Genome-wide association study identifies multiple susceptibility loci for multiple myeloma

A meta-analysis of genome-wide association studies of multiple myeloma among men and women of African ancestry

Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10-6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10-12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

Search for multiple myeloma risk factors using Mendelian randomization

The etiology of multiple myeloma (MM) is poorly understood. Summary data from genome-wide association studies (GWASs) of multiple phenotypes can be exploited in a Mendelian randomization (MR) phenome-wide association study (PheWAS) to search for factors influencing MM risk. We performed an MR-PheWAS analyzing 249 phenotypes, proxied by 10 225 genetic variants, and summary genetic data from a GWAS of 7717 MM cases and 29 304 controls. Odds ratios (ORs) per 1 standard deviation increase in each phenotype were estimated under an inverse variance weighted random effects model. A Bonferroni-corrected threshold of P = 2 × 10-4 was considered significant, whereas P < .05 was considered suggestive of an association. Although no significant associations with MM risk were observed among the 249 phenotypes, 28 phenotypes showed evidence suggestive of association, including increased levels of serum vitamin B6 and blood carnitine (P = 1.1 × 10-3) with greater MM risk and ω-3 fatty acids (P = 5.4 × 10-4) with reduced MM risk. A suggestive association between increased telomere length and reduced MM risk was also noted; however, this association was primarily driven by the previously identified risk variant rs10936599 at 3q26 (TERC). Although not statistically significant, increased body mass index was associated with increased risk (OR, 1.10; 95% confidence interval, 0.99-1.22), supporting findings from a previous meta-analysis of prospective observational studies. Our study did not provide evidence supporting any modifiable factors examined as having a major influence on MM risk; however, it provides insight into factors for which the evidence has previously been mixed.

Coinherited genetics of multiple myeloma and its precursor, monoclonal gammopathy of undetermined significance

So far, 23 germline susceptibility loci have been associated with multiple myeloma (MM) risk. It is unclear whether the genetic variation associated with MM susceptibility also predisposes to its precursor, monoclonal gammopathy of undetermined significance (MGUS). Leveraging 2434 MM cases, 754 MGUS cases, and 2 independent sets of controls (2567/879), we investigated potential shared genetic susceptibility of MM and MGUS by (1) performing MM and MGUS genome-wide association studies (GWAS); (2) validating the association of a polygenic risk score (PRS) based on 23 established MM loci (MM-PRS) with risk of MM, and for the first time with MGUS; and (3) examining genetic correlation of MM and MGUS. Heritability and genetic estimates yielded 17% (standard error [SE] ±0.04) and 15% (SE ±0.11) for MM and MGUS risk, respectively, and a 55% (SE ±0.30) genetic correlation. The MM-PRS was associated with risk of MM when assessed continuously (odds ratio [OR], 1.17 per SD; 95% confidence interval [CI], 1.13-1.21) or categorically (OR, 1.70; 95% CI, 1.38-2.09 for highest; OR, 0.71; 95% CI, 0.55-0.90 for lowest compared with middle quintile). The MM-PRS was similarly associated with MGUS (OR, 1.19 per SD; 95% CI, 1.14-1.26 as a continuous measure, OR, 1.77, 95%CI: 1.29-2.43 for highest and OR, 0.70, 95%CI: 0.50-0.98 for lowest compared with middle quintile). MM and MGUS associations did not differ by age, sex, or MM immunoglobulin isotype. We validated a 23-SNP MM-PRS in an independent series of MM cases and provide evidence for its association with MGUS. Our results suggest shared common genetic susceptibility to MM and MGUS.

Machine Learning Applicability for Classification of PAD/VCD Chemotherapy Response Using 53 Multiple Myeloma RNA Sequencing Profiles

Multiple myeloma (MM) affects ~500,000 people and results in ~100,000 deaths annually, being currently considered treatable but incurable. There are several MM chemotherapy treatment regimens, among which eleven include bortezomib, a proteasome-targeted drug. MM patients respond differently to bortezomib, and new prognostic biomarkers are needed to personalize treatments. However, there is a shortage of clinically annotated MM molecular data that could be used to establish novel molecular diagnostics. We report new RNA sequencing profiles for 53 MM patients annotated with responses on two similar chemotherapy regimens: bortezomib, doxorubicin, dexamethasone (PAD), and bortezomib, cyclophosphamide, dexamethasone (VCD), or with responses to their combinations. Fourteen patients received both PAD and VCD; six received only PAD, and 33 received only VCD. We compared profiles for the good and poor responders and found five genes commonly regulated here and in the previous datasets for other bortezomib regimens (all upregulated in the good responders): FGFR3, MAF, IGHA2, IGHV1-69, and GRB14. Four of these genes are linked with known immunoglobulin locus rearrangements. We then used five machine learning (ML) methods to build a classifier distinguishing good and poor responders for two cohorts: PAD + VCD (53 patients), and separately VCD (47 patients). We showed that the application of FloWPS dynamic data trimming was beneficial for all ML methods tested in both cohorts, and also in the previous MM bortezomib datasets. However, the ML models build for the different datasets did not allow cross-transferring, which can be due to different treatment regimens, experimental profiling methods, and MM heterogeneity.

The Landscape of Signaling Pathways and Proteasome Inhibitors Combinations in Multiple Myeloma

Multiple myeloma is a malignancy of terminally differentiated plasma cells, characterized by an extreme genetic heterogeneity that poses great challenges for its successful treatment. Due to antibody overproduction, MM cells depend on the precise regulation of the protein degradation systems. Despite the success of PIs in MM treatment, resistance and adverse toxic effects such as peripheral neuropathy and cardiotoxicity could arise. To this end, the use of rational combinatorial treatments might allow lowering the dose of inhibitors and therefore, minimize their side-effects. Even though the suppression of different cellular pathways in combination with proteasome inhibitors have shown remarkable anti-myeloma activities in preclinical models, many of these promising combinations often failed in clinical trials. Substantial progress has been made by the simultaneous targeting of proteasome and different aspects of MM-associated immune dysfunctions. Moreover, targeting deranged metabolic hubs could represent a new avenue to identify effective therapeutic combinations with PIs. Finally, epigenetic drugs targeting either DNA methylation, histone modifiers/readers, or chromatin remodelers are showing pleiotropic anti-myeloma effects alone and in combination with PIs. We envisage that the positive outcome of patients will probably depend on the availability of more effective drug combinations and treatment of early MM stages. Therefore, the identification of sensitive targets and aberrant signaling pathways is instrumental for the development of new personalized therapies for MM patients.

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.

