Analysis of Nuclear Encoded Mitochondrial Gene Networks in Cervical Cancer

Meneur, Cecile; Eswaran, Sangavi; Adiga, Divya; Sriharikrishnaa, S.; G, Nadeem Khan; Mallya, Sandeep; Chakrabarty, Sanjiban; Kabekkodu, Shama Prasada

doi:10.31557/apjcp.2021.22.6.1799

Cited by 13 publications

(5 citation statements)

References 51 publications

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“…9 a). The suggested drugs of our study also reported by the other researchers such as Docetaxel [ 70 , 91 ], Temsirolimus [ 72 , 74 , 88 , 89 ], Paclitaxel [ 14 , 70 , 73 , 80 , 82 , 87 , 89 , 91 ], Vincristine [ 14 , 70 , 91 ], Everolimus [ 89 ], Vinorelbine [ 14 , 73 , 91 ], cabazitaxel [ 90 ], Lapatinib [ 74 , 86 , 88 , 89 ], Irinotecan [ 73 , 91 ], Imatinib[ 88 – 90 ] for the treatment of CC infections (see Fig. 9 b).…”

Section: Discussionsupporting

confidence: 87%

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Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

et al. 2022

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Cervical cancer (CC) is considered as the fourth most common women cancer globally.that shows malignant features of local infiltration and invasion into adjacent organs and tissues. There are several individual studies in the literature that explored CC-causing hub-genes (HubGs), however, we observed that their results are not so consistent. Therefore, the main objective of this study was to explore hub of the HubGs (hHubGs) that might be more representative CC-causing HubGs compare to the single study based HubGs. We reviewed 52 published articles and found 255 HubGs/studied-genes in total. Among them, we selected 10 HubGs (CDK1, CDK2, CHEK1, MKI67, TOP2A, BRCA1, PLK1, CCNA2, CCNB1, TYMS) as the hHubGs by the protein–protein interaction (PPI) network analysis. Then, we validated their differential expression patterns between CC and control samples through the GPEA database. The enrichment analysis of HubGs revealed some crucial CC-causing biological processes (BPs), molecular functions (MFs) and cellular components (CCs) by involving hHubGs. The gene regulatory network (GRN) analysis identified four TFs proteins and three miRNAs as the key transcriptional and post-transcriptional regulators of hHubGs. Then, we identified hHubGs-guided top-ranked FDA-approved 10 candidate drugs and validated them against the state-of-the-arts independent receptors by molecular docking analysis. Finally, we investigated the binding stability of the top-ranked three candidate drugs (Docetaxel, Temsirolimus, Paclitaxel) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore the finding of this study might be the useful resources for CC diagnosis and therapies.

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Section: Discussionsupporting

confidence: 87%

“…Several research groups already suggested transcriptome-guided different sets of repurposable drugs for the treatment against CC [ 23 , 24 , 69 , 70 , 72 – 91 ]. We collected host transcriptome-guided 80 meta-drug agents by the literature review of CC disease [see Table S2] for exploring candidate drugs.…”

Section: Methodsmentioning

confidence: 99%

Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

et al. 2022

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“…Then, we selected top-ranked three drugs as the candidate drugs, where the first three drugs showed strong binding affinities with all target proteins ( Figure 6 ), where red * denoted published and proposed receptors, and blue ** denoted published receptors. Some other independent studies also recommended our suggested drugs, including Vincristine [ 56 , 57 ], Vinorelbine [ 57 , 58 ], and Paclitaxel [ 56 , 57 , 58 , 59 , 60 ], for the treatment against CC. Finally, we examined the stability of top-ranked three drugs (Vincristine, Vinorelbine, Paclitaxel) by using 100 ns MD-based MM-PBSA simulations for three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance according to the laws of physics [ 61 , 62 ].…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer

Reza

Harun-Or-Roshid

Islam

et al. 2022

IJMS

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Bioinformatics analysis has been playing a vital role in identifying potential genomic biomarkers more accurately from an enormous number of candidates by reducing time and cost compared to the wet-lab-based experimental procedures for disease diagnosis, prognosis, and therapies. Cervical cancer (CC) is one of the most malignant diseases seen in women worldwide. This study aimed at identifying potential key genes (KGs), highlighting their functions, signaling pathways, and candidate drugs for CC diagnosis and targeting therapies. Four publicly available microarray datasets of CC were analyzed for identifying differentially expressed genes (DEGs) by the LIMMA approach through GEO2R online tool. We identified 116 common DEGs (cDEGs) that were utilized to identify seven KGs (AURKA, BRCA1, CCNB1, CDK1, MCM2, NCAPG2, and TOP2A) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of KGs revealed some important functions and signaling pathways that were significantly associated with CC infections. The interaction network analysis identified four TFs proteins and two miRNAs as the key transcriptional and post-transcriptional regulators of KGs. Considering seven KGs-based proteins, four key TFs proteins, and already published top-ranked seven KGs-based proteins (where five KGs were common with our proposed seven KGs) as drug target receptors, we performed their docking analysis with the 80 meta-drug agents that were already published by different reputed journals as CC drugs. We found Paclitaxel, Vinorelbine, Vincristine, Docetaxel, Everolimus, Temsirolimus, and Cabazitaxel as the top-ranked seven candidate drugs. Finally, we investigated the binding stability of the top-ranked three drugs (Paclitaxel, Vincristine, Vinorelbine) by using 100 ns MD-based MM-PBSA simulations with the three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance. Therefore, the proposed drugs might play a vital role in the treatment against CC.

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“…TACCO provides information about DEGs in 26 different cancer types from the TCGA datasets. TACCO can be used for pathway analysis and prognostic model construction using input gene lists 25 , 110 . We identified the DEHGs between tumor and normal tissue samples in the TCGA-HNSCC data set, using the "select DEGs" option with a parameter cutoff p -value ≤ 0.05 and expression of log2 fold change > + 2 and < − 2, calculated using EBSeq, Wilcoxon rank-sum test and multiple test correction 25 .…”

Section: Methodsmentioning

confidence: 99%

Integrated computational analysis reveals HOX genes cluster as oncogenic drivers in head and neck squamous cell carcinoma

Shenoy

Morgan

Hunter

et al. 2022

Sci Rep

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Alterations in homeobox (HOX) gene expression are involved in the progression of several cancer types including head and neck squamous cell carcinoma (HNSCC). However, regulation of the entire HOX cluster in the pathophysiology of HNSCC is still elusive. By using different comprehensive databases, we have identified the significance of differentially expressed HOX genes (DEHGs) in stage stratification and HPV status in the cancer genome atlas (TCGA)-HNSCC datasets. The genetic and epigenetic alterations, druggable genes, their associated functional pathways and their possible association with cancer hallmarks were identified. We have performed extensive analysis to identify the target genes of DEHGs driving HNSCC. The differentially expressed HOX cluster-embedded microRNAs (DEHMs) in HNSCC and their association with HOX-target genes were evaluated to construct a regulatory network of the HOX cluster in HNSCC. Our analysis identified sixteen DEHGs in HNSCC and determined their importance in stage stratification and HPV infection. We found a total of 55 HNSCC driver genes that were identified as targets of DEHGs. The involvement of DEHGs and their targets in cancer-associated signaling mechanisms have confirmed their role in pathophysiology. Further, we found that their oncogenic nature could be targeted by using the novel and approved anti-neoplastic drugs in HNSCC. Construction of the regulatory network depicted the interaction between DEHGs, DEHMs and their targets genes in HNSCC. Hence, aberrantly expressed HOX cluster genes function in a coordinated manner to drive HNSCC. It could provide a broad perspective to carry out the experimental investigation, to understand the underlying oncogenic mechanism and allow the discovery of new clinical biomarkers for HNSCC.

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Analysis of Nuclear Encoded Mitochondrial Gene Networks in Cervical Cancer

Cited by 13 publications

References 51 publications

Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer

Integrated computational analysis reveals HOX genes cluster as oncogenic drivers in head and neck squamous cell carcinoma

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