Whole-genome sequencing of multiple myeloma reveals oncogenic pathways are targeted somatically through multiple mechanisms

Biological and clinical determinants shaping heterogeneity in mantle cell lymphoma

ABSTRACT

Mantle cell lymphoma (MCL) is an uncommon mature B-cell lymphoma that presents a clinical spectrum ranging from indolent to aggressive disease, with challenges in disease management and prognostication. MCL is characterized by significant genomic instability, affecting various cellular processes, including cell cycle regulation, cell survival, DNA damage response and telomere maintenance, NOTCH and NF-κB/ B-cell receptor pathways, and chromatin modification. Recent molecular and next-generation sequencing studies unveiled a broad genetic diversity among the 2 molecular subsets, conventional MCL (cMCL) and leukemic nonnodal MCL (nnMCL), which may partially explain their clinical heterogeneity. Some asymptomatic and genetically stable nnMCL not requiring treatment at diagnosis may eventually progress clinically. Overall, the high proliferation of tumor cells, blastoid morphology, TP53 and/or CDKN2A/B inactivation, and high genetic complexity influence treatment outcome in cases treated with standard regimens. Emerging targeted and immunotherapeutic strategies are promising for refractory or relapsed cases and a few genetic and nongenetic determinants of refractoriness have been reported. This review summarizes the recent advances in MCL biology, focusing on molecular insights, prognostic markers, and novel therapeutic approaches.

The Interplay between the DNA Damage Response (DDR) Network and the Mitogen-Activated Protein Kinase (MAPK) Signaling Pathway in Multiple Myeloma

The DNA damage response (DDR) network and the mitogen-activated protein kinase (MAPK) signaling pathway are crucial mechanisms for the survival of all living beings. An accumulating body of evidence suggests that there is crosstalk between these two systems, thus favoring the appropriate functioning of multi-cellular organisms. On the other hand, aberrations within these mechanisms are thought to play a vital role in the onset and progression of several diseases, including cancer, as well as in the emergence of drug resistance. Here, we provide an overview of the current knowledge regarding alterations in the DDR machinery and the MAPK signaling pathway as well as abnormalities in the DDR/MAPK functional crosstalk in multiple myeloma, the second most common hematologic malignancy. We also present the latest advances in the development of anti-myeloma drugs targeting crucial DDR- and MAPK-associated molecular components. These data could potentially be exploited to discover new therapeutic targets and effective biomarkers as well as for the design of novel clinical trials. Interestingly, they might provide a new approach to increase the efficacy of anti-myeloma therapy by combining drugs targeting the DDR network and the MAPK signaling pathway.

Approach to High-Risk Multiple Myeloma

Improving the outcome of high-risk myeloma (HRMM) is a key therapeutic aim for the next decade. To achieve this aim, it is necessary to understand in detail the genetic drivers underlying this clinical behavior and to target its biology therapeutically. Advances have already been made, with a focus on consensus guidance and the application of novel immunotherapeutic approaches. Cases of HRMM are likely to have impaired prognosis even with novel strategies. However, if disease eradication and minimal disease states are achieved, then cure may be possible.

Accurate and sensitive mutational signature analysis with MuSiCal

Mutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. Here we present Mutational Signature Calculator (MuSiCal), a rigorous analytical framework with algorithms that solve major problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing more than 2,700 cancer genomes, we provide an improved catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous 'flat' signatures and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.

Hotspot propensity across mutational processes

The sparsity of mutations observed across tumours hinders our ability to study mutation rate variability at nucleotide resolution. To circumvent this, here we investigated the propensity of mutational processes to form mutational hotspots as a readout of their mutation rate variability at single base resolution. Mutational signatures 1 and 17 have the highest hotspot propensity (5-78 times higher than other processes). After accounting for trinucleotide mutational probabilities, sequence composition and mutational heterogeneity at 10 Kbp, most (94-95%) signature 17 hotspots remain unexplained, suggesting a significant role of local genomic features. For signature 1, the inclusion of genome-wide distribution of methylated CpG sites into models can explain most (80-100%) of the hotspot propensity. There is an increased hotspot propensity of signature 1 in normal tissues and de novo germline mutations. We demonstrate that hotspot propensity is a useful readout to assess the accuracy of mutation rate models at nucleotide resolution. This new approach and the findings derived from it open up new avenues for a range of somatic and germline studies investigating and modelling mutagenesis.

Contribution of histone variants to aneuploidy: a cancer perspective

Histone variants, which generally differ in few amino acid residues, can replace core histones (H1, H2A, H2B, and H3) to confer specific structural and functional features to regulate cellular functions. In addition to their role in DNA packaging, histones modulate key processes such as gene expression regulation and chromosome segregation, which are frequently dysregulated in cancer cells. During the years, histones variants have gained significant attention as gatekeepers of chromosome stability, raising interest in understanding how structural and functional alterations can contribute to tumourigenesis. Beside the well-established role of the histone H3 variant CENP-A in centromere specification and maintenance, a growing body of literature has described mutations, aberrant expression patterns and post-translational modifications of a variety of histone variants in several cancers, also coining the term "oncohistones." At the molecular level, mechanistic studies have been dissecting the biological mechanisms behind histones and missegregation events, with the potential to uncover novel clinically-relevant targets. In this review, we focus on the current understanding and highlight knowledge gaps of the contribution of histone variants to aneuploidy, and we have compiled a database (HistoPloidyDB) of histone gene alterations linked to aneuploidy in cancers of the The Cancer Genome Atlas project.

Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes

Ferroptosis is distinct from classic apoptotic cell death characterized by the accumulation of reactive oxygen species (ROS) and lipid peroxides on the cell membrane. Increasing findings have demonstrated that ferroptosis plays an important role in cancer development, but the exploration of ferroptosis in breast cancer is limited. In our study, we aimed to establish a ferroptosis activation-related model based on the differentially expressed genes between a group exhibiting high ferroptosis activation and a group exhibiting low ferroptosis activation. By using machine learning to establish the model, we verified the accuracy and efficiency of our model in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) set and gene expression omnibus (GEO) dataset. Additionally, our research innovatively utilized single-cell RNA sequencing data to systematically reveal the microenvironment in the high and low FeAS groups, which demonstrated differences between the two groups from comprehensive aspects, including the activation condition of transcription factors, cell pseudotime features, cell communication, immune infiltration, chemotherapy efficiency, and potential drug resistance. In conclusion, different ferroptosis activation levels play a vital role in influencing the outcome of breast cancer patients and altering the tumor microenvironment in different molecular aspects. By analyzing differences in ferroptosis activation levels, our risk model is characterized by a good prognostic capacity in assessing the outcome of breast cancer patients, and the risk score can be used to prompt clinical treatment to prevent potential drug resistance. By identifying the different tumor microenvironment landscapes between the high- and low-risk groups, our risk model provides molecular insight into ferroptosis in breast cancer patients.