Insights into the Links between MYC and 3D Chromatin Structure and Epigenetics Regulation: Implications for Cancer Therapy

MYC is embedded in the transcriptional oasis of the 8q24 gene desert. A plethora of genomic elements has roles in MYC aberrant expression in cancer development by interacting with transcription factors and epigenetics regulators as well as altering the structure of chromatin at the MYC locus and tissue-specific long-range enhancer-promoter contacts. Furthermore, MYC is a master regulator of several human cancers by modulating the transcription of numerous cancer-related genes through epigenetic mechanisms. This review provides a comprehensive overview of the three-dimensional genomic organization around MYC and the role of epigenetic machinery in transcription and function of MYC as well as discusses various epigenetic-targeted therapeutic strategies in MYC-driven cancers.

Upregulation of ATIC in multiple myeloma tissues based on tissue microarray and gene microarrays

PURPOSE

Multiple myeloma (MM) is characterized by the malignant proliferation of plasma cells, which produce a monoclonal immunoglobulin protein. The role of 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase (ATIC) has not yet been well studied in the area of MM. Thus, in the current study, we sought to examine the expression levels, including mRNA and protein levels of ATIC in MM.

METHODS

Multiple myeloma microarray and RNA-seq data were screened from the SRA, GEO, ArrayExpress, and Oncomine databases. The mRNA level of ATIC was extracted from the high throughput data, and the prognostic value was studied. The protein level of ATIC was also detected by in-house immunohistochemistry on a tissue microarray. Potential signaling pathways were enriched with ATIC-related genes in MM.

RESULTS

Both the mRNA and protein levels of ATIC were significantly upregulated in MM samples as compared to normal samples. Furthermore, the summarized Standardized Mean Difference was 1.66 with 674 cases of MM based on 10 independent studies including the in-house tissue microarray. The overall hazard ratio of ATIC in MM was 1.7 with 1631 cases of MM based on five microarrays. In the KEGG pathway analysis, the ATIC-related genes were mainly enriched in the pathway of complement and coagulation cascades.

CONCLUSION

We provided the first evidence supporting the upregulation of ATIC may play an essential part in the tumorigenesis and development of MM. The promoting cancer capacity may be related to the pathway of complement and coagulation cascades.

Shaping the Treatment Paradigm Based on the Current Understanding of the Pathobiology of Multiple Myeloma: An Overview

Multiple myeloma is an incurable malignancy which despite progressive improvements in overall survival over the last decade remains characterised by recurrent relapse with progressively shorter duration of response and treatment-free intervals with each subsequent treatment. Efforts to unravel the complex and heterogeneous genomic alterations, the marked dysregulation of the immune system and the multifarious interplay between malignant plasma cells and those of the tumour microenvironment have not only led to improved understanding of myelomagenesis and disease progression but have facilitated the rapid development of novel therapeutics including immunotherapies and small molecules bringing us a step closer to therapies that no doubt will extend survival. Novel therapeutic combinations both in the upfront and relapsed setting as well as novel methods to assess response and guide management are rapidly transforming the management of myeloma.

Pathogenic Single Nucleotide Polymorphisms on Autophagy-Related Genes

In recent years, the study of single nucleotide polymorphisms (SNPs) has gained increasing importance in biomedical research, as they can either be at the molecular origin of a determined disorder or directly affect the efficiency of a given treatment. In this regard, sequence variations in genes involved in pro-survival cellular pathways are commonly associated with pathologies, as the alteration of these routes compromises cellular homeostasis. This is the case of autophagy, an evolutionarily conserved pathway that counteracts extracellular and intracellular stressors by mediating the turnover of cytosolic components through lysosomal degradation. Accordingly, autophagy dysregulation has been extensively described in a wide range of human pathologies, including cancer, neurodegeneration, or inflammatory alterations. Thus, it is not surprising that pathogenic gene variants in genes encoding crucial effectors of the autophagosome/lysosome axis are increasingly being identified. In this review, we present a comprehensive list of clinically relevant SNPs in autophagy-related genes, highlighting the scope and relevance of autophagy alterations in human disease.

Role of Polycomb Complexes in Normal and Malignant Plasma Cells

Plasma cells (PC) are the main effectors of adaptive immunity, responsible for producing antibodies to defend the body against pathogens. They are the result of a complex highly regulated cell differentiation process, taking place in several anatomical locations and involving unique genetic events. Pathologically, PC can undergo tumorigenesis and cause a group of diseases known as plasma cell dyscrasias, including multiple myeloma (MM). MM is a severe disease with poor prognosis that is characterized by the accumulation of malignant PC within the bone marrow, as well as high clinical and molecular heterogeneity. MM patients frequently develop resistance to treatment, leading to relapse. Polycomb group (PcG) proteins are epigenetic regulators involved in cell fate and carcinogenesis. The emerging roles of PcG in PC differentiation and myelomagenesis position them as potential therapeutic targets in MM. Here, we focus on the roles of PcG proteins in normal and malignant plasma cells, as well as their therapeutic implications.

Do myeloproliferative neoplasms and multiple myeloma share the same genetic susceptibility loci?

Myeloproliferative neoplasms (MPNs) are a group of diseases that cause myeloid hematopoietic cells to overproliferate. Epidemiological and familial studies suggest that genetic factors contribute to the risk of developing MPN, but the genetic susceptibility of MPN is still not well known. Indeed, only few loci are known to have a clear role in the predisposition to this disease. Some studies reported a diagnosis of MPNs and multiple myeloma (MM) in the same patients, but the biological causes are still unclear. We tested the hypothesis that the two diseases share at least partly the same genetic risk loci. In the context of a European multicenter study with 460 cases and 880 controls, we analyzed the effect of the known MM risk loci, individually and in a polygenic risk score (PRS). The most significant result was obtained among patients with chronic myeloid leukemia (CML) for PS0RS1C1-rs2285803, which showed to be associated with an increased risk (OR = 3.28, 95% CI 1.79-6.02, P = .00012, P = .00276 when taking into account multiple testing). Additionally, the PRS showed an association with MPN risk when comparing the last with the first quartile of the PRS (OR = 2.39, 95% CI 1.64-3.48, P = 5.98 × 10^-6 ). In conclusion, our results suggest a potential common genetic background between MPN and MM, which needs to be further investigated.

Clearance of HBsAg in a patient with familial multiple myeloma after a bortezomib-based regimen combined with anti-HBV drug: A case report

RATIONALE

Reactivation of hepatitis B virus (HBV) after treatment with bortezomib-based regimens in HBV-positive patients with multiple myeloma (MM) has been reported in the past few years. Nevertheless, there is evidence of inhibition of HBV replication by bortezomib in transgenic mice. However, there is still no clinical evidence that bortezomib inhibits HBV.

PATIENT CONCERNS

A 55-year-old MM patient with a family history of MM, who was also a chronic HBV carrier, achieved HBV clearance after treatment with a bortezomib-based regimen in combination with anti-HBV drugs.

