Recent advances in understanding multiple myeloma

Using Proteomics Data to Identify Personalized Treatments in Multiple Myeloma: A Machine Learning Approach

This paper describes a machine learning (ML) decision support system to provide a list of chemotherapeutics that individual multiple myeloma (MM) patients are sensitive/resistant to, based on their proteomic profile. The methodology used in this study involved understanding the parameter space and selecting the dominant features (proteomics data), identifying patterns of proteomic profiles and their association to the recommended treatments, and defining the decision support system of personalized treatment as a classification problem. During the data analysis, we compared several ML algorithms, such as linear regression, Random Forest, and support vector machines, to classify patients as sensitive/resistant to therapeutics. A further analysis examined data-balancing techniques that emerged due to the small cohort size. The results suggest that utilizing proteomics data is a promising approach for identifying effective treatment options for patients with MM (reaching on average an accuracy of 81%). Although this pilot study was limited by the small patient cohort (39 patients), which restricted the training and validation of the explored ML solutions to identify complex associations between proteins, it holds great promise for developing personalized anti-MM treatments using ML approaches.

Current status of drug development for patients with multiple myeloma: a review of comparison in China and the rest of world

Multiple myeloma (MM) is a highly heterogeneous malignancy. The treatment of MM has been significantly advanced in recent years. B cell maturation antigen (BCMA)-targeted immunotherapy and chimeric antigen receptor T (CAR-T) cell therapy have been approved for the treatment of relapsed and refractory MM (RRMM), which will be launched in China shortly. The CD38 (cluster of differentiation 38) antibody, daratumumab, improves the clinical outcomes both RRMM and newly diagnosed MM patients. The combination of daratumumab, bortezomib and dexamethasone achieved favorable outcomes as the first-line therapy in China. However, high-risk patients have limited benefits from these advanced therapeutics, and usually relapse early, progressing into aggressive end-stage MM. Therefore, novel therapies are sought to improve the cancer prognosis in these patients. This review furnishes an overview of the recent clinical developments of these novel drugs and compares the drug candidates under development in China to the rest of the world.

Integrative Analysis of Gene Expression Through One-Class Logistic Regression Machine Learning Identifies Stemness Features in Multiple Myeloma

Tumor progression includes the obtainment of progenitor and stem cell-like features and the gradual loss of a differentiated phenotype. Stemness was defined as the potential for differentiation and self-renewal from the cell of origin. Previous studies have confirmed the effective application of stemness in a number of malignancies. However, the mechanisms underlying the growth and maintenance of multiple myeloma (MM) stem cells remain unclear. We calculated the stemness index for samples of MM by utilizing a novel one-class logistic regression (OCLR) machine learning algorithm and found that mRNA expression-based stemness index (mRNAsi) was an independent prognostic factor of MM. Based on the same cutoff value, mRNAsi could stratify MM patients into low and high groups with different outcomes. We identified 127 stemness-related signatures using weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Functional annotation and pathway enrichment analysis indicated that these genes were mainly involved in the cell cycle, cell differentiation, and DNA replication and repair. Using the molecular complex detection (MCODE) algorithm, we identified 34 pivotal signatures. Meanwhile, we conducted unsupervised clustering and classified the MM cohorts into three MM stemness (MMS) clusters with distinct prognoses. Samples in MMS-cluster3 possessed the highest stemness fractions and the worst prognosis. Additionally, we applied the ESTIMATE algorithm to infer differential immune infiltration among the three MMS clusters. The immune core and stromal score were significantly lower in MMS-cluster3 than in the other clusters, supporting the negative relation between stemness and anticancer immunity. Finally, we proposed a prognostic nomogram that allows for individualized assessment of the 3- and 5-year overall survival (OS) probabilities among patients with MM. Our study comprehensively assessed the MM stemness index based on large cohorts and built a 34-gene based classifier for predicting prognosis and potential strategies for stemness treatment.

