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Multiple Myeloma Patient Similarity Network Reveals Prognostically Informative Subgroups

NEW YORK – An Icahn School of Medicine at Mount Sinai-led team has established a "patient similarity network" outlining genomic and transcriptomic features that are shared by, and differ between, multiple myeloma tumors found in hundreds of individuals.

"In a PSN, patients are represented as nodes, much like in a social network, and connected with one another based on how similar their genomic and transcriptomic profiles are," co-senior and co-corresponding authors Samir Parekh and Alessandro Laganà, cancer, genetics, and genomics researchers affiliated with the Tisch Cancer Institute and other Icahn School of Medicine departments, and their colleagues explained.

They suggested that their new study, published in Science Advances on Wednesday, "confirms the advantages of using multiple features to dissect cancer heterogeneity and the ability of PSNs to handle multiple data types to generate clear and interpretable disease models."

Using whole-genome sequencing, exome sequencing, and/or RNA sequencing, the researchers profiled somatic variants, large and small copy number changes, chromosomal translocations, gene fusion events, and gene expression patterns in tumors from 655 patients with the bone marrow malignancy who had enrolled in the Multiple Myeloma Research Foundation's CoMMpass study, identifying three main MM subtypes and a dozen subgroups with distinct combinations of features ranging from translocations to gains or losses involving portions of chromosomes 1, 16, or 17.

"MM is characterized by remarkable clinical and genomic heterogeneity," the authors wrote, adding that the "[a]ccurate classification of patients with MM into biologically homogeneous classes is … essential for diagnosis, prognosis, and clinical management."

In addition to providing a more refined view of MM subtypes compared to gene expression-based classifications, the clusters uncovered with the MM-PSN approach appeared to provide informative prognostic insights, the team explained.

In general, patients with group 2 tumors tended to have shorter progression-free and overall survival times than patients with tumors falling in the group 1 subtype, the researchers reported. But there were prognostic differences between the subgroups as well.

They found that MM patients with tumors that contained a chromosome 1 gain and a chromosome 4-chromosome 14 translocation affecting the MMSET/FGFR3 genes had significantly higher rates of disease relapse, for example, along with shorter progression-free survival and overall survival times, relative to patients with additional chromosome gains or with the chromosome 4 and 14 translocation alone.

The team confirmed these and other findings with a survival analysis that focused on 559 MM patients who had their tumors profiled prior to starting treatment. They also saw hints that a chromosome 1 gain alone, which involves the 1q arm of the chromosome and turned up in six MM subgroups, tended to correspond with enhanced relapse risk. Based on these and other results, they proposed the inclusion of chromosome 1q profiling within staging systems used internationally for MM.

"While the prognostic impact of [the 1q gain] has been previously investigated and established in numerous studies, our network model and analysis have revealed a much higher significance and centrality of this genetic lesion in risk assessment of treatment-naïve patients with MM," the authors wrote. "Ongoing research is now focused on a deeper characterization of the MM-PSN subgroups, and, in particular, those enriched for gain (1q), to gain novel insights into the molecular mechanisms that drive each disease subtype."