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Despite recent therapeutic advances that have doubled the median survival time of patients with multiple myeloma, intratumor genetic heterogeneity contributes to disease progression and emergence of drug resistance. miRNAs are noncoding small RNAs that play important roles in the regulation of gene expression and have been implicated in cancer progression and drug resistance. We investigated the role of the miR-221-222 family in dexamethasone-induced drug resistance in multiple myeloma using the isogenic cell lines MM1R and MM1S, which represent models of resistance and sensitivity, respectively. Analysis of array comparative genome hybridization data revealed gain of chromosome X regions at band p11.3, wherein the miR-221-222 resides, in resistant MM1R cells but not in sensitive MM1S cells. DNA copy number gains in MM1R cells were associated with increased miR-221-222 expression and downregulation of p53-upregulated modulator of apoptosis (PUMA) as a likely proapoptotic target. We confirmed PUMA mRNA as a direct target of miR-221-222 in MM1S and MM1R cells by both gain-of-function and loss-of-function studies. In addition, miR-221-222 treatment rendered MM1S cells resistant to dexamethasone, whereas anti-miR-221-222 partially restored the dexamethasone sensitivity of MM1R cells. These studies have uncovered a role for miR-221-222 in multiple myeloma drug resistance and suggest a potential therapeutic role for inhibitors of miR-221-222 binding to PUMA mRNA as a means of overcoming dexamethasone resistance in patients. The clinical utility of this approach is predicated on the ability of antisense miR-221-222 to increase survival while reducing tumor burden and is strongly supported by the metastatic propensity of MM1R cells in preclinical mouse xenograft models of multiple myeloma. Moreover, our observation of increased levels of miR-221-222 with decreased PUMA expression in multiple myeloma cells from patients at relapse versus untreated controls suggests an even broader role for miR-221-222 in drug resistance and provides a rationale for the targeting of miR-221-222 as a means of improving patient outcomes., (©2015 American Association for Cancer Research.)

Wnt/β-catenin signaling underlies the pathogenesis of a broad range of human cancers, including the deadly plasma cell cancer multiple myeloma. In this study, we report that downregulation of the tumor suppressor microRNA miR-30-5p is a frequent pathogenetic event in multiple myeloma. Evidence was developed that miR-30-5p downregulation occurs as a result of interaction between multiple myeloma cells and bone marrow stromal cells, which in turn enhances expression of BCL9, a transcriptional coactivator of the Wnt signaling pathway known to promote multiple myeloma cell proliferation, survival, migration, drug resistance, and formation of multiple myeloma cancer stem cells. The potential for clinical translation of strategies to re-express miR-30-5p as a therapeutic approach was further encouraged by the capacity of miR-30c and miR-30 mix to reduce tumor burden and metastatic potential in vivo in three murine xenograft models of human multiple myeloma without adversely affecting associated bone disease. Together, our findings offer a preclinical rationale to explore miR-30-5p delivery as an effective therapeutic strategy to eradicate multiple myeloma cells in vivo., (©2014 AACR.)

Background: Multiple myeloma (MM) is a malignant proliferation of plasma B cells. Based on recurrent aneuploidy such as copy number alterations (CNAs), myeloma is divided into two subtypes with different CNA patterns and patient survival outcomes. How aneuploidy events arise, and whether they contribute to cancer cell evolution are actively studied. The large amount of transcriptomic changes resultant of CNAs (dosage effect) pose big challenges for identifying functional consequences of CNAs in myeloma in terms of specific driver genes and pathways. In this study, we hypothesize that gene-wise dosage effect varies as a result from complex regulatory networks that translate the impact of CNAs to gene expression, and studying this variation can provide insights into functional effects of CNAs., Results: We propose gene-wise dosage effect score and genome-wide karyotype plot as tools to measure and visualize concordant copy number and expression changes across cancer samples. We find that dosage effect in myeloma is widespread yet variable, and it is correlated with gene expression level and CNA frequencies in different chromosomes. Our analysis suggests that despite the enrichment of differentially expressed genes between hyperdiploid MM and non-hyperdiploid MM in the trisomy chromosomes, the chromosomal proportion of dosage sensitive genes is higher in the non-trisomy chromosomes. Dosage-sensitive genes are enriched by genes with protein translation and localization functions, and dosage resistant genes are enriched by apoptosis genes. These results point to future studies on differential dosage sensitivity and resistance of pro- and anti-proliferation pathways and their variation across patients as therapeutic targets and prognosis markers., Conclusions: Our findings support the hypothesis that recurrent CNAs in myeloma are selected by their functional consequences. The novel dosage effect score defined in this work will facilitate integration of copy number and expression data for identifying driver genes in cancer genomics studies. The accompanying R code is available at http://www.canevolve.org/dosageEffect/.

Multiple myeloma (MM) is a cancer of antibody-making plasma cells. It frequently harbors alterations in DNA and chromosome copy numbers, and can be divided into two major subtypes, hyperdiploid (HMM) and non-hyperdiploid multiple myeloma (NHMM). The two subtypes have different survival prognosis, possibly due to different but converging paths to oncogenesis. Existing methods for identifying the two subtypes are fluorescence in situ hybridization (FISH) and copy number microarrays, with increased cost and sample requirements. We hypothesize that chromosome alterations have their imprint in gene expression through dosage effect. Using five MM expression datasets that have HMM status measured by FISH and copy number microarrays, we have developed and validated a K-nearest-neighbor method to classify MM into HMM and NHMM based on gene expression profiles. Classification accuracy for test datasets ranges from 0.83 to 0.88. This classification will enable researchers to study differences and commonalities of the two MM subtypes in disease biology and prognosis using expression datasets without need for additional subtype measurements. Our study also supports the advantages of using cancer specific characteristics in feature design and pooling multiple rounds of classification results to improve accuracy. We provide R source code and processed datasets at www.ChengLiLab.org/software.

Multiple myeloma is a hematological cancer of plasma B-cells and remains incurable. Two major subtypes of myeloma, hyperdiploid (HMM) and non-hyperdiploid myeloma (NHMM), have distinct chromosomal alterations and different survival outcomes. Transcription factors (TrFs) have been implicated in myeloma oncogenesis but their dysregulation in myeloma subtypes are less studied. Here we develop a TrF-pathway co-expression analysis to identify altered co-expression between two sample types. We apply the method to the two myeloma subtypes and the cell cycle arrest pathway, which is significantly differentially expressed between the two subtypes. We find that TrFs MYC, NF-κB and HOXA9 have significantly lower co-expression with cell cycle arrest in HMM, co-occurring with their over-activation in HMM. In contrast, TrFs ESR1, SP1 and E2F1 have significantly lower co-expression with cell cycle arrest in NHMM. SP1 ChIP targets are enriched by cell cycle arrest genes. These results motivate a cooperation model of ESR1 and SP1 in regulating cell cycle arrest, and a hypothesis that their over-activation in NHMM disrupts proper regulation of cell cycle arrest. Co-targeting ESR1 and SP1 shows a synergistic effect on inhibiting myeloma proliferation in NHMM cell lines. Therefore, studying TrF-pathway co-expression dysregulation in human cancers facilitates forming novel hypotheses towards clinical utility.