Chimeric antigen receptor T cell therapy in multiple myeloma: promise and challenges

Despite a sea change in the therapeutic landscape, multiple myeloma (MM), a cancer of antibody producing plasma cells, remains incurable requiring continued intervention for disease control. In this context, chimeric antigen receptor (CAR) T cell therapy has emerged as a promising immunotherapeutic approach with unprecedented results in heavily treated relapsed and/or refractory MM patients. Although B cell maturation antigen (BCMA) is the current lead target for CAR-T cell therapy in MM, several other antigenic targets are also being investigated. Relapses, however, are inevitable in spite of the promising early responses, and may be mediated by antigenic modulation, poor persistence and "immunostat" in tumor microenvironment. Akin to multi-agent chemotherapy, multi-targeted CAR-T antigens and combinatorial approaches are underway to overcome the resistance mechanisms. Further, CAR-T specific toxicity concerns such as cytokine release syndrome and neurotoxicity, as well as manufacturing time lag are other key challenges. Allogeneic CAR that offers "off-the-shelf" options, and mRNA transfected CAR are being developed to mitigate the access and safety issues. In this review we provide the comprehensive review of the most current clinical trial data for CAR-T in myeloma, challenges associated with this therapy and discuss its future in myeloma therapeutics.

Trends in the use of therapeutic plasma exchange in multiple myeloma

INTRODUCTION

Therapeutic plasma exchange (TPE) is traditionally performed for hyperviscosity, neuropathy and to mitigate renal injury in the setting of high clonal free light chain burden in patients with multiple myeloma (MM) with unknown clinical benefit.

MATERIALS AND METHODS

Retrospective study of adults ≥18 years with MM who received TPE in the in-patient setting in the United States from 1993 to 2015. We examined the temporal trends of TPE utilization in MM hospitalizations, hospital charges, in-hospital mortality, and length of hospitalization and the predictors of in-hospital mortality and length of hospitalizations.

RESULTS

The number of MM-hospitalizations for TPE in adults increased significantly from 1993 to 2015 (1% in 1993-1999 to 2.1% in 2008-2015 of all MM discharges, P for trend <.0001). About 70% of TPE recipients had acute kidney injury (AKI). The median hospital charges increased 5-fold during the time period ($ 24 407 to $ 113 496; P for trend <.0001). In-hospital mortality decreased (17.5% (SE 2.66) in 1993-1997 to 8.7% (1.39) in 2007 to 2013) P for trend <.005) while the length of stay remained unchanged (11.2 days vs 11.9 days, P for trend 0.17). On adjusted analysis, significant predictors of in-hospital mortality among MM TPE recipients include, Charlson Comorbidity Index (CCI) (3 vs 2 adjusted odds ratio, aOR 2.16, 95% CI 1.26-3.71; P = .005), year (continuous) (aOR 0.93, 95% CI 0.90-0.96; P < .001) and race (other vs white; aOR 0.44, 95% CI 0.25-0.78; P = 0.004).

CONCLUSIONS

There has been a substantial increase in the use and associated cost of TPE in hospitalized MM patients.

Minimal residual disease analysis in myeloma - when, why and where

The primary hurdle in the path to curing multiple myeloma (MM) is defining a validated minimal residual disease (MRD) and its utility in the therapeutic decision making. A better definition of MRD will aid in tailoring MM therapy further to address the clonal heterogeneity and genomic instability and overcome patient's ineffective immune surveillance. MRD analysis can define the logical endpoint for maintenance therapy, in addition also aids in providing a better clinical end point for studies comparing novel agents in myeloma. MRD is a surrogate for the survival in MM. Guidelines for global incorporation of MRD in myeloma are fraught with lack of standardization, universal availability and abridged physicians' understanding of MRD modalities. We aimed at addressing some of the frequently asked questions in the MRD assessment and will also place in perspective some arguments in favor of MRD assessment in routine practice and clinical trial scenario.

Lenalidomide Maintenance After Autologous Stem-Cell Transplantation in Newly Diagnosed Multiple Myeloma: A Meta-Analysis