DIAGNOSES

The diagnosis was MM with chronic carrier of HBV.

INTERVENTIONS

He received bortezomib-based regimen for MM as well as entecavir as a prophylaxis to prevent HBV reactivation.

OUTCOMES

This patient achieved HBsAg and HBV-DNA clearance after 2 months and the remission was maintained during the next 2 years. He also achieved complete remission of MM and underwent consolidation therapy with autologous hematopoietic stem cell transplantation.

LESSONS

This is the first case of MM with HBV clearance after receiving a bortezomib-based regimen combined with anti-HBV drug. Research on related mechanisms might provide new suggestions and hope for better management of HBV positive patients with MM and for the treatment of HBV patients.

Alteration of genome folding via contact domain boundary insertion

Animal chromosomes are partitioned into contact domains. Pathogenic domain disruptions can result from chromosomal rearrangements or perturbation of architectural factors. However, such broad-scale alterations are insufficient to define the minimal requirements for domain formation. Moreover, to what extent domains can be engineered is just beginning to be explored. In an attempt to create contact domains, we inserted a 2-kb DNA sequence underlying a tissue-invariant domain boundary-containing a CTCF-binding site (CBS) and a transcription start site (TSS)-into 16 ectopic loci across 11 chromosomes, and characterized its architectural impact. Depending on local constraints, this fragment variably formed new domains, partitioned existing ones, altered compartmentalization and initiated contacts reflecting chromatin loop extrusion. Deletions of the CBS or the TSS individually or in combination within inserts revealed its distinct contributions to genome folding. Altogether, short DNA insertions can suffice to shape the spatial genome in a manner influenced by chromatin context.

Cancer Predisposition Genes in Cancer-Free Families

Simple Summary

Familial clustering of cancer and identification of high- and low-risk cancer predisposition gene variants implicate that there are families that are at a high to moderate excess risk of cancer. We wanted to test genetically whether there are families protected from cancer. We whole-genome sequenced 51 elderly individuals without any personal or family history of cancer. We identified less high-risk loss-of-function variants in known and suggested cancer predisposition genes in these cancer-free individuals than in the general population. However, our results for low-risk variants were not conclusive. Our study suggests that random environmental causes of cancer are so dominant that a clear demarcation of cancer-free populations using genetic data may not be feasible. However, carrier identification of and counseling about prevalent high-risk cancer predisposition genes is useful.

Abstract

Familial clustering, twin concordance, and identification of high- and low-penetrance cancer predisposition variants support the idea that there are families that are at a high to moderate excess risk of cancer. To what extent there may be families that are protected from cancer is unknown. We wanted to test genetically whether cancer-free families share fewer breast, colorectal, and prostate cancer risk alleles than the population at large. We addressed this question by whole-genome sequencing (WGS) of 51 elderly cancer-free individuals whose numerous (ca. 1000) family members were found to be cancer-free (‘cancer-free families’, CFFs) based on face-to-face interviews. The average coverage of the 51 samples in the WGS was 42x. We compared cancer risk allele frequencies in cancer-free individuals with those in the general population available in public databases. The CFF members had fewer loss-of-function variants in suggested cancer predisposition genes compared to the ExAC data, and for high-risk cancer predisposition genes, no pathogenic variants were found in CFFs. For common low-penetrance breast, colorectal, and prostate cancer risk alleles, the results were not conclusive. The results suggest that, in line with twin and family studies, random environmental causes are so dominant that a clear demarcation of cancer-free populations using genetic data may not be feasible.

Dysregulation of LncRNA ANRIL mediated by miR-411-3p inhibits the malignant proliferation and tumor stem cell like property of multiple myeloma via hypoxia-inducible factor 1α

Long non-coding RNA (lncRNA) ANRIL has been reported to be closely related to the relapse of multiple myeloma patients. However, the functional role and underlying mechanism of lncRNA ANRIL in multiple myeloma are not known. This study aims to investigate the biological function of lncRNA ANRIL in multiple myeloma. In this study, compared with normal tissues from healthy donors, lncRNA ANRIL and HIF-1α expressions were up-regulated in tumor tissues from multiple myeloma patients. miR-411-3p expression was down-regulated in tumor tissues from multiple myeloma patients. Besides, lncRNA ANRIL can interact with miR-411-3p. HIF-1α was confirmed to be a target of miR-411-3p. Correlation analysis showed that lncRNA ANRIL expression was negatively correlated with miR-411-3p expression. HIF-1α expression was negatively correlated with miR-411-3p expression. Further transfection experiments showed that knockdown of ANRIL or overexpression of miR-411-3p significantly inhibited cell proliferation, tumor formation ability and tumor stem cell like property, promoted cell apoptosis in vitro. Finally, miR-411-3p mimic reduced tumor volume, improved survival rate, suppressed malignant proliferation and tumor stem cell like property in U266 xenograft model. Our results demonstrate that lncRNA ANRIL mediated by miR-411-3p promotes the malignant proliferation and tumor stem cell like property of multiple myeloma through regulating HIF-1α.

Mouse tumor susceptibility genes identify drug combinations for multiple myeloma

Long-term genetic studies utilizing backcross and congenic strain analyses coupled with positional cloning strategies and functional studies identified Cdkn2a, Mtor, and Mndal as mouse plasmacytoma susceptibility/resistance genes. Tumor incidence data in congenic strains carrying the resistance alleles of Cdkn2a and Mtor led us to hypothesize that drug combinations affecting these pathways are likely to have an additive, if not synergistic effect in inhibiting tumor cell growth. Traditional and novel systems-level genomic approaches were used to assess combination activity, disease specificity, and clinical potential of a drug combination involving rapamycin/everolimus, an Mtor inhibitor, with entinostat, an histone deacetylase inhibitor. The combination synergistically repressed oncogenic MYC and activated the Cdkn2a tumor suppressor. The identification of MYC as a primary upstream regulator led to the identification of small molecule binders of the G-quadruplex structure that forms in the NHEIII region of the MYC promoter. These studies highlight the importance of identifying drug combinations which simultaneously upregulate tumor suppressors and downregulate oncogenes.

Concordance in survival among first-degree relatives diagnosed with indolent lymphoid malignancies including chronic lymphocytic leukemia

Objectives

To investigate concordance in survival time among first‐degree relatives with lymphoid malignancies.

Methods

By linkage of national Swedish registers, we identified 66 430 patients diagnosed with a lymphoid malignancy 1958‐2016 with information on first‐degree relationships and follow‐up until 2017. Among these, we identified pairs of first‐degree relatives with any (N = 3326) or a similar (N = 690) lymphoid malignancy subtype. We defined survival in the first‐degree relative as good, expected, or poor based on tertiles of deviance residuals from a multivariable Cox regression model. Next, we used Cox regression to estimate hazard ratios (HR) of death with 95% confidence intervals (CI) among patients, using the survival of their first‐degree relative as exposure and adjusting for confounders.

