Progress in the identification of gene mutations involved in multiple myeloma

Dissecting the Puzzling Roles of FAM46C: A Multifaceted Pan-Cancer Tumour Suppressor with Increasing Clinical Relevance

FAM46C is a well-established tumour suppressor with a role that is not completely defined or universally accepted. Although FAM46C expression is down-modulated in several tumours, significant mutations in the FAM46C gene are only found in multiple myeloma (MM). Consequently, its tumour suppressor activity has primarily been studied in the MM context. However, emerging evidence suggests that FAM46C is involved also in other cancer types, namely colorectal, prostate and gastric cancer and squamous cell and hepatocellular carcinoma, where FAM46C expression was found to be significantly reduced in tumoural versus non-tumoural tissues and where FAM46C was shown to possess anti-proliferative properties. Accordingly, FAM46C was recently proposed to function as a pan-cancer prognostic marker, bringing FAM46C under the spotlight and attracting growing interest from the scientific community in the pathways modulated by FAM46C and in its mechanistic activity. Here, we will provide the first comprehensive review regarding FAM46C by covering (1) the intracellular pathways regulated by FAM46C, namely the MAPK/ERK, PI3K/AKT, β-catenin and TGF-β/SMAD pathways; (2) the models regarding its mode of action, specifically the poly(A) polymerase, intracellular trafficking modulator and inhibitor of centriole duplication models, focusing on connections and interdependencies; (3) the regulation of FAM46C expression in different environments by interferons, IL-4, TLR engagement or transcriptional modulators; and, lastly, (4) how FAM46C expression levels associate with increased/decreased tumour cell sensitivity to anticancer agents, such as bortezomib, dexamethasone, lenalidomide, pomalidomide, doxorubicin, melphalan, SK1-I, docetaxel and norcantharidin.

Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. To investigate global interactions in MM, we combined a known protein interaction network with a large clinically annotated MM dataset. We hypothesized that an unbiased network analysis method based on large-scale similarities in gene expression, copy number aberration, and protein interactions may provide novel biological insights. Applying a novel measure of network robustness, Ollivier-Ricci Curvature, we examined patterns in the RNA-Seq gene expression and CNA data and how they relate to clinical outcomes. Hierarchical clustering using ORC differentiated high-risk subtypes with low progression free survival. Differential gene expression analysis defined 118 genes with significantly aberrant expression. These genes, while not previously associated with MM, were associated with DNA repair, apoptosis, and the immune system. Univariate analysis identified 8/118 to be prognostic genes; all associated with the immune system. A network topology analysis identified both hub and bridge genes which connect known genes of biological significance of MM. Taken together, gene interaction network analysis in MM uses a novel method of global assessment to demonstrate complex immune dysregulation associated with shorter survival.

Molecular genetic aberrations in the pathogenesis of multiple myeloma

Multiple myeloma (MM) is the second most common form of blood cancer characterized by clonal expansion of malignant plasma cells within the bone marrow. MM is a complex, progressive, and highly heterogeneous malignancy, which occurs via a multistep transformation process involving primary and secondary oncogenic events. Recent advances in molecular techniques have further expanded our understanding of the mutational landscape, clonal composition, and dynamic evolution patterns of MM. The first part of this review describes the key oncogenic events involved in the initiation and progression of MM, together with their prognostic impact. The latter part highlights the most prominent findings concerning genomic aberrations promoted by gene expression profiling (GEP) and next-generation sequencing (NGS) in MM. This review provides a concise understanding of the molecular pathogenesis of the MM genome and the importance of adopting emerging molecular technology in future clinical management of MM.

