Integrated systems biology approach using gene network analysis to identify the important pathways and new potential drug targets for Neuroblastoma

Computational Analysis of Albaflavenone Interaction with SlMAPK1 for Drought Resistance in Tomato

As global agricultural challenges intensify, particularly drought stress, the exploration of innovative strategies for crop resilience has become crucial. This study focuses on the role of the microbial endophyte metabolite Albaflavenone in enhancing drought resistance in tomato (Solanum lycopersicum L.) through the activation of the SlMAPK1 protein in the MAPK pathway. To computationally analyze the interaction between Albaflavenone and SlMAPK1 and to elucidate the potential enhancement of drought tolerance in tomato plants through this interaction. We utilized molecular docking, homology modeling, and molecular dynamics simulations to investigate the binding affinities and interaction dynamics between SlMAPK1 and Albaflavenone. Functional network analysis was employed to examine protein-protein interactions within the MAPK pathway, while the MM-GBSA method was used to calculate binding free energies. Our computational analyses revealed that Albaflavenone exhibited a high binding affinity to SlMAPK1 with a binding energy of - 8.9 kcal/mol. Molecular dynamics simulations showed this interaction significantly stabilized SlMAPK1, suggesting enhanced activity. Specifically, the root mean square deviation (RMSD) of the Albaflavenone-SlMAPK1 complex stabilized at around 3.1 Å, while the root mean square fluctuations (RMSF) indicated consistent amino acid conformations. Additionally, the radius of gyration (Rg) analysis demonstrated minimal variance, suggesting a compact and stable protein-ligand complex. The significant binding affinity between Albaflavenone and SlMAPK1 highlights the potential of leveraging plant-microbe interactions in developing sustainable agricultural practices. These findings also demonstrate the effectiveness of computational methods in dissecting complex biological interactions, contributing to a deeper understanding of plant resilience strategies against environmental stresses.

Potential Signature Therapeutic Biomarkers TOP2A, MAD2L1, and CDK1 in Colorectal Cancer: A Systems Biomedicine-Based Approach

Colorectal cancer is the third deadliest and fourth most diagnosed cancer. It is heterogeneously driven by varied mutations and mutagens, and thus, it is challenging for targeted therapy. The rapid advancement of high-throughput technology presents considerable opportunities for discovering new colon cancer biomarkers. In the present study, we have explored and identified the biomarkers based on molecular interactions. We curated cancer datasets that were not micro-dissected and performed gene expression analysis. The protein-protein interactions were curated, and a network was constructed for the up-regulated genes. The hub genes were analyzed using 12 different topological parameters. The correlation analysis selected TOP2A, CDK1, CCNB1, AURKA, and MAD2L1 as hub genes. Further, survival analysis was performed to determine the effectiveness of the hub gene on the patient's survival rate. Our findings explore various transcription factors such as E2F4, FOXM1, E2F6, MAX, and SIN3A, along with kinases CSNK2A1, MAPK14, CDK1, CDK4, and CDK2, as potential molecular signatures and aid researchers in understanding the pathophysiological mechanisms underlying CRC development and thus providing novel therapeutic and diagnostic recourse. Furthermore, investigating miRNAs, we focused on hsa-miR-215-5p, hsa-miR-192-5p, and hsa-miR-193b-3p due to their observed impact on a diverse set of colorectal cancer genes. Thereby, the current approach brings into light CRC- related genes at the RNA and protein levels that can potentially act as novel biomarkers opening doors to diagnostic and treatment purposes.

A comprehensive integrated gene network construction to explore the essential role of Notch 1 in lung adenocarcinoma (LUAD)

The heterogeneous biological landscape of non-small cell lung cancer (NSCLC) is largely attributed to the activation of Notch signalling pathway. Among the Notch family transmembrane proteins, neurogenic locus notch homolog protein1 (NOTCH1) is a putative oncogene in NSCLC which activates the pathway as negative prognostic factor. This study aims to explore integrated network approach in lung adenocarcinoma (LUAD) especially linked to the notch pathway and its receptors. Our gene set enrichment analysis reveals the key Notch pathway genes are predominantly down regulated in LUAD. There were 675 genes with a total of 6517 functional interactions and 6 densely connected clusters of 38 miRNAs, 84 transcription factors with 156 edges identified through network construction. Here we report five key genes namely NOTCH1, CDH1, ERBB2, GAPDH and COL1A1 significantly enriched in Notch pathway which are further validated through the KM plot, box plots, stage plots and TIMER analysis. In addition, the NOTCH1 receptor is strongly linked to the immune checkpoint inhibitor CD274 (PD-L1) and can be considered as prognostic marker and tumour suppressor gene in LUAD which surely provide the basis for early diagnosis and futuristic immunotherapeutic targets for LUAD.Communicated by Ramaswamy H. Sarma.

