Prognostic Biomarker In Multiple Myeloma Research Articles

Navigating the clinical landscape: Update on the diagnostic and prognostic biomarkers in multiple myeloma.

Multiple myeloma, a complex hematologic malignancy, has devastating consequences for patients, including dramatic bone loss, severe bone pain, and pathological fractures that markedly decrease the quality of life and impact the survival of affected patients. This necessitates a refined understanding of biomarkers for accurate diagnosis and prognosis of such severe malignancy. Therefore, this article comprehensively covers current research, elucidating the diverse spectrum of biomarkers employed in clinical settings. From traditional serum markers to advanced molecular profiling techniques, the review provides a thorough examination of their utility and limitations. Through this scoping review, emphasis is placed on the evolving landscape of personalized medicine, where biomarkers play a pivotal role in tailoring therapeutic strategies. The integration of genomic, proteomic, next generation sequencing and flow cytometric data further enriches the discussion, unravelling the molecular intricacies underlying disease progression. The updated criteria allow for the treatment of people who clearly would benefit from therapy and might live longer if treated before significant organ damage occurs. Navigating through the evolving diagnostic and prognostic paradigms in multiple myeloma, this article equips clinicians and researchers with crucial insights for optimizing patient care and advancing future therapeutic approaches.

Integrating p53-associated genes and infiltrating immune cell characterization as a prognostic biomarker in multiple myeloma

BackgroundTumor genetic anomalies and immune dysregulation are pivotal in the progression of multiple myeloma (MM). Accurate patient stratification is essential for effective MM management, yet current models fail to comprehensively incorporate both molecular and immune profiles. MethodsWe examined 776 samples from the MMRF CoMMpass database, employing univariate regression with LASSO and CIBERSORT algorithms to identify 15 p53-related genes and six immune cells with prognostic significance in MM. A p53-TIC (tumor-infiltrating immune cells) classifier was constructed by calculating scores using the bootstrap-multicox method, which was further validated externally (GSE136337) and through ten-fold internal cross-validation for its predictive reliability and robustness. ResultsThe p53-TIC classifier demonstrated excellent performance in predicting the prognosis in MM. Specifically, patients in the p53low/TIChigh subgroup had the most favorable prognosis and the lowest tumor mutational burden (TMB). Conversely, those in the p53high/TIClow subgroup, with the least favorable prognosis and the highest TMB, were predicted to have the best anti-PD1 and anti-CTLA4 response rate (40 %), which can be explained by their higher expression of PD1 and CTLA4. The three-year area under the curve (AUC) was 0.80 in the total sample. ConclusionsOur study highlights the potential of an integrated analysis of p53-associated genes and TIC in predicting prognosis and aiding clinical decision-making in MM patients. This finding underscores the significance of comprehending the intricate interplay between genetic abnormalities and immune dysfunction in MM. Further research into this area may lead to the development of more effective treatment strategies.

BCMA Re-Emergence: Can It Serve As a Prognostic Biomarker in Multiple Myeloma after CAR-T?

BCMA Re-Emergence: Can It Serve As a Prognostic Biomarker in Multiple Myeloma after CAR-T?

CRIP1 Upregulated Along with chr1q-Gain Indicates Immune Dysregulation and Portends Poor Outcomes in Multiple Myeloma

