Proteomic Characterization of Plasma Cells from Patients with Multiple Myeloma

Suvannasankha, Attaya; Crean, Colin D.; Leyes, Heather M; Wongsaengsak, Sariya; Qi, Guihong; Kim, Jong Won; Wang, Mu

doi:10.4172/jpb.1000461

Cited by 2 publications

(1 citation statement)

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“…However, some effort has been done also on analysis of patient cells. For example, ion intensity-based label-free quantitative MS identified a panel of 9 upregulated, and 9 downregulated proteins in PCs isolated from the BM of MM patients when compared to healthy donors [ 284 ].…”

Section: Omics In MMmentioning

confidence: 99%

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Ovejero

Moreaux

2021

Exploration of Targeted Anti-Tumor Therapy

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Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

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Section: Omics In MMmentioning

confidence: 99%