Cross talk of tumor protein D52 (TPD52) with KLF9, PKCε, and MicroRNA 223 in ovarian cancer.

BACKGROUND: Gynecologic cancers comprise malignancies in the female reproductive organs. Ovarian cancer ranks sixth in terms of incidence rates while seventh in terms of mortality rates. The stage at which ovarian cancer is diagnosed mainly determines the survival outcomes of patients. Various screening approaches are presently employed for diagnosing ovarian cancer; however, these techniques have low accuracy and are non-specific, resulting in high mortality rates of patients due to this disease. Hence, it is crucial to identify improved screening and diagnostic markers to overcome this cancer. This study aimed to find new biomarkers to facilitate the prognosis and diagnosis of ovarian cancer. METHODS: Bioinformatics approaches were used to predict the tertiary structure and cellular localization along with phylogenetic analysis of TPD52. Its molecular interactions were determined through KEGG analysis, and real-time PCR-based expression analysis was performed to assess its co-expression with another oncogenic cellular pathway (miR-223, KLF9, and PKCε) proteins in ovarian cancer. RESULTS: Bioinformatics analysis depicted the cytoplasmic localization of TPD52 and the high conservation of its coiled-coil domains. Further study revealed that TPD52 mRNA and miRNA-223 expression was elevated, while the expression of KLF 9 and PKCε was reduced in the blood of ovarian cancer patients. Furthermore, TPD52 and miR-223 expression were upregulated in the early stages of cancer and non-metastatic cancers. CONCLUSION: TPD52, miR-223, PKCε, and KLF9, can be used as a blood based markers for disease prognosis, metastasis, and treatment response. The study outcomes hold great potential to be translated at the clinical level after further validation on larger cohorts.

Investigating isoform switching in RHBDF2 and its role in neoplastic growth in breast cancer.

Background: Breast cancer is the second leading cause of cancer-related deaths globally, and its prevalence rates are increasing daily. In the past, studies predicting therapeutic drug targets for cancer therapy focused on the assumption that one gene is responsible for producing one protein. Therefore, there is always an immense need to find promising and novel anti-cancer drug targets. Furthermore, proteases have an integral role in cell proliferation and growth because the proteolysis mechanism is an irreversible process that aids in regulating cellular growth during tumorigenesis. Therefore, an inactive rhomboid protease known as iRhom2 encoded by the gene RHBDF2 can be considered an important target for cancer treatment. Speculatively, previous studies on gene expression analysis of RHBDF2 showed heterogenous behaviour during tumorigenesis. Consistent with this, several studies have reported the antagonistic role of iRhom2 in tumorigenesis, i.e., either they are involved in negative regulation of EGFR ligands via the ERAD pathway or positively regulate EGFR ligands via the EGFR signalling pathway. Additionally, different opinions suggest iRhom2 mediated cleavage of EGFR ligands takes place TACE dependently or TACE independently. However, reconciling these seemingly opposing roles is still unclear and might be attributed to more than one transcript isoform of iRhom2. Methods: To observe the differences at isoform resolution, the current strategy identified isoform switching in RHBDF2 via differential transcript usage using RNA-seq data during breast cancer initiation and progression. Furthermore, interacting partners were found via correlation and enriched to explain their antagonistic role. Results: Isoform switching was observed at DCIS, grade 2 and grade 3, from canonical to the cub isoform. Neither EGFR nor ERAD was found enriched. However, pathways leading to TACE-dependent EGFR signalling pathways were more observant, specifically MAPK signalling pathways, GPCR signalling pathways, and toll-like receptor pathways. Nevertheless, it was noteworthy that during CTCs, the cub isoform switches back to the canonical isoform, and the proteasomal degradation pathway and cytoplasmic ribosomal protein pathways were significantly enriched. Therefore, it could be inferred that cub isoform functions during cancer initiation in EGFR signalling. In contrast, during metastasis, where invasion is the primary task, the isoform switches back to the canonical isoform.

Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer.

Pancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify cancer specific biomarkers, therapeutic targets, and their associated pathways involved in the PaCa progression. RNA-seq and microarray datasets were obtained from public repositories such as the European Bioinformatics Institute (EBI) and Gene Expression Omnibus (GEO) databases. Differential gene expression (DE) analysis of data was performed to identify significant differentially expressed genes (DEGs) in PaCa cells in comparison to the normal cells. Gene co-expression network analysis was performed to identify the modules co-expressed genes, which are strongly associated with PaCa and as well as the identification of hub genes in the modules. The key underlaying pathways were obtained from the enrichment analysis of hub genes and studied in the context of PaCa progression. The significant pathways, hub genes, and their expression profile were validated against The Cancer Genome Atlas (TCGA) data, and key biomarkers and therapeutic targets with hub genes were determined. Important hub genes identified included ITGA1, ITGA2, ITGB1, ITGB3, MET, LAMB1, VEGFA, PTK2, and TGFß1. Enrichment analysis characterizes the involvement of hub genes in multiple pathways. Important ones that are determined are ECM-receptor interaction and focal adhesion pathways. The interaction of overexpressed surface proteins of these pathways with extracellular molecules initiates multiple signaling cascades including stress fiber and lamellipodia formation, PI3K-Akt, MAPK, JAK/STAT, and Wnt signaling pathways. Identified biomarkers may have a strong influence on the PaCa early stage development and progression. Further, analysis of these pathways and hub genes can help in the identification of putative therapeutic targets and development of effective therapies for PaCa.

