Evidence map›Paper›PMID 34638221›Full record

ReviewCancers2021

Gene Expression Profiling as a Potential Tool for Precision Oncology in Non-Small Cell Lung Cancer.

Sara Hijazo-Pechero, Ania Alay, Raúl Marín, Noelia Vilariño, Cristina Muñoz-Pinedo, Alberto Villanueva, David Santamaría, Ernest Nadal, Xavier Solé

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.1field-weighted citation impact, top 7% 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

19 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. [Research Progress of TNMB Staging in Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025
    Review
  3. Self-Normalizing Multi-Omics Neural Network for Pan-Cancer Prognostication.International journal of molecular sciences · 2025
    Article
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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

9 authors at 3 institutions in 2 countries.

Sara Hijazo-PecheroUnit of Bioinformatics for Precision Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, 08908 Barcelona, Spain.
Ania AlayUnit of Bioinformatics for Precision Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, 08908 Barcelona, Spain.
Raúl MarínUnit of Bioinformatics for Precision Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, 08908 Barcelona, Spain.ORCID 0000-0003-4877-4032
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, 08908 Barcelona, Spain.
Cristina Muñoz-PinedoPreclinical 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, 08908 Barcelona, Spain.ORCID 0000-0002-9120-664X
Alberto VillanuevaProgram Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908 Barcelona, Spain.
David SantamaríaINSERM U1218, ACTION Laboratory, Institut Européen de Chimie et Biologie (IECB), Université de Bordeaux, F-33607 Pessac, France.
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, 08908 Barcelona, Spain.ORCID 0000-0002-9674-5554
Xavier SoléUnit of Bioinformatics for Precision Oncology, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, 08908 Barcelona, Spain.
Institut d'Investigació Biomédica de Bellvitge · ESBellvitge University Hospital · ESUniversité de Bordeaux · FR

Funding

Agència de Gestió d'Ajuts Universitaris i de Recerca 2021 FI_B1 00218Ministerio de Ciencia, Innovación y Universidades FPU19/01734Ministerio de Ciencia, Innovación y Universidades RTI2018-102134-A-I00
6 · The paper itself

Abstract

Recent technological advances and the application of high-throughput mutation and transcriptome analyses have improved our understanding of cancer diseases, including non-small cell lung cancer. For instance, genomic profiling has allowed the identification of mutational events which can be treated with specific agents. However, detection of DNA alterations does not fully recapitulate the complexity of the disease and it does not allow selection of patients that benefit from chemo- or immunotherapy. In this context, transcriptional profiling has emerged as a promising tool for patient stratification and treatment guidance. For instance, transcriptional profiling has proven to be especially useful in the context of acquired resistance to targeted therapies and patients lacking targetable genomic alterations. Moreover, the comprehensive characterization of the expression level of the different pathways and genes involved in tumor progression is likely to better predict clinical benefit from different treatments than single biomarkers such as PD-L1 or tumor mutational burden in the case of immunotherapy. However, intrinsic technical and analytical limitations have hindered the use of these expression signatures in the clinical setting. In this review, we will focus on the data reported on molecular classification of non-small cell lung cancer and discuss the potential of transcriptional profiling as a predictor of survival and as a patient stratification tool to further personalize treatments.

Indexed as

gene expression profilingimmunotherapynon-small cell lung cancerprognosistargeted therapytranscriptional subtypes

Identifiers

PMID34638221
PMCPMC8507534
OpenAlexW3200805784

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.