Evidence map›Paper›PMID 37943164›Full record

ArticleMolecular oncology2024

Transcriptional analysis of landmark molecular pathways in lung adenocarcinoma results in a clinically relevant classification with potential therapeutic implications.

Sara Hijazo-Pechero, Ania Alay, David Cordero, Raúl Marín, Noelia Vilariño, Ramón Palmero, Jesús Brenes, Aina Montalban-Casafont, Ernest Nadal, Xavier Solé

Open access · goldAbstract read
In one paragraph

Article in Molecular oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 20% 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.

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

6 citing papers in PubMed, 4 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

10 authors at 3 institutions in 1 country.

Sara Hijazo-PecheroUnit of Bioinformatics for Precision Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, Barcelona, Spain.
Ania AlayUnit of Bioinformatics for Precision Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, Barcelona, Spain.
David CorderoUnit of Bioinformatics for Precision Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, Barcelona, Spain.
Raúl MarínUnit of Bioinformatics for Precision Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, Barcelona, Spain.
Noelia VilariñoPreclinical and Experimental Research in Thoracic Tumors (PrETT), Molecular Mechanisms and Experimental Therapy in Oncology Program (Oncobell), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain.
Ramón PalmeroPreclinical and Experimental Research in Thoracic Tumors (PrETT), Molecular Mechanisms and Experimental Therapy in Oncology Program (Oncobell), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain.
Jesús BrenesThoracic Oncology Unit, Department of Medical Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, Barcelona, Spain.
Aina Montalban-CasafontMolecular Biology CORE, Center for Biomedical Diagnostics (CDB), Hospital Clínic de Barcelona, Spain.
Ernest NadalPreclinical and Experimental Research in Thoracic Tumors (PrETT), Molecular Mechanisms and Experimental Therapy in Oncology Program (Oncobell), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain.ORCID 0000-0002-9674-5554
Xavier SoléTranslational Genomics and Targeted Therapies in Solid Tumors, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain.ORCID 0000-0002-2197-3325
Institut d'Investigació Biomédica de Bellvitge · ESHospital Clínic de Barcelona · ESInstitut Català d'Oncologia · ES

Funding

Agència de Gestió d'Ajuts Universitaris i de Recerca FI_B2 00066European Regional Development FundInstituto de Salud Carlos III CM19/00245Instituto de Salud Carlos III CM21/00073Instituto de Salud Carlos III PI18/00920Instituto de Salud Carlos III PI21/00789Ministerio de Ciencia, Innovación y Universidades FPU19/01734Ministerio de Ciencia, Innovación y Universidades RTI2018-102134-A-I00
6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) is a molecularly heterogeneous disease. In addition to genomic alterations, cancer transcriptional profiling can be helpful to tailor cancer treatment and to estimate each patient's outcome. Transcriptional activity levels of 50 molecular pathways were inferred in 4573 LUAD patients using Gene Set Variation Analysis (GSVA) method. Seven LUAD subtypes were defined and independently validated based on the combined behavior of the studied pathways: AD (adenocarcinoma subtype) 1-7. AD1, AD4, and AD5 subtypes were associated with better overall survival. AD1 and AD4 subtypes were enriched in epidermal growth factor receptor (EGFR) mutations, whereas AD2 and AD6 showed higher tumor protein p53 (TP53) alteration frequencies. AD2 and AD6 subtypes correlated with higher genome instability, proliferation-related pathway expression, and specific sensitivity to chemotherapy, based on data from LUAD cell lines. LUAD subtypes were able to predict immunotherapy response in addition to CD274 (PD-L1) gene expression and tumor mutational burden (TMB). AD2 and AD4 subtypes were associated with potential resistance and response to immunotherapy, respectively. Thus, analysis of transcriptomic data could improve patient stratification beyond genomics and single biomarkers (i.e., PD-L1 and TMB) and may lay the foundation for more personalized treatment avenues, especially in driver-negative LUAD.

Indexed as

AdenocarcinomaAdenocarcinoma of LungLung NeoplasmsB7-H1 AntigenHumansImmunotherapyB7-H1 Antigenimmunotherapylung adenocarcinomamolecular pathwaysprecision oncologytranscriptional subtypes

Identifiers

PMID37943164
PMCPMC10850798
OpenAlexW4388525527

What OpenQuestion holds

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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.