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Biology subjects

Kumar, K. V.

Publications and source records attributed to Kumar, K. V..

2 recordsLinked to original sources

MyeloDB: A multi-omics resource for Multiple Myeloma

Multiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all haematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 15 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes i.e., CBFB, MANF, MBNL1, SEPHS2 and UFM1 as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB is freely accessible at: (https://project.iith.ac.in/cgntlab/myelodb/)

genomics↗

AMLdb: A comprehensive multi-omics platform to understand the pathogenesis and discover biomarkers for acute myeloid leukemia

Acute myeloid leukemia (AML) is one of the leading leukemic malignancies in adults. The heterogeneity of the disease makes the diagnosis and treatment extremely difficult. Despite the significant developments and the rapid advancements in finding new medication targets, the treatment for AML remains a challenge. With the advent of next-generation sequencing (NGS) technologies, exploration at the molecular level for the identification of biomarkers and drug targets has been the main focus for the researchers to come up with novel therapies for better prognosis and survival outcomes of AML patients. However, the massive amounts of data generated from the NGS platforms demands the necessity to create a comprehensive platform on AML to save the time invested in mining literature. To facilitate this, we developed AMLdb, an interactive multi-omics platform that allows users to query, visualize, retrieve and analyze AML-related multi-omics data. It provides a diverse collection of data resourced from various repositories allowing for a more comprehensive analysis. AMLdb contains 86 datasets for gene expression profiles, 15 datasets for methylation profiles, CRISPR-Cas9 knockout screens of 26 AML cell lines, sensitivity of 26 AML cell lines to 288 drugs, mutations in 41 unique genes in 23 AML cell lines and information on 27 experimentally validated biomarkers. The data provided can be used for deriving conclusions on potential targets for therapies, sensitivity of these targets towards the drugs, patient classification, prediction of treatment strategies and outcomes, chances of relapse etc. In this study, we have reported five genes i.e., CBFB, ENO1, IMPDH2, SEPHS2 and MYH9 identified via our analysis using AMLdb as potential targets. Amongst this, CBFB, IMPDH2, SEPHS2 and MYH9 have been previously validated as targets by experimental studies which is in par with our results. However, ENO1 is a novel target identified using AMLdb which needs further investigation. We anticipates that, AMLdb can be a valuable resource to aid the research community accelerate the development of effective therapies for AML. AMLdb is freely accessible at https://project.iith.ac.in/cgntlab/amldb/ without any restrictions.

genomics↗