Evidence map›Paper›PMID 26837275›Full record

ArticleScientific reports2016

Transcriptional Profiles from Paired Normal Samples Offer Complementary Information on Cancer Patient Survival--Evidence from TCGA Pan-Cancer Data.

Xiu Huang, David F Stern, Hongyu Zhao

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 1 pooled it
–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

57 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Evolutionary Transcriptomics of Cancer Development.International journal of molecular sciences · 2025
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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

3 authors.

Xiu HuangProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
David F SternDepartment of Pathology, School of Medicine, Yale University, New Haven, CT 06520, USA.
Hongyu ZhaoProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale Pathology Tissue Services Shared ResourceP30CA016359 · NCI · YALE UNIVERSITY · PI DAVID L RIMM · 1985 to 2026
$85.0M
Clinical Study of PHY906, a Novel Chinese Herbal Medicine, as a Modulator of IrinP01CA154295 · NCI · YALE UNIVERSITY · PI CHENG, YUNG-CHI · 2011 to 2016
$6.4M
STATISTICAL METHODS TO MAP GENES FOR COMPLEX TRAITSR01GM059507 · NIGMS · YALE UNIVERSITY · PI ZHAO, HONGYU · 1999 to 2013
$3.6M
NCATS NIH HHS UL1 TR001863NCI NIH HHS CA154295NCI NIH HHS P01 CA154295NCI NIH HHS P30 CA016359NIGMS NIH HHS GM059507NIGMS NIH HHS R01 GM059507
6 · The paper itself

Abstract

Although normal tissue samples adjacent to tumors are sometimes collected from patients in cancer studies, they are often used as normal controls to identify genes differentially expressed between tumor and normal samples. However, it is in general more difficult to obtain and clearly define paired normal samples, and whether these samples should be treated as "normal" due to their close proximity to tumors. In this article, by analyzing the accrued data in The Cancer Genome Atlas (TCGA), we show the surprising results that the paired normal samples are in general more informative on patient survival than tumors. Different lines of evidence suggest that this is likely due to tumor micro-environment instead of tumor cell contamination or field cancerization effect. Pathway analyses suggest that tumor micro-environment may play an important role in cancer patient survival either by boosting the adjacent metabolism or the in situ immunization. Our results suggest the potential benefit of collecting and profiling matched normal tissues to gain more insights on disease etiology and patient progression.

Indexed as

Gene Regulatory NetworksTranscriptomeDatabases, GeneticDisease ProgressionGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNeoplasmsSurvival AnalysisTumor Microenvironment

Identifiers

PMID26837275
PMCPMC4738355

What OpenQuestion holds

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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.