Investigating mechanistic insights of curcumin in blocking the Interleukin-8 signaling pathway associated with Breast Cancer: An in-silico approach.

Interleukin-8 (IL-8) is a chemokine, a type of signaling molecule that has a role in immunological responses and inflammation. In recent years, IL-8 is additionally related to cancer growth and recurrence. Breast cancer growth, progression, and metastatic development are all linked to IL-8. Breast cancer cells are known to develop faster when IL-8 stimulates their proliferation and survival. It can also cause angiogenesis, or the creation of new blood vessels, which is necessary for tumor nutrition and growth. IL-8 and curcumin have been subjects of interest in drug design, particularly in the context of inflammation-related disorders and cancer. This study aims to give an overview of the role of IL-8. Inhibitor-based treatment approaches were being used to target IL-8 with curcumin. Molecular docking method was employed to find a potential interaction to supress competitive inhibition of IL-8 with curcumin. PASS analysis and ADMET characteristics were also being carried out. In the end, IL-8 complexed with curcumin is chosen for MD simulations. Overall, our results showed that during the simulation, the complex stayed comparatively stable. It is also possible to investigate curcumin further as a possible treatment option. The combined results imply that IL-8 and their genetic alterations can be studied in precision cancer therapeutic treatments, utilizing target-driven therapy and early diagnosis.

Unravelling driver genes as potential therapeutic targets in ovarian cancer via integrated bioinformatics approach.

Target-driven cancer therapy is a notable advancement in precision oncology that has been accompanied by substantial medical accomplishments. Ovarian cancer is a highly frequent neoplasm in women and exhibits significant genomic and clinical heterogeneity. In a previous publication, we presented an extensive bioinformatics study aimed at identifying specific biomarkers associated with ovarian cancer. The findings of the network analysis indicate the presence of a cluster of nine dysregulated hub genes that exhibited significance in the underlying biological processes and contributed to the initiation of ovarian cancer. Here in this research article, we are proceeding our previous research by taking all hub genes into consideration for further analysis. GEPIA2 was used to identify patterns in the expression of critical genes. The KM plotter analysis indicated that the out of all genes 5 genes are statistically significant. The cBioPortal platform was further used to investigate the frequency of genetic mutations across the board and how they affected the survival of the patients. Maximum mutation was reported by ELAVL2. In order to discover viable therapeutic candidates after competitive inhibition of ELAVL2 with small molecular drug complex, high throughput screening and docking studies were used. Five compounds were identified. Overall, our results suggest that the ELAV-like protein 2-ZINC03830554 complex was relatively stable during the molecular dynamic simulation. The five compounds that have been found can also be further examined as potential therapeutic possibilities. The combined findings suggest that ELAVL2, together with their genetic changes, can be investigated in therapeutic interventions for precision oncology, leveraging early diagnostics and target-driven therapy.

Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach.

Ovarian cancer is the eighth-most common cancer in women and has the highest rate of death among all gynecological malignancies in the Western world. Increasing evidence shows that miRNAs are connected to the progression of ovarian cancer. In the current study, we focus on the identification of miRNA and its associated genes that are responsible for the early prognosis of patients with ovarian cancer. The microarray dataset GSE119055 used in this study was retrieved via the publicly available GEO database by NCBI for the analysis of DEGs. The miRNA GSE119055 dataset includes six ovarian carcinoma samples along with three healthy/primary samples. In our study, DEM analysis of ovarian carcinoma and healthy subjects was performed using R Software to transform and normalize all transcriptomic data along with packages from Bioconductor. Results: We identified miRNA and its associated hub genes from the samples of ovarian cancer. We discovered the top five upregulated miRNAs (hsa-miR-130b-3p, hsa-miR-18a-5p, hsa-miR-182-5p, hsa-miR-187-3p, and hsa-miR-378a-3p) and the top five downregulated miRNAs (hsa-miR-501-3p, hsa-miR-4324, hsa-miR-500a-3p, hsa-miR-1271-5p, and hsa-miR-660-5p) from the network and their associated genes, which include seven common genes (SCN2A, BCL2, MAF, ZNF532, CADM1, ELAVL2, and ESRRG) that were considered hub genes for the downregulated network. Similarly, for upregulated miRNAs we found two hub genes (PRKACB and TAOK1).

Role of different non-coding RNAs as ovarian cancer biomarkers.

BACKGROUND: Among many gynecological malignancies ovarian cancer is the most prominent and leading cause of female mortality worldwide. Despite extensive research, the underlying cause of disease progression and pathology is still unknown. In the progression of ovarian cancer different non-coding RNAs have been recognized as important regulators. The biology of ovarian cancer which includes cancer initiation, progression, and dissemination is found to be regulated by different ncRNA. Clinically ncRNA shows high prognostic and diagnostic importance. RESULTS: In this review, we prioritize the role of different non-coding RNA and their perspective in diagnosis as potential biomarkers in the case of ovarian cancer. Summary of some of the few miRNAs involved in epithelial ovarian cancer their expression and clinical features are being provided in the table. Also, in cancer cell proliferation, apoptosis, invasion, and migration abnormal expression of piRNAs are emerging as a crucial regulator hence the role of few piRNAs is being given. Both tRFs and tiRNAs play important roles in tumorigenesis and are promising diagnostic biomarkers and therapeutic targets for cancer. lncRNA has shown a leading role in malignant transformation and potential therapeutic value in ovarian cancer therapy. CONCLUSIONS: Hence in this review we demonstrated the role of different ncRNA that play an important role in serving strong potential as a therapeutic approach for the treatment of ovarian cancer.

High throughput screening, docking, and molecular dynamics studies to identify potential inhibitors of human calcium/calmodulin-dependent protein kinase IV.

Calcium/calmodulin-dependent protein kinase IV (CAMKIV) is associated with many diseases including cancer and neurodegenerative disorders and thus being considered as a potential drug target. Here, we have employed the knowledge of three-dimensional structure of CAMKIV to identify new inhibitors for possible therapeutic intervention. We have employed virtual high throughput screening of 12,500 natural compounds of Zinc database to screen the best possible inhibitors of CAMKIV. Subsequently, 40 compounds which showed significant docking scores (-11.6 to -10.0 kcal/mol) were selected and further filtered through Lipinski rule and drug likeness parameter to get best inhibitors of CAMKIV. Docking results are indicating that ligands are binding to the hydrophobic cavity of the kinase domain of CAMKIV and forming a significant number of non-covalent interactions. Four compounds, ZINC02098378, ZINC12866674, ZINC04293413, and ZINC13403020, showing excellent binding affinity and drug likeness were subjected to molecular dynamics simulation to evaluate their mechanism of interaction and stability of protein-ligand complex. Our observations clearly suggesting that these selected ligands may be further employed for therapeutic intervention to address CAMKIV associated diseases. Communicated by Ramaswamy H. Sarma.