Elucidating the molecular role of MUC5B in progressive lung adenocarcinoma: Prospects for early diagnosis

Gel-forming mucin MUC5B is significantly deregulated in lung adenocarcinoma (LUAD), however, its role in tumor progression is not yet clearly understood. Here, we used an integrated computational-pipeline-initiated with gene expression analysis followed by network, functional-enrichment, O-linked glycosylation analyses, mutational profiling, and immune cell infiltration estimation to functionally characterize MUC5B gene in LUAD. Thereafter, clinical biomarker validation was supported by the overall survival (OA) and comparative expression profiling across clinical stages using computational algorithms. The gene expression profile of LUAD identified MUC5B to be significantly up-regulated (logFC: 2.36; p-value: 0.01). Network analysis on LUAD interactome screened MUC5B-related genes, having key enrichment in immune suppression and O-linked glycosylation with serine-threonine-rich tandem repeats being highly glycosylated. Furthermore, positive correlation of mutant MUC5B with immune cells in tumor microenvironment (TME) such as cancer-associated fibroblasts and myeloid-derived suppressor cells indicates TME-mediated tumor progression. The positive correlation with immune inhibitors suggested the enhanced tumor proliferation mediated by MUC5B. Structural stability due to genetic alterations identified overall rigid N-H-backbone dynamics (S2 : 0.756), indicating an overall stable mutant protein. Moreover, the low median OA (<50 months) with a hazard ratio of 1.4 and clinical profile of MUC5B gene showed high median expression corresponding to lymph node (N2) and tumor (T3) stages. Our study concludes by highlighting the functional role of O-glycosylated and mutant MUC5B in promoting LUAD by immune suppression. Further, clinical gene expression validation of MUC5B suggests its potential role as a diagnostic biomarker for LUAD metastasis.

FN1 and cancer-associated fibroblasts markers influence immune microenvironment in clear cell renal cell carcinoma

BACKGROUND

Altered tumor microenvironment (TME) is characterized in clear cell renal cell carcinoma (ccRCC) as a result of the heterogeneity observed in the TME. Modulations in TME have shown tumor metastasis promotion; hence, identifying TME-based biomarkers can be critical for theranostics application.

METHODS

Here, we performed an integrated systems biology approach utilizing differential gene expression, network metrics and clinical samples cohorts to prioritize the major deregulated genes and their associated pathways specific for metastasis.

RESULTS

The gene expression profiling of 140 ccRCC samples resulted in 3657 differentially expressed genes, from which a network of 1867 up-regulated genes were further computed using network metrics for screening hub-genes. The specific pathways of ccRCC entailed through functional enrichment analysis of the hub-gene clusters indicated the role of the identified hub-genes in the enriched pathways, further validating the functional significance of the hub-genes. The positive correlation of TME cells, namely cancer-associated fibroblasts (CAFs) and its biomarkers (FAP and S100A4) with FN1, signified the role of hub-gene signaling for promoting metastasis in ccRCC. Thereafter, comparative expression, differential methylation, genetic alteration and overall survival analysis were analyzed to validate the screened hub-genes.

CONCLUSIONS

The hub-genes were validated and prioritized by correlating with expression-based parameters, including histological grades, tumor, metastatic and pathological stages (based on median transcript per million; analysis of variance [ANOVA], P ≤ 0.05) from a clinically curated ccRCC dataset to further substantiate the translational benefits of the screened hub-genes as potential diagnostic biomarkers for ccRCC.

