Analysis of Nuclear Encoded Mitochondrial Gene Networks in Cervical Cancer

MDMNI-DGD: A novel graph neural network approach for druggable gene discovery based on the integration of multi-omics data and the multi-view network

Accurately predicting druggable genes is of paramount importance for enhancing the efficacy of targeted therapies, reducing drug-related toxicities and improving patients' survival rates. Nevertheless, accurately predicting candidate cancer-druggable genes remains a critical challenge in translational medicine due to the high heterogeneity and complexity of cancer data. In this study, we proposed a novel graph neural approach called Druggable Gene Discovery based on the Integration of Multi-omics Data and the Multi-view Network (MDMNI-DGD), aiming to predict and evaluate cancer-druggable genes. MDMNI-DGD integrated a comprehensive set of multi-omics data, including copy number variations, DNA methylation, somatic mutations, and gene expression profiles. Simultaneously, it constructed the multi-view gene association network based on protein-protein interactions (PPI), protein structural domains, gene co-expression, pathway co-occurrence, gene sequence and gene ontology. Compared to other state-of-the-art approaches, MDMNI-DGD exhibits excellent performance in key evaluation metrics such as AUROC and AUPR. Moreover, the case study has also demonstrated the efficacy of our approach in discovering potentially druggable genes. Among more than 20,000 protein-coding genes, MDMNI-DGD successfully identified 872 potentially druggable genes. The findings from this investigation may serve to bolster the assessment of pan-cancer druggable genes, potentially catalyzing the development of more personalized and efficacious therapeutic interventions.

Cancer pharmacoinformatics: Databases and analytical tools

Cancer is a subject of extensive investigation, and the utilization of omics technology has resulted in the generation of substantial volumes of big data in cancer research. Numerous databases are being developed to manage and organize this data effectively. These databases encompass various domains such as genomics, transcriptomics, proteomics, metabolomics, immunology, and drug discovery. The application of computational tools into various core components of pharmaceutical sciences constitutes "Pharmacoinformatics", an emerging paradigm in rational drug discovery. The three major features of pharmacoinformatics include (i) Structure modelling of putative drugs and targets, (ii) Compilation of databases and analysis using statistical approaches, and (iii) Employing artificial intelligence/machine learning algorithms for the discovery of novel therapeutic molecules. The development, updating, and analysis of databases using statistical approaches play a pivotal role in pharmacoinformatics. Multiple software tools are associated with oncoinformatics research. This review catalogs the databases and computational tools related to cancer drug discovery and highlights their potential implications in the pharmacoinformatics of cancer.

Analysis of miR-497/195 cluster identifies new therapeutic targets in cervical cancer

OBJECTIVE

miR-497/195, located at 17p13.1, is a highly conserved miRNA cluster whose abnormal expression is a key regulator of carcinogenesis. We performed a comprehensive analysis of the miR-497/195 cluster to determine its prognostic utility and role in cervical cancer (CC) using publicly available datasets.

RESULTS

In silico analysis and validation revealed that this cluster is downregulated in CC. A total of 60 target genes of miR-497/195 cluster were identified as differentially expressed between normal and CC samples. ShinyGO, STRING, CytoHubba, Timer 2.0, HPA, and HCMBD were used for functional enrichment, PPIN network construction, hub gene identification, immune infiltration correlation, histopathological expression, and determination of the metastatic potential of miR-497/195 cluster and their target genes. PPIN analysis identified CCNE1, CCNE2, ANLN, RACGAP1, KIF23, CHEK1, CDC25A, E2F7, CDK1, and CEP55 as the top 10 hub genes (HGs). Furthermore, the upregulation of RECK, ATD5, and BCL2, downregulation of OSBPL3, RCAN3, and HIST1H3H effected overall survival of CC patients. We identified 6 targets (TFAP2A, CLSPN, RASEF, HIST1H3H, AKT3, and ITPR1) of miR-497/195 cluster to influence metastasis. In addition, 8 druggable genes and 38 potential drugs were also identified. Our study identified miR-497/195 cluster target genes and pathways that could be used for prognostic and therapeutic applications in CC.