Loss of Heterozygosity in the Circulating Tumor DNA and CD138+ Bone Marrow Cells in Multiple Myeloma

Multiple myeloma (MM) is characterized by heterogeneity of tumor cells. The study of tumor cells from blood, bone marrow, plasmacytoma, etc., allows us to identify similarities and differences in tumor lesions of various anatomical localizations. The aim of this study was to compare the loss of heterozygosity (LOH) by tumor cells by assessing STR profiles of different MM lesions. We examined paired samples of plasma circulating tumor DNA (ctDNA) and CD138+ bone marrow cells in MM patients. For patients with plasmacytomas (66% of 38 patients included), the STR profile of plasmacytomas was also studied when biopsy samples were available. Diverse patterns of LOH were found in lesions of different localization for most patients. LOH in plasma ctDNA, bone marrow, and plasmacytoma samples was found for 55%, 71%, and 100% of patients, respectively. One could expect a greater variety of STR profiles in aberrant loci for patients with plasmacytomas. This hypothesis was not confirmed-no difference in the frequency of LOH in MM patients with or without plasmacytomas was found. This indicates the genetic diversity of tumor clones in MM, regardless of the presence of extramedullar lesions. Therefore, we conclude that risk stratification based on molecular tests performed solely on bone marrow samples may not be sufficient for all MM patients, including those without plasmacytomas. Due to genetic heterogeneity of MM tumor cells from various lesions, the high diagnostic value of liquid biopsy approaches becomes obvious.

Mutational analysis and protein profiling predict drug sensitivity in multiple myeloma cell lines

INTRODUCTION

Multiple myeloma (MM) is a heterogeneous disease where cancer-driver mutations and aberrant signaling may lead to disease progression and drug resistance. Drug responses vary greatly, and there is an unmet need for biomarkers that can guide precision cancer medicine in this disease.

METHODS

To identify potential predictors of drug sensitivity, we applied integrated data from drug sensitivity screening, mutational analysis and functional signaling pathway profiling in 9 cell line models of MM. We studied the sensitivity to 33 targeted drugs and their association with the mutational status of cancer-driver genes and activity level of signaling proteins.

RESULTS

We found that sensitivity to mitogen-activated protein kinase kinase 1 (MEK1) and phosphatidylinositol-3 kinase (PI3K) inhibitors correlated with mutations in NRAS/KRAS, and PI3K family genes, respectively. Phosphorylation status of MEK1 and protein kinase B (AKT) correlated with sensitivity to MEK and PI3K inhibition, respectively. In addition, we found that enhanced phosphorylation of proteins, including Tank-binding kinase 1 (TBK1), as well as high expression of B cell lymphoma 2 (Bcl-2), correlated with low sensitivity to MEK inhibitors.

DISCUSSION

Taken together, this study shows that mutational status and signaling protein profiling might be used in further studies to predict drug sensitivities and identify resistance markers in MM.

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.

Molecular characterization of multiple myeloma

Multiple myeloma (MM) is a hematologic malignancy that occurs when plasma cells, a type of white blood cell, grow out of control and start to overproduce antibodies that accumulates in blood and bone marrow. Despite the recent advance the survival rate for MM has not been increased significantly, which opens the need for identifying new molecular targets. This review article presents the most frequently observed gene mutations (KRAS (22.0%), NRAS (18.0%), DIS3 (9.3%), TTN (8.3%), ZNF717 (8.3%), TENT5C (7.3%), TP53 (7.3%) %), BRAF (6.3%), MUC16 (6.3%), RYR2 (5.4%), LRP1B (5.4%)) in MM patients and its rates, correlations, clinical significance, importance in the framework of MM disease and potential novel targets which are collected from the literature. The genes that are mutated in MM patients (211) taken from cBioportal data set. In conclusion, in the study conducted in MM patients, the 3 genes with the most frequent mutations were recorded as KRAS, NRAS and DIS3, respectively. In addition, in the context of our literature reviews and the data obtained, it appears that the TZNF717, TTN, MUC16, RYR2 genes need further study within the framework of MM.

MicroRNA-125a/b-5p promotes malignant behavior in multiple myeloma cells and xenograft tumor growth by targeting DIS3

