Reproducible Radiomics Features from Multi-MRI-Scanner Test-Retest-Study: Influence on Performance and Generalizability of Models.

BACKGROUND: Radiomics models trained on data from one center typically show a decline of performance when applied to data from external centers, hindering their introduction into large-scale clinical practice. Current expert recommendations suggest to use only reproducible radiomics features isolated by multiscanner test-retest experiments, which might help to overcome the problem of limited generalizability to external data. PURPOSE: To evaluate the influence of using only a subset of robust radiomics features, defined in a prior in vivo multi-MRI-scanner test-retest-study, on the performance and generalizability of radiomics models. STUDY TYPE: Retrospective. POPULATION: Patients with monoclonal plasma cell disorders. Training set (117 MRIs from center 1); internal test set (42 MRIs from center 1); external test set (143 MRIs from center 2-8). FIELD STRENGTH/SEQUENCE: 1.5T and 3.0T; T1-weighted turbo spin echo. ASSESSMENT: The task for the radiomics models was to predict plasma cell infiltration, determined by bone marrow biopsy, noninvasively from MRI. Radiomics machine learning models, including linear regressor, support vector regressor (SVR), and random forest regressor (RFR), were trained on data from center 1, using either all radiomics features, or using only reproducible radiomics features. Models were tested on an internal (center 1) and a multicentric external data set (center 2-8). STATISTICAL TESTS: Pearson correlation coefficient r and mean absolute error (MAE) between predicted and actual plasma cell infiltration. Fisher's z-transformation, Wilcoxon signed-rank test, Wilcoxon rank-sum test; significance level P < 0.05. RESULTS: When using only reproducible features compared with all features, the performance of the SVR on the external test set significantly improved (r = 0.43 vs. r = 0.18 and MAE = 22.6 vs. MAE = 28.2). For the RFR, the performance on the external test set deteriorated when using only reproducible instead of all radiomics features (r = 0.33 vs. r = 0.44, P = 0.29 and MAE = 21.9 vs. MAE = 20.5, P = 0.10). CONCLUSION: Using only reproducible radiomics features improves the external performance of some, but not all machine learning models, and did not automatically lead to an improvement of the external performance of the overall best radiomics model. TECHNICAL EFFICACY: Stage 2.

International Myeloma Working Group immunotherapy committee consensus guidelines and recommendations for optimal use of T-cell-engaging bispecific antibodies in multiple myeloma.

Multiple myeloma remains an incurable disease, despite the development of numerous drug classes and combinations that have contributed to improved overall survival. Immunotherapies directed against cancer cell-surface antigens, such as chimeric antigen receptor (CAR) T-cell therapy and T-cell-redirecting bispecific antibodies, have recently received regulatory approvals and shown unprecedented efficacy. However, these immunotherapies have unique mechanisms of action and toxicities that are different to previous treatments for myeloma, so experiences from clinical trials and early access programmes are essential for providing specific recommendations for management of patients, especially as these agents become available across many parts of the world. Here, we provide expert consensus clinical practice guidelines for the use of bispecific antibodies for the treatment of myeloma. The International Myeloma Working Group is also involved in the collection of prospective real-time data of patients treated with such immunotherapies, with the aim of learning continuously and adapting clinical practices to optimise the management of patients receiving immunotherapies.

Pre-Clinical Assessment of SAR442257, a CD38/CD3xCD28 Trispecific T Cell Engager in Treatment of Relapsed/Refractory Multiple Myeloma.

Current treatment strategies for multiple myeloma (MM) are highly effective, but most patients develop relapsed/refractory disease (RRMM). The anti-CD38/CD3xCD28 trispecific antibody SAR442257 targets CD38 and CD28 on MM cells and co-stimulates CD3 and CD28 on T cells (TCs). We evaluated different key aspects such as MM cells and T cells avidity interaction, tumor killing, and biomarkers for drug potency in three distinct cohorts of RRMM patients. We found that a significantly higher proportion of RRMM patients (86%) exhibited aberrant co-expression of CD28 compared to newly diagnosed MM (NDMM) patients (19%). Furthermore, SAR442257 mediated significantly higher TC activation, resulting in enhanced MM killing compared to bispecific functional knockout controls for all relapse cohorts (Pearson's r = 0.7). Finally, patients refractory to anti-CD38 therapy had higher levels of TGF-ß (up to 20-fold) compared to other cohorts. This can limit the activity of SAR442257. Vactoserib, a TGF-ß inhibitor, was able to mitigate this effect and restore sensitivity to SAR442257 in these experiments. In conclusion, SAR442257 has high potential for enhancing TC cytotoxicity by co-targeting CD38 and CD28 on MM and CD3/CD28 on T cells.

