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Vuree, S.

Publications and source records attributed to Vuree, S..

2 recordsLinked to original sources

In silico approaches to identify the role of lncRNAs in Prostate cancer and Androgen receptor-targeted proteins

Long non-coding RNA (lncRNAs) are known to have a role in pathogenesis of a broad spectrum of malignancies.These are found to have a significant role as signal transduction mediators in cancer signaling pathways. Prostate Cancer (PCa) is emerging with increasing cases worldwide even as advanced approaches in clinical diagnosis and treatment of PCa are still challenging to address. To enhance patient stratification, there is an indefatigable need to understand risk that can allow new approaches of treatment based on prognosis. While PCa is known to have mediated androgen receptor (AR) stimulation, the latter plays a key role in regulating transcription of genes via nuclear translocation which in turn leads to response to androgens. LncRNAs have been implicated in developing clinical diagnostic and prognostic biomarkers in a broad spectrum of cancers. In our present study, 12 lncRNAs identified from clinical samples from our erstwhile PCa patients were docked with PCa and AR targeted 36 proteins. We identified three lncRNAs, viz. SCARNA10, NPBWR1, ANKRD20A9P are common between the targeted proteins and discern that SCARNA10 lncRNA could serve as a prognostic signature for PCa and AR biogenesis. We also sought to check the coding potential of interfacial residues associated with lncRNA docking sites.x

bioinformatics↗

Integrative Multi-Omics Approaches for Identifying Cervical Cancer Therapeutic Targets

After breast cancer, cervical cancer (CC) is one of the most common malignancies in women globally. Over 90% of chronic infections are caused by human papillomavirus (HPV) and its subtypes. Extensive research efforts are required to identify the treatment targets and prognostic indicators for recurring and metastatic cancers. It may be possible because of omics methods, including genomes, epigenomics, transcriptomics, proteomics, and metabolomics. High throughput (HT) data on the differential mRNA and miRNA expression and their crucial interrelationships enable promising integration and interpretation of the results. Clinical data and multi-omics have risen to the top of the heap in delivering molecular and cellular activities. They aid in comparing data from different omics approaches and bridging the gap between genotype and phenotype. Therefore, multi-omic techniques may improve the knowledge of the molecular basis of the physiology and primary cause of disease, revealing a new route for the prognosis, diagnosis, prevention, and therapy of human diseases.

systems biology↗