Maternal and fetal mitochondrial gene dysregulation in hypertensive disorders of pregnancy

Mitochondrial dysfunction has been implicated in pregnancy-induced hypertension (PIH). The role of mitochondrial gene dysregulation in PIH, and consequences for maternal-fetal interactions, remain elusive. Here, we investigated mitochondrial gene expression and dysregulation in maternal and placental tissues from pregnancies with and without PIH; further, we measured circulating mitochondrial DNA (mtDNA) mutational load, an index of mtDNA integrity. Differential gene expression analysis followed by Time Course Gene Set Analysis (TcGSA) was conducted on publicly available high throughput sequencing transcriptomic data sets. Mutational load analysis was carried out on peripheral mononuclear blood cells from healthy pregnant individuals and individuals with preeclampsia. Thirty mitochondrial differentially expressed genes (mtDEGs) were detected in the maternal cell-free circulating transcriptome, whereas nine were detected in placental transcriptome from pregnancies with PIH. In PIH pregnancies, maternal mitochondrial dysregulation was associated with pathways involved in inflammation, cell death/survival, and placental development, whereas fetal mitochondrial dysregulation was associated with increased production of extracellular vesicles (EVs) at term. Mothers with preeclampsia did not exhibit a significantly different degree of mtDNA mutational load. Our findings support the involvement of maternal mitochondrial dysregulation in the pathophysiology of PIH and suggest that mitochondria may mediate maternal-fetal interactions during healthy pregnancy.NEW & NOTEWORTHY This study identifies aberrant maternal and fetal expression of mitochondrial genes in pregnancies with gestational hypertension and preeclampsia. Mitochondrial gene dysregulation may be a common etiological factor contributing to the development of de novo hypertension in pregnancy-associated hypertensive disorders.

Double C-2 like domain beta (DOC2B) induces calcium dependent oxidative stress to promote lipotoxicity and mitochondrial dysfunction for its tumor suppressive function

Mitochondria are biosynthetic and bioenergetic organelles that regulate many biological processes, including metabolism, oxidative stress, and cell death. Cervical cancer (CC) cells show impairments in mitochondrial structure and function and are linked with cancer progression. DOC2B is a tumor suppressor with anti-proliferative, anti-migratory, anti-invasive, and anti-metastatic function in CC. For the first time, we demonstrated the role of the DOC2B-mitochondrial axis with tumor growth regulatory functions in CC. We used DOC2B overexpression and knockdown model systems to show that DOC2B is localized to mitochondria and induces Ca²⁺-mediated lipotoxicity. DOC2B expression induced mitochondrial morphological changes with the subsequent reduction in mitochondrial DNA copy number, mitochondrial mass, and mitochondrial membrane potential. Intracellular and mitochondrial Ca²⁺, intracellular O^.-₂, and ATP levels were substantially elevated in the presence of DOC2B. DOC2B manipulation reduced glucose uptake, lactate production, and mitochondrial complex-IV activity. The presence of DOC2B significantly reduced the proteins associated with mitochondrial structure and biogenesis with the concomitant activation of AMPK signaling. Augmented lipid peroxidation (LPO) in the presence of DOC2B was a Ca²⁺-dependent process. Our findings demonstrated that DOC2B promotes lipid accumulation, oxidative stress, and LPO through intracellular Ca²⁺ overload, which may contribute to mitochondrial dysfunction and tumor-suppressive properties of DOC2B. We propose that the DOC2B-Ca²⁺-oxidative stress-LPO-mitochondrial axis could be targeted for confining CC. Further, the induction of lipotoxicity in tumor cells by activating DOC2B could serve as a novel therapeutic approach in CC.

Integrated bioinformatic analysis to understand the association between phthalate exposure and breast cancer progression

Phthalates have been extensively used as plasticizers while manufacturing plastic-based consumer products. Estradiol mimicking properties and association studies suggest phthalates may contribute to breast cancer (BC). We performed an in-silico analysis and functional studies to understand the association between phthalate exposure and BC progression. Search for phthalate-responsive genes using the comparative toxicogenomics database identified 20 genes as commonly altered in response to multiple phthalates exposure. Of the 20 genes, 12 were significantly differentially expressed between normal and BC samples. In BC samples, 9 out of 20 genes showed a negative correlation between promoter methylation and its expression. AHR, BAX, BCL2, CAT, ESR2, IL6, and PTGS2 expression differed significantly between metastatic and non-metastatic BC samples. Gene set enrichment analysis identified metabolism, ATP-binding cassette transporters, insulin signaling, and type II diabetes as highly enriched pathways. The diagnostic assessment based on 20 genes expression suggested a sensitivity and a specificity >0.91. The aberrantly expressed phthalate interactive gene influenced the overall survival of BC patients. Drug-gene interaction analysis identified 14 genes and 523 candidate drugs, including 19 BC treatment-approved drugs. Di(2-ethylhexyl) phthlate (DEHP) exposure increased the growth, proliferation, and migration of MCF-7 and MDA-MB-231 cells in-vitro. DEHP exposure induced morphological changes, actin cytoskeletal remodeling, increased ROS content, reduced basal level lipid peroxidation, and induced epithelial to mesenchymal transition (EMT). The present approach can help to explore the potentially damaging effects of environmental agents on cancer risk and understand the underlined pathways and molecular mechanisms.

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

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.

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

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.

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

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.