Background: The gain of chromosome 1q (chr1q-gain), one of the frequently occurring copy number aberrations in multiple myeloma (MM), is associated with a poor prognosis. However, the specific high-risk genes involved and the underlying molecular mechanisms remain elusive. Method: In this study, we gathered a comprehensive dataset comprising bulk transcriptome data from 1271 multiple myeloma (MM) patients, including 413 patients from the GSE4581 dataset and 858 patients from the MMRF dataset. Additionally, we acquired single-cell RNA sequencing data from various disease stages, which included 12 MM patients, 7 patients with monoclonal gammopathy of undetermined significance (MGUS), 4 patients with amyloidosis (AL), 6 patients with smoldering multiple myeloma (SMM), and 11 healthy control donors from GSE117156. Cox regression and Kaplan-Meier curves were employed to identify and validate significant candidates associated with adverse prognosis among the overexpressed genes in patients with chr1q-gain. Furthermore, the expression profiles of the candidates in malignant plasma cells from MM patients compared to plasma cells in healthy donors were evaluated at single cell resolution. Gene Set Enrichment Analysis (GSEA) was conducted to uncover the pathways enriched in high-CRIP1 groups. To better understand the immune infiltration in MM, we utilized CIBERSORTx to infer the immune cell composition. Results: A total of 541 genes were found to be upregulated in multiple myeloma (MM) patients with chr1q-gain in the GSE4581 dataset, with a false discovery rate (FDR) of less than 0.05 and a log fold change (LogFC) greater than 0.5.We identified five genes (CRIP1, ANP32E, CKS1B, RBFA, TOP2A) associated with poor prognosis through univariate Cox and multivariate Cox regression analyses and successfully validated in MMRF dataset(n=858). Upon characterizing the expression of these candidate genes in malignant plasma cells at a single-cell resolution, we made an interesting observation: CRIP1 was uniquely expressed in multiple myeloma (MM) patients when compared to healthy donors, individuals with MGUS, SMM and AL patients. Moreover, the GSEA results showed significant enrichment of the “Anti-viral Mechanism by IFN-stimulated Genes” (Normalized Enrichment Score, NES=1.98, False Discovery Rate, FDR=0.017) and “Interferon Signaling” (NES=2.11, FDR<0.001) in CRIP1-low MM patients. These findings suggest that CRIP1 may play a role in the development of multiple myeloma by influencing the tumor immune microenvironment through the regulation of these pathways. Analysis of immune cell infiltration in MM showed the expression level of CRIP1 is negatively correlated with CD4 naïve T cells ( R=-0.24, P<0.001) and positively correlated with Monocytes ( R=0.19, P<0.001). Tumors with high CRIP1 expression showed increased infiltration of CD8 T cells, CD4 memory T cells, activated NK cells, M0 macrophages, and Eosinophils. Conclusions: The study showed that CRIP1 upregulated along with chr1q-gain was highly expressed in MM patients compared to healthy individuals and associated with immune dysregulation. The patients with higher CRIP1 expression have poorer survival. CRIP1 could serve as a potential therapeutic target and prognostic biomarker in multiple myeloma.

Identification of mutation gene prognostic biomarker in multiple myeloma through gene panel exome sequencing and transcriptome analysis in Chinese population

BackgroundThe 5-year survival rate of multiple myeloma (MM) in China is less than 40%, with considerable individual heterogeneity. Gene mutations are important predictive biomarkers that influence MM treatment decision. The aim of our study was to uncover the clinical significance of mutated genes in MM in the Chinese population. MethodsTargeted exon panel sequencing was performed of 400 genes to detect the gene mutation status in plasma cells from 50 patients with MM. DAVID was used to explore the functions and pathways of mutated genes. Detection of mutant gene expression, prognosis and immune cell infiltration with GSE6477. GEO2R was utilized to identify differentially expressed genes (DEGs). Kaplan-Meier and CIBERSORT were applied to compare survival distributions and evaluate the gene expression associated with immune cell infiltration, respectively. ResultsMutations of 337 genes were identified in MM. The mutation types included SNP, INS, and DEL, but the dominant mutation type was SNP. Function and pathway analysis of mutant genes were performed to elucidate DNA modifications. We identified a total number of 660 downregulated and 587 upregulated genes from the GSE6477 dataset. Thirty-three common genes were present in both the mutant genes and DEGs. The functions and pathways of the mutated genes were enriched in myeloid cell differentiation, regulation of hemopoiesis, etc. Moreover, we found that the low expression of BCL6, BIRC3, HLA-DQA1, and VCAN was correlated with poor prognosis in MM. ConclusionsThe mutations and low expression of BCL6, BIRC3, HLA-DQA1, and VCAN were correlated with poor prognosis and immune cell infiltration in MM. This study is the first to reveal the spectrum of mutations in the Chinese population by the use of an NGS panel.

Targeting ABCB6 with nitidine chloride inhibits PI3K/AKT signaling pathway to promote ferroptosis in multiple myeloma.