Results

There was no concordance in survival among first‐degree relatives with any lymphoid malignancy (HR_good = 1.00 (reference), HR_Expected = 1.02, 95% CI: 0.89‐1.17, HR_Poor = 1.12, 95% CI: 0.98‐1.27, P_trend = .08). Among first‐degree relatives with indolent lymphoma, including chronic lymphocytic leukemia, those with a first‐degree relative to an expected or poor survival had worse outcome compared to those with a first‐degree relative with good survival (HR_Expected = 1.44, 95% CI: 0.82‐2.53, HR_Poor = 1.79, 95% CI: 1.07‐3.00, P_trend = .03).

Conclusion

Our results support a role of inherited factors in the outcome of indolent lymphoma, including chronic lymphocytic leukemia.

The SLAMF3 rs509749 polymorphism correlates with malignant potential in multiple myeloma

The signaling lymphocytic activation molecule family 3 (SLAMF3) is highly expressed on plasma cells from patients with multiple myeloma (MM) and induces high malignant potential by ERK signaling mediated via the interaction with adaptor proteins SHP2 and GRB2. This study focused on the single-nucleotide polymorphism (SNP) of the SLAMF3 gene (rs509749, 1804A>G, M602V) in MM. The SNP G allele was a major type, and the frequencies of the GG, GA, and AA genotypes were 61.8%, 29.4%, and 8.8%, respectively, in patients with MM, which was almost the same as in healthy the control group in the Japanese population. Interestingly, patients with GG genotypes had significantly shorter overall survival times than patients with GA/AA genotypes. Consistent with those results, SLAMF3-overexpressing KMS-34 cells with the G allele (V₆₀₂) had higher cell proliferation potential and were more resistant to anti-MM agents than those with the A allele (M₆₀₂). When those cells were subcutaneously inoculated into NOG mice, tumor sizes in mice receiving V₆₀₂ cells rapidly increased, and survival was significantly shorter than in mice injected with M₆₀₂ cells. Furthermore, SLAMF3 V₆₀₂ molecules bound more tightly to SHP2 and GRB2, with increased SHP2 and ERK phosphorylation compared with M₆₀₂ cells. The mRNA expression of cell cycle-related genes (CCND1 and CCNE1) and anti-apoptotic genes (BCL2L and p21) was increased in V₆₀₂ cells compared with M₆₀₂ cells. The results thus suggested that the G allele of SLAMF3 SNP rs509749 may be associated with MM disease progression.

MPRAscore: robust and non-parametric analysis of massively parallel reporter assays

MOTIVATION

Massively parallel reporter assays (MPRA) enable systematic screening of DNA sequence variants for effects on transcriptional activity. However, convenient analysis tools are still needed.

RESULTS

We introduce MPRAscore, a novel tool to infer allele-specific effects on transcription from MPRA data. MPRAscore uses a weighted, variance-regularized method to calculate variant effect sizes robustly, and a permutation approach to test for significance without assuming normality or independence.

AVAILABILITY AND IMPLEMENTATION

Source code (C++), precompiled binaries and data used in the paper at https://github.com/abhisheknrl/MPRAscore and https://www.ncbi.nlm.nih.gov/bioproject/PRJNA554195.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Abnormal PTBP1 Expression Sustains the Disease Progression of Multiple Myeloma

Multiple myeloma (MM) is a hematopoietic malignancy characterized by heterogeneity, which corresponds to alternative splicing (AS) profiles and disadjust gene expression. Bioinformatics analysis of AS factors possibly related to MM progression identified the polypyrimidine tract binding protein (PTBP1) as candidate. The purpose of this study was to confirm the incidence and prognostic value of PTBP1 in MM patients. Several cohorts of 2971 patients presenting newly diagnosed and relapsed MM were enrolled. Correlations between PTBP1 expression and clinicopathological characteristics, proliferative activity, and response to therapy of myeloma cells were analyzed. Moreover, the effect of PTBP1 on the AS pattern of specific aerobic glycolysis-related genes was explored in MM patients. Clinically, PTBP1 expression was present at all stages; it increased with disease progression and poor prognosis, which was even stronger elevated in patients with high tumor burden and drug resistance. Mechanistically, PTBP1 modulated AS of PKM2 and aerobic glycolysis-related genes in MM patients, which play synergistic or additive effects in clinical outcome. PTBP1 may be a novel marker for prognostic prediction and a promising therapeutic target for the development of anti-MM treatments.

A centromere-associated gene score for rapid determination of risk in multiple myeloma

Risk stratification in patients with multiple myeloma (MM) remains a challenge. As clinicopathological characteristics have been proven deficient for accurately defining risk stratification, molecular markers have gradually become the focus of interests. This study investigated the expressions of centromere-associated genes in MM patients, their potential as prognostic markers, and their roles in disease progression. Several cohorts of 2301 MM patients were enrolled and gene expression profiling (GEP) was used to screen for CENP-A through CENP-W. Correlations between centromere-associated genes and clinicopathological characteristics, proliferative activity and recurrence of MM patients were analyzed. Clinically, CENP-E/H/K/L/N/U/W expressions were present at high-risk MM, which were even stronger elevated in patients with high tumor burden and recurrence. Mechanistically, CENP-E/H/K/L/N/U/W and FOXM1 were positively expressed in MM patients, which play synergistic or additive effects in clinical outcome. Furthermore, CENP-E/H/K/L/N/U/W were used to construct a centromere-associated gene score (CGS) model, which proved to be strongly prognostic values in several independent cohorts compared to usual clinical prognostic parameters using multivariate Cox analysis. Patients in the CGS low-risk group were significantly related to better clinical outcome than those in high-risk group. In this study, we provided proof-of-concept that CENP-E/H/K/L/N/U/W have critical roles in MM patients' progression and prognosis. The CGS model validated in different datasets clearly indicated novel risk stratification for personalized anti-MM treatments.

Genomic Instability in Multiple Myeloma

Genomic instability (GIN), an increased tendency to acquire genomic alterations, is a cancer hallmark. However, its frequency, underlying causes, and disease relevance vary across different cancers. Multiple myeloma (MM), a plasma cell malignancy, evolves through premalignant phases characterized by genomic abnormalities. Next-generation sequencing (NGS) methods are deconstructing the genomic landscape of MM across the continuum of its development, inextricably linking malignant transformation and disease progression with increasing acquisition of genomic alterations, and illuminating the mechanisms that generate these alterations. Although GIN drives disease evolution, it also creates vulnerabilities such as dependencies on 'superfluous' repair mechanisms and the induction of tumor-specific antigens that can be targeted. We review the mechanisms of GIN in MM, the associated vulnerabilities, and therapeutic targeting strategies.