SWI/SNF complexes in hematological malignancies: biological implications and therapeutic opportunities

Hematological malignancies are a highly heterogeneous group of diseases with varied molecular and phenotypical characteristics. SWI/SNF (SWItch/Sucrose Non-Fermentable) chromatin remodeling complexes play significant roles in the regulation of gene expression, being essential for processes such as cell maintenance and differentiation in hematopoietic stem cells. Furthermore, alterations in SWI/SNF complex subunits, especially in ARID1A/1B/2, SMARCA2/4, and BCL7A, are highly recurrent across a wide variety of lymphoid and myeloid malignancies. Most genetic alterations cause a loss of function of the subunit, suggesting a tumor suppressor role. However, SWI/SNF subunits can also be required for tumor maintenance or even play an oncogenic role in certain disease contexts. The recurrent alterations of SWI/SNF subunits highlight not only the biological relevance of SWI/SNF complexes in hematological malignancies but also their clinical potential. In particular, increasing evidence has shown that mutations in SWI/SNF complex subunits confer resistance to several antineoplastic agents routinely used for the treatment of hematological malignancies. Furthermore, mutations in SWI/SNF subunits often create synthetic lethality relationships with other SWI/SNF or non-SWI/SNF proteins that could be exploited therapeutically. In conclusion, SWI/SNF complexes are recurrently altered in hematological malignancies and some SWI/SNF subunits may be essential for tumor maintenance. These alterations, as well as their synthetic lethal relationships with SWI/SNF and non-SWI/SNF proteins, may be pharmacologically exploited for the treatment of diverse hematological cancers.

Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma

Large-scale analyses of genomic data from patients with newly diagnosed multiple myeloma (ndMM) have been undertaken, however, large-scale analysis of relapsed/refractory MM (rrMM) has not been performed. We hypothesize that somatic variants chronicle the therapeutic exposures and clonal structure of myeloma from ndMM to rrMM stages. We generated whole-genome sequencing (WGS) data from 418 tumors (386 patients) derived from 6 rrMM clinical trials and compared them with WGS from 198 unrelated patients with ndMM in a population-based case-control fashion. We identified significantly enriched events at the rrMM stage, including drivers (DUOX2, EZH2, TP53), biallelic inactivation (TP53), noncoding mutations in bona fide drivers (TP53BP1, BLM), copy number aberrations (CNAs; 1qGain, 17pLOH), and double-hit events (Amp1q-ISS3, 1qGain-17p loss-of-heterozygosity). Mutational signature analysis identified a subclonal defective mismatch repair signature enriched in rrMM and highly active in high mutation burden tumors, a likely feature of therapy-associated expanding subclones. Further analysis focused on the association of genomic aberrations enriched at different stages of resistance to immunomodulatory agent (IMiD)-based therapy. This analysis revealed that TP53, DUOX2, 1qGain, and 17p loss-of-heterozygosity increased in prevalence from ndMM to lenalidomide resistant (LENR) to pomalidomide resistant (POMR) stages, whereas enrichment of MAML3 along with immunoglobulin lambda (IGL) and MYC translocations distinguished POM from the LEN subgroup. Genomic drivers associated with rrMM are those that confer clonal selective advantage under therapeutic pressure. Their role in therapy evasion should be further evaluated in longitudinal patient samples, to confirm these associations with the evolution of clinical resistance and to identify molecular subsets of rrMM for the development of targeted therapies.

Multi-omics approach dissects cis-regulatory mechanisms underlying North Carolina macular dystrophy, a retinal enhanceropathy

North Carolina macular dystrophy (NCMD) is a rare autosomal-dominant disease affecting macular development. The disease is caused by non-coding single-nucleotide variants (SNVs) in two hotspot regions near PRDM13 and by duplications in two distinct chromosomal loci, overlapping DNase I hypersensitive sites near either PRDM13 or IRX1. To unravel the mechanisms by which these variants cause disease, we first established a genome-wide multi-omics retinal database, RegRet. Integration of UMI-4C profiles we generated on adult human retina then allowed fine-mapping of the interactions of the PRDM13 and IRX1 promoters and the identification of eighteen candidate cis-regulatory elements (cCREs), the activity of which was investigated by luciferase and Xenopus enhancer assays. Next, luciferase assays showed that the non-coding SNVs located in the two hotspot regions of PRDM13 affect cCRE activity, including two NCMD-associated non-coding SNVs that we identified herein. Interestingly, the cCRE containing one of these SNVs was shown to interact with the PRDM13 promoter, demonstrated in vivo activity in Xenopus, and is active at the developmental stage when progenitor cells of the central retina exit mitosis, suggesting that this region is a PRDM13 enhancer. Finally, mining of single-cell transcriptional data of embryonic and adult retina revealed the highest expression of PRDM13 and IRX1 when amacrine cells start to synapse with retinal ganglion cells, supporting the hypothesis that altered PRDM13 or IRX1 expression impairs interactions between these cells during retinogenesis. Overall, this study provides insight into the cis-regulatory mechanisms of NCMD and supports that this condition is a retinal enhanceropathy.

Multiple Myeloma: Bioinformatic Analysis for Identification of Key Genes and Pathways

Multiple myeloma (MM) is a hematological malignancy in which monoclonal plasma cells multiply in the bone marrow and monoclonal immunoglobulins are overproduced in older people. Several molecular and cytogenetic advances allow scientists to identify several genetic and chromosomal abnormalities that cause the disease. The comprehension of the pathophysiology of MM requires an understanding of the characteristics of malignant clones and the changes in the bone marrow microenvironment. This study aims to identify the central genes and to determine the key signaling pathways in MM by in silico approaches. A list of 114 differentially expressed genes (DEGs) is important in the prognosis of MM. The DEGs are collected from scientific publications and databases (https://www.ncbi.nlm.nih.gov/). These data are analyzed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) software (https://string-db.org/) through the construction of protein-protein interaction (PPI) networks and enrichment analysis of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, by CytoHubba, AutoAnnotate, Bingo Apps plugins in Cytoscape software (https://cytoscape.org/) and by DAVID database (https://david.ncifcrf.gov/). The analysis of the results shows that there are 7 core genes, including TP53; MYC; CDND1; IL6; UBA52; EZH2, and MDM2. These top genes appear to play a role in the promotion and progression of MM. According to functional enrichment analysis, these genes are mainly involved in the following signaling pathways: Epstein-Barr virus infection, microRNA pathway, PI3K-Akt signaling pathway, and p53 signaling pathway. Several crucial genes, including TP53, MYC, CDND1, IL6, UBA52, EZH2, and MDM2, are significantly correlated with MM, which may exert their role in the onset and evolution of MM.

