Updates

MSF-sponsored investigators Drs. Yubao Wang (L) and Gareth Morgan (R) from NYU Langone Health recently reported the identification of over 300 transcriptional targets of NSD2 and the mechanisms of their regulation. Using a novel genetic model that allows for rapid degradation of NSD2, they found that NSD2 target genes show an enrichment for oncogenic signaling pathways and transcription factors, including some that are oncogenic drivers in MM, reenforcing the role of NSD2 as an oncogene in t(4;14) MM. This model can now also be used to identify synthetical lethality targets, that, with NSD2 depletion, can selectively kill NSD2-driven tumor cells such as those of the t(4;14) MM.

MSF has made an investment in Predicta Biosciences to support the development of advanced diagnostics to improve clinical decision-making ultimately leading to improved clinical outcomes for multiple myeloma patients.

The MMRF believes that only teamwork and strategic planning can conquer cancer. Exemplifying this belief, in 2011 the MMRF began CoMMpass, a unique biological study of >1,000 myeloma patients. CoMMpass data continues to drive new discoveries and important clinical insights. Recently at iwMyeloma 2024, MSF grantees Drs. Ben Barwick and Larry Boise of Winship Cancer Institute of Emory University discussed the contributions of the CoMMpass study to new insights in high-risk MM, including t(4;14).

Previously, MSF announced the launch of the “Computational Biology Fellowship Program in MM”. Under the mentorship of translational medicine and computational biology experts in MM, fellowship recipients will also collaborate with MSF Fellows at other institutions contributing to research for high-risk MM, with a focus on the t(4;14) subtype. 2024 Fellows include:

• Minghao Dang
• Romane Cathelin
• Michael Durante

MSF has made an investment in Slingshot Biosciences whose innovative platform includes the development of synthetic cells. The Emeryville, California-based company is focused on maximizing the application of it’s FlowCyte technology to:

• Improve the accuracy and performance of biomedical instruments and devices
• Lower the cost and barriers of drug development and diagnostics
• Make healthcare more accessible around the world

Dr. Corynn Kasap (UCSF) presents abstract at the annual meeting of the American Society of Hematology. As part of an MSF-sponsored collaboration including Dr. Arun Wiita (UCSF) and colleagues at Emory Univ. and Univ. of Florida, the team showed that the cell surface protein CD70 is elevated on t(4;14) MM cells. Investigators also showed effective CAR-T targeting of CD70+ MM cells using both scFv-based CD70 antibody fragments and a fragment of the natural CD70 ligand, CD27. This discovery highlights a potential new cellular therapy treatment for t(4;14) myeloma.

Utilizing advances in artificial intelligence (AI), a multi-institutional collaboration led by Drs. Ola Landgren and Francesco Maura utilized clinical and genomic information to create a model for Individualized Risk in NDMM (IRMMa). The model demonstrates the potential to help guide therapeutic decisions for personalized treatment strategies in multiple myeloma. These results further highlight the importance for continued collaboration and the incorporation of computational biology and AI to improve treatment decisions and outcomes for myeloma patients.

The University of Texas MD Anderson Cancer Center and NYU Langone Health join Sylvester Cancer Center at the University of Miami to lead the MSF Computational Biology Fellowship program. Recipients of these 3-year fellowships are under the mentorship of experts in MM Translational Medicine and Computational Biology and will be part of the MSF network of scientists focused on advancing therapies for MM patients with high-risk disease, with an emphasis on the t(4;14) subtype.

The t(4:14) is seen in 10-15% of newly diagnosed multiple myeloma cases and is associated with a high risk of disease progression and poor prognosis. The dysregulation of genes and pathways associated with the t(4;14) translocation leads to an increase in the proliferation of cancer cells and a decreased sensitivity to current treatments. In addition to poor prognosis, patients with t(4;14) myeloma may also experience more severe symptoms such as bone pain, fatigue, anemia, and kidney damage. Focused research on t(4;14) myeloma is needed to better understand its complex biology and to identify vulnerabilities that can be exploited for the development of new targeted therapies that yield significant improvement.

The use of computational biology and artificial intelligence is playing an increasing role in cancer research. To help understand the complexities of MM biology and to inform treatment decisions, MSF is funding post-doctoral fellowships in Computational Biology. These fellowships will serve to support MSF-sponsored research grants while providing the training to help address the need for research faculty focused on computational biology in MM. Under the leadership of Drs. Ola Landgren and Francesco Maura (Sylvester Comprehensive Cancer Center at the University of Miami), the initial recipients of the MSF Fellowships will also be awarded to two additional institutions.