Since multiple myeloma (MM) remains a cureless malignancy of plasma cells to date, it becomes imperative to develop novel drugs and therapeutic targets for MM. We screened a small molecule library comprising 3633 natural product drugs, which demonstrated that Nitidine Chloride (NC), an extract from traditional Chinese medicine Zanthoxylum nitidum. We used Surface Plasmon Resonance-High Performance Liquid Chromatography-Protein Mass Spectrometry (SPR-HPLC-MS), Cellular Thermal Shift Assay (CETSA), molecular docking, and SPR assay to identify the potential targets of NC, in which ABCB6 was the unique target of NC. The effects of ABCB6 on cellular proliferation and drug resistance were determined by CCK8, western blot, flow cytometry, site-mutation cells, transmission electron microscopy, immunohistochemistry staining and xenograft model in vitro and in vivo. NC induced MM cell death by promoting ferroptosis. ABCB6 is the direct target of NC. ABCB6 expression was increased in MM samples compared to normal controls, which was significantly associated with MM relapse and poor outcomes. VGSK was the inferred binding epitope of NC on the ABCB6 protein. In the ABCB6-mutated MM cells, NC did not display cancer resistance, implying the vital role of ABCB6 in NC's bioactivity. Moreover, the silencing of ABCB6 significantly inhibited MM cell growth. Mechanistically, the direct binding of NC to ABCB6 suppressed PI3K/AKT signaling pathway to promote ferroptosis. In conclusion, ABCB6 can be a potential therapeutic target and prognostic biomarker in MM, while NC can be considered a novel drug for MM treatment.

Peripheral blood monocyte count is a dynamic prognostic biomarker in multiple myeloma.

With the growing knowledge of multiple myeloma (MM) pathobiology and the introduction of novel therapies, risk stratification continues to evolve. Myeloid-derived suppressor cells and tumor-associated macrophages, derived from peripheral blood monocytes, support malignant plasma cell proliferation in the bone marrow. Because peripheral blood absolute monocyte count (AMC) is thought to reflect the bone marrow microenvironment, we sought to evaluate the prognostic significance of AMC in MM. We retrospectively analyzed 10 822 patients newly diagnosed with MM between 2000 and 2019 at Veteran's Administration hospitals. We obtained AMC closest to diagnosis and every 3 months thereafter up to 2.5 years. Patients were stratified into 4 groups: low, normal, elevated, and severely elevated AMC (<0.2, 0.2-<0.8, 0.8-<1.25, and ≥1.25 × 103/mm3, respectively). Abnormal AMC at diagnosis was observed in 25.3% of the patients and was associated with an inferior overall survival (OS). In patients with low, severely elevated, elevated, and normal AMC, respectively, median OS at diagnosis was 2.3, 2.7, 3.1, and 3.6 years (P< .001) and at 2.5 years was 2.0, 2.6, 3.4, and 3.9 years (P< .001). Patients with normal AMC at diagnosis who developed an abnormal AMC >1 year after diagnosis also had an inferior OS relative to patients who maintained a normal AMC. Abnormal AMC was also associated with inferior OS independent of validated prognostic markers, including the international staging system and lactate dehydrogenase. Our findings provide novel clues for future prospective studies on the functional role of monocytes in MM, which could be a readily available metric for risk stratification.

Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils Novel Prognostic Biomarkers in Multiple Myeloma.

Molecular heterogeneity has great significance in the disease biology of multiple myeloma (MM). Thus, the analysis combined single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data were performed to investigate the clonal evolution characteristics and to find novel prognostic targets in MM. The scRNA-seq data were analyzed by the Seurat pipeline and Monocle 2 to identify MM cell branches with different differentiation states. Marker genes in each branch were uploaded to the STRING database to construct the Protein-Protein Interaction (PPI) network, followed by the detection of hub genes by Cytoscape software. Using bulk RNA-seq data, Kaplan-Meier (K-M) survival analysis was then carried out to determine prognostic biomarkers in MM. A total of 342 marker genes in two branches with different differentiation states were identified, and the top 20 marker genes with the highest scores in the network calculated by the MCC algorithm were selected as hub genes in MM. Furthermore, K-M survival analysis revealed that higher NDUFB8, COX6C, NDUFA6, USMG5, and COX5B expression correlated closely with a worse prognosis in MM patients. Moreover, ssGSEA and Pearson analyses showed that their expression had a significant negative correlation with the proportion of Tcm (central memory cell) immune cells. Our findings identified NDUFB8, COX6C, NDUFA6, USMG5, and COX5B as novel prognostic biomarkers in MM, and also revealed the significance of genetic heterogeneity during cell differentiation in MM prognosis.