An integrative analysis of GEO data to identify possible therapeutic biomarkers of prostate cancer and targeting potential protein through Zea mays phytochemicals by virtual screening approaches

Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are specific to PC and identify drug candidates derived from plants. The information about cancer is critical for clinicians to make decisions about patient treatment in the era of precision medicine. Advances in genomics technology have opened up new possibilities for identifying genes that are associated with cancer, including PC. This study identifies novel differentially expressed genes for PC. The seven PC microarray datasets were selected from the National Center for Biotechnology Information (NCBI)/Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were found based on a fold change of |logFC| ≥ 1 and an adjusted p-value of <0.05. The DEGs were further studied using several bioinformatics tools, including STRING, CytoHubba, SRplot, Coremine Medical database, FunRich and GeneMANIA, cBioPortal. The six new potential biomarkers, GAGE2A, GAGE12G, GAGE2E, GAGE13, GAGE12F and CSAG1 were identified. These biomarkers are associated with biological processes (BPs) such as cell division, and gene expression regulation, so these genes may have a crucial role in PC progression and may serve as potential biomarkers for PC. A total of 497 phytochemicals from corn plants have been screened against the target protein and found LTS0176591 as the best lead molecule with docking score of -6.31 kcal/mol. Further, molecular mechanics-generalized born surface area (MM-GBSA), molecular dynamics simulation, principal component analysis (PCA), free energy landscape (FEL) and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) were carried out to validate the findings.Communicated by Ramaswamy H. Sarma.

Unveiling Potential Targeted Therapeutic Opportunities for Co-Overexpressed Targeting Protein for Xklp2 and Aurora-A Kinase in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most prevalent and leading causes of cancer deaths globally, with limited diagnostic and clinically significant therapeutic targets. Identifying the genes and processes involved in developing and progressing LUAD is crucial for developing effective targeted therapeutics and improving patient outcomes. Therefore, the study aimed to explore the RNA sequencing data of LUAD from The Cancer Genome Atlas (TCGA) and gene expression profile datasets involving GSE10072, GSE31210, and GSE32863 from the Gene Expression Omnibus (GEO) databases. The differential gene expression and the downstream analysis determined clinically significant biomarkers using a network-based approach. These therapeutic targets predominantly enriched the dysregulation of mitotic cell cycle regulation and revealed the co-overexpression of Aurora-A Kinase (AURKA) and Targeting Protein for Xklp2 (TPX2) with high survival risk in LUAD patients. The hydrophobic residues of the AURKA-TPX2 interaction were considered as the target site to block the autophosphorylation of AURKA during the mitotic cell cycle. The tyrosine kinase inhibitor (TKI) dacomitinib demonstrated the strong binding potential to hinder TPX2, shielding the AURKA destabilization. This in silico study lays the foundation for repurposing targeted therapeutic options to impede the Protein-Protein Interactions (PPIs) in LUAD progression and aid in future translational investigations.

Comprehensive analysis on the diagnostic role of circulatory exosome-based miR-92a-3p for osteoblastic metastases in prostate adenocarcinoma

Prostate adenocarcinoma (PRAD) is the second leading cause of death in men and the key factor that attributes to the severity and higher mortality rates is the tumor's ability to promote osteoblastic metastases (OM). Currently, no blood-based biomarkers are present that bridges the crosstalk between PRAD and OM progression. Conversely, circulatory microRNAs (miRNAs) are gaining interest among the scientific community for its potential as blood-based markers for cancer detection. Using computational pipeline, this study screened exosome-based miRNA that is functionally regulating OM in PRAD. We retrieved the expression profile of miRNA, mRNA from PRAD microarray, and RNA-Seq samples deposited in global repositories and identified the differentially expressed miRNAs (DEMs) and differentially expressed genes. Thereafter, the average expression of the miRNAs was identified in extracellular vesicle specifically in exosomes. Survival analysis and clinical profiling identified functionally significant miR-92a-3p to be a key factor in OM. This was further examined by the interactions with various noncoding RNA elements, transcription factors, oncogenes, tumor suppressor genes, and protein kinases regulated by miR-92a-3p. Identifying the expression pattern, nodal metastasis, Gleason score, and hazard ratio deciphered the critical role of the targets regulated by miR-92a-3p. Further, binding association analyzed through energy, seed match and accessibility showed the miRNA-targets involved in cytokine, TGF-β, and Wnt signaling having close regulatory role in promoting OM. Our findings highlight the potent role of miR-92a-3p as blood-based diagnostic biomarker for OM. The comprehensive insights from our study can be elemental in designing diagnostic biomarker for PRAD.