Evaluation of pro-apoptotic potential of taxifolin against liver cancer.

Liver cancer is the second most common cause of cancer-induced deaths worldwide. Liver cirrhosis and cancer are a consequence of the abnormal angio-architecture formation of liver and formation of new blood vessels. This angiogenesis is driven by overexpression of hypoxia-inducible factor 1-alpha (Hif1-α) and vascular endothelial growth factor (VEGF). Apart from this, protein kinase B (Akt) is also impaired in liver cancer. Despite the advancement in conventional treatments, liver cancer remains largely incurable. Nowadays, the use of naturally occurring anticancer agents particularly flavonoids is subject to more attention due to their enhanced physicochemical properties. Therefore, this study underlines the use of a natural anticancer agent taxifolin in the treatment of liver cancer using hepatocellular carcinoma cell line HepG2 and Huh7. The aim of our study is to devise a natural and efficient solution for the disease prevalent in Pakistan. The study involved the assessment of binding of ligand taxifolin using molecular docking. The binding of taxifolin with the proteins (Hif1-α, VEGF and Akt) was calculated by docking using Vina and Chimera. Further evaluation was performed by cell viability assay (MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) Assay), colony formation assay, cell migration assay, DNA ladder assay and flow cytometry. To see whether taxifolin directly affected expression levels, analysis of gene expression of Hif1-α, VEGF and Akt was performed using real-time polymerase chain reaction (qPCR) and western blotting. In silico docking experiments revealed that these proteins showed favorable docking scores with taxifolin. Treatment with taxifolin resulted in the inhibition of the liver cancer growth and migration, and induced apoptosis in HepG2 and Huh7 cell lines at an inhibitory concentration (IC50) value of 0.15 µM and 0.22 µM, respectively. The expression of HIF1-α, VEGF and Akt was significantly reduced in a dose- dependent manner. The inhibitory effect of taxifolin on hepatic cells suggested its chemopreventive and therapeutic potential. The studied compound taxifolin exhibited pronounced pro-apoptotic and hepatoprotective potential. Our study has confirmed the pro-apoptotic potential of taxifolin in liver cancer cell lines and will pave a way to the use of taxifolin as a chemotherapeutic agent after its further validation on the animal models and humans based epidemiological studies.

Unravelling Structure, Localization, and Genetic Crosstalk of KLF3 in Human Breast Cancer.

Breast cancer is the most prevailing disease among women. It actually develops from breast tissue and has heterogeneous and complex nature that constitutes multiple tumor quiddities. These features are associated with different histological forms, distinctive biological characteristics, and clinical patterns. The predisposition of breast cancer has been attributed to a number of genetic factors, associated with the worst outcomes. Unfortunately, their behavior with relevance to clinical significance remained poorly understood. So, there is a need to further explore the nature of the disease at the transcriptome level. The focus of this study was to explore the influence of Krüppel-like factor 3 (KLF3), tumor protein D52 (TPD52), microRNA 124 (miR-124), and protein kinase C epsilon (PKCε) expression on breast cancer. Moreover, this study was also aimed at predicting the tertiary structure of KLF3 protein. Expression of genes was analyzed through real-time PCR using the delta cycle threshold method, and statistical significance was calculated by two-way ANOVA in Graphpad Prism. For the construction of a 3D model, various bioinformatics software programs, Swiss Model and UCSF Chimera, were employed. The expression of KLF3, miR-124, and PKCε genes was decreased (fold change: 0.076443, 0.06969, and 0.011597, respectively). However, there was 2-fold increased expression of TPD52 with p value < 0.001 relative to control. Tertiary structure of KLF3 exhibited 80.72% structure conservation with its template KLF4 and was 95.06% structurally favored by a Ramachandran plot. These genes might be predictors of stage, metastasis, receptor, and treatment status and used as new biomarkers for breast cancer diagnosis. However, extensive investigations at the tissue level and in in vivo are required to further strengthen their role as a potential biomarker for prognosis of breast cancer.

Bridging the gap by discerning SNPs in linkage disequilibrium and their role in breast cancer.

Breast Cancer is the most common cancer among women with several genes involved in disease susceptibility. As majority of genome-wide significant variants fall outside the coding region, it is likely that some of them alter specific gene functions. GWAS database was used to interpret the regulatory functions of these genetic variants. A total of 320 SNPs for breast cancer were selected via GWAS, which were entered into the SNAP web portal tool, to determine the one's found to be in Linkage Disequilibrium (r2 < 0.80). The resulting 2024 proxy SNP's were processed in RegulomeDB to predict their regulatory role. Of these, 1440 produced a score ranging from 1-6, whereas the remaining produced no data. Only the variants under score 4 (cut-off value) in RegulomeDB has been studied further. From these variants, 221 had scores of less than 4, indicating a high degree of potential regulatory role associated with them. Further study revealed that 61 of the 221 SNPs were reported to be genome-wide significant for breast cancer, 52 to be associated with other diseases, 99 as unconfirmed for association with breast cancer, leaving only 9 to be novel proxy SNPs linked to breast cancer. Therefore, the study further confirmed postulation of non-coding variants being linked to disease risk thereby, requiring additional validation through genome-wide association studies to substantiate their underlying mechanism.