Table 2 In silico studies for SARS-CoV-2 or its proteins interaction with various molecular targets linked to oncogenesis
From: Oncogenic potential of SARS-CoV-2—targeting hallmarks of cancer pathways
S.No | GEO Accession | Software Used | Perturbed Biological functions | Molecular Targets, TFs, and miRNAs | Oncogenesis Implication | References |
|---|---|---|---|---|---|---|
1 | GSE157103 GSE75097 | LASSO, Random Forest, Support Vector Machine, Enrichr, STRING, Cytoscape, CytoHubba, MCODE, NetworkAnalyst, DSigDB, CIBERSORT | DNA repair, cell cycle regulation, bladder cancer, Kaposi sarcoma-associated herpesvirus infection, and metabolic pathways | TP53, CCND1, MDM2, RB1, HIF-1A, EP300, STAT3, CDK2, HSP90AA1, and PPARG | The study reveals key molecular pathways and genes, such as TP53, HIF-1A, and STAT3, that are implicated in COVID-19 suggesting a potential link to oncogenesis | [27] |
2 | GSE178331 GSE150392 GSE66360 GSE150392 GSE162736 GSE178246 | R, p-adjust function, DESeq2, GEO2R, clusterProfiler, STRING, Cytoscape, GeneMANIA, TRRUST, NetworkAnalyst, ggplot2 | TNF signaling pathway, IL-17 signaling pathway | IL-1B, CXCL8, CTNNB1, FOS, PTGS2, EGR2, NFKBIA, ZFP36 miR-26b-5p, miR-335-5p, miR-124-3p, let-7b-5p, let-7a-5p, and miR-146a-5p | COVID-19-induced inflammation may exacerbate AMI, influencing cancer-related pathways | [28] |
3 | BioGRID, STRING, SARS2-Human Proteome Interaction Database SHPID | Cytoscape, CentiScaPe | Cytokine signaling, cell cycle regulation, and apoptosis | RPL11, MDM2, TP53, RPS27A, ACTB, FN1, COL2A1, ITGA5, ALDOA, RRM2B, BAG2, and HGS | RPS27A- Involved in cancer progression through regulation of p53 and MDM2 interaction, influencing cellular stress response TP53- Functions as a tumor suppressor by inducing cell cycle arrest and apoptosis, counteracted by MDM2 HIF1alpha- Responds to oxidative stress and is upregulated in cancer and COVID-19 conditions | [29] |
4 | GSE152418 GSE119336 | R LIMMA package, jvenn, Enrichr, STRING, Cytoscape, CytoHubba, NetworkAnalyst | Glyoxylate and dicarboxylate metabolism, fatty acid biosynthesis, metabolism of steroids, bile acid and bile salt metabolism | SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1 | COVID-19 may exacerbate ICC through shared metabolic and immune disruptions, highlighting new therapeutic targets and drug opportunities | [30] |
5 | GSE196822 GSE119794 | DEseq2 R, Enrichr, STRING, Cytoscape, CytoHubba, JASPAR, MiRTarBase, NetworkAnalyst | Central carbon metabolism in cancer, Neutrophil extracellular trap formation, Viral carcino- genesis, and Transcriptional misregulation in cancer | ESPL1, HJURP, MKI67, KIF4A, CDK1, TOP2A, CCNB2, UBE2C, AURKB, TPX2 FOXC1, GATA2, YY1, FOXL1, hsa-miR-16-5p, and has-miR-193b-3p | Shared DEGs between COVID-19 and pancreatic cancer are involved in pathways related to viral genome replication, cancer development, immune system regulation, and cell cycle progression, suggesting a potential link between viral infections and cancer progression | [31] |
6 | GSE147507 GSE150316 | DESeq2, StringTie, STAR, samtools, FastQC, MultiQC, REVIGO, EBSeq, Moomin, IsoformSwitchAnalyzeR, TEtools, TFBSTools, MAFFT, meta-CATS, GREAT, DAVID | PI3K/AKT signaling pathway, Neutrophil and granulocyte activation, IL-1-mediated signaling pathway, Proteolysis, Stress-activated signaling cascades, Amoebiasis pathways, p75NTR-mediated signaling pathways, TrkA receptor signaling pathways, and IFN-α/β signaling pathway | PIK3CA, PIK3CB, PIK3CD, PIK3CG, AKT1, AKT2, AKT3, PTEN, MTOR, CXCL8, IL-1B, IL-6, IL-8, IL-10, IL-17A, IL-18, TNF, NF-κB, IL1R1, IL1R2, IL1RN, MYD88, IRAK4, IRAK1, TRAF6, CTSB, CTSD, CTSL, CTSZ, MMP2, MMP9 MMP14, UCHL1, UCHL3, MAPK1, MAPK3, MAPK8, MAPK9, JNK1, JNK2, JUN, ATF2, ATF4, ACTB, ACTG1, GTPBP2, RHOA, RHOB, RHOC, RAC1, ARPC1B, NTRK1, NTRK2, NTRK3, P75NTR, GRB2, SHC1, SOS1, TRKB, TRKC, PLCG1, IFNA1, IFNA2, IFNA4, IFNB1, IFNAR1, IFNAR2, JAK1, JAK2, STAT1, STAT2, CLTC, DNM2, AP2M1, PIK3R1, PIK3R2, TP53, MYC, KRAS, BRAF, EGFR, CDK4, CDK6, CCND1, RB1, CDK1, CDK2, CCNA2, CCNB1, CCNE1, and E2F1 | This study highlights key genes and pathways central to oncogenesis, including PI3K/AKT signaling which drives uncontrolled cell proliferation and survival. Dysregulation of NF-κB signaling and inflammation-related cytokines IL6, and TNF further promote cancer progression by creating a tumor-supportive microenvironment. Additionally, mutations in tumor suppressors like TP53 and oncogenes such as KRAS contribute to cancer development and resistance to treatment | [32] |
7 | 13 TCGA cancer cohorts | Single-Sample Gene-Set Enrichment Analysis ssGSEA, Gene-Set Enrichment Analysis GSEA, Weighted Gene Co-Expression Network Analysis WGCNA | Cell cycle, mismatch repair, TGF-β, Wnt signaling, VEGF, Notch signaling, T cell receptor signaling, and Jak-STAT signaling | ACE2, PD-L1, EOMES, IRF4, and TBX21 | ACE2 upregulation correlates with reduced cancer progression, decreased cell proliferation, stemness, and EMT, as well as downregulation of oncogenic pathways, suggesting ACE2 may act as a protective factor against cancer progression | [33] |
8 | GSE111016 GSE171110 | R, Enrichr, STRING, Cytoscape, Cytohubba, GeneMANIA, NetworkAnalyst, DisGeNET | Th1 and Th2 cell differentiation, chemical carcinogenesis- receptor activation, hematopoietic cell lineage, Nucleotide metabolism, and renin-angiotensin system | ACE, ALDH1L, CYP1A1, PYGL, KLF5, NNMT, PHGDH, IDO1, EME1, CD52, MYBL2, CDC25A, BCL6, CD3D, and ESM1 | The study suggests that key genes such as ACE, KLF5, IDO1, and CDC25A, which are implicated in the pathological mechanisms of both COVID-19 and sarcopenia, may also contribute to oncogenesis through pathways such as chemical carcinogenesis – receptor activation, cellular senescence, and alterations in the tryptophan metabolic pathways | [34] |