To discover previously unknown subtypes of the blood cancer called multiple myeloma, Mount Sinai researchers have developed a novel model using DNA and RNA sequencing data from hundreds of patients. According to Science Advances in November, they also identified possible therapeutic options based on their results. This is the first study to use multi-omics, or the integration and analysis of numerous data sources, to develop a computer model of multiple myeloma, dubbed the Multiple Myeloma Patient Similarity Network by the researchers (MM-PSN). Several genes linked to a high risk of recurrence were found in the study.
This study has immediate implications for the development of novel precision medicine tools and clinical trials, as different subgroups of patients may respond to various targeted and immuno-oncology therapies depending on their genomic and transcriptomic profiles," lead author Alessandro Lagana, Ph.D., Assistant Professor of Oncological Sciences at The Tisch Cancer Institute at Mount Sinai, said. As shown by these investigations, a better knowledge of myeloma pathology will lead to new medication repurposing techniques targeted at tailoring treatments to particular patient subgroups.
MM-PSN, according to researchers, reflects the intricacy of multiple myeloma by grouping individuals with substantially comparable DNA and RNA profiles into more granular and homogenous groupings than earlier classifications. It was used to portray patients as nodes in a social network, depending on their DNA and RNA profiles, as in the MM-PSN model. The DNA and RNA sequencing data of 655 newly diagnosed multiple myeloma patients was used to build MM-PSN. Three main groups and 12 subgroups were identified, each with distinct genetic and molecular characteristics, revealing remarkable diversity within previously defined disease subtypes—such as hyperdiploid and MMSET-translocated, which are chromosome abnormalities—and novel insights into the occurrence of primary and secondary genomic changes within each patient's cancer.
The Most relevant genetic variable linked with recurrence was an aberration on chromosome 1; the research recommends that it should now be included in worldwide myeloma staging systems. Researchers also discovered new types of high-risk individuals with multiple myeloma, including one with the most excellent chance of recurrence and the lowest overall survival and another with a better prognosis.
17 Nov 2021 • Vol 7, Issue 47 • DOI: 10.1126/sciadv.abg9551