Purpose Lenalidomide maintenance therapy after autologous stem-cell transplantation (ASCT) demonstrated prolonged progression-free survival (PFS) versus placebo or observation in several randomized controlled trials (RCTs) of patients with newly diagnosed multiple myeloma (NDMM). All studies had PFS as the primary end point, and none were powered for overall survival (OS) as a primary end point. Thus, a meta-analysis was conducted to better understand the impact of lenalidomide maintenance in this setting. Patients and Methods The meta-analysis was conducted using primary-source patient-level data and documentation from three RCTs (Cancer and Leukemia Group B 100104, Gruppo Italiano Malattie Ematologiche dell'Adulto RV-MM-PI-209, and Intergroupe Francophone du Myélome 2005-02) that met the following prespecified inclusion criteria: an RCT in patients with NDMM receiving ASCT followed by lenalidomide maintenance versus placebo or observation with patient-level data available and achieved database lock for primary efficacy analysis. Results Overall, 1,208 patients were included in the meta-analysis (605 patients in the lenalidomide maintenance group and 603 in the placebo or observation group). The median PFS was 52.8 months for the lenalidomide group and 23.5 months for the placebo or observation group (hazard ratio, 0.48; 95% CI, 0.41 to 0.55). At a median follow-up time of 79.5 months for all surviving patients, the median OS had not been reached for the lenalidomide maintenance group, whereas it was 86.0 months for the placebo or observation group (hazard ratio, 0.75; 95% CI, 0.63 to 0.90; P = .001). The cumulative incidence rate of a second primary malignancy before disease progression was higher with lenalidomide maintenance versus placebo or observation, whereas the cumulative incidence rates of progression, death, or death as a result of myeloma were all higher with placebo or observation versus lenalidomide maintenance. Conclusion This meta-analysis demonstrates a significant OS benefit and confirms the PFS benefit with lenalidomide maintenance after ASCT in patients with NDMM when compared with placebo or observation.

Outcome of autologous hematopoietic stem cell transplantation in refractory multiple myeloma

BACKGROUND

Despite the introduction of effective, novel agents, the outcome of patients with refractory multiple myeloma remains poor, particularly those who are refractory to both proteasome inhibitors (PIs) and immunomodulatory agents (IMiDs). Limited data are available on the role of autologous hematopoietic stem cell transplantation in this population.

METHODS

Patients with refractory myeloma who underwent first autologous hematopoietic stem cell transplantation (auto-HCT) between March 2000 and October 2015 were retrospectively analyzed. Those who had primary refractory disease and those with relapsed and refractory disease were included. Disease that was refractory to at least 1 PI and at least 1 IMiD was classified as double-refractory multiple myeloma (DR-MM).

RESULTS

In total, 233 patients were identified, including 105 (45%) classified with DR-MM and 128 (55%) classified with nondouble-refractory myeloma (NDR-MM). At a median follow-up of 42 months for surviving patients, at least a partial response was observed in 188 patients (81%; 83 patients in the DR-MM group [79%] and 105 patients in the NDR-MM [82%]; P = .77). A near complete response or better was observed in 52 patients (22%; 25 patients in the DR-MM group [24%] and 27 patients in the NDR-MM group [21%]; P = .77). The median progression-free survival was 17.6 months (14.4 months in the DR-MM group and 18.2 months in the NDR-MM group), and the 2-year progression-free survival rate was 38% (35% in the DR-MM group and 40% in the NDR-MM group; P = .40). The median overall survival was 48 months (38.9 months in the DR-MM group and 56.6 months in the NDR-MM group), and the 2-year overall survival rate was 74% (71% in the DR-MM group and 76% in the NDR-MM group; P = .27).

CONCLUSIONS

The current findings indicate that auto-HCT is an effective and safe therapy in patients with refractory multiple myeloma, including those who are refractory to IMiDs and PIs. Cancer 2017;123:3568-75. © 2017 American Cancer Society.

ACTB, CDKN1B, GAPDH, GRB2, RHOA and SDCBP Were Identified as Reference Genes in Neuroendocrine Lung Cancer via the nCounter Technology

Background

Neuroendocrine lung cancer (NELC) represents 25% of all lung cancer cases and large patient collectives exist as formalin-fixed, paraffin-embedded (FFPE) tissue only. FFPE is controversially discussed as source for molecular biological analyses and reference genes for NELC are poorly establishes.

Material and methods

Forty-three representative FFPE-specimens were used for mRNA expression analysis using the digital nCounter technology (NanoString). Based on recent literature, a total of 91 mRNA targets were investigated as potential tumor markers or reference genes. The geNorm, NormFinder algorithms and coefficient of correlation were used to identify the most stable reference genes. Statistical analysis was performed by using the R programming environment (version 3.1.1)

Results

RNA integrity (RIN) ranged from 1.8 to 2.6 and concentrations from 34 to 2,109 ng/μl. However, the nCounter technology gave evaluable results for all samples tested. ACTB, CDKN1B, GAPDH, GRB2, RHOA and SDCBP were identified as constantly expressed genes with high stability (M-)values according to geNorm, NormFinder and coefficients of correlation.

Conclusion

FFPE-derived mRNA is suitable for molecular biological investigations via the nCounter technology, although it is highly degraded. ACTB, CDKN1B, GAPDH, GRB2, RHOA and SDCBP are potent reference genes in neuroendocrine tumors of the lung.