Cancer-biomarkers associated with sex hormone receptors and recent therapeutic advancements: a comprehensive review

Hormones and its regulation plays vital role in causing breast, prostate, ovarian and endometrial cancers collectively known as hormone-sensitive cancers. This review discusses the various functions of the sex hormones and the biological pathways involved in causing hormone-associated cancer under differential regulation. We have also attempted to explore the biomarkers associated with the cancers and the current therapeutic availability to treat such cancers. Among various sex hormones such as estrogen, progesterone and androgen, estrogen the female sex hormone and its receptor had a major contribution in causing cancer and hence are considered a predominant target in treating the associated cancers. Other hormones and receptors such a androgen, progesterone, and their respective receptors were also reported to have a significant correlation in causing cancers. Apart from these receptors certain enzymes that act as precursors or as promoters are also targeted for treatment strategies. The drugs commonly used belong to the selective drug classes such as selective estrogen receptor modulators and selective progesterone receptor modulators. In the case of androgen regulation androgen deprivation therapies are practiced. It is also suggested that the use of natural substances to treat cancer could prevent resistance and reduce side effects. Identification of significant targets and the discovery of many efficient drugs shall be possible in the future with better understanding of hormone regulation and its influence on cancer causative mechanisms.

Translational protein RpsE as an alternative target for novel nucleoside analogues to treat MDR Enterobacter cloacae ATCC 13047: network analysis and molecular dynamics study

The pathogenic Enterobacter cloacae subsp. cloacae str. ATCC 13047 has contemporarily emerged as a multi-drug resistant strain. To formulate an effective treatment option, alternative therapeutic methods need to be explored. The present study focused on Gene Interaction Network study of 46 antimicrobial resistance genes to reveal the densely interconnecting and functional hub genes in E. cloacae ATCC 13047. The AMR genes were subjected to clustering, topological and functional enrichment analysis, revealing rpsE (RpsE), acrA (AcrA) and arnT (ArnT) as novel therapeutic drug targets for hindering drug resistance in the pathogenic strain. Network topology further indicated translational protein RpsE to be exploited as a promising drug-target candidate for which the structure was predicted, optimized and validated through molecular dynamics simulations (MDS). Absorption, distribution, metabolism and excretion screening recognized ZINC5441082 (N-Isopentyladenosine) (Lead_1) and ZINC1319816 (cyclopentyl-aminopurinyl-hydroxymethyl-oxolanediol) (Lead_2) as orally bioavailable compounds against RpsE. Molecular docking and MDS confirmed the binding efficacy and protein-ligand complex stability. Furthermore, binding free energy (G_bind) calculations, principal component and free energy landscape analyses affirmed the predicted nucleoside analogues against RpsE protein to be comprehensively examined as a potential treatment strategy against E. cloacae ATCC 13047.

A critical review of datasets and computational suites for improving cancer theranostics and biomarker discovery

Cancer has been constantly evolving and so is the research pertaining to cancer diagnosis and therapeutic regimens. Early detection and specific therapeutics are the key features of modern cancer therapy. These requirements can only be fulfilled with the integration of diverse high-throughput technologies. Integration of advanced omics methodology involving genomics, epigenomics, proteomics, and transcriptomics provide a clear understanding of multi-faceted cancer. In the past few years, tremendous high-throughput data have been generated from cancer genomics and epigenomic analyses, which on further methodological analyses can yield better biological insights. The major epigenetic alterations reported in cancer are DNA methylation levels, histone post-translational modifications, and epi-miRNA regulating the oncogenes and tumor suppressor genes. While the genomic analyses like gene expression profiling, cancer gene prediction, and genome annotation divulge the genetic alterations in oncogenes or tumor suppressor genes. Also, systems biology approach using biological networks is being extensively used to identify novel cancer biomarkers. Therefore, integration of these multi-dimensional approaches will help to identify potential diagnostic and therapeutic biomarkers. Here, we reviewed the critical databases and tools dedicated to various epigenomic and genomic alterations in cancer. The review further focuses on the multi-omics resources available for further validating the identified cancer biomarkers. We also highlighted the tools for cancer biomarker discovery using a systems biology approach utilizing genomic and epigenomic data. Biomarkers predicted using such integrative approaches are shown to be more clinically relevant.

