Evidence map›Paper›PMID 26568296›Full record

ArticleLaboratory investigation; a journal of technical methods and pathology2016

Intra-tumor genetic heterogeneity in rectal cancer.

Karin M Hardiman, Peter J Ulintz, Rork D Kuick, Daniel H Hovelson, Christopher M Gates, Ashwini Bhasi, Ana Rodrigues Grant, Jianhua Liu, Andi K Cani, Joel K Greenson and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Laboratory investigation; a journal of technical methods and pathology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
7.8field-weighted citation impact, top 2% 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

51 citing papers in PubMed, 66 citations in OpenAlex.

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  14. Evolution of Lung Cancer in the Context of Immunotherapy.Clinical Medicine Insights. Oncology · 2020
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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

12 authors at 1 institution in 1 country.

Karin M HardimanDepartment of Surgery, University of Michigan, Ann Arbor, MI, USA.
Peter J UlintzDepartment of Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Rork D KuickDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Daniel H HovelsonDepartment of Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Christopher M GatesDepartment of Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Ashwini BhasiDepartment of Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Ana Rodrigues GrantDepartment of Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Jianhua LiuDepartment of Surgery, University of Michigan, Ann Arbor, MI, USA.
Andi K CaniDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
Joel K GreensonDepartment of Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Scott A TomlinsDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
Eric R FearonDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
University of Michigan · US

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI THEODORE S LAWRENCE · 1988 to 2026
$178.2M
Translational Research in GI CancerP50CA130810 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BRENNER, DEAN E. · 2010 to 2016
$11.8M
NCI NIH HHS 5P50CA130810NCI NIH HHS P30 CA046592NCI NIH HHS P50 CA130810PHS HHS 5P30A046592
6 · The paper itself

Abstract

Colorectal cancer arises in part from the cumulative effects of multiple gene lesions. Recent studies in selected cancer types have revealed significant intra-tumor genetic heterogeneity and highlighted its potential role in disease progression and resistance to therapy. We hypothesized the existence of significant intra-tumor genetic heterogeneity in rectal cancers involving variations in localized somatic mutations and copy number abnormalities. Two or three spatially disparate regions from each of six rectal tumors were dissected and subjected to the next-generation whole-exome DNA sequencing, Oncoscan SNP arrays, and targeted confirmatory sequencing and analysis. The resulting data were integrated to define subclones using SciClone. Mutant-allele tumor heterogeneity (MATH) scores, mutant allele frequency correlation, and mutation percent concordance were calculated, and copy number analysis including measurement of correlation between samples was performed. Somatic mutations profiles in individual cancers were similar to prior studies, with some variants found in previously reported significantly mutated genes and many patient-specific mutations in each tumor. Significant intra-tumor heterogeneity was identified in the spatially disparate regions of individual cancers. All tumors had some heterogeneity but the degree of heterogeneity was quite variable in the samples studied. We found that 67-97% of exonic somatic mutations were shared among all regions of an individual's tumor. The SciClone computational method identified 2-8 shared and unshared subclones in the spatially disparate areas in each tumor. MATH scores ranged from 7 to 41. Allele frequency correlation scores ranged from R(2)=0.69-0.96. Measurements of correlation between samples for copy number changes varied from R(2)=0.74-0.93. All tumors had some heterogeneity, but the degree was highly variable in the samples studied. The occurrence of significant intra-tumor heterogeneity may allow selected tumors to have a genetic reservoir to draw from in their evolutionary response to therapy and other challenges.

Indexed as

Genetic HeterogeneityAgedComputational BiologyFemaleGene DosageGene FrequencyHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedMutationOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideRectal NeoplasmsRectum

Identifiers

PMID26568296
PMCPMC4695247
OpenAlexW2406334358

What OpenQuestion holds

Textmetadata
LicenceTDM
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.