Biomarker For Multiple Myeloma Research Articles

Elevated serum levels of soluble B-cell maturation antigen as a prognostic biomarker for multiple myeloma.

Serum B-cell maturation antigen (sBCMA) levels can serve as a sensitive biomarker in multiple myeloma (MM). In the research setting, sBCMA levels can be accurately detected by enzyme-linked immunosorbent assay (ELISA), but the approach has not been approved for clinical use. Here, we used a novel chemiluminescence method to assess sBCMA levels in 759 serum samples from 17 healthy donors and 443 patients with plasma cell (PC) diseases including AL amyloidosis, POEMS syndrome and MM. Serum BCMA levels were elevated 16.1-fold in patients with newly diagnosed MM compared to healthy donors and rare PC diseases patients. Specifically, the sBCMA levels in patients with progressive disease were 64.6-fold higher than those who showed partial response or above to treatment. The sBCMA level also correlated negatively with the response depth of MM patients. In newly diagnosed and relapsed MM patients, survival was significantly longer among those subjects whose sBCMA levels are below the median levels compared with those above the median value. We optimized the accuracy of the survival prediction further by integrating sBCMA level into the Second Revised International Staging System (R2-ISS). Our findings provide evidence that the novel chemiluminescence method is sensitive and practical for measuring sBCMA levels in clinical samples and confirm that sBCMA might serve as an independent prognostic biomarker for MM.

Exploring natural killer cell-related biomarkers in multiple myeloma: a novel nature killer cell-related model predicting prognosis and immunotherapy response using single-cell study

BackgroundNatural killer cells (NKs) may be involved in multiple myeloma (MM) progression. The present study elucidated the correlation between NKs and the progression of MM using single-cell binding transcriptome probes to identify NK cell-related biomarkers.MethodsSingle-cell analysis was performed including cell and subtype annotation, cell communication, and pseudotime analysis. Hallmark pathway enrichment analysis of NKs and NKs-related differentially expressed genes (DEGs) were conducted using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein–protein interaction (PPI) networks. Then, a risk model was structured based on biomarkers identified through univariate Cox regression analysis and least absolute shrinkage and selection operator regression analysis and subsequently validated. Additionally, correlation of clinical characteristics, gene set enrichment analysis, immune analysis, regulatory network, and drug forecasting were explored.ResultsA total of 13 cell clusters were obtained and annotated, including 8 cell populations that consisted of NKs. Utilizing 123 PPI network node genes, 8 NK-related DEGs were selected to construct a prognostic model. Immune cell infiltration results suggested that 11 immune cells exhibited marked differences in the high and low-risk groups. Finally, the model was used to screen potential drug targets to enhance immunotherapy efficacy.ConclusionA new prognostic model for MM associated with NKs was constructed and validated. This model provides a fresh perspective for predicting patient outcomes, immunotherapeutic response, and candidate drugs.

Circulating plasma cells as a predictive biomarker in Multiple myeloma: an updated systematic review and meta-analysis

Background Circulating plasma cells (CPCs) are defined by the presence of peripheral blood clonal plasma cells, which would contribute to the progression and dissemination of multiple myeloma (MM). An increasing number of studies have demonstrated the predictive potential of CPCs in the past few years. Therefore, there is a growing need for an updated meta-analysis to identify the specific relationship between CPCs and the prognosis of MM based on the current research status. Methods The PubMed, Embase, and Cochrane Library databases were screened to determine eligible studies from inception to November 5, 2023. Publications that reported the prognostic value of CPCs in MM patients were included. Hazard ratios (HRs) with 95% confidence intervals (CIs) of overall survival (OS) and progression-free survival (PFS) were extracted to pool the results. Subgroup analyses were performed based on region, sample size, cut-off value, detection time, initial treatment, and data type. The association between CPCs level and clinicopathological characteristics, including the International Staging System (ISS), Revised-ISS (R-ISS), and cytogenetic abnormalities were also evaluated. Statistical analyses were conducted using STATA 17.0 software. Results Twenty-two studies with a total of 5637 myeloma patients were enrolled in the current meta-analysis. The results indicated that myeloma patients with elevated CPCs were expected to have a poor OS (HR = 2.19, 95% CI: 1.81–2.66, p < 0.001) and PFS (HR = 2.45, 95% CI: 1.93–3.12, p < 0.001). Subgroup analyses did not alter the prognostic role of CPCs, regardless of region, sample size, cut-off value, detection time, initial treatment, or data type. Moreover, the increased CPCs were significantly related to advanced tumour stage (ISS III vs. ISS I–II: pooled OR = 2.89, 95% CI: 2.41–3.46, p < 0.001; R-ISS III vs. R-ISS I–II: pooled OR = 3.65, 95% CI: 2.43–5.50, p < 0.001) and high-risk cytogenetics (high-risk vs. standard-risk: OR = 2.22, 95% CI: 1.60–3.08, p < 0.001). Conclusion Our meta-analysis confirmed that the increased number of CPCs had a negative impact on the PFS and OS of MM patients. Therefore, CPCs could be a promising prognostic biomarker that helps with risk stratification and disease monitoring.

