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Rahmat, M.

Publications and source records attributed to Rahmat, M..

3 recordsLinked to original sources

Novel mechanism of MYC deregulation in Multiple Myeloma

MYC deregulation occurs in 67% of multiple myeloma (MM) cases and associates with progression and worse prognosis in MM. Enhanced MYC expression is known to be driven by translocation or amplification events, but it only occurs in 40% of MM patients. Here, we describe a new mechanism of MYC regulation, whereby epigenetic regulation of MYC by increased accessibility of a cell-type specific enhancer leads to increased MYC expression. We found enhancer activity does not associate with enhancer hijacking events. We identified specific binding of c-MAF, IRF4, and SPIB transcription factors to the enhancer can activate MYC. In addition, we discovered focal amplification of this specific enhancer in approximately 4% of MM patients. Together, our findings define a new epigenetic mechanism of MYC deregulation in MM beyond known translocations or amplifications and point to the importance of non-coding regulatory elements and their associated transcription factor networks as drivers of MM progression.

cancer biology↗

Selective Enhancer Dependencies in MYC-Intact and MYC-Rearranged Germinal Center B-cell Diffuse Large B-cell Lymphoma

High expression of MYC and its target genes define a subset of germinal center B-cell diffuse large B-cell lymphoma (GCB-DLBCL) associated with poor outcomes. Half of these high-grade cases show chromosomal rearrangements between the MYC locus and heterologous enhancer-bearing loci, while focal deletions of the adjacent non-coding gene PVT1 are enriched in MYC-intact cases. To identify genomic drivers of MYC activation, we used high-throughput CRISPR-interference (CRISPRi) profiling of candidate enhancers in the MYC locus and rearrangement partner loci in GCB-DLBCL cell lines and mantle cell lymphoma (MCL) comparators that lacked common rearrangements between MYC and immunoglobulin (Ig) loci. Rearrangements between MYC and non-Ig loci were associated with unique dependencies on specific enhancer subunits within those partner loci. Notably, fitness dependency on enhancer modules within the BCL6 super-enhancer (BCL6-SE) cluster regulated by a transcription factor complex of MEF2B, POU2F2, and POU2AF1 was higher in cell lines bearing a recurrent MYC::BCL6-SE rearrangement. In contrast, GCB-DLBCL cell lines without MYC rearrangement were highly dependent on a previously uncharacterized 3 enhancer within the MYC locus itself (GCBME-1), that is regulated in part by the same triad of factors. GCBME-1 is evolutionarily conserved and active in normal germinal center B cells in humans and mice, suggesting a key role in normal germinal center B cell biology. Finally, we show that the PVT1 promoter limits MYC activation by either native or heterologous enhancers and demonstrate that this limitation is bypassed by 3 rearrangements that remove PVT1 from its position in cis with the rearranged MYC gene. Key pointsO_LICRISPR-interference screens identify a conserved germinal center B cell MYC enhancer that is essential for GCB-DLBCL lacking MYC rearrangements. C_LIO_LIFunctional profiling of MYC partner loci reveals principles of MYC enhancer-hijacking activation by non-immunoglobulin rearrangements. C_LI

cancer biology↗

Genetic Subtypes of Smoldering Multiple Myeloma are associated with Distinct Pathogenic Phenotypes and Clinical Outcomes

Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrated 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identified six distinct genetic subtypes. These subtypes were differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three subtypes were associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification model.

cancer biology↗