Evidence map›Paper›PMID 27015839›Full record

ArticleBMC cancer2016

At least two well-spaced samples are needed to genotype a solid tumor.

Kimberly Siegmund, Darryl Shibata

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2016. 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
1.3field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Evolution of Premalignant Disease.Cold Spring Harbor perspectives in medicine · 2017
    Review
  6. New insights into the earliest stages of colorectal tumorigenesis.Expert review of gastroenterology & hepatology · 2017
    Review
  7. Article
  8. 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

2 authors at 1 institution in 1 country.

Kimberly SiegmundDepartment of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, CA, USA.
Darryl ShibataDepartment of Pathology, University of Southern California Keck School of Medicine, 1441 Eastlake Avenue , NOR2424, Los Angeles, CA, 90033, USA. dshibata@usc.edu.
University of Southern California · US

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
"Born to be Bad": Is Abnormal Cell Mobility Already Present At Initiation?R21CA185016 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SHIBATA, DARRYL K · 2014 to 2015
$394k
NCI NIH HHS P30 CA014089NCI NIH HHS P30CA014089NCI NIH HHS R21 CA185016
6 · The paper itself

Abstract

backgroundHuman cancers are often sequenced to identify mutations. However, cancers are spatially heterogeneous populations with public mutations in all cells and private mutations in some cells. Without empiric knowledge of how mutations are distributed within a solid tumor it is uncertain whether single or multiple samples adequately sample its heterogeneity.

methodsUsing a cohort of 12 human colorectal tumors with well-validated mutations, the abilities to correctly classify public and private mutations were tested (paired t-test) with one sample or two samples obtained from opposite tumor sides.

resultsTwo samples were significantly better than a single sample for correctly identifying public (99% versus 97%) and private mutations (85% versus 46%). Confounding single sample accuracy was that many private mutations appeared "clonal" in individual samples. Two samples detected the most frequent private mutations in 11 of the 12 tumors.

conclusionsTwo spatially-separated samples efficiently distinguish public from private mutations because private mutations common in one specimen are usually less frequent or absent in another sample. The patch-like private mutation topography in most colorectal tumors inherently limits the information in single tumor samples. The correct identification of public and private mutations may aid efforts to target mutations present in all tumor cells.

Indexed as

Genetic HeterogeneityGenotypeColorectal NeoplasmsDNA Copy Number VariationsExomeHigh-Throughput Nucleotide SequencingHumansMutationPolymorphism, Single NucleotideSample SizeColorectal cancerExome sequencingMutation topographyTumor heterogeneity

Identifiers

PMID27015839
PMCPMC4807557
OpenAlexW2309995842

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.