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&amp;lt;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&amp;lt;0.001) and positively correlated with Monocytes ( R=0.19, P&amp;lt;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.

Soluble CD163; A Possible New Biomarker in Multiple Myeloma

INTRODUCTION Tumor associated macrophages (TAM) constitute a major part of the bone marrow microenvironment and play a pivotal role in growth of various hematologic malignancies, such as Multiple Myeloma (MM). Cytokines secreted by TAM, such as hemoglobin scavenger receptor CD163, can be detected in their soluble form (sCD163) and reflect the TAM burden. It was recently published that bone marrow TAMs protect neoplastic plasmacytes from chemotherapy-based apoptosis. In our study, we aimed to investigate the clinical utility of sCD163 in patients with Multiple Myeloma. PATIENTS AND METHODS One hundred and nineteen patients were included in the study of whom 80 had symptomatic MM, 30 appeared to have SMM and 8 had MGUS. Clinical and laboratory characteristics were reviewed, after patients' informed consent form. Their median age was 68 yrs (range, 30-89), 53% were men and 47%women; 39%, 27%, and 35% of MM patients were staged ISS1, ISS2 and ISS3 respectively. Serum sCD163 was tested in frozen sera collected at patients' diagnosis and in 30 healthy individuals (HI) . Measurements were performed by ELISA (Duo-Set R&amp;D Quantiquine) according to the manufacturer's instructions. Median value of variables was used as the cut off point. Median time to treatment (TTT) was 0 months (range,0-248) in MM patients and median overall survival (OS) was 67 months (range, 0-248). Statistical analysis was performed with the SPSS v.26 software. RESULTS Median sCD163 was 26618 pg/ml (11831- 35548) in HI, 24366 pg/ml (13166 - 27429) in MGUS, 27665 (18266-39088) pg/ml in SMM, and 27870 (20720-37478) pg/ml in MM patients.Significantly lower levels of CD163 were observed between MGUS and HI (p=0.001) and HI and MM patients (p=0.015). Shorter time to treatment was observed in all MM patients including SMM with sCD163 levels above median (p = 0.034). Patients who became symptomatic after 6 months of diagnosis were studied separately, with levels above the median indicating a shorter time to therapy (p=0.003). Also, a trend of shorter overall survival was observed in all patients (MM, SMM, MGUS) with levels of CD163 above median (p=0.07). CONCLUSION Our findings reveal that serum sCD163 levels differed in patients with MGUS, SMM, MM, and HI, and could predict TTT in MM, indicating that cells of the monocyte-macrophage lineage may play a role in disease pathophysiology and progression. sCD163 could eventually prove to be a significant prognostic factor in MM.

A Prognostic Model Integrating Circulating Clonal Plasma Cells into R-ISS and PET-CT Based Tumor Burden in Transplant-Ineligible Multiple Myeloma