A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma

Purpose

Risk stratification in patients with multiple myeloma (MM) remains a challenge. As clinicopathological characteristics have been demonstrated insufficient for exactly defining MM risk, and molecular biomarkers have become the focuses of interests. Prognostic predictions based on gene expression profiles (GEPs) have been the most accurate to this day. The purpose of our study was to construct a risk score based on stemness genes to evaluate the prognosis in MM.

Materials and Methods

Bioinformatics studies by ingenuity pathway analyses in side population (SP) and non-SP (MP) cells of MM patients were performed. Firstly, co-expression network was built to confirm hub genes associated with the top five Kyoto Encyclopedia of Genes and Genomes pathways. Functional analyses of hub genes were used to confirm the biologic functions. Next, these selective genes were utilized for construction of prognostic model, and this model was validated in independent testing sets. Finally, five stemness genes (ROCK1, GSK3B, BRAF, MAPK1 and MAPK14) were used to build a MM side population 5 (MMSP5) gene model, which was demonstrated to be forcefully prognostic compared to usual clinical prognostic parameters by multivariate cox analysis. MM patients in MMSP5 low-risk group were significantly related to better prognosis than those in high-risk group in independent testing sets.

Conclusion

Our study provided proof-of-concept that MMSP5 model can be adopted to evaluate recurrence risk and clinical outcome for MM. The MMSP5 model evaluated in different databases clearly indicated novel risk stratification for personalized anti-MM treatments.

Functional Genetic Variant in ATG5 Gene Promoter in Acute Myocardial Infarction

Coronary artery disease (CAD) including acute myocardial infarction (AMI) is an inflammatory and metabolic disease mainly caused by atherosclerosis. Dysfunctional autophagy has been associated with abnormal lipid metabolism and inflammation. In previous studies, we have reported altered autophagic activity in AMI patients. As autophagy-related protein 5 (ATG5) is a core protein in autophagy, we speculated that altered ATG5 level may contribute to CAD and AMI development. In this study, the promoter of the ATG5 gene was genetically and functionally investigated in large groups of AMI patients (n = 378) and ethnic-matched healthy controls (n = 386). The results showed that a total of 15 genetic variants including 6 single-nucleotide polymorphisms (SNPs) in the ATG5 gene promoter were found in this study population. A novel deletion variant (g.106326168_70delTCT) and an SNP [g.106325757C > G (rs190825454)] were found in one 66-year-old male patient with non-ST-segment elevated AMI, but in none of controls. In cultured HEK-293 and H9c2 cells, the deletion variant significantly decreased the transcriptional activity of the ATG5 gene promoter (P < 0.01). In contrast, the genetic variants either identified only in controls or found in both AMI patients and controls did not affect the transcriptional activity of the ATG5 gene promoter (P > 0.05). Furthermore, an electrophoretic mobility shift assay showed that the deletion variant evidently affected the binding of a transcription factor. Therefore, the genetic variant identified in AMI may affect the activity of the ATG5 gene promoter and change the ATG5 level, contributing to AMI as a rare risk factor.

Genome-wide study on uveal melanoma patients finds association to DNA repair gene TDP1

Uveal melanoma is a life-threatening disease for which data on germline predisposition are essentially limited to mutations in the BAP1 gene. Many risk factors are shared between uveal melanoma and cutaneous melanoma, and these include fair skin color and light eye color. We carried out a genome-wide association study on 590 uveal melanoma patients and 5199 controls. Using a P-value limit of 10 we identified 11 loci with related odds ratios for the risk alleles ranging from 1.32 to 1.78. The smallest P-value in the overall analysis reached 1.07 × 10 for rs3759710 at 14q32.11, which is intronic to TDP1 (tyrosyl-DNA phosphodiesterase 1). This locus emerged as a genome-wide significant association for uveal melanoma clinical subtypes with any chromosomal aberrations (P = 10) and presence of epithelioid cells (P = 10). TDP1 is a DNA repair enzyme capable of repairing many types of DNA damage, including oxidative DNA lesions which may be relevant for uveal melanoma. We additionally wanted to replicate the previous candidate locus for uveal melanoma at chromosome 5p15.33 intronic to the CLPTM1L gene. Our analysis gave an odds ratio of 1.23 (95% confidence interval: 1.09-1.38; P = 0.0008) for the C allele of rs421284 and 1.21 (95% confidence interval: 1.07-1.36; P = 0.002) for the C allele of rs452932. Our data thus replicated the association of uveal melanoma with the CLPTM1L locus. Our data on TDP1 offer an attractive model positing that oxidative damage in pigmented tissue may be an initiation event in uveal melanoma and the level of damage may be regulated by the degree and type of iris pigmentation.

Second malignancies in multiple myeloma; emerging patterns and future directions

The changing landscape of treatment options for multiple myeloma has led to a higher proportion of patients achieving deep, long-lasting responses to therapy. With the associated improvement in overall survival, the development of subsequent second malignancies has become of increased significance. The risk of second malignancy after multiple myeloma is affected by a combination of patient-, disease- and therapy-related risk factors. This review discusses recent data refining our knowledge of these contributing factors, including current treatment modalities which increase risk (i.e. high-dose melphalan with autologous stem cell transplant and lenalidomide maintenance therapy). We highlight emerging data towards individualized risk- and response-adapted treatment strategies and discuss key areas requiring future research.

Next-Generation Sequencing for Clinical Management of Multiple Myeloma: Ready for Prime Time?

Personalized treatment is an attractive strategy that promises increased efficacy with reduced side effects in cancer. The feasibility of such an approach has been greatly boosted by next-generation sequencing (NGS) techniques, which can return detailed information on the genome and on the transcriptome of each patient's tumor, thus highlighting biomarkers of response or druggable targets that may differ from case to case. However, while the number of cancers sequenced is growing exponentially, much fewer cases are amenable to a molecularly-guided treatment outside of clinical trials to date. In multiple myeloma, genomic analysis shows a variety of gene mutations, aneuploidies, segmental copy-number changes, translocations that are extremely heterogeneous, and more numerous than other hematological malignancies. Currently, in routine clinical practice we employ reduced FISH panels that only capture three high-risk features as part of the R-ISS. On the contrary, recent advances have suggested that extending genomic analysis to the full spectrum of recurrent mutations and structural abnormalities in multiple myeloma may have biological and clinical implications. Furthermore, increased efficacy of novel treatments can now produce deeper responses, and standard methods do not have enough sensitivity to stratify patients in complete biochemical remission. Consequently, NGS techniques have been developed to monitor the size of the clone to a sensitivity of up to a cell in a million after treatment. However, even these techniques are not within reach of standard laboratories. In this review we will recapitulate recent advances in multiple myeloma genomics, with special focus on the ones that may have immediate translational impact. We will analyze the benefits and pitfalls of NGS-based diagnostics, highlighting crucial aspects that will need to be taken into account before this can be implemented in most laboratories. We will make the point that a new era in myeloma diagnostics and minimal residual disease monitoring is close and conventional genetic testing will not be able to return the required information. This will mandate that even in routine practice NGS should soon be adopted owing to a higher informative potential with increasing clinical benefits.

