The location of the t(4;14) translocation breakpoint within the NSD2 gene identifies a subset of patients with high-risk NDMM.

Although translocation events between chromosome 4 (NSD2 gene) and chromosome 14 (immunoglobulin heavy chain [IgH] locus) (t(4;14)) is considered high risk in newly diagnosed multiple myeloma (NDMM), only ∼30% to 40% of t(4;14) patients are clinically high risk. We generated and compared a large whole genome sequencing (WGS) and transcriptome (RNA sequencing) from 258 t(4;14) (n = 153 discovery, n = 105 replication) and 183 non-t(4;14) NDMM patients with associated clinical data. A landmark survival analysis indicated only ∼25% of t(4;14) patients had an overall survival (OS) <24 months, and a comparative analysis of the patient subgroups identified biomarkers associated with this poor outcome, including translocation breakpoints located in the NSD2 gene and expression of IgH-NSD2 fusion transcripts. Three breakpoints were identified and are designated as: "no-disruption" (upstream of NSD2), "early-disruption" (in the 5' UTR), and "late-disruption" (within the NSD2 gene). Our results show a significant difference in OS based on the location of DNA breakpoints (median OS 28.6 "late-disruption" vs 59.2 "early disruption" vs 75.1 months "no disruption"). These findings have been replicated in an independent replication dataset. Also, univariate and multivariate analysis suggest high-risk markers such as del17p, 1p independently contribute to poor outcome in t(4;14) MM patients.

Loss of COP9 signalosome genes at 2q37 is associated with IMiD resistance in multiple myeloma.

The acquisition of a multidrug refractory state is a major cause of mortality in myeloma. Myeloma drugs that target the cereblon (CRBN) protein include widely used immunomodulatory drugs (IMiDs), and newer CRBN E3 ligase modulator drugs (CELMoDs), in clinical trials. CRBN genetic disruption causes resistance and poor outcomes with IMiDs. Here, we investigate alternative genomic associations of IMiD resistance, using large whole-genome sequencing patient datasets (n = 522 cases) at newly diagnosed, lenalidomide (LEN)-refractory and lenalidomide-then-pomalidomide (LEN-then-POM)-refractory timepoints. Selecting gene targets reproducibly identified by published CRISPR/shRNA IMiD resistance screens, we found little evidence of genetic disruption by mutation associated with IMiD resistance. However, we identified a chromosome region, 2q37, containing COP9 signalosome members COPS7B and COPS8, copy loss of which significantly enriches between newly diagnosed (incidence 5.5%), LEN-refractory (10.0%), and LEN-then-POM-refractory states (16.4%), and may adversely affect outcomes when clonal fraction is high. In a separate dataset (50 patients) with sequential samples taken throughout treatment, we identified acquisition of 2q37 loss in 16% cases with IMiD exposure, but none in cases without IMiD exposure. The COP9 signalosome is essential for maintenance of the CUL4-DDB1-CRBN E3 ubiquitin ligase. This region may represent a novel marker of IMiD resistance with clinical utility.

Multiple cereblon genetic changes are associated with acquired resistance to lenalidomide or pomalidomide in multiple myeloma.

Emergence of drug resistance to all available therapies is the major challenge to improving survival in myeloma. Cereblon (CRBN) is the essential binding protein of the widely used immunomodulatory drugs (IMiDs) and novel CRBN E3 ligase modulator drugs (CELMoDs) in myeloma, as well as certain proteolysis targeting chimeras (PROTACs), in development for a range of diseases. Using whole-genome sequencing (WGS) data from 455 patients and RNA sequencing (RNASeq) data from 655 patients, including newly diagnosed (WGS, n = 198; RNASeq, n = 437), lenalidomide (LEN)-refractory (WGS, n = 203; RNASeq, n = 176), and pomalidomide (POM)-refractory cohorts (WGS, n = 54; RNASeq, n = 42), we found incremental increases in the frequency of 3 CRBN aberrations, namely point mutations, copy losses/structural variations, and a specific variant transcript (exon 10 spliced), with progressive IMiD exposure, until almost one-third of patients had CBRN alterations by the time they were POM refractory. We found all 3 CRBN aberrations were associated with inferior outcomes to POM in those already refractory to LEN, including those with gene copy losses and structural variations, a finding not previously described. This represents the first comprehensive analysis and largest data set of CBRN alterations in myeloma patients as they progress through therapy. It will help inform patient selection for sequential therapies with CRBN-targeting drugs.