Introduction: Circulating clonal plasma cell (cCPC) is an easily obtained and non-invasive biomarker in multiple myeloma (MM), providing distinct prognostic information from the revised-international staging system (R-ISS). However, its prognostic relevance has been investigated primarily in transplant-eligible and clinical trial settings. Consequently, there is limited data on the impact of cCPC on outcomes and optimal cut-off values in transplant-ineligible (TIE) MM patients. Moreover, appropriate combinations to refine risk stratification, such as tumor burden measured by positron emission tomography-computed tomography (PET-CT), have yet to be fully explored. Methods: We performed a retrospective analysis on newly diagnosed TIE-MM patients with available peripheral blood (PB) flow cytometry (FCM) and PET-CT data from 2011 to 2021. Patients with primary plasma cell leukemia (n=8), defined as &amp;gt;5% monoclonal plasma cells in PB, were excluded from the study. Quantification of cCPC was performed using 6-color (2011-2016) or 8-color (2017-2021) FCM staining for CD19, CD56, CD38, CD138, cytoplasmic κ, and cytoplasmic λ to confirm monoclonality (Beckman Coulter, USA), which required at least 150000 mononuclear cell counts with the detectable limit at 0.01% (10 -4) based on previous reports (Gonsalves et al). Tumor burden was assessed by calculating total lesion glycolysis (TLG) using the following formula: the mean standardized uptake value (SUV) multiplied by the total tumor volume with an absolute SUV &amp;gt;2.5, using Metavol Software (Hokkaido University, Japan). Receiver operating curve analysis with the Youden index was employed to determine the optimal cutoff for predicting 2-year progression-free survival (PFS) and 5-year overall survival (OS). The predictive performance of R-ISS, cCPC, and TLG alone, along with their combinations, was compared using Harrell's concordance index (c-index). Results: 114 patients with TIE-MM were analyzed. The median age was 78 years (interquartile range [IQR] 73-83). The number of patients classified as R-ISS Ⅰ, Ⅱ, and Ⅲ was 12 (10.5%), 82 (71.9%), and 20 (17.5%), respectively. Most patients (85.1%) received proteasome inhibitor-based induction remission therapy. cCPCs were detectable in 90 patients (80.7%), with a median level of 6 ×10 -4 (IQR 1-22). Regarding tumor burden, 73 patients (64%) had at least one fluorodeoxyglucose avid lesion with a median TLG of 34.7 (IQR 0-268). cCPC levels were significantly correlated with CPC in bone marrow (R =0.24, P =0.01) but not with TLG (R =-0.01, P =0.88) and involved free light chain levels (R =0.07, P =0.41). The optimal cut-off values in predicting 2-year PFS and 5-year OS were 9 and 10 ×10 -4 for cCPC, and 325 and 343 for TLG, respectively. For simplicity, we classified &amp;gt;10 ×10 -4 for cCPC and &amp;gt;300 for TLG as high-risks. Notably, approximately two-thirds of the patients (62.3%) had at least one high-risk feature (Figure 1). Both high cCPC and TLG showed significant associations with worse OS and PFS (5-year OS rate: cCPC high vs. low, 40.2% vs. 69.3%; TLG high vs. low, 38% vs. 64.5%; 2-year PFS rate: cCPC high vs. low, 45.7% vs. 69.1%; TLG high vs. low, 46.4% vs. 64% all P &amp;lt; 0.05). These factors retained prognostic significance after adjustment for R-ISS on multivariate analysis. Finally, we constructed a novel predictive model integrating RISS, cCPC, and TLG. This model discriminated OS among patients with 0 (5-year OS rate, 80% [95% confidence interval 68.4%-93.6%]), 1 (50.5% [37.7%-67.7%]), and ≧2 factors (29% [13.3%-63.5%], P &amp;lt;0.001, Figure 2). The c-index was the highest (0.651) in this combined model compared to the single use of these risk factors (0.585, 0.594, and 0.569). Conclusions: We demonstrated the prognostic impact of cCPC, which is independently associated with R-ISS and TLG, on real-world TIE-MM patients. The new prediction model, integrated with these different clinical and biological features, may provide robust outcome discrimination.

The Potential of JAG Ligands as Therapeutic Targets and Predictive Biomarkers in Multiple Myeloma.