FN1 encoding fibronectin as a pivotal signaling gene for therapeutic intervention against pancreatic cancer

The delayed diagnosis of pancreatic cancer has resulted in rising mortality rate and low survival rate that can be circumvented using potent theranostics biomarkers. The treatment gets complicated with delayed detection resulting in lowered 5-year relative survival rate. In our present study, we employed systems biology approach to identify central genes that play crucial roles in tumor progression. Pancreatic cancer genes collected from various databases were used to construct a statistically significant interactome with 812 genes that was further analysed thoroughly using topological parameters and functional enrichment analysis. The significant genes in the network were then identified based on the maximum degree parameter. The overall survival analysis indicated through hazard ratio [HR] and gene expression [log Fold Change] across pancreatic adenocarcinoma revealed the critical role of FN1 [HR 1.4; log2(FC) 5.748], FGA [HR 0.78; log2(FC) 1.639] FGG [HR 0.9; log2(FC) 1.597], C3 [HR 1.1; log2(FC) 2.637], and QSOX1 [HR 1.4; log2(FC) 2.371]. The functional significance of the identified hub genes signified the enrichment of integrin cell surface interactions and proteoglycan syndecan-mediated cell signaling. The differential expression, low overall survival and functional significance of FN1 gene implied its possible role in controlling metastasis in pancreatic cancer. Furthermore, alternate splice variants of FN1 gene showed 10 protein coding transcripts with conserved cell attachment site and functional domains indicating the variants' potential role in pancreatic cancer. The strong association of the identified hub-genes can be better directed to design potential theranostics biomarkers for metastasized pancreatic tumor.

Organ-specific host differential gene expression analysis in systemic candidiasis: A systems biology approach

Patients admitted to the hospital with coronavirus disease (COVID-19) are at risk for acquiring mycotic infections in particular Candidemia. Candida albicans (C. albicans) constitutes an important component of the human mycobiome and the most common cause of invasive fungal infections. Invasive yeast infections are gaining interest among the scientific community as a consequence of complications associated with severe COVID-19 infections. Early identification and surveillance for Candida infections is critical for decreasing the COVID-19 mortality. Our current study attempted to understand the molecular-level interactions between the human genes in different organs during systematic candidiasis. Our research findings have shed light on the molecular events that occur during Candidiasis in organs such as the kidney, liver, and spleen. The differentially expressed genes (up and down-regulated) in each organ will aid in designing organ-specific therapeutic protocols for systemic candidiasis. We observed organ-specific immune responses such as the development of the acute phase response in the liver; TGF-pathway and genes involved in lymphocyte activation, and leukocyte proliferation in the kidney. We have also observed that in the kidney, filament production, up-regulation of iron acquisition mechanisms, and metabolic adaptability are aided by the late initiation of innate defense mechanisms, which is likely related to the low number of resident immune cells and the sluggish recruitment of new effector cells. Our findings point to major pathways that play essential roles in specific organs during systemic candidiasis. The hub genes discovered in the study can be used to develop novel drugs for clinical management of Candidiasis.

A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements

In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.

Network topology analysis of essential genes interactome of Helicobacter pylori to explore novel therapeutic targets

The Helicobacter pylori chronic colonization produces a wide range of gastric diseases in the gastric mucosa by abetting inflammation. Amidst coevolution and reorganization of its metabolism with humans, it has become difficult still imperative to understand and prevent its growth. This study focus to explore functional insights into identification of hub proteins/genes by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We have constructed a PPI network of 123 essential genes along with 1213 interactions in H. pylori 26695. The degree and other centrality measures analysis assist in identifying the important hub nodes, which are top-ranked proteins. A total of nine proteins (recA, guaA, dnaK, rpsB, rplQ, rpmA, rpmC, rpmF, and rpsE) were obtained with high degree (k), betweenness centrality (BC) value. Gene ontology analysis reveals 8, 5 and 3 GO terms correspond to biological processes, cellular components and molecular function respectively. Gene complexes of hypothetical proteins (HPs) were related to aminoacyl-tRNA biosynthesis, biosynthesis of secondary metabolites, bacterial secretion system and protein export. The MCODE analysis revealed that protein from module M1, M3 and M6 include the proteins which have highest degree and BC values. It is noteworthy to mention that the bifunctional GMP synthase/glutamine amidotransferase protein (guaA), molecular chaperon (dnaK), recombinase A (recA) constitute as hub proteins. As a result, these genes are considered as network hub nodes that might be used as therapeutic targets. Our analysis affords a detailed understanding of the molecular process and pathways regulated by the essential genes in H. pylori 26695.