Comparison of RNA-seq and microarray platforms for splice event detection using a cross-platform algorithm.

BACKGROUND: RNA-seq is a reference technology for determining alternative splicing at genome-wide level. Exon arrays remain widely used for the analysis of gene expression, but show poor validation rate with regard to splicing events. Commercial arrays that include probes within exon junctions have been developed in order to overcome this problem. We compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of transcript splicing events. Three different breast cancer cell lines were treated with CX-4945, a drug that severely affects splicing. To enable a direct comparison of the two platforms, we adapted EventPointer, an algorithm that detects and labels alternative splicing events using junction arrays, to work also on RNA-seq data. Common results and discrepancies between the technologies were validated and/or resolved by over 200 PCR experiments. RESULTS: As might be expected, RNA-seq appears superior in cases where the technologies disagree and is able to discover novel splicing events beyond the limitations of physical probe-sets. We observe a high degree of coherence between the two technologies, however, with correlation of EventPointer results over 0.90. Through decimation, the detection power of the junction arrays is equivalent to RNA-seq with up to 60 million reads. CONCLUSIONS: Our results suggest, therefore, that exon-junction arrays are a viable alternative to RNA-seq for detection of alternative splicing events when focusing on well-described transcriptional regions.

CalMaTe: a method and software to improve allele-specific copy number of SNP arrays for downstream segmentation.

SUMMARY: CalMaTe calibrates preprocessed allele-specific copy number estimates (ASCNs) from DNA microarrays by controlling for single-nucleotide polymorphism-specific allelic crosstalk. The resulting ASCNs are on average more accurate, which increases the power of segmentation methods for detecting changes between copy number states in tumor studies including copy neutral loss of heterozygosity. CalMaTe applies to any ASCNs regardless of preprocessing method and microarray technology, e.g. Affymetrix and Illumina. AVAILABILITY: The method is available on CRAN (http://cran.r-project.org/) in the open-source R package calmate, which also includes an add-on to the Aroma Project framework (http://www.aroma-project.org/).

Multiple Myeloma Patient Tumors With High Levels of Cereblon Exon-10 Deletion Splice Variant Upregulate Clinically Targetable Pro-Inflammatory Cytokine Pathways.

Immunomodulatory drugs (IMiDs), including lenalidomide and pomalidomide, are used in the routine treatment for multiple myeloma (MM) patients. Cereblon (CRBN) is the direct molecular target of IMiDs. While CRBN is not an essential gene for MM cell proliferation, the frequency of CRBN genetic aberrations, including mutation, copy number loss, and exon-10 (which includes a portion of the IMiD-binding domain) splicing, have been reported to incrementally increase in later-line patients. CRBN exon-10 splicing has also been shown to be associated with decreased progression-free survival in both newly diagnosed and relapsed refractory MM patients. Although we did not find significant general splicing defects among patients with CRBN exon-10 splice variant when compared to those expressing the full-length transcript, we identified upregulated TNFA signaling via NFKB, inflammatory response, and IL-10 signaling pathways in patients with exon-10 splice variant across various data sets-all potentially promoting tumor growth via chronic growth signals. We examined master regulators that mediate transcriptional programs in CRBN exon-10 splice variant patients and identified BATF, EZH2, and IKZF1 as the key candidates across the four data sets. Upregulated downstream targets of BATF, EZH2, and IKZF1 are components of TNFA signaling via NFKB, IL2/STAT5 signaling pathways, and IFNG response pathways. Previously, BATF-mediated transcriptional regulation was associated with venetoclax sensitivity in MM. Interestingly, we found that an EZH2 sensitivity gene expression signature also correlated with high BATF or venetoclax sensitivity scores in these tumors. Together, these data provide a rationale for investigating EZH2 inhibitors or venetoclax in combination with the next generation CRBN-targeting agents, such as CELMoDs, for patients overexpressing the CRBN exon-10 splice variant.

ACNE: a summarization method to estimate allele-specific copy numbers for Affymetrix SNP arrays.