The NOTCH ligands JAG1 and JAG2 have been correlated in vitro with multiple myeloma (MM) cell proliferation, drug resistance, self-renewal and a pathological crosstalk with the tumor microenvironment resulting in angiogenesis and osteoclastogenesis. These findings suggest that a therapeutic approach targeting JAG ligands might be helpful for the care of MM patients and lead us to explore the role of JAG1 and JAG2 in a MM in vivo model and primary patient samples. JAG1 and JAG2 protein expression represents a common feature in MM cell lines; therefore, we assessed their function through JAG1/2 conditional silencing in a MM xenograft model. We observed that JAG1 and JAG2 showed potential as therapeutic targets in MM, as their silencing resulted in a reduction in the tumor burden. Moreover, JAG1 and JAG2 protein expression in MM patients was positively correlated with the presence of MM cells in patients' bone marrow biopsies. Finally, taking advantage of the Multiple Myeloma Research Foundation (MMRF) CoMMpass global dataset, we showed that JAG2 gene expression level was a predictive biomarker associated with patients' overall survival and progression-free survival, independently from other main molecular or clinical features. Overall, these results strengthened the rationale for the development of a JAG1/2-tailored approach and the use of JAG2 as a predictive biomarker in MM.

LncRNA MALAT1, MEG3, and PANDAR Levels may be Potential Diagnostic Biomarkers in Multiple Myeloma

Aim: Long non-coding RNAs (lncRNAs) play a significant role in the development of various diseases, including cancer, and have been investigated as potential diagnostic and prognostic markers. The specific mechanisms underlying their involvement in the progression and development of multiple myeloma (MM), as well as their potential as diagnostic markers, remain to be fully elucidated. This study aimed to elucidate the involvement of lncRNAs in the pathogenesis of MM, explore their relationship with clinical parameters, and assess their potential as biomarkers for MM diagnosis.&#x0D; Material and Methods: Patients above 18 years of age, diagnosed with MM and not yet receiving treatment, were included in the study. The expression levels of three lncRNAs (MALAT1, PANDAR, MEG3) regulated by the p53 gene were determined in a study involving 19 patients diagnosed with MM and 20 healthy volunteers. The expression levels were determined using RT-PCR.&#x0D; Results: The levels of plasma lncRNAs were observed to be significantly down-regulated (p

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.

Identification of Immunoglobulin Gene Rearrangement Biomarkers in Multiple Myeloma through cfDNA-Based Liquid Biopsy Using tchDNA-Seq.

Multiple myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of pathogenic CD138+ plasma cells (PPCs) in bone marrow (BM). Recent years have seen a significant increase in the treatment options for MM; however, most patients who achieve complete the response ultimately relapse. The earlier detection of tumor-related clonal DNA would thus be very beneficial for patients with MM and would enable timely therapeutic interventions to improve outcomes. Liquid biopsy of "cell-free DNA" (cfDNA) as a minimally invasive approach might be more effective than BM aspiration not only for the diagnosis but also for the detection of early recurrence. Most studies thus far have addressed the comparative quantification of patient-specific biomarkers in cfDNA with PPCs and BM samples, which have shown good correlations. However, there are limitations to this approach, such as the difficulty in obtaining enough circulating free tumor DNA to achieve sufficient sensitivity for the assessment of minimal residual disease. Herein, we summarize current data on methodologies to characterize MM, and we present evidence that targeted capture hybridization DNA sequencing (tchDNA-Seq) can provide robust biomarkers in cfDNA, including immunoglobulin (IG) rearrangements. We also show that detection can be improved by prior purification of the cfDNA. Overall, liquid biopsies of cfDNA to monitor IG rearrangements have the potential to provide important diagnostic, prognostic, and predictive information in patients with MM.

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.

Advances in Biomarkers for Multiple Myeloma

Multiple myeloma (MM) is the second most common malignancy in hematology. MM is characterized by the malignant proliferation of plasma cells in the bone marrow, accompanied by the secretion of monoclonal immunoglobulin, mainly occurring in the elderly. The clinical manifestations of MM include renal dysfunction, bone destruction, infection, anemia, hemorrhage, hypercalcemia, and hyperviscosity syndrome. The recent discovery of biomarkers related to the diagnosis or prognosis of MM provides an important basis for the diagnosis and treatment of MM. This paper reviews the research progress of biomarkers expressed in tissues and peripheral blood at home and abroad.

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.