Multiple myeloma (MM) is a hematological malignancy with a high prevalence and is characterized by the clonal expansion of malignant plasma cells. As a new tumor suppressor, defective in sister chromatid joining (DIS3) was reported to be a gene closely related to MM. This study elucidated the biological functions and underlying mechanisms of DIS3 in MM. DIS3 mRNA and protein levels were detected using RT-qPCR and western blotting, respectively. Methyl thiazolyl tetrazolium assays, flow cytometry analyses, Transwell assays, and wound healing assays were performed to detect the proliferation, apoptosis, invasion, and migration of MM cells. The binding relationship between miR-125a/b-5p and DIS3 was verified using luciferase reporter assays and RNA pulldown assays. Xenograft tumor models were established in nude mice to investigate the effects of miR-125a/b-5p and DIS3 on tumor growth in vivo. DIS3 levels were downregulated in MM cells, and DIS3 upregulation inhibited the malignant behaviors of MM cells. Mechanistically, miR-125a/b-5p directly targeted the 3' untranslated region of DIS3. The expression of miR-125a/b-5p was upregulated in MM cells, miR-125a/b-5p knockdown inhibited the malignant behaviors of MM cells, and the inhibitory effect was reversed by DIS3 downregulation. The results of in vivo experiments indicated that miR-125a/b-5p promoted tumor growth by downregulating DIS3. Overall, miR-125a/b-5p promotes MM cellular processes and xenograft tumor growth by targeting DIS3.

Antitumor efficacy of XPO1 inhibitor Selinexor in KRAS-mutant lung adenocarcinoma patient-derived xenografts

Gain-of-function Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations occur in 25% of lung adenocarcinomas, and these tumors are challenging to treat. Some preclinical work, largely based on cell lines, suggested KRASmut lung cancers are especially dependent on the nuclear export protein exportin-1 (XPO1), while other work supports XPO1 being a broader cancer dependency. To investigate the sensitivity of KRASmut lung cancers to XPO1 inhibition in models that more closely match clinical tumors, we treated 10 independently established lung cancer patient-derived tumor xenografts (PDXs) with the clinical XPO1 inhibitor, Selinexor. Monotherapy with Selinexor reduced tumor growth in all KRASmut PDXs, which included 4 different codon mutations, and was more effective than the clinical MEK1/2 inhibitor, Trametinib. Selinexor was equally effective in KRASG12C and KRASG12D tumors, with TP53 mutations being a biomarker for a weaker drug response. By mining genome-wide dropout datasets, we identified XPO1 as a universal cancer cell dependency and confirmed this functionally in two KRASWT PDX models harboring kinase drivers. However, targeted kinase inhibitors were more effective than Selinexor in these models. Our findings support continued investigation of XPO1 inhibitors in KRASmut lung adenocarcinoma, regardless of the codon alteration.

Structural and functional characterization of multiple myeloma associated cytoplasmic poly(A) polymerase FAM46C

Background

Multiple myeloma (MM) is a hematologic malignancy characterized by the accumulation of aberrant plasma cells within the bone marrow. The high frequent mutation of family with sequence similarity 46, member C (FAM46C) is closely related with the occurrence and progression of MM. Recently, FAM46C has been identified as a non‐canonical poly(A) polymerase (PAP) that functions as a tumor suppressor in MM. This study aimed to elucidate the structural features of this novel non‐canonical PAP and how MM‐related mutations affect the structural and biochemical properties of FAM46C, eventually advancing our understandings towards FAM46C mutation‐related MM occurrence.

Methods

We purified and crystallized a mammalian FAM46C construct, and solved its structure. Next, we characterized the property of FAM46C as a PAP through a combination of structural analysis, site‐directed mutagenesis and biochemical assays, and by comparison with its homolog FAM46B. Finally, we structurally analyzed MM‐related FAM46C mutations and tested the enzymatic activity of corresponding mutants.

Results

We determined the crystal structure of a mammalian FAM46C protein at 2.35 Å, and confirmed that FAM46C preferentially consumed adenosine triphosphate (ATP) and extended A‐rich RNA substrates. FAM46C showed a weaker PAP activity than its homolog FAM46B, and this difference was largely dependent on the residue variance at particular sites. Of them, residues at positions 77, 290, and 298 of mouse FAM46C were most important for the divergence in enzymatic activity. Among the MM‐associated FAM46C mutants, those residing at the catalytic site (D90G and D90H) or putative RNA‐binding site (I155L, S156F, D182Y, F184L, Y247V, and M270V) showed abolished or compromised PAP activity of FAM46C, while N72A and S248A did not severely affect the PAP activity. FAM46C mutants D90G, D90H, I155L, S156F, F184L, Y247V, and M270V had significantly lower inhibitory effect on apoptosis of RPMI‐8226 cells as compared to wild‐type FAM46C.

