Singapore (Commonwealth Union) – Scientists at the National University of Singapore (NUS) are embarking on a groundbreaking mission to exploit vulnerabilities within the pathways of cancer development, with the aim of revolutionizing treatment approaches for high-risk myeloma.
In a pioneering study conducted by researchers from NUS’s Cancer Science Institute of Singapore (CSI Singapore), vital insights have emerged regarding the role played by histone methyltransferase NSD2 and its epigenetic target PKCα in driving the heightened aggressiveness and treatment resistance of t(4;14) translocated multiple myeloma (MM), a particularly high-risk subtype of blood cancer.
This landmark research was spearheaded by Professor Wee Joo Chng, Senior Principal Investigator at CSI Singapore, and Dr. Phyllis Chong Shu Yun, Senior Research Fellow at CSI Singapore. Their team’s findings have illuminated the mechanism by which NSD2 activates PKCα, ultimately triggering increased glycolysis and the overproduction of lactate, thereby fueling malignancy and undermining the effectiveness of immunomodulatory drugs. These discoveries offer promising avenues for enhancing myeloma treatment.
Myeloma stands as the second most prevalent blood cancer, with t(4;14) myeloma accounting for 15 to 20 percent of MM cases. Regrettably, patients afflicted with t(4;14) myeloma face a bleaker prognosis characterized by shorter overall survival, compounded by the challenge that the pivotal deregulated gene in this subtype is not amenable to drug targeting.
“Our study aims to overcome the limitations of targeting the key deregulated gene in t(4;14) myeloma. It sheds light on the metabolic reprogramming of MM in response to the oxygen- and nutrient-deprived bone marrow microenvironment. By exploring the epigenome and metabolome of NSD2, we sought alternative vulnerabilities that could revolutionize treatment strategies,” explained Professor Chng, the lead author of the study.
The distinctive link between NSD2 and cellular metabolism, facilitated through histone methylation, opens up new vistas in the battle against high-risk MM subtypes. The study’s impact is multifaceted, with the potential to influence the development of innovative medications and non-invasive diagnostic tests. For individuals grappling with t(4;14) myeloma, targeted interventions aimed at metabolic processes could usher in promising therapeutic choices, whether through dietary adjustments or tailored pharmacological strategies. Furthermore, the revelation that lactate levels could serve as predictive biomarkers for drug responses underscores the transformative potential of metabolite signatures in the realm of personalized medicine.
Published in Cancer Research by the American Association for Cancer Research on July 18, 2023, this study represents a significant leap forward in unraveling the intricacies of MM and holds the promise of enhancing treatment outcomes for patients affected by high-risk subtypes.
Looking ahead, Professor Chng and his team are poised to leverage the insights garnered from this study to devise therapeutic interventions tailored to t(4;14) myeloma. The successful metabolic characterization of t(4;14) myeloma also paves the way for the team to extend their metabolomic framework to profile other genetically high-risk MM subtypes, such as t(14;16) or those with 1q21 amplifications, charting a course toward bespoke interventions and individualized care.Biomarkers serve as vital indicators that help physicians identify cancer at its earliest and most treatable stages. There are indicators that help physicians identify cancer at its earliest and most treatable stages. Biomarkers serve as vital indicators that help physicians identify cancer at its earliest and most treatable stages. Several types of biomarkers used in cancer research and clinical practice. These include Diagnostic Biomarkers which can confirm the presence of cancer. They can include specific proteins, genes, or mutations that are associated with a particular cancer type. Prognostic Biomarkers can provide information about the likely course and outcome of the disease. They help doctors determine the risk of cancer recurrence and guide treatment decisions. Predictive Biomarkers assist in tailoring treatment plans. They can indicate how a patient is likely to respond to a specific therapy, helping doctors choose the most effective treatment option.