MM-468 Longitudinal Assessment of Minimal Residual Disease Dynamics in Patients With Multiple Myeloma who Achieve Complete Response after First Line Therapy

Minimal residual disease negativity is the most reliable biomarker in Multiple Myeloma (MM) associated with prolonged PFS and OS. However, MRD negativity at a single timepoint cannot guarantee for its sustainability overtime, hence relapses are also observed in MRDneg patients. To evaluate the prognostic value of MRD at distinct timepoints, assess the frequency and prognostication of MRD dynamics overtime, and highlight possible associating alterations in the bone marrow (BM) microenvironment. MRD and BM profiling were evaluated with Next-Generation Flow (NGF) in 313 MM patients achieving complete remission (CR), divided in two groups based on the timing of their first MRD evaluation: Group A:240 patients examined for MRD at their first evidence of CR; Group B:73 patients having a minimum of 24-month CR period when first tested for MRD. The median follow-up monitoring was 35 months. A second, third and fourth consecutive MRD assessment was performed for 52%, 34% and 18% patients respectively (median time interval:6 months). 106/313 (33.9%) patients were MRDpos in their first examination (same frequency in both groups) having a shorter PFS than MRDneg patients (HR:0.36, 95% CI:0.22-0.61, p<0.0001). MRDpos patients in Group B had a 2-fold higher risk of subsequent progression than those of Group A (HR:0.51, 95% CI: 0.24-1.05, p=0.03), probably due to their higher tumor burden (median: 3×10-4 vs. 3×10-5, p<0.001). 34% of patients changed their MRD status overtime with those changing from MRDneg to MRDpos showing a 2.2-fold higher risk for relapse than those with persistent MRD. Surprisingly, patients changing from MRDpos to MRDneg had a more favorable prognosis when compared to continuously MRDneg patients. Changes in the MRD status were accompanied by alterations in the BM composition and particularly in differential prevalence of NK cells and B cell subsets. MRD prognostication stands irrespective of CR durability, while tumor burden can further stratify MRDpos patients with different risk of progression. MRD should be periodically re-evaluated, since MRD dynamics may confer a distinct prognostication than a persisting MRD status. MRD dynamics are accompanied by alterations in BM immune profiling, which may shed light in the underlying biology of MRD.

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

P-170: Evaluating serum free light chain ratio as a biomarker for multiple myeloma

P-170: Evaluating serum free light chain ratio as a biomarker for multiple myeloma

Repeatability and test-retest reproducibility of mean apparent diffusion coefficient measurements of focal and diffuse disease in relapsed multiple myeloma at 3T whole body diffusion-weighted MRI (WB-DW-MRI).

To assess the test-retest reproducibility and intra/interobserver agreement of apparent diffusion coefficient (ADC) measurements of myeloma lesions using whole body diffusion-weighted MRI (WB-DW-MRI) at 3T MRI. Following ethical approval, 11 consenting patients with relapsed multiple myeloma were prospectively recruited and underwent baseline WB-DW-MRI. For a single bed position, axial DWI was repeated after a short interval to permit test-retest measurements.Mean ADC measurement was performed by two experienced observers. Intra- and interobserver agreement and test-retest reproducibility were assessed, using coefficient of variation (CV) and interclass correlation coefficient (ICC) measures, for diffuse and focal lesions (small ≤10 mm and large >10 mm). 47 sites of disease were outlined (23 focal, 24 diffuse) in different bed positions (pelvis = 22, thorax = 20, head and neck = 5). For all lesions, there was excellent intraobserver agreement with ICC of 0.99 (0.98-0.99) and COV of 5%. For interobserver agreement, ICC was 0.89 (0.8-0.934) and COV was 17%. There was poor interobserver agreement for diffuse disease (ICC = 0.46) and small lesions (ICC = 0.54).For test-retest reproducibility, excellent ICC (0.916) and COV (14.5%) values for mean ADC measurements were observed. ICCs of test-retest were similar between focal lesions (0.83) and diffuse infiltration (0.80), while ICCs were higher in pelvic (0.95) compared to thoracic (0.81) region and in small (0.96) compared to large (0.8) lesions. ADC measurements of focal lesions in multiple myeloma are repeatable and reproducible, while there is more variation in ADC measurements of diffuse disease in patients with multiple myeloma. Mean ADC measurements are repeatable and reproducible in focal lesions in multiple myeloma, while the ADC measurements of diffuse disease in multiple myeloma are more subject to variation. The evidence supports the future potential role of ADC measurements as predictive quantitative biomarker in multiple myeloma.