Increased Levels of Circulating Plasma Cells in Patients with Newly Diagnosed Multiple Myeloma Are Independently Associated with Poor Prognosis

The presence of circulating tumor cells (CTCs) has long been suggested as a valuable prognostic biomarker in Multiple Myeloma (MM). Recently, increased baseline CTC levels in patients with newly-diagnosed MM (NDMM) have been associated with adverse outcomes in the GEM2012MENOS65/GEM2014MAIN and FORTE trials. Since January 2017, we have been evaluating the presence of CTCs utilizing Next-generation Flow cytometry (NGF) with a median limit of detection (LOD) reaching 2x10-6. NGF assessment has been performed according to the EuroFlow guidelines for sample preparation, antibodies, cytometer settings and analysis of data. Currently, we have analyzed 525 matched BM and PB samples from NDMM patients and have found clonal plasma cells in 100% of BM and 89.1% (468/525) of PB samples respectively. Patients presented with ISS III/R-ISS III, high-risk cytogenetics, serum β2 microglobulin above median and hemoglobin levels ≤ 8.5 g/dL had increased CTC levels. Inversely, the absence of CTCs or their low prevalence (<10-5) was associated with an increased normal plasma cell compartment within the BM (R2=0.82, P < .0001). No association was detected between the CTC number and the therapeutic response to induction treatment in accordance with previous reports. Nevertheless, over a median follow-up monitoring of 42 months (range: 3-66 months), a running log-rank test with a step increase of 0.1% CTCs, highlighted an optimal cut-off point for PFS risk assessment at the level of 2x10-4. In the multivariable analysis, NDMM patients with CTCs above this cut-off showed a 2.2-fold higher risk of progression which was independent from ISS, induction scheme and baseline cytogenetics (HR: 2.2, 95% CI: 1.24 - 3.28, P< .001). Our large number of matched samples allowed for a phenotypic comparison between BM clonal cells and CTCs. The majority of patients with detectable CTCs (86%) showed a matched phenotypic profile of aberrant plasma cell in the two sites. However, 66 patients showed phenotypic discrepancies based on one of the following patterns: i) all phenotypic subsets were present in both BM and PB but with significantly altered ratios (≥20% of relative prevalence) for at least two concomitant subsets; ii) presence of ≥ 1 phenotypic subsets (with a minimum relative prevalence of 20% of all clonal cells) only in the BM; and iii) presence of ≥ 1 phenotypic subsets only in the PB. Remarkably, patients with phenotypic discrepancies had significantly higher CTC levels than those with a phenotypic agreement on the two sites (P < .001), together with signs of a more diffuse disease pattern, as evidenced by the imaging results. It is likely that these patients may share a patchy BM infiltration (and/or even extramedullary disease) and accumulate circulating clonal cells from various sites (thus leading to increased tumor burden) with a spatial clonal heterogeneity, which, as a total, may differ from a specific phenotype derived from a particular BM site. The biological differences among patients with differential baseline CTCs expand beyond the tumor cells. Performing a deep phenotypic approach for the identification of 32 distinct immune subsets, we analyzed the immune profile of both ΒΜ and PB in NDMM patients differing to their CTC levels by two log decimals. Patients with CTCs ≥ 5x10-3 had substantially increased levels of total T cells (especially CD8+), NK cells, tumor associated macrophages (TAMs) and an elevated ratio of memory to naïve B cells (P < .0001 for all subsets) in their BM microenvironment than those with less than 5x10-5 CTCs. The same differences, though with weaker statistical significance, applied also in PB, where, we could also identify a clear immune signature with characteristics of tumor suppression and T cell exhaustion for NDMM with the high CTC burden. Altogether, our results confirm the negative and independent prognostic impact of increased CTC levels in the NDMM and further imply its relevance in the real-world setting to establish improved risk-stratification models. Moreover, since the liquid biopsy is a better representative of the entire tumor load than a tissue biopsy sample, the analysis of CTCs may serve as the new hallmark for the real-time evaluation of a patient's disease and/or immune status.