Tracking Clonal Evolution of Multiple Myeloma Using Targeted Next-Generation DNA Sequencing

Clonal evolution drives treatment failure in multiple myeloma (MM). Here, we used a custom 372-gene panel to track genetic changes occurring during MM progression at different stages of the disease. A tumor-only targeted next-generation DNA sequencing was performed on 69 samples sequentially collected from 30 MM patients. The MAPK/ERK pathway was mostly affected with KRAS mutated in 47% of patients. Acquisition and loss of mutations were observed in 63% and 37% of patients, respectively. Four different patterns of mutation evolution were found: branching-, mutation acquisition-, mutation loss- and a stable mutational pathway. Better response to anti-myeloma therapy was more frequently observed in patients who followed the mutation loss-compared to the mutation acquisition pathway. More than two-thirds of patients had druggable genes mutated (including cases of heavily pre-treated disease). Only 7% of patients had a stable copy number variants profile. Consequently, a redistribution in stages according to R-ISS between the first and paired samples (R-ISS″) was seen. The higher the R-ISS″, the higher the risk of MM progression and death. We provided new insights into the genetics of MM evolution, especially in heavily pre-treated patients. Additionally, we confirmed that redefining R-ISS at MM relapse is of high clinical value.

Racial and ethnic differences in clonal hematopoiesis, tumor markers, and outcomes of patients with multiple myeloma

Age of onset and survival disparities exist for racial and ethnic minority patients diagnosed with MM.

Differences in somatic mutations in tumor and blood (ie, clonal hematopoiesis) may contribute to disparities in outcomes observed.

Multiple myeloma (MM) incidence, mortality, and survival vary by race and ethnicity, but the causes of differences remain unclear. We investigated demographic, clinical, and molecular features of diverse MM patients to elucidate mechanisms driving clinical disparities. This study included 495 MM patients (self-reported Hispanic, n = 45; non-Hispanic Black, n = 52; non-Hispanic White, n = 398). Hispanic and non-Hispanic Black individuals had an earlier age of onset than non-Hispanic White individuals (53 and 57 vs 63 years, respectively, P < .001). There were no differences in treatment by race and ethnicity groups, but non-Hispanic Black patients had a longer time to hematopoietic cell transplant than non-Hispanic White patients (376 days vs 248 days; P = .01). Overall survival (OS) was improved for non-Hispanic Black compared with non-Hispanic White patients (HR, 0.50; 95% CI, 0.31-0.81; P = .005), although this association was attenuated after adjusting for clinical features (HR, 0.62; 95% CI, 0.37-1.03; P = .06). Tumor mutations in IRF4 were most common in Hispanic patients, and mutations in SP140, AUTS2, and SETD2 were most common in non-Hispanic Black patients. Differences in tumor expression of BCL7A, SPEF2, and ANKRD26 by race and ethnicity were observed. Clonal hematopoiesis was detected in 12% of patients and associated with inferior OS in non-Hispanic Black patients compared with patients without clonal hematopoiesis (HR, 4.36; 95% CI, 1.36-14.00). This study provides insight into differences in molecular features that may drive clinical disparities in MM patients receiving comparable treatment, with the novel inclusion of Hispanic individuals.

KRAS and RAS-MAPK Pathway Deregulation in Mature B Cell Lymphoproliferative Disorders

KRAS mutations account for the most frequent mutations in human cancers, and are generally correlated with disease aggressiveness, poor prognosis, and poor response to therapies. KRAS is required for adult hematopoiesis and plays a key role in B cell development and mature B cell proliferation and survival, proved to be critical for B cell receptor-induced ERK pathway activation. In mature B cell neoplasms, commonly seen in adults, KRAS and RAS-MAPK pathway aberrations occur in a relevant fraction of patients, reaching high recurrence in some specific subtypes like multiple myeloma and hairy cell leukemia. As inhibitors targeting the RAS-MAPK pathway are being developed and improved, it is of outmost importance to precisely identify all subgroups of patients that could potentially benefit from their use. Herein, we review the role of KRAS and RAS-MAPK signaling in malignant hematopoiesis, focusing on mature B cell lymphoproliferative disorders. We discuss KRAS and RAS-MAPK pathway aberrations describing type, incidence, mutual exclusion with other genetic abnormalities, and association with prognosis. We review the current therapeutic strategies applied in mature B cell neoplasms to counteract RAS-MAPK signaling in pre-clinical and clinical studies, including most promising combination therapies. We finally present an overview of genetically engineered mouse models bearing KRAS and RAS-MAPK pathway aberrations in the hematopoietic compartment, which are valuable tools in the understanding of cancer biology and etiology.

Single-cell profiling of tumour evolution in multiple myeloma - opportunities for precision medicine

Multiple myeloma (MM) is a haematological malignancy of plasma cells characterized by substantial intraclonal genetic heterogeneity. Although therapeutic advances made in the past few years have led to improved outcomes and longer survival, MM remains largely incurable. Over the past decade, genomic analyses of patient samples have demonstrated that MM is not a single disease but rather a spectrum of haematological entities that all share similar clinical symptoms. Moreover, analyses of samples from monoclonal gammopathy of undetermined significance and smouldering MM have also shown the existence of genetic heterogeneity in precursor stages, in some cases remarkably similar to that of MM. This heterogeneity highlights the need for a greater dissection of underlying disease biology, especially the clonal diversity and molecular events underpinning MM at each stage to enable the stratification of individuals with a high risk of progression. Emerging single-cell sequencing technologies present a superlative solution to delineate the complexity of monoclonal gammopathy of undetermined significance, smouldering MM and MM. In this Review, we discuss how genomics has revealed novel insights into clonal evolution patterns of MM and provide examples from single-cell studies that are beginning to unravel the mutational and phenotypic characteristics of individual cells within the bone marrow tumour, immune microenvironment and peripheral blood. We also address future perspectives on clinical application, proposing that multi-omics single-cell profiling can guide early patient diagnosis, risk stratification and treatment strategies.

