| Literature DB >> 34127402 |
Jing Yang1, Shilin Zhao1, Jing Wang1, Quanhu Sheng1, Qi Liu2, Yu Shyr3.
Abstract
There are increasing studies aimed to reveal genomic hallmarks predictive of immune checkpoint blockade (ICB) treatment response, which generated a large number of data and provided an unprecedented opportunity to identify response-related features and evaluate their robustness across cohorts. However, those valuable data sets are not easily accessible to the research community. To take full advantage of existing large-scale immuno-genomic profiles, we developed Immu-Mela (http://bioinfo.vanderbilt.edu/database/Immu-Mela/), a multidimensional immuno-genomic portal that provides interactive exploration of associations between ICB responsiveness and multi-omics features in melanoma, including genetic, transcriptomics, immune cells, and single-cell populations. Immu-Mela also enables integrative analysis of any two genomic features. We demonstrated the value of Immu-Mela by identifying known and novel genomic features associated with ICB response. In addition, Immu-Mela allows users to upload their data sets (unrestricted to any cancer types) and co-analyze with existing data to identify and validate signatures of interest. Immu-Mela reduces barriers between researchers and complex genomic data, facilitating discoveries in cancer immunotherapy.Entities:
Keywords: Biomarker; CTLA-4 blockade; Immune checkpoint; Immunotherapy; Melanoma; Multidimensional genomics; PD-1/PD-L1 blockade
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Year: 2021 PMID: 34127402 PMCID: PMC8349898 DOI: 10.1016/j.jgg.2021.03.016
Source DB: PubMed Journal: J Genet Genomics ISSN: 1673-8527 Impact factor: 4.275