Sign in
Genetic & Genomic MedicineCancers
Peer-reviewed journal article

Functional signatures in non-small-cell lung cancer: a systematic review and meta-analysis of sex-based differences in transcriptomic studies

Irene Pérez-DíeziD, Marta R. HidalgoiD, Pablo Malmierca-MerloiD, Zoraida AndreuiD, Sergio Romera-GineriD, Rosa FarrásiD, María de la Iglesia-VayáiD, Mariano ProvencioiD, Atocha RomeroiD, Francisco Garcia‐GarcíaiD

Abstract

While studies have established the existence of differences in the epidemiological and clinical patterns of lung adenocarcinoma between male and female patients, we know relatively little regarding the molecular mechanisms underlying such sex-based differences. In this study, we explore said differences through a meta-analysis of transcriptomic data. We performed a meta-analysis of the functional profiling of nine public datasets that included 1,366 samples from Gene Expression Omnibus and The Cancer Genome Atlas databases. Meta-analysis results show an enrichment of Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways related to the immune response, nucleic acid metabolism, and purinergic signaling. We discovered the overrepresentation of terms associated with the immune response, particularly with acute inflammatory response, and purinergic signaling in female lung adenocarcinoma patients, which could influence reported clinical differences. Further evaluations of the identified differential biological processes and pathways could lead to the discovery of new biomarkers and therapeutic targets. Our findings also emphasize the relevance of sex-specific analyses in biomedicine, which represents a crucial aspect influencing biological variability in disease. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=171 SRC="FIGDIR/small/20180026v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1f7e9feorg.highwire.dtl.DTLVardef@1235f33org.highwire.dtl.DTLVardef@13f422borg.highwire.dtl.DTLVardef@11378a_HPS_FORMAT_FIGEXP M_FIG C_FIG

02 /Specification & Classification

Click any tag to browse matching papers
Citations
24
FWCI
0.79
Field percentile
top 34%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.