Evidence map›Paper›PMID 32005111›Full record

ArticleBMC cancer2020

Simplified molecular classification of lung adenocarcinomas based on EGFR, KRAS, and TP53 mutations.

Roberto Ruiz-Cordero, Junsheng Ma, Abha Khanna, Genevieve Lyons, Waree Rinsurongkawong, Roland Bassett, Ming Guo, Mark J Routbort, Jianjun Zhang, Ferdinandos Skoulidis and 7 more

Abstract read
In one paragraph

Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  8. Aryl Hydrocarbon Receptor (AHR) Suppresses Arsenic (AsInternational journal of biological sciences · 2025
    Article
  9. Journal of clinical medicine · 2024
    Article
  10. Review
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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

17 authors.

Roberto Ruiz-CorderoDepartment of Pathology, University of California San Francisco, 1825 4th Street, Room L2181A, San Francisco, CA, 94158, USA. Roberto.Ruiz-Cordero@ucsf.edu.ORCID http://orcid.org/0000-0002-9747-6069
Junsheng MaDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Abha KhannaDepartment of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Genevieve LyonsDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Waree RinsurongkawongDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Roland BassettDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Ming GuoDepartment of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Mark J RoutbortDepartment of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jianjun ZhangDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Ferdinandos SkoulidisDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
John HeymachDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Emily B RoartyDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Zhenya TangDepartment of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
L Jeffrey MedeirosDepartment of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Keyur P PatelDepartment of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Rajyalakshmi LuthraDepartment of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Sinchita Roy-ChowdhuriDepartment of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672NCI NIH HHS P30CA016672
6 · The paper itself

Abstract

backgroundGene expression profiling has consistently identified three molecular subtypes of lung adenocarcinoma that have prognostic implications. To facilitate stratification of patients with this disease into similar molecular subtypes, we developed and validated a simple, mutually exclusive classification.

methodsMutational status of EGFR, KRAS, and TP53 was used to define seven mutually exclusive molecular subtypes. A development cohort of 283 cytology specimens of lung adenocarcinoma was used to evaluate the associations between the proposed classification and clinicopathologic variables including demographic characteristics, smoking history, fluorescence in situ hybridization and molecular results. For validation and prognostic assessment, 63 of the 283 cytology specimens with available survival data were combined with a separate cohort of 428 surgical pathology specimens of lung adenocarcinoma.

resultsThe proposed classification yielded significant associations between these molecular subtypes and clinical and prognostic features. We found better overall survival in patients who underwent surgery and had tumors enriched for EGFR mutations. Worse overall survival was associated with older age, stage IV disease, and tumors with co-mutations in KRAS and TP53. Interestingly, neither chemotherapy nor radiation therapy showed benefit to overall survival.

conclusionsThe mutational status of EGFR, KRAS, and TP53 can be used to easily classify lung adenocarcinoma patients into seven subtypes that show a relationship with prognosis, especially in patients who underwent surgery, and these subtypes are similar to classifications based on more complex genomic methods reported previously.

Indexed as

Adenocarcinoma of LungAdultAgedAged, 80 and overAge FactorsErbB ReceptorsFemaleGenetic Association StudiesHigh-Throughput Nucleotide SequencingHumansLung NeoplasmsMaleMiddle AgedMutationPrecision MedicinePrognosisEGFR protein, humanErbB ReceptorsKRAS protein, humanProto-Oncogene Proteins p21(ras)TP53 protein, humanTumor Suppressor Protein p53Lung adenocarcinomaMolecular subtypesNext generation sequencing

Identifiers

PMID32005111
PMCPMC6995064

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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.