Comparison of Clinical Characteristics and Genetic Aberrations of Plasma Cell Disorders in Thailand Population

Multiple myeloma is an incurable malignancy of plasma cells resulting from impaired terminal B cell development. Almost all patients with multiple myeloma eventually have a relapse. Many studies have demonstrated the importance of the various genomic mutations that characterize multiple myeloma as a complex heterogeneous disease. In recent years, next-generation sequencing has been used to identify the genomic mutation landscape and clonal heterogeneity of multiple myeloma. This is the first study, a prospective observational study, to identify somatic mutations in plasma cell disorders in the Thai population using targeted next-generation sequencing. Twenty-seven patients with plasma cell disorders were enrolled comprising 17 cases of newly diagnosed multiple myeloma, 5 cases of relapsed/refractory multiple myeloma, and 5 cases of other plasma cell disorders. The pathogenic mutations were found in 17 of 27 patients. Seventy percent of those who had a mutation (12/17 patients) habored a single mutation, whereas the others had more than one mutation. Fifteen pathogenic mutation genes were identified: ATM, BRAF, CYLD, DIS3, DNMT3A, FBXW7, FLT3, GNA13, IRF4, KMT2A, NRAS, SAMHD1, TENT5C, TP53, and TRAF3. Most have previously been reported to be involved in the RAS/MAPK pathway, the nuclear factor kappa B pathway, the DNA-repair pathway, the CRBN pathway, tumor suppressor gene mutation, or an epigenetic mutation. However, the current study also identified mutations that had not been reported to be related to myeloma: GNA13 and FBXW7. Therefore, a deep understanding of molecular genomics would inevitably improve the clinical management of plasma cell disorder patients, and the increased knowledge would ultimately result in better outcomes for the patients.

Epidemiology, genetics and treatment of multiple myeloma and precursor diseases

Multiple myeloma (MM) is a hematological malignancy caused by the clonal expansion of plasma cells. The incidence of MM worldwide is increasing with greater than 140 000 people being diagnosed with MM per year. Whereas 5-year survival after a diagnosis of MM has improved from 28% in 1975 to 56% in 2012, the disease remains essentially incurable. In this review, we summarize our current understanding of MM including its epidemiology, genetics and biology. We will also provide an overview of MM management that has led to improvements in survival, including recent changes to diagnosis and therapies. Areas of unmet need include the management of patients with high-risk MM, those with reduced performance status and those refractory to standard therapies. Ongoing research into the biology and early detection of MM as well as the development of novel therapies, such as immunotherapies, has the potential to influence MM practice in the future.

Genome Instability in Multiple Myeloma: Facts and Factors

Multiple myeloma (MM) is a malignant neoplasm of terminally differentiated immunoglobulin-producing B lymphocytes called plasma cells. MM is the second most common hematologic malignancy, and it poses a heavy economic and social burden because it remains incurable and confers a profound disability to patients. Despite current progress in MM treatment, the disease invariably recurs, even after the transplantation of autologous hematopoietic stem cells (ASCT). Biological processes leading to a pathological myeloma clone and the mechanisms of further evolution of the disease are far from complete understanding. Genetically, MM is a complex disease that demonstrates a high level of heterogeneity. Myeloma genomes carry numerous genetic changes, including structural genome variations and chromosomal gains and losses, and these changes occur in combinations with point mutations affecting various cellular pathways, including genome maintenance. MM genome instability in its extreme is manifested in mutation kataegis and complex genomic rearrangements: chromothripsis, templated insertions, and chromoplexy. Chemotherapeutic agents used to treat MM add another level of complexity because many of them exacerbate genome instability. Genome abnormalities are driver events and deciphering their mechanisms will help understand the causes of MM and play a pivotal role in developing new therapies.

The Relationship of ABCB1/MDR1 and CYP1A1 Variants with the Risk of Disease Development and Shortening of Overall Survival in Patients with Multiple Myeloma

(1) Background: The aim of our study was to analyze the possible relationship of ABCB1 and CYP1A1 gene variants with susceptibility and outcome of multiple myeloma (MM); (2) Methods: Genomic DNA samples from 110 newly-diagnosed MM patients and 100 healthy blood donors were analyzed by methods-PCR-RFLP (for ABCB1 3435C > T, CYP1A1 6235T > C-m1), automated DNA sequencing (for ABCB1 1236C > T, 2677G > T/A) and allele-specific PCR (for CYP1A1 4889A > G-m2); (3) Results: The genotypic frequencies of CYP1A1 4889A > G variant were not in Hardy-Weinberg equilibrium for MM patients. The presence of m1 and m2 CYP1A1 alleles decreased the risk of MM-OR = 0.49 (p = 0.011) and OR = 0.27 (p = 0.0003), respectively. In turn, TT genotype (ABCB1 2677G > T/A) increased the risk of this disease (p = 0.007). In the multivariate Cox analysis CT + TT genotypes (ABCB1 3435C > T) were associated with decreased risk of death (HR = 0.29, p = 0.04). In log-rank test in patients with CT genotype (ABCB1 3435C > T) was observed association of overall survival with the type of treatment; (4) Conclusions: Our findings suggest that T-alleles of ABCB1 2677G > T/A and m1/m2 alleles of CYP1A1 affected the susceptibility of MM. Moreover, T-allele of ABCB1 3435C > T might be independent positive prognostic factor in MM.

The Significance of mRNA in the Biology of Multiple Myeloma and Its Clinical Implications

Multiple myeloma (MM) is a genetically complex disease that results from a multistep transformation of normal to malignant plasma cells in the bone marrow. However, the molecular mechanisms responsible for the initiation and heterogeneous evolution of MM remain largely unknown. A fundamental step needed to understand the oncogenesis of MM and its response to therapy is the identification of driver mutations. The introduction of gene expression profiling (GEP) in MM is an important step in elucidating the molecular heterogeneity of MM and its clinical relevance. Since some mutations in myeloma occur in non-coding regions, studies based on the analysis of mRNA provide more comprehensive information on the oncogenic pathways and mechanisms relevant to MM biology. In this review, we discuss the role of gene expression profiling in understanding the biology of multiple myeloma together with the clinical manifestation of the disease, as well as its impact on treatment decisions and future directions.

Clonal Evolution of Multiple Myeloma-Clinical and Diagnostic Implications

Plasma cell dyscrasias are a heterogeneous group of diseases characterized by the expansion of bone marrow plasma cells. Malignant transformation of plasma cells depends on the continuity of events resulting in a sequence of well-defined disease stages, from monoclonal gammopathy of undetermined significance (MGUS) through smoldering myeloma (SMM) to symptomatic multiple myeloma (MM). Evolution of a pre-malignant cell into a malignant cell, as well as further tumor progression, dissemination, and relapse, require development of multiple driver lesions conferring selective advantage of the dominant clone and allowing subsequent evolution under selective pressure of microenvironment and treatment. This process of natural selection facilitates tumor plasticity leading to the formation of genetically complex and heterogenous tumors that are notoriously difficult to treat. Better understanding of the mechanisms underlying tumor evolution in MM and identification of lesions driving the evolution from the premalignant clone is therefore a key to development of effective treatment and long-term disease control. Here, we review recent advances in clonal evolution patterns and genomic landscape dynamics of MM, focusing on their clinical implications.

