Evidence map›Paper›PMID 20643781›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2010

Lung squamous cell carcinoma mRNA expression subtypes are reproducible, clinically important, and correspond to normal cell types.

Matthew D Wilkerson, Xiaoying Yin, Katherine A Hoadley, Yufeng Liu, Michele C Hayward, Christopher R Cabanski, Kenneth Muldrew, C Ryan Miller, Scott H Randell, Mark A Socinski and 8 more

Abstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
168citing papers in PubMed, 3 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

168 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Integrative genomics analysis identifies candidate drivers at 3q26-29 amplicon in squamous cell carcinoma of the lung.Clinical cancer research : an official journal of the American Association for Cancer Research · 2013
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108 more citing papers are in PubMed but not listed here.

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

18 authors.

Matthew D WilkersonLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 27599, USA.
Xiaoying Yin
Katherine A Hoadley
Yufeng Liu
Michele C Hayward
Christopher R Cabanski
Kenneth Muldrew
C Ryan Miller
Scott H Randell
Mark A Socinski
Alden M Parsons
William K Funkhouser
Carrie B Lee
Patrick J Roberts
Leigh Thorne
Philip S Bernard
Charles M Perou
D Neil Hayes

Funding

UNC-CH CENTER FOR ENVIRONMENTAL HEALTH &SUSCEPTIBILITYP30ES010126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Melissa A. Troester · 2001 to 2026
$36.3M
Multidisciplinary Clinical Research Career Develop(RMI)K12RR023248 · NCRR · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ORRINGER, EUGENE P · 2005 to 2007
$6.3M
Flexible statistical machine learning techniques for cancer-related dataR01CA149569 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIU, YUFENG, WU, YICHAO · 2010 to 2014
$1.5M
Micro RNA Regulation of Human Airway Epithelial PhenotypeRC1HL100108 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HAMMOND, SCOTT M, HAYES, DAVID N · 2009 to 2010
$1000k
Lung squamous cell carcinoma subtypes: genomic abberations and clinical detectionF32CA142039 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WILKERSON, MATTHEW DEVIN · 2009 to 2011
$127k
NCI NIH HHS F32 CA142039NCI NIH HHS F32CA142039NCI NIH HHS R01 CA149569NCRR NIH HHS K12 RR023248NCRR NIH HHS K12-RR023248NHLBI NIH HHS RC1 HL100108NIEHS NIH HHS P30 ES010126
6 · The paper itself

Abstract

purposeLung squamous cell carcinoma (SCC) is clinically and genetically heterogeneous, and current diagnostic practices do not adequately substratify this heterogeneity. A robust, biologically based SCC subclassification may describe this variability and lead to more precise patient prognosis and management. We sought to determine if SCC mRNA expression subtypes exist, are reproducible across multiple patient cohorts, and are clinically relevant. EXPERIMENTAL

designSubtypes were detected by unsupervised consensus clustering in five published discovery cohorts of mRNA microarrays, totaling 382 SCC patients. An independent validation cohort of 56 SCC patients was collected and assayed by microarrays. A nearest-centroid subtype predictor was built using discovery cohorts. Validation cohort subtypes were predicted and evaluated for confirmation. Subtype survival outcome, clinical covariates, and biological processes were compared by statistical and bioinformatic methods.

resultsFour lung SCC mRNA expression subtypes, named primitive, classical, secretory, and basal, were detected and independently validated (P < 0.001). The primitive subtype had the worst survival outcome (P < 0.05) and is an independent predictor of survival (P < 0.05). Tumor differentiation and patient sex were associated with subtype. The expression profiles of the subtypes contained distinct biological processes (primitive: proliferation; classical: xenobiotic metabolism; secretory: immune response; basal: cell adhesion) and suggested distinct pharmacologic interventions. Comparison with lung model systems revealed distinct subtype to cell type correspondence.

conclusionsLung SCC consists of four mRNA expression subtypes that have different survival outcomes, patient populations, and biological processes. The subtypes stratify patients for more precise prognosis and targeted research.

Indexed as

AgedCarcinoma, Squamous CellCohort StudiesFemaleGene Expression Regulation, NeoplasticHumansLung NeoplasmsMaleMiddle AgedOligonucleotide Array Sequence AnalysisReproducibility of ResultsRNA, MessengerSurvival AnalysisTreatment OutcomeRNA, Messenger

Identifiers

PMID20643781
PMCPMC2953768

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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.