MAF protein mediates innate resistance to proteasome inhibition therapy in multiple myeloma

Established and Novel Prognostic Biomarkers in Multiple Myeloma

Multiple myeloma (MM) is an incurable plasma cell malignancy characterized by notable interpatient heterogeneity. There have been important advances in therapy and overall survival, but some patients with high-risk features still have poor survival rates. Therefore, accurate identification of this subset of patients has been integral to improvement of patient outcome. During the last few years, cytogenetics, gene expression profiling, MRI and PET/CT, as well as serum free light chain assays have been used as accurate biomarkers to better characterize the diverse course and outcome of the disease. With the recent advances of massive parallel sequencing techniques, the development of new models that better stratify high-risk groups are beginning to be developed. The use of multiparameter flow cytometry and next-generation sequencing have paved the way for assessment of minimal residual disease and better prognostication of post-therapeutic outcomes. Circulating tumor cells and circulating tumor DNA are promising potential biomarkers that demonstrate the spatial and temporal heterogeneity of MM. Finally, more prognostic markers are being developed that are specific to immunotherapeutic agents. In this review, we discuss these traditional and novel biomarkers that have been developed for MM and also those that can predict disease progression from precursor stages. Together, these biomarkers will help improve our understanding of the intrapatient and interpatient variabilities and help develop precision medicine for patients with high-risk MM.

3D genome of multiple myeloma reveals spatial genome disorganization associated with copy number variations

The Hi-C method is widely used to study the functional roles of the three-dimensional (3D) architecture of genomes. Here, we integrate Hi-C, whole-genome sequencing (WGS) and RNA-seq to study the 3D genome architecture of multiple myeloma (MM) and how it associates with genomic variation and gene expression. Our results show that Hi-C interaction matrices are biased by copy number variations (CNVs) and can be used to detect CNVs. Also, combining Hi-C and WGS data can improve the detection of translocations. We find that CNV breakpoints significantly overlap with topologically associating domain (TAD) boundaries. Compared to normal B cells, the numbers of TADs increases by 25% in MM, the average size of TADs is smaller, and about 20% of genomic regions switch their chromatin A/B compartment types. In summary, we report a 3D genome interaction map of aneuploid MM cells and reveal the relationship among CNVs, translocations, 3D genome reorganization, and gene expression regulation.

Chromosome conformation capture techniques enable the study of genome organization in cancer cells. Here, the authors use Hi-C, WGS, and RNA-seq to study the 3D genome of multiple myeloma and find that genome disorganization is associated with copy number variations and changes in gene expression.

Developmental pathways associated with cancer metastasis: Notch, Wnt, and Hedgehog

Master developmental pathways, such as Notch, Wnt, and Hedgehog, are signaling systems that control proliferation, cell death, motility, migration, and stemness. These systems are not only commonly activated in many solid tumors, where they drive or contribute to cancer initiation, but also in primary and metastatic tumor development. The reactivation of developmental pathways in cancer stroma favors the development of cancer stem cells and allows their maintenance, indicating these signaling pathways as particularly attractive targets for efficient anticancer therapies, especially in advanced primary tumors and metastatic cancers. Metastasis is the worst feature of cancer development. This feature results from a cascade of events emerging from the hijacking of epithelial-mesenchymal transition, angiogenesis, migration, and invasion by transforming cells and is associated with poor survival, drug resistance, and tumor relapse. In the present review, we summarize and discuss experimental data suggesting pivotal roles for developmental pathways in cancer development and metastasis, considering the therapeutic potential. Emerging targeted antimetastatic therapies based on Notch, Wnt, and Hedgehog pathways are also discussed.