A Comprehensive Review of the Genomics of Multiple Myeloma: Evolutionary Trajectories, Gene Expression Profiling, and Emerging Therapeutics

Multiple myeloma (MM) is a blood cancer characterized by the accumulation of malignant monoclonal plasma cells in the bone marrow. It develops through a series of premalignant plasma cell dyscrasia stages, most notable of which is the Monoclonal Gammopathy of Undetermined Significance (MGUS). Significant advances have been achieved in uncovering the genomic aberrancies underlying the pathogenesis of MGUS-MM. In this review, we discuss in-depth the genomic evolution of MM and focus on the prognostic implications of the accompanied molecular and cytogenetic aberrations. We also dive into the latest investigatory techniques used for the diagnoses and risk stratification of MM patients.

Pathogenic noncoding variants in the neurofibromatosis and schwannomatosis predisposition genes

Neurofibromatosis type 1 (NF1), type 2 (NF2), and schwannomatosis are a group of autosomal dominant disorders that predispose to the development of nerve sheath tumors. Pathogenic variants (PVs) that cause NF1 and NF2 are located in the NF1 and NF2 loci, respectively. To date, most variants associated with schwannomatosis have been identified in the SMARCB1 and LZTR1 genes, and a missense variant in the DGCR8 gene was recently reported to predispose to schwannomas. In spite of the high detection rate for PVs in NF1 and NF2 (over 90% of non-mosaic germline variants can be identified by routine genetic screening) underlying PVs for a proportion of clinical cases remain undetected. A higher proportion of non-NF2 schwannomatosis cases have no detected PV, with PVs currently only identified in around 70%-86% of familial cases and 30%-40% of non-NF2 sporadic schwannomatosis cases. A number of variants of uncertain significance have been observed for each disorder, many of them located in noncoding, regulatory, or intergenic regions. Here we summarize noncoding variants in this group of genes and discuss their established or potential role in the pathogenesis of NF1, NF2, and schwannomatosis.

Copy number evolution and its relationship with patient outcome-an analysis of 178 matched presentation-relapse tumor pairs from the Myeloma XI trial

Structural chromosomal changes including copy number aberrations (CNAs) are a major feature of multiple myeloma (MM), however their evolution in context of modern biological therapy is not well characterized. To investigate acquisition of CNAs and their prognostic relevance in context of first-line therapy, we profiled tumor diagnosis-relapse pairs from 178 NCRI Myeloma XI (ISRCTN49407852) trial patients using digital multiplex ligation-dependent probe amplification. CNA profiles acquired at relapse differed substantially between MM subtypes: hyperdiploid (HRD) tumors evolved predominantly in branching pattern vs. linear pattern in t(4;14) vs. stable pattern in t(11;14). CNA acquisition also differed between subtypes based on CCND expression, with a marked enrichment of acquired del(17p) in CCND2 over CCND1 tumors. Acquired CNAs were not influenced by high-dose melphalan or lenalidomide maintenance randomization. A branching evolution pattern was significantly associated with inferior overall survival (OS; hazard ratio (HR) 2.61, P = 0.0048). As an individual lesion, acquisition of gain(1q) at relapse was associated with shorter OS, independent of other risk markers or time of relapse (HR = 2.00; P = 0.021). There is an increasing need for rational therapy sequencing in MM. Our data supports the value of repeat molecular profiling to characterize disease evolution and inform management of MM relapse.

The Immunity-malignancy equilibrium in multiple myeloma: lessons from oncogenic events in plasma cells

Multiple myeloma (MM) is a malignancy of plasma cells (PC) that grow within the bone marrow and maintain massive immunoglobulin (Ig) production. Disease evolution is driven by genetic lesions, whose effects on cell biology and fitness underlie addictions and vulnerabilities of myeloma cells. Several genes mutated in myeloma are strictly involved in dictating PC identity and antibody factory function. Here, we evaluate the impact of mutations in IRF4, PRDM1, and XBP1, essential transcription factors driving the B to PC differentiation, on MM cell biology and homeostasis. These factors are highly specialized, with limited overlap in their downstream transcriptional programs. Indeed, IRF4 sustains metabolism, survival, and proliferation, while PRDM1 and XBP1 are mainly responsible for endoplasmic reticulum expansion and sustained Ig secretion. Interestingly, IRF4 undergoes activating mutations and translocations, while PRDM1 and XBP1 are hit by loss-of-function events, raising the hypothesis that containment of the secretory program, but not its complete extinction, may be beneficial to malignant PCs. Finally, recent studies unveiled that also the PRDM1 target, FAM46C/TENT5C, an onco-suppressor uniquely and frequently mutated or deleted in myeloma, is directly and potently involved in orchestrating ER homeostasis and secretory activity. Inactivating mutations found in this gene and its interactors strengthen the notion that reduced secretory capacity confers advantage to myeloma cells. We believe that dissection of the evolutionary pressure on genes driving PC-specific functions in myeloma will disclose the cellular strategies by which myeloma cells maintain an equilibrium between antibody production and survival, thus unveiling novel therapeutic targets.

Genoppi is an open-source software for robust and standardized integration of proteomic and genetic data

Combining genetic and cell-type-specific proteomic datasets can generate biological insights and therapeutic hypotheses, but a technical and statistical framework for such analyses is lacking. Here, we present an open-source computational tool called Genoppi (lagelab.org/genoppi) that enables robust, standardized, and intuitive integration of quantitative proteomic results with genetic data. We use Genoppi to analyze 16 cell-type-specific protein interaction datasets of four proteins (BCL2, TDP-43, MDM2, PTEN) involved in cancer and neurological disease. Through systematic quality control of the data and integration with published protein interactions, we show a general pattern of both cell-type-independent and cell-type-specific interactions across three cancer cell types and one human iPSC-derived neuronal cell type. Furthermore, through the integration of proteomic and genetic datasets in Genoppi, our results suggest that the neuron-specific interactions of these proteins are mediating their genetic involvement in neurodegenerative diseases. Importantly, our analyses suggest that human iPSC-derived neurons are a relevant model system for studying the involvement of BCL2 and TDP-43 in amyotrophic lateral sclerosis.

The Interaction of the Tumor Suppressor FAM46C with p62 and FNDC3 Proteins Integrates Protein and Secretory Homeostasis

FAM46C is a non-canonical poly(A) polymerase uniquely mutated in up to 20% of multiple myeloma (MM) patients, implying a tissue-specific tumor suppressor function. Here, we report that FAM46C selectively stabilizes mRNAs encoding endoplasmic reticulum (ER)-targeted proteins, thereby concertedly enhancing the expression of proteins that control ER protein import, folding, N-glycosylation, and trafficking and boosting protein secretion. This role requires the interaction with the ER membrane resident proteins FNDC3A and FNDC3B. In MM cells, FAM46C expression raises secretory capacity beyond sustainability, inducing ROS accumulation, ATP shortage, and cell death. FAM46C activity is regulated through rapid proteasomal degradation or the inhibitory interaction with the ZZ domain of the autophagic receptor p62 that hinders its association with FNDC3 proteins via sequestration in p62⁺ aggregates. Altogether, our data disclose a p62/FAM46C/FNDC3 circuit coordinating sustainable secretory activity and survival, providing an explanation for the MM-specific oncosuppressive role of FAM46C and uncovering potential therapeutic opportunities against cancer.

