Evidence map›Paper›PMID 26446941›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2016

A Composite Gene Expression Signature Optimizes Prediction of Colorectal Cancer Metastasis and Outcome.

Michael J Schell, Mingli Yang, Edoardo Missiaglia, Mauro Delorenzi, Charlotte Soneson, Binglin Yue, Michael V Nebozhyn, Andrey Loboda, Gregory Bloom, Timothy J Yeatman

Abstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Pan-cancer drivers of metastasis.Molecular cancer · 2025
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  9. Cancers · 2021
    Article
  10. Increased Expression ofJournal of personalized medicine · 2021
    Article
  11. Article
  12. Article
  13. MLH1 Deficiency Induces Cetuximab Resistance in Colon Cancer via Her-2/PI3K/AKT Signaling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020
    Article
  14. Article
  15. Article
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  18. Repurposing EGFR Inhibitor Utility in Colorectal Cancer in MutantCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019
    Article
  19. Article
  20. 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

10 authors.

Michael J SchellMoffitt Cancer Center & Research Institute, Tampa, Florida. Yeatman@gibbscc.org Michael.schell@moffitt.org.
Mingli YangGibbs Cancer Center & Research Institute, Spartanburg, South Carolina.
Edoardo MissiagliaSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Mauro DelorenziSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland. Ludwig Center for Cancer Research, University of Lausanne (CH), Lausanne, Switzerland. Department of Oncology, University of Lausanne (CH), Lausanne, Switzerland.
Charlotte SonesonSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Binglin YueMoffitt Cancer Center & Research Institute, Tampa, Florida.
Michael V NebozhynMerck, Sharp and Dohme, West Point, Pennsylvania.
Andrey LobodaMerck, Sharp and Dohme, West Point, Pennsylvania.
Gregory BloomMoffitt Cancer Center & Research Institute, Tampa, Florida.
Timothy J YeatmanGibbs Cancer Center & Research Institute, Spartanburg, South Carolina. Yeatman@gibbscc.org Michael.schell@moffitt.org.

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI KENNETH Lynn WRIGHT · 1998 to 2026
$93.5M
INDIVIDUALIZING COLON CANCER THERAPY USING HYBRID RNA AND DNA MOLECULAR SIGNATUREU01CA157960 · NCI · SPARTANBURG REGIONAL MEDICAL CENTER · PI YEATMAN, TIMOTHY J · 2012 to 2016
$2.8M
NCI NIH HHS P30 CA076292NCI NIH HHS P30-CA76292NCI NIH HHS U01 CA157960NCI NIH HHS U01CA157960
6 · The paper itself

Abstract

purposeWe previously found that an epithelial-to-mesenchymal transition (EMT)-based gene expression signature was highly correlated with the first principal component (PC1) of 326 colorectal cancer tumors and was prognostic. This study was designed to improve these signatures for better prediction of metastasis and outcome. EXPERIMENTAL

designA total of 468 colorectal cancer tumors including all stages (I-IV) and metastatic lesions were used to develop a new prognostic score (ΔPC1.EMT) by subtracting the EMT signature score from its correlated PC1 signature score. The score was validated on six other independent datasets with a total of 3,697 tumors.

resultsΔPC1.EMT was found to be far more predictive of metastasis and outcome than its parent scores. It performed well in stages I to III, among microsatellite instability subtypes, and across multiple mutation-based subclasses, demonstrating a refined capacity to predict distant metastatic potential even in tumors with a "good" prognosis. For example, in the PETACC-3 clinical trial dataset, it predicted worse overall survival in an adjusted multivariable model for stage III patients (HR standardized by interquartile range [IQR] = 1.50; 95% confidence interval, 1.25-1.81; P = 0.000016, N = 644). The improved performance of ΔPC1.EMT was related to its propensity to identify epithelial-like subpopulations as well as mesenchymal-like subpopulations. Biologically, the signature was correlated positively with RAS signaling but negatively with mitochondrial metabolism. ΔPC1.EMT was a "best of assessed" prognostic score when compared with 10 other known prognostic signatures.

conclusionsThe study developed a prognostic signature score with a propensity to detect non-EMT features, including epithelial cancer stem cell-related properties, thereby improving its potential to predict metastasis and poorer outcome in stage I-III patients.

Indexed as

Gene Expression ProfilingTranscriptomeCluster AnalysisColorectal NeoplasmsEpithelial-Mesenchymal TransitionFemaleGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMaleMicrosatellite InstabilityNeoplasm MetastasisNeoplasm StagingPatient Outcome AssessmentPrognosisProportional Hazards Models

Identifiers

PMID26446941
PMCPMC4802496

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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.