Conclusions

FAM46C is a prokaryotic‐like PAP with preference for A‐rich RNA substrates, and showed distinct enzymatic efficiency with its homolog FAM46B. The MM‐related missense mutations of FAM46C lead to various structural and biochemical outcomes to the protein.

Prognostic significance of esterase gene expression in multiple myeloma

BACKGROUND

Esterase enzymes differ in substrate specificity and biological function and may display dysregulated expression in cancer. This study evaluated the biological significance of esterase expression in multiple myeloma (MM).

METHODS

For gene expression profiling and evaluation of genomic variants in the Institute for Molecular Medicine Finland (FIMM) cohort, bone marrow aspirates were obtained from patients with newly diagnosed MM (NDMM) or relapsed/refractory MM (RRMM). CD138+ plasma cells were enriched and used for RNA sequencing and analysis, and to evaluate genomic variation. The Multiple Myeloma Research Foundation (MMRF) Relating Clinical Outcomes in MM to Personal Assessment of Genetic Profile (CoMMpass) dataset was used for validation of the findings from FIMM.

RESULTS

MM patients (NDMM, n = 56; RRMM, n = 78) provided 171 bone marrow aspirates (NDMM, n = 56; RRMM, n = 115). Specific esterases exhibited relatively high or low expression in MM, and expression of specific esterases (UCHL5, SIAE, ESD, PAFAH1B3, PNPLA4 and PON1) was significantly altered on progression from NDMM to RRMM. High expression of OVCA2, PAFAH1B3, SIAE and USP4, and low expression of PCED1B, were identified as poor prognostic markers (P < 0.05). The MMRF CoMMpass dataset provided validation that higher expression of PAFAH1B3 and SIAE, and lower expression of PCED1B, were associated with poor prognosis.

CONCLUSIONS

Esterase gene expression levels change as patients progress from NDMM to RRMM. High expression of OVCA2, PAFAH1B3, USP4 and SIAE, and low expression of PCED1B, are poor prognostic markers in MM, suggesting a role for these esterases in myeloma biology.

A prognostic survival model based on metabolism-related gene expression in plasma cell myeloma

Accurate survival prediction of persons with plasma cell myeloma (PCM) is challenging. We interrogated clinical and laboratory co-variates and RNA matrices of 1040 subjects with PCM from public datasets in the Gene Expression Omnibus database in training (N = 1) and validation (N = 2) datasets. Genes regulating plasma cell metabolism correlated with survival were identified and seven used to build a metabolic risk score using Lasso Cox regression analyses. The score had robust predictive performance with 5-year survival area under the curve (AUCs): 0.71 (95% confidence interval, 0.65, 0.76), 0.88 (0.67, 1.00) and 0.64 (0.57, 0.70). Subjects in the high-risk training cohort (score > median) had worse 5-year survival compared with those in the low-risk cohort (62% [55, 68%] vs. 85% [80, 90%]; p < 0.001). This was also so for the validation cohorts. A nomogram combining metabolic risk score with Revised International Staging System (R-ISS) score increased survival prediction from an AUC = 0.63 [0.58, 0.69] to an AUC = 0.73 [0.66, 0.78]; p = 0.015. Modelling predictions were confirmed in in vitro tests with PCM cell lines. Our metabolic risk score increases survival prediction accuracy in PCM.

Prognostic value of integrated cytogenetic, somatic variation, and copy number variation analyses in Korean patients with newly diagnosed multiple myeloma

BACKGROUND

To investigate the prognostic value of gene variants and copy number variations (CNVs) in patients with newly diagnosed multiple myeloma (NDMM), an integrative genomic analysis was performed.

METHODS

Sixty-seven patients with NDMM exhibiting more than 60% plasma cells in the bone marrow aspirate were enrolled in the study. Whole-exome sequencing was conducted on bone marrow nucleated cells. Mutation and CNV analyses were performed using the CNVkit and Nexus Copy Number software. In addition, karyotype and fluorescent in situ hybridization were utilized for the integrated analysis.