Chromothripsis as a pathogenic driver of multiple myeloma

Analysis of the genetic basis for multiple myeloma (MM) has informed many of our current concepts of the biology that underlies disease initiation and progression. Studying these events in further detail is predicted to deliver important insights into its pathogenesis, prognosis and treatment. Information from whole genome sequencing of structural variation is revealing the role of these events as drivers of MM. In particular, we discuss how the insights we have gained from studying chromothripsis suggest that it can be used to provide information on disease initiation and that, as a consequence, it can be used for the clinical classification of myeloma precursor diseases allowing for early intervention and prognostic determination. For newly diagnosed MM, the integration of information on the presence of chromothripsis has the potential to significantly enhance current risk prediction strategies and to better characterize patients with high-risk disease biology. In this article we summarize the genetic basis for MM and the role played by chromothripsis as a critical pathogenic factor active at early disease phases.

Construction and validation of a prognostic signature using CNV-driven genes for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the major causes of cancer-related deaths worldwide. Copy number variations (CNVs) affect the expression of genes and play critical roles in carcinogenesis. We aimed to identify specific CNV-driven genes and establish a prognostic model for HCC.

Methods

Integrative analysis of CNVs difference data and differentially expressed genes (DEGs) data from The Cancer Genome Atlas (TCGA) were conducted to identify critical CNV-driven genes for HCC. A risk model was constructed based on univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses. The associations between CNV-driven genes signature and infiltrating immune cells were explored. The International Cancer Genome Consortium (ICGC) dataset was utilized to validate this model.

Results

After integrative analysis of CNVs and corresponding mRNA expression profiles, 568 CNV-driven genes were identified. Sixty-three CNV-driven genes were found to be markedly associated with overall survival (OS) after univariate Cox regression analysis. Finally, eight CNV-driven genes were screened to generate a prognostic risk model. Compared with low-risk group, the OS of patients in the high-risk group was significantly shorter in both the TCGA [hazard ratio (HR) =6.14, 95% confidence interval (CI): 2.72-13.86, P<0.001] and ICGC (HR =3.23, 95% CI: 1.17-8.92, P<0.001) datasets. Further analysis revealed the infiltrating neutrophils were positively correlated with risk score. Meanwhile, the high-risk group was associated with higher expression of immune checkpoint genes.

Conclusions

A novel signature based on CNV-driven genes was built to predict the survival of HCC patients and showed good performance. The results of our study may improve understanding of the mechanism that drives HCC, and provide an immunological perspective for individualized therapies.

mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies

Mutational signatures have emerged as powerful biomarkers in cancer patients, with prognostic and therapeutic implications. Wider clinical utility requires access to reproducible algorithms, which allow characterization of mutational signatures in a given tumor sample. Here, we show how mutational signature fitting can be applied to hematological cancer genomes to identify biologically and clinically important mutational processes, highlighting the importance of careful interpretation in light of biological knowledge. Our newly released R package mmsig comes with a dynamic error-suppression procedure that improves specificity in important clinical and biological settings. In particular, mmsig allows accurate detection of mutational signatures with low abundance, such as those introduced by APOBEC cytidine deaminases. This is particularly important in the most recent mutational signature reference (COSMIC v3.1) where each signature is more clearly defined. Our mutational signature fitting algorithm mmsig is a robust tool that can be implemented immediately in the clinic.

Rustad et al. present a software package for the R statistical environment for the accurately quantify of somatic mutational signatures in hematological malignancies

Management of patients with difficult-to-treat multiple myeloma

Newer treatments for multiple myeloma (MM) have improved response rates and survival for many patients. However, MM remains challenging to treat due to the propensity for multiple relapses, cumulative and emergent toxicities from prior therapies and increasing genomic complexity that arises due to clonal evolution. In particular, patients with relapsed/refractory MM often require increased complexity of treatment, yet still experience poorer outcomes compared with patients who are newly diagnosed. Additionally, several patient subgroups, including those with extramedullary disease and patients who are frail and/or have multiple comorbidities, have an unfavorable prognosis and remain undertreated. This review (based on an Updates-in-Hematology session at the 25th European Hematology Association Annual Congress 2020) discusses the management of these difficult-to-treat patients with MM.

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

Designing Evolutionary-based Interception Strategies to Block the Transition from Precursor Phases to Multiple Myeloma

The development of next-generation sequencing technology has dramatically improved our understanding of the genetic landscape of multiple myeloma. Several new drivers and recurrent events have been reported and linked to a potential driver role. This complex landscape is enhanced by intraclonal mutational heterogeneity and variability introduced through the dimensions of time and space. The evolutionary history of multiple myeloma is driven by both the accumulation of different genomic drivers and by the activity of different mutational processes active overtime. In this review, we describe how these new findings and sequencing technologies have been progressively allowed to understand and reshape our knowledge of the complexity of multiple myeloma at each of its developmental stages: premalignant, at diagnosis, and in relapsed/refractory states. We discuss how these evolutionary concepts can be utilized in the clinic to alter evolutionary trajectories providing a framework for therapeutic intervention at early-disease stages.

VLA4-Targeted Nanoparticles Hijack Cell Adhesion-Mediated Drug Resistance to Target Refractory Myeloma Cells and Prolong Survival

PURPOSE

In multiple myeloma, drug-resistant cells underlie relapse or progression following chemotherapy. Cell adhesion-mediated drug resistance (CAM-DR) is an established mechanism used by myeloma cells (MMC) to survive chemotherapy and its markers are upregulated in residual disease. The integrin very late antigen 4 (VLA4; α₄β₁) is a key mediator of CAM-DR and its expression affects drug sensitivity of MMCs. Rather than trying to inhibit its function, here, we hypothesized that upregulation of VLA4 by resistant MMCs could be exploited for targeted delivery of drugs, which would improve safety and efficacy of treatments.

EXPERIMENTAL DESIGN

We synthetized 20 nm VLA4-targeted micellar nanoparticles (V-NP) carrying DiI for tracing or a novel camptothecin prodrug (V-CP). Human or murine MMCs, alone or with stroma, and immunocompetent mice with orthotopic multiple myeloma were used to track delivery of NPs and response to treatments.

RESULTS

V-NPs selectively delivered their payload to MMCs in vitro and in vivo, and chemotherapy increased their uptake by surviving MMCs. V-CP, alone or in combination with melphalan, was well tolerated and prolonged survival in myeloma-bearing mice. V-CP also reduced the dose requirement for melphalan, reducing tumor burden in association with suboptimal dosing without increasing overall toxicity.