GWAS in cancer: progress and challenges

The genome-wide association study (GWAS) is an effective method to detect single-nucleotide polymorphisms (SNPs) of multiple individual genes based on linkage disequilibrium (LD). GWAS examines genotypes and distinguishing gene characteristics that are exhibited in diseases. In the past few decades, more and more literature has reported the results of applying GWAS to study tumors. Although many pleiotropic loci associated with complex phenotypes have been identified by GWAS, the biological functions of many genetic variation loci remain unclear, and the genetic mechanisms of most complex phenotypes cannot be systematically explained. In this article, we will review the new findings of several tumor types, and categorize the new sites and mechanisms that have recently been discovered. We linked the mechanisms of action of various tumors and searched for links to related gene expression pathways. We found that susceptible sites can be divided into hub genes and peripheral genes; the two interact to link gene expression in a variety of diseases.

Prognostic role of minichromosome maintenance family in multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy. The minichromosome maintenance (MCM) family involve in DNA replication and is vital in limiting replication in cell cycle. The prognostic role of MCMs in MM is still unclear. We took four independent GEO datasets to analyze the relationship between the expression of MCMs and myeloma progression and survival. The expression of MCMs showed an upward trend with myeloma progression in 205 patients. High MCM2/3/4/6/8 expression was associated with both poor EFS and OS (all p < 0.050). Multivariate analysis demonstrated that high MCM2 expression, B2M, and LDH were independent risk factors. Moreover, the combination of MCM2/B2M and MCM2/LDH was a better tool in prognostication. In conclusion, high MCM2 expression is an independent adverse prognostic factor and could be used as a prognostic biomarker in MM.

Genetic predisposition for multiple myeloma

Multiple myeloma (MM) is the second most common blood malignancy. Epidemiological family studies going back to the 1920s have provided evidence for familial aggregation, suggesting a subset of cases have an inherited genetic background. Recently, studies aimed at explaining this phenomenon have begun to provide direct evidence for genetic predisposition to MM. Genome-wide association studies have identified common risk alleles at 24 independent loci. Sequencing studies of familial cases and kindreds have begun to identify promising candidate genes where variants with strong effects on MM risk might reside. Finally, functional studies are starting to give insight into how identified risk alleles promote the development of MM. Here, we review recent findings in MM predisposition field, and highlight open questions and future directions.

High expression of chaperonin-containing TCP1 subunit 3 may induce dismal prognosis in multiple myeloma

The prognosis role of CCT3 in MM and the possible pathways it involved were studied in our research. By analyzing ten independent datasets (including 48 healthy donors, 2220 MM, 73 MGUS, and 6 PCL), CCT3 was found to express higher in MM than healthy donors, and the expression level was gradually increased from MGUS, SMM, MM to PCL (all P < 0.01). By analyzing three independent datasets (GSE24080, GSE2658, and GSE4204), we found that CCT3 was a significant indicator of poor prognosis (all P < 0.01). KEGG and GSEA analysis showed that CCT3 expression was associated with JAK-STAT3 pathway, Hippo signaling pathway, and WNT signaling pathway. In addition, different expressed genes analysis revealed MYC, which was one of the downstream genes regulated by JAK-STAT3 pathway, was upregulated in MM. This confirms that JAK-STAT3 signaling pathway may promote the progress of disease which was regulated by CCT3 expression. Our study revealed that CCT3 may play a supporting role at the diagnosis of myeloid, and high expression of CCT3 suggested poor prognosis in MM. CCT3 expression may promote the progression of MM mainly by regulating MYC through JAK-STAT3 signaling pathway.

MiR-135b-5p promotes viability, proliferation, migration and invasion of gastric cancer cells by targeting Krüppel-like factor 4 (KLF4)

INTRODUCTION

The expression of MiR-135b-5p was up-regulated while Krüppel-like factor 4 (KLF4) expression was extremely low in human gastric carcinoma (GC) tissues. This study aimed to explore the role of miR-135b-5p in GC cells and its influence on various cell capacity and viability by targeting KLF4.

MATERIAL AND METHODS

The dual-luciferase reporter assay was first performed and the target relationship between miR-135b-5p and KLF4 was confirmed. Then three GC cell lines and the human normal gastric epithelial cell line (GES1) were analyzed for the expression level of miR-135b-5p and KLF4 mRNA by RT-qPCR. The BGC-823 GC cell line was chosen for subsequent assays.

RESULTS

The expression of miR-135b-5p and KLF4 was manipulated via transfection. The changes of proliferation, invasion, migration, viability, cycle and apoptosis of GC cells were evaluated by MTS, colony formation assay, transwell assay, wound healing assay and flow cytometry assay, respectively. Overexpression of MiR-135b-5p enhanced viability, proliferation, invasion and migration of GC cells, increased cell viability and reduced cell apoptosis. Replenishing of KLF4 functioned oppositely.

CONCLUSIONS

The inhibitory effects of ectopic KLF4 could be attenuated by co-transfection of miR-135b-5p. Collective data suggested that miR-135b-5p has a tumor-promoting role in GC cells via downregulating KLF4. Hence, inhibition of miR-135b-5p could be valuable for treatment of gastric cancer.

Enhanced expression of FCER1G predicts positive prognosis in multiple myeloma

Background: Multiple myeloma (MM) is the second most common hematologic malignancy worldwide and does not have sufficient prognostic indicators. FCER1G (Fc fragment Of IgE receptor Ig) is located on chromosome 1q23.3 and is involved in the innate immunity. Early studies have shown that FCER1G participates in many immune-related pathways encompassing multiple cell types. Meanwhile, it is associated with many malignancies. However, the relationship between MM and FCER1G has not been studied.

Methods: In this study, we integrated nine independent gene expression omnibus (GEO) datasets and analyzed the associations of FCER1G expression and myeloma progression, ISS stage, 1q21 amplification and survival in 2296 myeloma patients and 48 healthy donors.

