NFX1-123: A potential therapeutic target in cervical cancer.

NFX1-123 is a splice variant isoform of the NFX1 gene. It is highly expressed in cervical cancers caused by HPV, and NFX1-123 is a protein partner with the HPV oncoprotein E6. Together, NFX1-123 and E6 affect cellular growth, longevity, and differentiation. The expression status of NFX1-123 in cancers beyond cervical and head and neck cancers, and its potential as therapeutic target, have not been investigated. TSVdb of TCGA was used to quantify NFX1-123 expression in 24 cancers compared with normal tissues. The NFX1-123 protein structure was predicted and then submitted to retrieve suitable drug molecules. The top four compounds, found to bind in silico to NFX1-123, were tested experimentally to determine their effects on NFX1-123-related cellular growth, survival, and migration. 46% of cancers (11 of 24 had significant differences in NFX1-123 expression, with nine having had greater NFX1-123 expression, when compared with adjacent normal tissues. Bioinformatics and proteomic predictive analysis modeled the three-dimensional structure of NFX1-123, and drug libraries were screened for high-binding affinity compounds using this modeled structure. Seventeen drugs with binding energies ranging from -1.3 to -10 Kcal/mol were identified. The top four compounds were used to treat HPV- and HPV+ cervical cancer cell lines, three of which (Ropitoin, R428 and Ketoconazole) reduced NFX1-123 protein levels, inhibited cellular growth, survival, and migration, and enhanced the cytotoxicity of Cisplatin. These findings highlight cancers expressing high levels of NFX1-123, and drugs that target it, may reduce cellular growth, survival, and migration, making NFX1-123 a potential novel therapeutic target.

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.

Gene interaction network studies to decipher the multi-drug resistance mechanism in Salmonella enterica serovar Typhi CT18 reveal potential drug targets.

Salmonella enterica subsp. enterica serovar Typhi, a human enteric pathogen causing typhoid fever, developed resistance to multiple antibiotics over the years. The current study was dedicated to understand the multi-drug resistance (MDR) mechanism of S. enterica serovar Typhi CT18 and to identify potential drug targets that could be exploited for new drug discovery. We have employed gene interaction network analysis for 44 genes which had 275 interactions. Clustering analysis resulted in three highly interconnecting clusters (C1-C3). Functional enrichment analysis revealed the presence of drug target alteration and three different multi-drug efflux pumps in the bacteria that were associated with antibiotic resistance. We found seven genes (arnA,B,C,D,E,F,T) conferring resistance to Cationic Anti-Microbial Polypeptide (CAMP) molecules by membrane Lipopolysaccharide (LPS) modification, while macB was observed to be an essential controlling hub of the network and played a crucial role in MacAB-TolC efflux pump. Further, we identified five genes (mdtH, mdtM, mdtG, emrD and mdfA) which were involved in Major Facilitator Superfamily (MFS) efflux system and acrAB contributed towards AcrAB-TolC efflux pump. All three efflux pumps were seen to be highly dependent on tolC gene. The five genes, namely tolC, macB, acrA, acrB and mdfA which were involved in multiple resistance pathways, can act as potential drug targets for successful treatment strategies. Therefore, this study has provided profound insights into the MDR mechanism in S. Typhi CT18. Our results will be useful for experimental biologists to explore new leads for S. enterica.

System-wide coordinates of higher order functions in host-pathogen environment upon Mycobacterium tuberculosis infection.

Molecular signatures and their interactions behind the successful establishment of infection of Mycobacterium tuberculosis (Mtb) inside macrophage are largely unknown. In this work, we present an inter-system scale atlas of the gene expression signatures, their interactions and higher order gene functions of macrophage-Mtb environment at the time of infection. We have carried out large-scale meta-analysis of previously published gene expression microarray studies andhave identified a ranked list of differentially expressed genes and their higher order functions in intracellular Mtb as well as the infected macrophage. Comparative analysis of gene expression signatures of intracellular Mtb with the in vitro dormant Mtb at different hypoxic and oxidative stress conditions led to the identification of the large number of Mtb functional groups, namely operons, regulons and pathways that were common and unique to the intracellular environment and dormancy state. Some of the functions that are specific to intracellular Mtb are cholesterol degradation and biosynthesis of immunomodulatory phenolic compounds. The molecular signatures we have identified to be involved in adaptation to different stress conditions in macrophage environment may be critical for designing therapeutic interventions against tuberculosis. And, our approach may be broadly applicable for investigating other host-pathogen interactions.