RESULTS

Eighty-three driver gene mutations were detected in 63 patients with NDMM. The median number of mutations per patient was 2.0 (95% confidence interval [CI] = 2.0-3.0, range = 0-8). MAML2 and BHLHE41 mutations were associated with decreased survival. CNVs were detected in 56 patients (72.7%; 56/67). The median number of CNVs per patient was 6.0 (95% CI = 5.7-7.0; range = 0-16). Among the CNVs, 1q gain, 6p gain, 6q loss, 8p loss, and 13q loss were associated with decreased survival. Additionally, 1q gain and 6p gain were independent adverse prognostic factors. Increased numbers of CNVs and driver gene mutations were associated with poor clinical outcomes. Cluster analysis revealed that patients with the highest number of driver mutations along with 1q gain, 6p gain, and 13q loss exhibited the poorest prognosis.

CONCLUSIONS

In addition to the known prognostic factors, the integrated analysis of genetic variations and CNVs could contribute to prognostic stratification of patients with NDMM.

The clinical impact of hepatitis C virus infection in Egyptian multiple myeloma patients

BACKGROUND

Multiple myeloma (MM) is a human B cell neoplasia characterized by the clonal proliferation of malignant plasma cells in the bone marrow. Worldwide, hepatitis C virus (HCV) infection is a public health problem. For MM patients, the clinical impact of preexisting HCV infection is still unclear. We aim to assess the clinical characteristics and the prevalence of the HCV infection in Egyptian MM patients. This observational study included 81 MM patients. HCV antibody assay was performed, and positive cases were confirmed using a reverse transcription-quantitative PCR (RT-PCR) method.

RESULTS

Fifteen (18.5%) patients were anti-HCV antibody positive. Only 6/15 (7.4%) patients were HCV RNA positive by RT-PCR. Liver affection in the form of hyperbilirubinemia with grade 4 adverse events was significantly higher in the anti-HCV positive/HCV RNA positive group versus anti HCV negative group (16.7% vs. 1.5%, p value = 0.005). The median HCV-RNA before the initiation of chemotherapy was 2.5 log IU/ml with mean ± SD = 4.25 ± 1.6 with no HCV reactivation. In the univariate and multivariate analysis, HCV infection was not an independent factor related to DFS. Low hemoglobin level < 10 g/dL (HR 0.59, 95% CI, 0.36-0.97, p value = 0.037) and abnormal serum total bilirubin level (HR 1.9, 95% CI 1.03-3.5, p value = 0.039) influenced DFS in the univariate analysis. However, in the multivariate analysis, serum calcium level greater than 12 mg/dL (HR 7.04, 95% CI 1.12-44.45, p value = 0.038) and abnormal serum total bilirubin level (HR 10.9, 95% CI 2.92-41.02, p value = < 0.001) remained statistically significant worse prognostic factors.

CONCLUSION

In conclusion, our study revealed the prevalence of HCV infection in Egyptian MM patients. Serologic tests at diagnosis are necessary to identify these patients, and confirmation of positive cases by molecular techniques should be mandatory, with regular follow-up for liver dysfunction. Finally, further larger studies explaining the molecular mechanisms linking HCV and the MM pathogenesis are warranted.

Functions and mechanisms of RNA tailing by metazoan terminal nucleotidyltransferases

Termini often determine the fate of RNA molecules. In recent years, 3' ends of almost all classes of RNA species have been shown to acquire nontemplated nucleotides that are added by terminal nucleotidyltransferases (TENTs). The best-described role of 3' tailing is the bulk polyadenylation of messenger RNAs in the cell nucleus that is catalyzed by canonical poly(A) polymerases (PAPs). However, many other enzymes that add adenosines, uridines, or even more complex combinations of nucleotides have recently been described. This review focuses on metazoan TENTs, which are either noncanonical PAPs or terminal uridylyltransferases with varying processivity. These enzymes regulate RNA stability and RNA functions and are crucial in early development, gamete production, and somatic tissues. TENTs regulate gene expression at the posttranscriptional level, participate in the maturation of many transcripts, and protect cells against viral invasion and the transposition of repetitive sequences. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Processing > 3' End Processing RNA Turnover and Surveillance > Regulation of RNA Stability.