MOTIVATION: Current algorithms for estimating DNA copy numbers (CNs) borrow concepts from gene expression analysis methods. However, single nucleotide polymorphism (SNP) arrays have special characteristics that, if taken into account, can improve the overall performance. For example, cross hybridization between alleles occurs in SNP probe pairs. In addition, most of the current CN methods are focused on total CNs, while it has been shown that allele-specific CNs are of paramount importance for some studies. Therefore, we have developed a summarization method that estimates high-quality allele-specific CNs. RESULTS: The proposed method estimates the allele-specific DNA CNs for all Affymetrix SNP arrays dealing directly with the cross hybridization between probes within SNP probesets. This algorithm outperforms (or at least it performs as well as) other state-of-the-art algorithms for computing DNA CNs. It better discerns an aberration from a normal state and it also gives more precise allele-specific CNs. AVAILABILITY: The method is available in the open-source R package ACNE, which also includes an add on to the aroma.affymetrix framework (http://www.aroma-project.org/).

Integrative multi-omics identifies high risk multiple myeloma subgroup associated with significant DNA loss and dysregulated DNA repair and cell cycle pathways.

BACKGROUND: Despite significant therapeutic advances in improving lives of multiple myeloma (MM) patients, it remains mostly incurable, with patients ultimately becoming refractory to therapies. MM is a genetically heterogeneous disease and therapeutic resistance is driven by a complex interplay of disease pathobiology and mechanisms of drug resistance. We applied a multi-omics strategy using tumor-derived gene expression, single nucleotide variant, copy number variant, and structural variant profiles to investigate molecular subgroups in 514 newly diagnosed MM (NDMM) samples and identified 12 molecularly defined MM subgroups (MDMS1-12) with distinct genomic and transcriptomic features. RESULTS: Our integrative approach let us identify NDMM subgroups with transversal profiles to previously described ones, based on single data types, which shows the impact of this approach for disease stratification. One key novel subgroup is our MDMS8, associated with poor clinical outcome [median overall survival, 38 months (global log-rank p-value < 1 × 10-6)], which uniquely presents a broad genomic loss (> 9% of entire genome, t-test p value < 1e-5) driving dysregulation of various transcriptional programs affecting DNA repair and cell cycle/mitotic processes. This subgroup was validated on multiple independent datasets, and a master regulator analyses identified transcription factors controlling MDMS8 transcriptomic profile, including CKS1B and PRKDC among others, which are regulators of the DNA repair and cell cycle pathways. CONCLUSION: Using multi-omics unsupervised clustering we were able to discover a new high-risk multiple myeloma patient segment. This high-risk group presents diverse previously known genetic markers, but also a new characteristic defined by accumulation of genomic loss which seems to drive transcriptional dysregulation of cell cycle, DNA repair and DNA damage. Finally, our work identified various master regulators, including E2F2 and CKS1B as the genes controlling these key biological pathways.

Getting DNA copy numbers without control samples.

BACKGROUND: The selection of the reference to scale the data in a copy number analysis has paramount importance to achieve accurate estimates. Usually this reference is generated using control samples included in the study. However, these control samples are not always available and in these cases, an artificial reference must be created. A proper generation of this signal is crucial in terms of both noise and bias.We propose NSA (Normality Search Algorithm), a scaling method that works with and without control samples. It is based on the assumption that genomic regions enriched in SNPs with identical copy numbers in both alleles are likely to be normal. These normal regions are predicted for each sample individually and used to calculate the final reference signal. NSA can be applied to any CN data regardless the microarray technology and preprocessing method. It also finds an optimal weighting of the samples minimizing possible batch effects. RESULTS: Five human datasets (a subset of HapMap samples, Glioblastoma Multiforme (GBM), Ovarian, Prostate and Lung Cancer experiments) have been analyzed. It is shown that using only tumoral samples, NSA is able to remove the bias in the copy number estimation, to reduce the noise and therefore, to increase the ability to detect copy number aberrations (CNAs). These improvements allow NSA to also detect recurrent aberrations more accurately than other state of the art methods. CONCLUSIONS: NSA provides a robust and accurate reference for scaling probe signals data to CN values without the need of control samples. It minimizes the problems of bias, noise and batch effects in the estimation of CNs. Therefore, NSA scaling approach helps to better detect recurrent CNAs than current methods. The automatic selection of references makes it useful to perform bulk analysis of many GEO or ArrayExpress experiments without the need of developing a parser to find the normal samples or possible batches within the data. The method is available in the open-source R package NSA, which is an add-on to the aroma.cn framework. http://www.aroma-project.org/addons.