This blog discusses the challenges in understanding and treating multiple myeloma, a type of cancer caused by malignant plasma cells in the bone marrow. It highlights the potential of ex vivo drug testing as a promising approach for precision medicine and a recent study that used this approach to stratify multiple myeloma patients for personalized treatment. The study identified molecular signatures that can predict drug sensitivity and improve clinical treatment responses, providing a valuable tool for delivering effective treatments to patients with multiple myeloma.
Understanding Multiple Myeloma
Multiple myeloma is one of the most challenging cancers to understand and treat. Despite concerted efforts unraveling its genetic complexity and new therapies prolonging survival, it remains incurable. Multiple myeloma is caused when the white blood cells in the bone marrow responsible for making antibodies (aka plasma cells) become malignant.
As in many cancers, the features that contribute to the development of malignancy are essential processes of normal, healthy plasma cells gone wrong. To generate a wide variety of antibodies and to maintain a memory of which antibodies have been created, plasma cells undergo frequent genetic rearrangements and have long “lifespans.” When these genetic rearrangements take the form of translocations to the wrong section of a chromosome, they promote abnormal cell survival and proliferation, leading to multiple myeloma.
What is Ex Vivo Drug Testing?
A newer approach to precision medicine involves drug testing directly on patient biopsies rather than traditional in vitro approaches. It’s called ex vivo drug testing, and a recent paper using an image-based analysis technique reported an improved ability to recommend treatments resulting in increased survival in patients with relapsed blood cancers.
Ex vivo drug testing can also be analyzed using single-cell approaches for testing the sensitivity of patient biopsies to immunotherapies. This method allows for the characterization of immune cell activation, target cell engagement, and target cell killing, giving a comprehensive profile of the treatment’s efficacy.
New Study Stratifies Multiple Myeloma Patients for Personalized Treatment
In a recent study in Nature Cancer, Kropivsek et. al. adapted these ex vivo drug testing approaches to study multiple myeloma and investigate its clinical predictive power in this context. Across 101 bone marrow samples from 70 multiple myeloma patients, the authors combined ex vivo drug testing with sample-matched genetics, proteomics, and cytokine profiling.
Some of the best current treatment options for multiple myeloma include proteasome inhibitors and the immunotherapy elotuzumab. The authors found that the expression of EYA3, a c-Myc regulator, as well as the DNA repair pathway was significantly involved in sensitivity to proteasome inhibitors. In response to elotuzumab, MHC Class II expression appears to be critical for treatment response.
In addition to better characterizing the molecular mechanisms behind drug sensitivity, the authors’ findings were able to significantly stratify clinical treatment responses in accordance with the molecular signatures found, including additional signatures relating to the bone marrow microenvironment. Taken together, the study provides a new method for studying drug response in multiple myeloma at scale to deliver the best possible combination of treatments to a given patient.
Outsourcing Bioinformatics Analysis: How Bridge Informatics Can Help
Groundbreaking studies like these are made possible by technological advances that make biological data generation, storage, and analysis faster and more accessible than ever before. From pipeline development and software engineering to deploying existing bioinformatics tools, Bridge Informatics can help you on every step of your research journey.
As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing, and interpreting genomic and transcriptomic data. Bridge Informatics’ bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. Click here to schedule a free introductory call with a member of our team.
Jane Cook, Biochemist & Content Writer, Bridge Informatics
Jane Cook, the leading Content Writer for Bridge Informatics, has written over 100 articles on the latest topics and trends for the bioinformatics community. Jane’s broad and deep interdisciplinary molecular biology experience spans developing biochemistry assays to genomics. Prior to joining Bridge, Jane held research assistant roles in biochemistry research labs across a variety of therapeutic areas.
While obtaining her B.A. in Biochemistry from Trinity College in Dublin, Ireland, Jane also studied journalism at New York University’s Arthur L. Carter Journalism Institute. As a native Texan, she embraces any challenge that comes her way. Jane hails from Dallas but returns to Ireland any and every chance she gets. If you’re interested in reaching out, please email [email protected] or [email protected].