIHRNCI NIH HHS P30 CA016042NCI NIH HHS P50 CA211015NCI NIH HHS R01 CA244729NCI NIH HHS U01 CA214194NCI NIH HHS U24 CA248265
6 · The paper itself

Abstract

Whole-genome sequencing can be used to estimate subclonal populations in tumours and this intra-tumoural heterogeneity is linked to clinical outcomes. Many algorithms have been developed for subclonal reconstruction, but their variabilities and consistencies are largely unknown. We evaluate sixteen pipelines for reconstructing the evolutionary histories of 293 localized prostate cancers from single samples, and eighteen pipelines for the reconstruction of 10 tumours with multi-region sampling. We show that predictions of subclonal architecture and timing of somatic mutations vary extensively across pipelines. Pipelines show consistent types of biases, with those incorporating SomaticSniper and Battenberg preferentially predicting homogenous cancer cell populations and those using MuTect tending to predict multiple populations of cancer cells. Subclonal reconstructions using multi-region sampling confirm that single-sample reconstructions systematically underestimate intra-tumoural heterogeneity, predicting on average fewer than half of the cancer cell populations identified by multi-region sequencing. Overall, these biases suggest caution in interpreting specific architectures and subclonal variants.

Indexed as

AlgorithmsGenetic HeterogeneityMutationBiomarkers, TumorClonal EvolutionClone CellsComputational BiologyDNA Copy Number VariationsHumansMaleModels, GeneticPolymorphism, Single NucleotideProstatic NeoplasmsWhole Genome SequencingBiomarkers, Tumor

Identifiers

PMID33288765
PMCPMC7721877
OpenAlexW3113128783

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.