Results: The expression of FCER1G showed a decreasing trend with the advance of myeloma. As ISS stage and 1q21 amplification level increased, the expression of FCER1G decreased (P = 0.0012 and 0.0036, respectively). MM patients with high FCER1G expression consistently had longer EFS and OS across three large sample datasets (EFS: P = 0.0057, 0.0049, OS: P = 0.0014, 0.00065, 0.0019 and 0.0029, respectively). Meanwhile, univariate and multivariate analysis indicated that high FCER1G expression was an independent favorable prognostic factor for EFS and OS in MM patients (EFS: P = 0.006, 0.027, OS: P =0.002,0.025, respectively).

Conclusions: The expression level of FCER1G negatively correlated with myeloma progression, and high FCER1G expression may be applied as a favorable biomarker in MM patients.

Socioeconomic Position is Positively Associated with Monoclonal Gammopathy of Undetermined Significance in a Population-based Cohort Study

Knowledge of social inequalities in monoclonal gammopathy of undetermined significance (MGUS) will contribute to understanding multiple myeloma (MM) etiology, as MGUS consistently precedes MM. The aim of the present study was to examine whether socioeconomic position (SEP) is associated with MGUS in a population-based cohort including information on potential MGUS risk factors. Overall, 4787 study participants aged 45-75 years with information on MGUS were included. SEP indicators (education, income) and potential risk factors (i.e., body mass index, diabetes, smoking, dietary factors) were assessed at baseline. Overall, 260 MGUS cases were detected at baseline and prospectively over a 10-year follow-up. In age-adjusted logistic regression models, a lower chance of having MGUS at baseline or developing MGUS during 10 years of follow-up was indicated for groups of low SEP with odds ratios (OR) of 0.39 (95% confidence interval [95%-CI] 0.19-0.76) for women and 0.48 (95% CI 0.10-1.16) for men in the lowest compared to the highest educational group. After additionally including potential mediating risk factors in the regression models, the estimated ORs changed only slightly in magnitude. Similar results were obtained for income. Current smoking and low fruit consumption were associated with MGUS independently of SEP in women, but not in men. The present study indicates a lower MGUS risk in lower SEP groups. Supporting evidence is given that smoking and diet play a role in the development of MGUS independently of SEP, while it has to be assumed that risk factors unknown to date are responsible for the observed social inequalities in MGUS.

Translocation (11;14) in newly diagnosed multiple myeloma, time to reclassify this standard risk chromosomal aberration?

OBJECTIVES

The most common translocation in multiple myeloma (MM) is t(11;14)(q13;q32), and its importance as prognostic factor has been controversial. The aim was to analyze its prognostic value.

METHOD

In this retrospective study of 469 newly diagnosed myeloma patients, outcomes in patients with (11;14) and standard risk (t(11;14)SR) or high risk (t(11;14)HR) cytogenetics were compared to outcomes of patients without t(11;14) and SR (non-t(11;14)SR) or HR (non-t(11;14)HR), respectively.

RESULTS

Overall progression-free survival (PFS) was shorter in t(11;14)SR than non-t(11;14)SR (median 28.9 vs 35.3 months); however, the difference was not significant (P = .2). Overall survival (OS) did not differ significantly between the groups. In the subgroup of patients that did not receive high-dose treatment, PFS was shorter for t(11;14)SR compared to non-t(11;14)SR, 10.6 vs 24.6 months (P = .01). Although OS were shorter for t(11,14)SR compared to non-t(11;14)SR (5-year OS 41.7% vs 63.8%), the difference was not significant (P = .1). In HDT patients, no significant difference was observed for OS or PFS between those with or without t(11;14).

CONCLUSION

This study shows that t(11;14) is associated with poorer outcome in MM, particularly in non-high-dose-treated SR patients. It should be considered an intermediate or high-risk marker in these patients.

PHF19 promotes multiple myeloma tumorigenicity through PRC2 activation and broad H3K27me3 domain formation

Dysregulation of polycomb repressive complex 2 (PRC2) promotes oncogenesis partly through its enzymatic function for inducing trimethylation of histone H3 lysine 27 (H3K27me3). However, it remains to be determined how PRC2 activity is regulated in normal and diseased settings. We here report a PRC2-associated cofactor, PHD finger protein 19 (PHF19; also known as polycomb-like 3), as a crucial mediator of tumorigenicity in multiple myeloma (MM). Overexpression and/or genomic amplification of PHF19 is found associated with malignant progression of MM and plasma cell leukemia, correlating to worse treatment outcomes. Using various MM models, we demonstrated a critical requirement of PHF19 for tumor growth in vitro and in vivo. Mechanistically, PHF19-mediated oncogenic effect relies on its PRC2-interacting and chromatin-binding functions. Chromatin immunoprecipitation followed by sequencing profiling showed a critical role for PHF19 in maintaining the H3K27me3 landscape. PHF19 depletion led to loss of broad H3K27me3 domains, possibly due to impaired H3K27me3 spreading from cytosine guanine dinucleotide islands, which is reminiscent to the reported effect of an "onco"-histone mutation, H3K27 to methionine (H3K27M). RNA-sequencing-based transcriptome profiling in MM lines also demonstrated a requirement of PHF19 for optimal silencing of PRC2 targets, which include cell cycle inhibitors and interferon-JAK-STAT signaling genes critically involved in tumor suppression. Correlation studies using patient sample data sets further support a clinical relevance of the PHF19-regulated pathways. Lastly, we show that MM cells are generally sensitive to PRC2 inhibitors. Collectively, this study demonstrates that PHF19 promotes MM tumorigenesis through enhancing H3K27me3 deposition and PRC2's gene-regulatory functions, lending support for PRC2 blockade as a means for MM therapeutics.

Colon Cancer-Associated Transcripts 1 and 2: Roles and functions in human cancers

The long noncoding RNAs (lncRNAs) Colon Cancer-Associated Transcripts 1 and 2 (CCAT1 and CCAT2) are located in a recurrently amplified region in cancers. Their proximity with the Myc oncogene and their interactions with its promoter provided further evidence for their contribution in the tumorigenesis processes. Several cell line and clinical studies have shown upregulation of these lncRNAs in diverse malignancies. Moreover, some single nucleotide variants within these genes have been associated with cancer risk or therapeutic response in different populations. Besides, these two lncRNAs act as sponges for some tumor suppressor microRNAs (miRNAs), thus promoting cancer evolution. In the current study, we review recent literature about their expression level, interaction with cancer-related pathways, their role in determination of cell fate and their contribution in malignant phenotype characteristics. Taken together, the current literature shows that these lncRNAs are putative targets for design of novel treatment strategies. Moreover, their expression levels in biopsied samples, exosomes, and sera of patients might be applied as diagnostic biomarkers or markers for patient follow-up.

Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes

BACKGROUND

While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS).