CONCLUSIONS

V-CP may be a safe and effective strategy to prevent or treat relapsing or refractory myeloma. V-NP targeting of resistant cells may suggest a new approach to environment-induced resistance in cancer.

An enhanced genetic model of relapsed IGH-translocated multiple myeloma evolutionary dynamics

Most patients with multiple myeloma (MM) die from progressive disease after relapse. To advance our understanding of MM evolution mechanisms, we performed whole-genome sequencing of 80 IGH-translocated tumour-normal newly diagnosed pairs and 24 matched relapsed tumours from the Myeloma XI trial. We identify multiple events as potentially important for survival and therapy-resistance at relapse including driver point mutations (e.g., TET2), translocations (MAP3K14), lengthened telomeres, and increased genomic instability (e.g., 17p deletions). Despite heterogeneous mutational processes contributing to relapsed mutations across MM subtypes, increased AID/APOBEC activity is particularly associated with shorter progression time to relapse, and contributes to higher mutational burden at relapse. In addition, we identify three enhanced major clonal evolution patterns of MM relapse, independent of treatment strategies and molecular karyotypes, questioning the viability of "evolutionary herding" approach in treating drug-resistant MM. Our data show that MM relapse is associated with acquisition of new mutations and clonal selection, and suggest APOBEC enzymes among potential targets for therapy-resistant MM.

A compendium of mutational cancer driver genes

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

Timing the initiation of multiple myeloma

The evolution and progression of multiple myeloma and its precursors over time is poorly understood. Here, we investigate the landscape and timing of mutational processes shaping multiple myeloma evolution in a large cohort of 89 whole genomes and 973 exomes. We identify eight processes, including a mutational signature caused by exposure to melphalan. Reconstructing the chronological activity of each mutational signature, we estimate that the initial transformation of a germinal center B-cell usually occurred during the first 2nd-3rd decades of life. We define four main patterns of activation-induced deaminase (AID) and apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) mutagenesis over time, including a subset of patients with evidence of prolonged AID activity during the pre-malignant phase, indicating antigen-responsiveness and germinal center reentry. Our findings provide a framework to study the etiology of multiple myeloma and explore strategies for prevention and early detection.

Biallelic loss of FAM46C triggers tumor growth with concomitant activation of Akt signaling in multiple myeloma cells

Loss of heterozygosity or mutation of the family with sequence similarity 46, member C (FAM46C) gene on chromosome band 1p12 is associated with shorter overall survival of patients with multiple myeloma (MM). In this study, using human MM cell lines (KMS‐11, OCI‐My5, and ANBL‐6), we generated FAM46C^−/− cell clones and examined the effect of disruption of FAM46C on cell survival and cellular signaling. Cell proliferation assays showed increased clonogenicity of FAM46C^−/− KMS‐11 cells compared to WT cells. Xenograft experiments showed significantly shorter overall survival of mice harboring the FAM46C^−/− cell‐derived tumors than mice with the FAM46C^WT cell‐derived tumors. Notably, levels of phosphorylated Akt and its substrates increased both in vitro and in vivo in the FAM46C^−/− cells compared to WT cells. In addition, caspase activities decreased in the FAM46C^−/− cells. Results of gene set enrichment analysis showed that loss of FAM46C significantly activated serum‐responsive genes while inactivating phosphatase and tensin homolog (PTEN)‐related genes. Mechanistically, loss of FAM46C decreased the PTEN activity, number of apoptotic cells, and caspase activities. PF‐04691502, a selective PI3K inhibitor, suppressed the augmented phosphorylation of Akt and its substrate FoxO3a. Treatment with afuresertib (a specific Akt inhibitor) in combination with bortezomib additively decreased FAM46C^−/− MM cell survival. Collectively, this study is the first to report that loss of FAM46C triggers the concomitant activation of the PI3K‐Akt signaling pathway, which might be a therapeutic target for MM with abnormalities in the FAM46C gene.

Liquid biopsies for multiple myeloma in a time of precision medicine

Multiple myeloma (MM) is a challenging, progressive, and highly heterogeneous hematological malignancy. MM is characterized by multifocal proliferation of neoplastic plasma cells in the bone marrow (BM) and sometimes in extramedullary organs. Despite the availability of novel drugs and the longer median overall survival, some patients survive more than 10 years while others die rapidly. This heterogeneity is mainly driven by biological characteristics of MM cells, including genetic abnormalities. Disease progressions are mainly due to the inability of drugs to overcome refractory disease and inevitable drug-resistant relapse. In clinical practice, a bone marrow biopsy, mostly performed in one site, is still used to access the genetics of MM. However, BM biopsy use is limited by its invasive nature and by often not accurately reflecting the mutational profile of MM. Recent insights into the genetic landscape of MM provide a valuable opportunity to implement precision medicine approaches aiming to enable better patient profiling and selection of targeted therapies. In this review, we explore the use of the emerging field of liquid biopsies in myeloma patients considering current unmet medical needs, such as assessing the dynamic mutational landscape of myeloma, early predictors of treatment response, and a less invasive response monitoring.

DCEP and bendamustine/prednisone as salvage therapy for quad- and penta-refractory multiple myeloma

Multiple myeloma (MM) almost invariably progresses through novel therapies. Patients with quad-refractory MM (refractory to bortezomib, carfilzomib, lenalidomide, and pomalidomide) and penta-refractory MM (additional refractoriness to daratumumab) have few treatment options. Two chemotherapy regimens, bendamustine/prednisone (BP) and dexamethasone, cyclophosphamide, etoposide, and cisplatin (DCEP), are often used in quad- and penta-refractory MM, but there are limited data on outcomes in this heavily pre-treated population. We conducted a single-center retrospective study to identify all patients who received DCEP and/or BP for quad- or penta-refractory MM. Disease response and refractoriness were defined by International Myeloma Working Group criteria. The primary endpoint was overall response rate (ORR). Secondary endpoints included overall survival (OS), progression-free survival (PFS), and duration of response (DOR). We identified 27 patients who received BP for quad- or penta-refractory MM. The median number of prior lines of therapy was 6. The ORR for BP was 26%. The median PFS for BP was 1.4 months (95% CI 1.1-1.6) and median OS was 8.7 months (95% CI 2.3-15.0). Patients treated with cyclophosphamide had less response to BP. Thirty-one patients received DCEP for quad-refractory or penta-refractory MM. The median number of prior treatment regimens was 8. The ORR to DCEP was 35%. The median PFS was 2.7 months (95% CI 1.5-3.8) and median OS was 6.2 months (95% CI 4.4-7.8). DCEP and BP retain efficacy in quad- and penta-refractory MM. Our analysis supports prospective study of these regimens, possibly in combination or in comparison with other agents in this area of unmet need.

