MyeloDB: a multi-omics resource for multiple myeloma.

Autor: Kumar A; Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India., Kumar KV; Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India., Kundal K; Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India., Sengupta A; Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India., Sharma S; Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India., R K; Department of Biological Sciences, Indian Institute of Science Education and Research, Berhampur, Odisha, 760010, India., Kumar R; Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India. rahulk@bt.iith.ac.in.
Jazyk: angličtina
Zdroj: Functional & integrative genomics [Funct Integr Genomics] 2024 Jan 20; Vol. 24 (1), pp. 17. Date of Electronic Publication: 2024 Jan 20.
DOI: 10.1007/s10142-023-01280-0
Abstrakt: 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 hematological 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 25 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 Database URL: https://project.iith.ac.in/cgntlab/myelodb/ .
(© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Databáze: MEDLINE
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