RESULTS

GWAS data on 7319 MM cases and 234,385 controls was integrated with Genotype-Tissue Expression Project (GTEx) data assayed in 48 tissues (sample sizes, N = 80-491), including lymphocyte cell lines and whole blood, to predict gene expression. We identified 108 genes at 13 independent regions associated with MM risk, all of which were in 1 Mb of known MM GWAS risk variants. Of these, 94 genes, located in eight regions, had not previously been considered as a candidate gene for that locus.

CONCLUSIONS

Our findings highlight the value of leveraging expression data from multiple tissues to identify candidate genes responsible for GWAS associations which provide insight into MM tumorigenesis. Among the genes identified, a number have plausible roles in MM biology, notably APOBEC3C, APOBEC3H, APOBEC3D, APOBEC3F, APOBEC3G, or have been previously implicated in other malignancies. The genes identified in this TWAS can be explored for follow-up and validation to further understand their role in MM biology.

Clinical use of SNP-microarrays for the detection of genome-wide changes in haematological malignancies

Single nucleotide polymorphism (SNP) microarrays are commonly used for the clinical investigation of constitutional genomic disorders; however, their adoption for investigating somatic changes is being recognised. With increasing importance being placed on defining the cancer genome, a shift in technology is imperative at a clinical level. Microarray platforms have the potential to become frontline testing, replacing or complementing standard investigations such as FISH or karyotype. This 'molecular karyotype approach' exemplified by SNP-microarrays has distinct advantages in the investigation of several haematological malignancies. A growing body of literature, including guidelines, has shown support for the use of SNP-microarrays in the clinical laboratory to aid in a more accurate definition of the cancer genome. Understanding the benefits of this technology along with discussing the barriers to its implementation is necessary for the development and incorporation of SNP-microarrays in a clinical laboratory for the investigation of haematological malignancies.

Regions of homozygosity as risk factors for multiple myeloma

Genomic regions of homozygosity (ROH), detectable in outbred populations, have been implicated as determinants of inherited risk. To examine whether ROH is associated with risk of multiple myeloma (MM), we performed whole-genome homozygosity analysis using single-nucleotide polymorphism genotype data from 2,282 MM cases and 5,197 controls, with replication in an additional 878 MM cases and 7,083 controls. Globally, the distribution of ROH between cases and controls was not significantly different. However, one ROH at chromosome 9q21, harboring the B-cell transcription factor gene KLF9, showed evidence of a consistent association and may therefore warrant further investigation as a candidate risk factor for MM. Overall, our analysis provides little support for a homozygosity signature being a significant factor in MM risk.

The effects of MicroRNA deregulation on pre-RNA processing network in multiple myeloma

Over the last few years, a detailed map of genetic and epigenetic lesions that underlie multiple myeloma (MM) has been created. Regulation of microRNA (miR)-dependent gene expression and mRNA splicing play significant roles in MM pathogenesis; however, to date an interplay between these processes is not yet delineated. Here we investigated miR-mediated regulation of splicing networks at the transcriptome level. Our studies show that a significant number (78%) of miRs which are either up- or down-regulated in patient CD138+ MM cells, but not in healthy donors (HD) CD138+ plasma cells (PC), target genes involved in early stages of pre-mRNA splicing. We also identified deregulated miRs that target core splicing factors (SF) and modifiers (SM, enhancers/silencers) which cause altered splicing in MM. Our studies suggest that Let-7f, in combination other miRs which are frequently and significantly deregulated in patients with overt MM, targets genes that regulate intron excision. Importantly, deregulated expression of certain miRs in MM promote increased intron retention, a novel characteristic of the MM genome, by inducing deregulated expression of the genes that regulate the splicing network. Our studies, therefore, provide the rationale for therapeutically targeting deregulated miRs to reverse aberrant splicing and improve patient outcome in MM.

Gene Co-expression Network and Copy Number Variation Analyses Identify Transcription Factors Associated With Multiple Myeloma Progression

Multiple myeloma (MM) has two clinical precursor stages of disease: monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). However, the mechanism of progression is not well understood. Because gene co-expression network analysis is a well-known method for discovering new gene functions and regulatory relationships, we utilized this framework to conduct differential co-expression analysis to identify interesting transcription factors (TFs) in two publicly available datasets. We then used copy number variation (CNV) data from a third public dataset to validate these TFs. First, we identified co-expressed gene modules in two publicly available datasets each containing three conditions: normal, MGUS, and SMM. These modules were assessed for condition-specific gene expression, and then enrichment analysis was conducted on condition-specific modules to identify their biological function and upstream TFs. TFs were assessed for differential gene expression between normal and MM precursors, then validated with CNV analysis to identify candidate genes. Functional enrichment analysis reaffirmed known functional categories in MM pathology, the main one relating to immune function. Enrichment analysis revealed a handful of differentially expressed TFs between normal and either MGUS or SMM in gene expression and/or CNV. Overall, we identified four genes of interest (MAX, TCF4, ZNF148, and ZNF281) that aid in our understanding of MM initiation and progression.

Germline Risk Contribution to Genomic Instability in Multiple Myeloma

Genomic instability, a well-established hallmark of human cancer, is also a driving force in the natural history of multiple myeloma (MM) - a difficult to treat and in most cases fatal neoplasm of immunoglobulin producing plasma cells that reside in the hematopoietic bone marrow. Long recognized manifestations of genomic instability in myeloma at the cytogenetic level include abnormal chromosome numbers (aneuploidy) caused by trisomy of odd-numbered chromosomes; recurrent oncogene-activating chromosomal translocations that involve immunoglobulin loci; and large-scale amplifications, inversions, and insertions/deletions (indels) of genetic material. Catastrophic genetic rearrangements that either shatter and illegitimately reassemble a single chromosome (chromotripsis) or lead to disordered segmental rearrangements of multiple chromosomes (chromoplexy) also occur. Genomic instability at the nucleotide level results in base substitution mutations and small indels that affect both the coding and non-coding genome. Sometimes this generates a distinctive signature of somatic mutations that can be attributed to defects in DNA repair pathways, the DNA damage response (DDR) or aberrant activity of mutator genes including members of the APOBEC family. In addition to myeloma development and progression, genomic instability promotes acquisition of drug resistance in patients with myeloma. Here we review recent findings on the genetic predisposition to myeloma, including newly identified candidate genes suggesting linkage of germline risk and compromised genomic stability control. The role of ethnic and familial risk factors for myeloma is highlighted. We address current research gaps that concern the lack of studies on the mechanism by which germline risk alleles promote genomic instability in myeloma, including the open question whether genetic modifiers of myeloma development act in tumor cells, the tumor microenvironment (TME), or in both. We conclude with a brief proposition for future research directions, which concentrate on the biological function of myeloma risk and genetic instability alleles, the potential links between the germline genome and somatic changes in myeloma, and the need to elucidate genetic modifiers in the TME.