Reconstructing the evolutionary history of multiple myeloma

Multiple myeloma is the second most common lymphoproliferative disorder, characterized by aberrant expansion of monoclonal plasma cells. In the last years, thanks to novel next generation sequencing technologies, multiple myeloma has emerged as one of the most complex hematological cancers, shaped over time by the activity of multiple mutational processes and by the acquisition of key driver events. In this review, we describe how whole genome sequencing is emerging as a key technology to decipher this complexity at every stage of myeloma development: precursors, diagnosis and relapsed/refractory. Defining the time windows when driver events are acquired improves our understanding of cancer etiology and paves the way for early diagnosis and ultimately prevention.

Genomic profiling of multiple myeloma: New insights and modern technologies

Advances in technologies for genomic profiling, primarily with next generation sequencing, have lead to a better understanding of the complex genomic landscape in multiple myeloma. Integrated analysis of whole genome, exome and transcriptome sequencing has lead to new insights on disease drivers including translocations, copy number alterations, somatic mutations, and altered gene expression. Disease progression in multiple myeloma is largely driven by structural variations including the traditional immunoglobulin heavy chain (IGH) translocations and hyperdiploidy which are early events in myelomagenesis as well as more complex events spanning over multiple chromosomes and involving amplifications and deletions. In this review, we will discuss recent insights on the genomic landscape of multiple myeloma and their implications for disease progression and personalized treatment. We will review how sequencing assays compare to current clinical methods and give an overview of modern technologies for interrogating genomic aberrations.

Identification of recurrent noncoding mutations in B-cell lymphoma using capture Hi-C

The identification of driver mutations is fundamental to understanding oncogenesis. Although genes frequently mutated in B-cell lymphoma have been identified, the search for driver mutations has largely focused on the coding genome. Here we report an analysis of the noncoding genome using whole-genome sequencing data from 117 patients with B-cell lymphoma. Using promoter capture Hi-C data in naive B cells, we define cis-regulatory elements, which represent an enriched subset of the noncoding genome in which to search for driver mutations. Regulatory regions were identified whose mutation significantly alters gene expression, including copy number variation at cis-regulatory elements targeting CD69, IGLL5, and MMP14, and single nucleotide variants in a cis-regulatory element for TPRG1 We also show the commonality of pathways targeted by coding and noncoding mutations, exemplified by MMP14, which regulates Notch signaling, a pathway important in lymphomagenesis and whose expression is associated with patient survival. This study provides an enhanced understanding of lymphomagenesis and describes the advantages of using chromosome conformation capture to decipher noncoding mutations relevant to cancer biology.

Comutation of PIK3CA and TP53 in Residual Disease After Preoperative Anti-HER2 Therapy in ERBB2 (HER2)-Amplified Early Breast Cancer

PURPOSE

To identify proteomic and genomic alterations in residual disease (RD) for human epidermal growth factor receptor 2 (HER2)-positive (HER2+) breast cancer (BC) after preoperative trastuzumab (H), lapatinib (L), or both (H+L) in combination with chemotherapy.

PATIENTS AND METHODS

Patients with stage II/III HER2+ BC (n = 100) were randomly assigned to preoperative treatment with H versus L 1,250mg versus H+L (L: 750 to 1,000 mg) plus 5-fluorouracil, epirubicin, and cyclophosphamide, followed by weekly paclitaxel. After receiving institutional review board–approved informed consent, targeted next-generation sequencing was performed on 20 patients’ formalin-fixed paraffin embedded tumors to characterize genomic alterations across 287 cancer-related genes. Reverse phase protein array (RPPA) analysis was performed on both the baseline biopsy and RD specimens, when available.

RESULTS

Two of 20 RD tissues were HER2 negative per next-generation sequencing; one sample had insufficient tissue. Of six pretreatment biopsy specimens, four were comutated with TP53 and PIK3CA. Of 17 HER2+ RD, seven specimens (41%) had PIK3CA mutations always comutated with TP53, and four (24%) also had concurrent CDK12 amplification. Overall, CDK12 amplification was observed in eight of the 17 (47%) HER2+ RD specimens. A total of 12 RD specimens (71%) had TP53 mutations. Although prevalence of individual TP53 and PIK3CA mutations was only modestly higher than published estimates for those in HER2+ primary BCs (55% and 32% for TP53 and PIK3CA, respectively), prevalence of these as comutations appeared higher (41%), compared with less than 10% in several series. On RPPA analysis of the RD tissue with comutations, the strongest Spearman ρ correlations were limited to EGFR and phospho-AKT (ρ, 0.999; P = .019) and phospho-mTOR and phospho-S6 ribosomal protein (ρ, 0.994; P = .048).

CONCLUSION

HER2-amplified RD tissue after preoperative H, L, or H+L plus chemotherapy was enriched for PIK3CA and TP53 comutations, and the RD tissue demonstrated activation of EGFR/AKT/mTOR signaling on RPPA.

Indirect Tumor Inhibitory Effects of MicroRNA-124 through Targeting EZH2 in The Multiple Myeloma Cell Line

Objective

Multiple myeloma (MM) is an incurable plasma cell malignancy. Several genetic and epigenetic changes affect numerous critical genes expression status in this disorder. CDKN2A gene is expressed at low level in almost all cases with MM disease. The mechanism of this gene down-regulation has remained controversial. In the present study, we targeted EZH2 by microRNA-124 (miR-124) in L-363 cells and assessed following possible impact on CDKN2A gene expression and phenotypic changes.

Materials and Methods

In this experimental study, growth inhibitory effects of miR-124 were measured by MTT assay in L-363 cell line. Likewise, cell cycle assay was measured by flowcytometery. The expression levels of EZH2 and CDKN2A were evaluated by real-time quantitative reverse-transcription polymerase chain reaction (qRT-PCR).

Results

qRT-PCR results showed induction of EZH2 gene expression after transduction of cells with lentivector expressing miR-124. The expression of CDKN2A was also upregulated as the result of EZH2 supression. Coincide with gene expression changes, cell cycle analysis by flow-cytometry indicated slightly increased G1-arrest in miR- transduced cells (P<0.05). MTT assay results also showed a significant decrease in viability and proliferation of miR- transduced cells (P<0.05).

Conclusion

It seems that assembling of H3K27me3 mark mediated by EZH2 is one of the key mechanisms of suppressing CDKN2A gene expression in MM disease. However, this suppressive function is applied by a multi-factor mechanism. In other words, targeting EZH2, as the core functional subunit of PRC2 complex, can increase expression of the downstream suppressive genes. Consequently, by increasing expression of tumor suppressor genes, myeloma cells are stopped from aberrant expansions and they become susceptible to regulated cellular death.