Evidence map›Paper›PMID 21353202›Full record

ArticleThe Annals of thoracic surgery2011

A 10-gene progenitor cell signature predicts poor prognosis in lung adenocarcinoma.

Mark Onaitis, Thomas A D'Amico, Cheryl P Clark, Justin Guinney, David H Harpole, Emma L Rawlins

Abstract read
In one paragraph

Article in The Annals of thoracic surgery, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 28% 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.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 7 citations in OpenAlex.

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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

6 authors at 3 institutions in 2 countries.

Mark OnaitisDepartment of Surgery, Duke University, Durham, North Carolina, USA. mark.onaitis@duke.edu
Thomas A D'Amico
Cheryl P Clark
Justin Guinney
David H Harpole
Emma L Rawlins
Duke University · USFred Hutch Cancer Center · USWellcome/Cancer Research UK Gurdon Institute · GB

Funding

Medical Research Council G0900424Wellcome Trust 092096
6 · The paper itself

Abstract

backgroundOne aspect of the cancer stem cell hypothesis is that patients with tumors that exhibit stem-like phenotypes have poor prognoses. Distal epithelial progenitors from lungs early in development demonstrate both self-renewal and potential to differentiate into all bronchial and alveolar epithelial cell types. By contrast, late progenitors are only able to produce alveolar cells. We sought to create a lung-specific progenitor cell signature for possible prognosis prediction in human lung cancer.

methodsA transgenic mouse was created in which embryonic distal epithelial progenitor cells express green fluorescent protein when tamoxifen is administered. Lung progenitor cells were harvested after tamoxifen injection at either embryonic day 11.5 (E11.5) or 17.5 (E17.5). The RNA extracted from these cells was hybridized to Affymetrix 430.2 mouse chips (Affymetrix, Santa Clara, CA). A genomic signature was created by comparing the cell types using L1 logistic regression and applied to transcriptome datasets of resected patients from our tumor bank and the National Institutes of Health Director's Challenge Consortium.

resultsWhen a 10-gene genomic signature was applied to resected human adenocarcinoma datasets, tumors that were transcriptionally similar to the early progenitors had a significantly worse prognosis than those similar to the late progenitors. Using a Cox model in which age and stage were included, the predicted score from the logistic regression model was an independent predictor of survival.

conclusionsA lung progenitor cell signature predicts poor prognosis in lung adenocarcinoma. Modulation of these genes or their signaling pathways may be effective therapeutic strategies in the future.

Indexed as

AdenocarcinomaAnimalsGene Expression ProfilingHumansLung NeoplasmsMiceNeoplastic Stem CellsPrognosis

Identifiers

PMID21353202
PMCPMC3376444
OpenAlexW2035813402

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.