P-098: Serological proteome analysis identifying autoantibodies against tumor-associated antigen ENO1 as a potential prognostic biomarker in multiple myeloma

P-098: Serological proteome analysis identifying autoantibodies against tumor-associated antigen ENO1 as a potential prognostic biomarker in multiple myeloma

A novel circRNA-miRNA-mRNA network revealed exosomal circ-ATP10A as a biomarker for multiple myeloma angiogenesis

ABSTRACT The importance of angiogenesis in multiple myeloma (MM) is unquestionable; however, to date, the success of antiangiogenic therapies has been fairly limited. Exosomal circular RNAs (circRNAs) have been proven to be pivotal players in angiogenesis in various cancers. Nevertheless, their role in MM remains unknown. Therefore, we aimed to identify differentially expressed circRNAs in peripheral blood exosomes from MM patients and explore their diagnostic and prognostic values. We screened 2,052 circRNAs with significant differential expression between MM patients and healthy controls via high-throughput sequencing. qRT-PCR confirmed that the expression of circ-ATP10A was significantly increased in MM patients. The bioinformatics analyses suggested that circ-ATP10A can act as a microRNA (miRNA) sponge and regulate the expression of downstream vascular endothelial growth factor-B (VEGFB), hypoxia-inducible factor-1alpha (HIF1A), platelet-derived growth factor subunit A (PDGFA), and fibroblast growth factor (FGF). The immunohistochemical results indicated that the circ-ATP10A level was positively correlated with the protein levels of VEGFB and marrow microvessel density (MVD) in MM patients, and the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC) and Kaplan-Meier survival curve analyses confirmed it as a prognostic biomarker. Collectively, our study indicates that exosomal circ-ATP10A is a valuable prognostic biomarker in MM and may promote MM angiogenesis by targeting hsa-miR-6758-3p/hsa-miR-3977/hsa-miR-6804-3p/hsa-miR-1266-3p/hsa-miR-3620-3p and modulating their downstream mRNAs, such as VEGFB, HIF1A, PDGF, and FGF.

A Molecular Signature of Circulating MicroRNA Can Predict Osteolytic Bone Disease in Multiple Myeloma.

Simple SummaryMultiple myeloma bone disease (MMBD) is one of the most important complications of multiple myeloma with a great impact on quality of life. Recent advances in the field of imaging techniques provided clinicians with a variety of imaging modalities with high sensitivity for the diagnosis of MMBD. However, no circulating biomarkers are available to support the diagnosis of MMBD in cases where the results are inconclusive. The aim of our study was to investigate the clinical utility of 19 miRNAs implicated in osteoporosis in MMBD. Our results suggest that the levels of circulating let-7b-5p, miR-143-3p, miR-17-5p, miR-335-5p, and miR-214-3p (standalone or combined in multi-miRNA models) can effectively predict the presence of MMBD in newly diagnosed MM patients.Background: Multiple myeloma bone disease (MMBD) constitutes a common and severe complication of multiple myeloma (MM), impacting the quality of life and survival. We evaluated the clinical value of a panel of 19 miRNAs associated with osteoporosis in MMBD. Methods: miRNAs were isolated from the plasma of 62 newly diagnosed MM patients with or without MMBD. First-strand cDNA was synthesized, and relative quantification was performed using qPCR. Lastly, we carried out extensive biostatistical analysis. Results: Circulating levels of let-7b-5p, miR-143-3p, miR-17-5p, miR-214-3p, and miR-335-5p were significantly higher in the blood plasma of MM patients with MMBD compared to those without. Receiver operating characteristic curve and logistic regression analyses showed that these miRNAs could accurately predict MMBD. Furthermore, a standalone multi-miRNA–based logistic regression model exhibited the best predictive potential regarding MMBD. Two of those miRNAs also have a prognostic role in MM since survival analysis indicated that lower circulating levels of both let-7b-5p and miR-335-5p were associated with significantly worse progression-free survival, independently of the established prognostic factors. Conclusions: Our study proposes a miRNA signature to facilitate MMBD diagnosis, especially in ambiguous cases. Moreover, we provide evidence of the prognostic role of let-7b-5p and miR-335-5p as non-invasive prognostic biomarkers in MM.

