Evidence map›Paper›PMID 41751534›Full record

ArticleGenes2026

Genetically Shared Signatures Between COVID-19 and Cancer Identified Through In Silico Case-Control Analysis.

Ammar Yasir Ahmed Ahmed, Sevinç Akçay

Abstract read
In one paragraph

Article in Genes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Ammar Yasir Ahmed AhmedCollege of Pharmacy, University of Al Maarif, Al Anbar P.O. Box 55431, Iraq.
Sevinç AkçayDepartment of Molecular Biology and Genetics, Faculty of Science and Arts, Kırşehir Ahi Evran University, Kırşehir 40100, Türkiye.ORCID 0000-0003-2961-3970

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesCancer patients are highly susceptible to infectious diseases due to malignancy- and treatment-induced immunosuppression. The coronavirus disease 2019 (COVID-19) pandemic highlighted this vulnerability, particularly in aggressive tumors such as triple-negative breast cancer (TNBC) and clear cell renal cell carcinoma (ccRCC). However, the molecular mechanisms linking cancer progression with COVID-19 severity remain poorly defined. This study aimed to identify shared molecular signatures between COVID-19 and TNBC, breast cancer, and ccRCC using integrative bioinformatics approaches.

methodsA comprehensive in silico case-control analysis was conducted using publicly available GEO transcriptomic datasets (GSE164805, GSE139038, GSE45498, and GSE105261). Differentially expressed genes (DEGs) were identified by comparing mild and severe COVID-19 cases with each cancer type. Protein-protein interaction (PPI) networks were constructed to identify hub genes, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Regulatory networks involving microRNAs (miRNAs) and transcription factors (TFs) were also examined.

resultsShared hub genes were identified across COVID-19 and cancer datasets, including

conclusionsThis integrative, severity-stratified analysis identifies shared molecular and regulatory features linking severe COVID-19 with aggressive cancers, highlighting persistent immune activation and altered immune communication as common underlying themes without implying causality or clinical outcome effects. These findings provide a systems-level, hypothesis-generating framework for understanding virus-cancer interactions and may inform future biomarker discovery and immune-focused therapeutic strategies in vulnerable cancer populations.

Indexed as

Carcinoma, Renal CellCOVID-19Kidney NeoplasmsTriple Negative Breast NeoplasmsCase-Control StudiesComputational BiologyComputer SimulationFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMicroRNAsProtein Interaction MapsSARS-CoV-2TranscriptomeMicroRNAsbreast cancercancer patientsclear cell renal cell carcinomadifferentially expressed genestriple-negative breast cancer

Identifiers

PMID41751534
PMCPMC12940708

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.