Increased expression of IFI16 predicts adverse prognosis in multiple myeloma.

Multiple myeloma (MM) is a malignancy of terminally differentiated plasma cells and does not have sufficient prognostic indicators. Interferon gamma inducible protein 16 (IFI16) plays a crucial role in B-cell differentiation. Several studies have shown that IFI16 predicted prognosis in many cancers. However, the relationship between MM prognosis and IFI16 expression has not been studied. In our study, we analyzed the prognostic role of IFI16 expression and explored the possible mechanism in MM progression by using 4498 myeloma patients and 52 healthy donors from 13 independent gene expression omnibus (GEO) datasets. The IFI16 expression increased with myeloma progression, ISS stage, 1q21 amplification, and relapse (all P < 0.01). MM patients with higher IFI16 expression had shorter survival in six datasets (all P < 0.05). Furthermore, multivariate analysis indicated that enhanced IFI16 expression was an independent poor prognostic factor for EFS and OS (P = 0.007, 0.009, respectively). And PPI, GO, KEGG, and GSEA also confirmed that IFI16 promoted MM progression by participating in tumor-related pathways. In conclusion, our study confirmed that IFI16 was a poor prognostic biomarker in MM.

Proteomic Characterization of Ubiquitin Receptor ADRM1/Rpn13

Background and Rationale 20S proteasome-based therapies are the mainstay of treatment of patients with multiple myeloma (MM); however, resistance to proteasome inhibitor (PI) therapies commonly develops underlying relapse of disease. We showed that inhibition of 19S-associated ubiquitin receptor (UbR) ADRM1/Rpn13, upstream of 20S proteasome, inhibits MM cell growth and overcomes PI-resistance in MM. hRpn13 recognizes polyubiquitinated proteins and facilitates their disassembly via 19S-associated deubiquitinating enzyme UCHL5, allowing for protein degradation via 20S proteasomal catalytic activities. To date, however, hRpn13-modulated protein substrates and downstream signaling remains unclear. Here, we utilized multiplexed proteomics with tandem mass spectrometry; GeneOntology (GO) enrichment; as well as pathway database KEGG and Reactome to identify hRpn13-associated signaling molecules and delineate functionally significant biological pathways. Materials and Methods CRISPR-Cas9 genome editing was performed to generate hRpn13-knockout (hRpn13-KO) HCT116 cells which were subjected to multiplexed proteomics. Functionally relevant proteins were categorized using GO, as well as KEGG- and Reactome-pathway analysis. The prognostic relevance of identified proteins was derived using Gene Expression Profiling (GEP) databases on uniformly treated MM patients. Protein expression level was determined by western blotting. CRISPR-Cas9-mediated hRpn13 deletion was confirmed using PCR and sequencing, as well as immunoblot analysis. Statistical significance was assessed with Student's t test Results Among 8766 proteins analyzed, 206 proteins were down-regulated, whereas 65 proteins were significantly up-regulated in hRpn13-KO cells compared to hRpn13-WT cells. Targeted hRpn13-deletion upregulated physiological pathways related to amino acid biosynthesis and transport, metabolism, proliferation, and apoptosis. We validated 5 such upregulated proteins (SLC1A3, THBS1, GLYR1, GCLM, and TIMM8A) using immunoblotting. As for hRpn13 deletion, treatment of MM.1S cells with Rpn13 inhibitor RA190 triggered a similar increase in SLC1A3, THBS1, GLYR1, GCLM, and TIMM8A levels. These data indicate that SLC1A3, THBS1, GLYR1, GCLM, and TIMM8A proteins are direct substrates of UbR hRpn13. On the other hand, hRpn13-deletion decreased levels of proteins involved in cell adhesion, biological regulation, antigen recognition, and extracellular matrix interactions. Clinical relevance in MM: We next screened 271 proteins against GEP datasets on MM patients (GSE6477; GSE13591; GSE6691). Among the 65 molecules upregulated in hRpn13-KO cells, 18 were expressed at significantly lower levels in MM patients vs normal plasma cells; and importantly, 2 (SLC1A3, THBS1) of these 18 proteins correlated with poor survival. In a functional validation study, blockade of hRpn13 with RA190 induced increased SLC1A3 and THBS1 levels, suggesting that targeting SLC1A3/THBS1 may restore abnormal amino acid metabolism in MM. We next screened 206 of 271 proteins that were downregulated in Rpn13-KO cells in GEP database of MM patients. Results show that 32 of these 206 molecules were highly expressed in MM patient samples vsnormal plasma cells, and that 2 (SLC16A7 and DBF4) of 32 correlated with poor survival. SLC16A7 encodes for monocarboxylate transporter 2 (MCT2), a key component of glycolysis, and DBF4 regulates DNA replication/cell proliferation. Importantly, RA190 decreased SLC16A and DB4 levels. Together, these data suggest that: 1) SLC16A, DBF4, SLC1A3, and THBS1 are downstream signaling targets of hRpn13; and 2) hRpn13-inhibition triggered MM cell death involves blockade of elevated glycolysis and DNA replication/cell growth via SLC16A and DBF4, respectively, as well as restoration of normal amino acid synthesis via SLC1A3. Conclusion Collectively, our study utilized CRISPR gene-editing, biochemical, and molecular strategies to identify UbR hRpn13-mediated proteomic alterations. We identified novel targets including SLC16A7, DBF4, SLC1A3, and Thrombospondin-1 which may serve as prognostic biomarkers in MM. Importantly, our findings further support hRpn13-directed therapeutics, as well as preclinical evaluation of novel strategies targeting SLC16A, DBF4, SLC1A3, and Thrombospondin-1, to enhance cytotoxicity and improve patient outcome in MM. Disclosures Chauhan: Oncopeptide AB: Consultancy; consultant to Stemline Therapeutics, Inc., and Equity owner in C4 Therapeutics.: Consultancy, Other: Equity owner in C4 Therapeutics.. Anderson:Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.; Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees.

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.

Comprehensive profiling of circular RNA expressions reveals potential diagnostic and prognostic biomarkers in multiple myeloma

BackgroundThis study aimed to explore the heterogeneity of circRNA expression pattern via microarray, and further evaluate the potential of 10 specific circRNAs as diagnostic and prognostic biomarkers in multiple myeloma (MM).MethodsIn exploration stage (stage I), circRNA expression profiles were detected by the microarray in bone marrow plasma cells from 4 MM patients and 4 healthy controls (HCs), and bioinformatic analyses were performed. In validation stage (stage II), top 10 upregulated and top 10 downregulated circRNAs identified in stage I were detected in 60 MM patients and 30 HCs for further validation; the diagnostic and prognostic values of these circRNAs in MM patients were analyzed.ResultsIn stage I, 122 upregulated and 260 downregulated circRNAs were identified in MM patients compared with HCs. GO, KEGG and pathway enrichment analyses revealed that these circRNAs were implicated in neoplastic pathways such as MAPK and VEGF signaling pathways. In stage II, circ-PTK2, circ-RNF217, circ-RERE, circ-NAGPA and circ-KCNQ5 were validated to be upregulated and circ-AFF2, circ-WWC3, circ-DNAJC5, circ-KLHL2, circ-IQGAP1 and circ-AL137655 were validated to be downregulated in MM compared with controls. Circ-PTK2 and circ-RNF217 were correlated with poor treatment response and survival, while circ-AFF2 predicted good treatment response and survival in MM patients.ConclusionsThis study provides valuable reference for profound understanding about circRNA expression patterns in MM, and validates that circ-PTK2, circ-RNF217 and circ-AFF2 might serve as potential prognostic biomarkers in MM.

Comprehensive profiling of circular RNA expressions reveals potential diagnostic and prognostic biomarkers in multiple myeloma

Comprehensive profiling of circular RNA expressions reveals potential diagnostic and prognostic biomarkers in multiple myeloma

MiRNAs with prognostic significance in multiple myeloma

Background:Multiple myeloma (MM) is a clonal plasma cell malignancy associated with hypercalcemia, bone lesions, and renal failure. The prognostic significance of the mutation of miRNAs, one kind of small noncoding RNA molecules that can modulate gene expression, should be confirmed in non-Hodgkin lymphomas (NHL). This study aimed to identify the prognostic value of miRNAs in patients with MM.Methods:A meta-analysis was performed to estimate the pooled hazard ratios and their corresponding 95% confidence intervals for the associations between levels of miRNA expression (predictive factors) and outcomes in patients with MM. We systematically searched the PubMed, Web of Science, and China National Knowledge Infrastructure databases (final search conducted January 1, 2018) to identify eligible studies. Eligible studies were included by certain inclusion and exclusion criteria, whose quality was assessed by Newcastle-Ottawa Scale.Results:After performing the literature search and review, 10 relevant studies, including 1214 cases, were identified. The results of our meta-analysis revealed that upregulated miR-92a level and downregulated miR-16, miR-25, miR-744, miR-15a, let-7e, and miR-19b expression were associated with poor prognosis in MM.Conclusions:This study identified miRNAs could serve as potential prognostic biomarkers in MM. Given the limited research available, the clinical application of these findings has yet to be verified.

Minimal residual disease negativity using deep sequencing is a major prognostic factor in multiple myeloma

AbstractThe introduction of novel agents has led to major improvements in clinical outcomes for patients with multiple myeloma. To shorten evaluation times for new treatments, health agencies are currently examining minimal residual disease (MRD) as a surrogate end point in clinical trials. We assessed the prognostic value of MRD, measured during maintenance therapy by next-generation sequencing (NGS). MRD negativity was defined as the absence of tumor plasma cell within 1 000 000 bone marrow cells (<10−6). Data were analyzed from a recent clinical trial that evaluated the role of transplantation in newly diagnosed myeloma patients treated with lenalidomide, bortezomib, and dexamethasone (RVD). MRD negativity was achieved at least once during maintenance in 127 patients (25%). At the start of maintenance therapy, MRD was a strong prognostic factor for both progression-free survival (adjusted hazard ratio, 0.22; 95% confidence interval, 0.15-0.34; P < .001) and overall survival (adjusted hazard ratio, 0.24; 95% confidence interval, 0.11-0.54; P = .001). Patients who were MRD negative had a higher probability of prolonged progression-free survival than patients with detectable residual disease, regardless of treatment group (RVD vs transplant), cytogenetic risk profile, or International Staging System disease stage at diagnosis. These results were similar after completion of maintenance therapy. Our findings confirm the value of MRD status, as determined by NGS, as a prognostic biomarker in multiple myeloma, and suggest that this approach could be used to adapt treatment strategies in future clinical trials.

Established and Novel Prognostic Biomarkers in Multiple Myeloma.

Multiple myeloma (MM) is an incurable plasma cell malignancy characterized by notable interpatient heterogeneity. There have been important advances in therapy and overall survival, but some patients with high-risk features still have poor survival rates. Therefore, accurate identification of this subset of patients has been integral to improvement of patient outcome. During the last few years, cytogenetics, gene expression profiling, MRI and PET/CT, as well as serum free light chain assays have been used as accurate biomarkers to better characterize the diverse course and outcome of the disease. With the recent advances of massive parallel sequencing techniques, the development of new models that better stratify high-risk groups are beginning to be developed. The use of multiparameter flow cytometry and next-generation sequencing have paved the way for assessment of minimal residual disease and better prognostication of post-therapeutic outcomes. Circulating tumor cells and circulating tumor DNA are promising potential biomarkers that demonstrate the spatial and temporal heterogeneity of MM. Finally, more prognostic markers are being developed that are specific to immunotherapeutic agents. In this review, we discuss these traditional and novel biomarkers that have been developed for MM and also those that can predict disease progression from precursor stages. Together, these biomarkers will help improve our understanding of the intrapatient and interpatient variabilities and help develop precision medicine for patients with high-risk MM.