The biological and clinical impact of deletions before and after large chromosomal gains in multiple myeloma.

Acquisition of a hyperdiploid (HY) karyotype or immunoglobulin heavy chain (IGH) translocations are considered key initiating events in multiple myeloma (MM). To explore if other genomic events can precede these events, we analyzed whole-genome sequencing (WGS) data from 1173 MM samples. Integrating molecular time and structural variants (SV) within early chromosomal duplications, we indeed identified pre-gain deletions in 9.4% of HY patients without IGH translocations, challenging HY as the earliest somatic event. Remarkably, these deletions affected tumor suppressor genes (TSG) and/or oncogenes in 2.4% of HY patients without IGH translocations, supporting their role in MM pathogenesis. Furthermore, our study points to post-gain deletions as novel driver mechanisms in MM. Using multi-omics approaches to investigate their biological impact, we found associations with poor clinical outcome in newly diagnosed patients and profound effects on both oncogene and TSG activity, despite the diploid gene status. Overall, this study provides novel insights into the temporal dynamics of genomic alterations in MM.

EVIDENCE meta-analysis: evaluating minimal residual disease as an intermediate clinical endpoint for multiple myeloma.

Estimating progression-free survival (PFS) and overall survival (OS) superiority during clinical trials of multiple myeloma (MM) has become increasingly challenging as novel therapeutics have improved patient outcomes. Thus, it is imperative to identify earlier endpoint surrogates that are predictive of long-term clinical benefit to expedite development of more effective therapies. Minimal residual disease (MRD)-negativity is a common intermediate endpoint that has shown prognostic value for clinical benefit in trials of patients with multiple myeloma (MM). This meta-analysis was based on the FDA guidance for considerations for a meta-analysis of MRD as a clinical endpoint and evaluates MRD-negativity as an early endpoint reasonably likely to predict long-term clinical benefit. Eligible studies were phase 2 or 3 randomized controlled clinical trials measuring MRD negativity as an endpoint in patients with MM, with follow-up of ≥6 months following an a priori defined time point of 12±3 months post-randomization. Eight newly diagnosed MM-(NDMM)-studies evaluating 4,907 patients were included. Trial-level associations between MRD-negativity and PFS were R2WLSiv (95% CI) 0.67 (0.43-0.91) and R2copula 0.84 (0.64->0.99) at the 12-month timepoint. The individual-level association between 12-month MRD negativity and PFS resulted in a global odds ratio of 4.02 (95% CI: 2.57-5.46). For relapse/refractory MM-(RRMM), there were four studies included, and the individual-level association between 12-month MRD negativity and PFS resulted in a global odds ratio of 7.67 (4.24-11.10). A clinical trial demonstrating a treatment effect on MRD is reasonably likely to eventually demonstrate a treatment effect on PFS, suggesting that MRD may be an early clinical endpoint reasonably likely to predict clinical benefit in MM, that may be used to support accelerated approval and thereby expedite the availability of new drugs to patients with MM.

Cytomegalovirus immunoglobulin serology prevalence in patients with newly diagnosed multiple myeloma treated within the GMMG-MM5 phase III trial.

OBJECTIVES: The seroprevalence of antibodies against Cytomegalovirus (CMV) is an established poor prognostic factor for patients receiving an allogeneic stem cell transplantation. However, the impact of CMV serology on outcome after autologous stem cell transplantation remains unknown. METHODS: Here, we analyzed the CMV immunoglobulin (Ig) serology of 446 newly-diagnosed multiple myeloma (MM) patients of the GMMG-MM5 phase III trial with a median follow-up of 58 months. RESULTS: CMV IgG and IgM positivity was seen in 51% and 6% of the patients, respectively. In multivariate analysis CMV IgG and CMV IgM serology show an age-depending effect for PFS. We identified positive CMV IgG/positive CMV IgM serology as an age-depending beneficial factor on PFS. DISCUSSION: Younger patients with a positive CMV IgG/positive CMV IgM serology experienced a favorable effect on PFS, whereas a positive CMV IgG/positive CMV IgM serology at older age has a disadvantageous effect on PFS.

Elotuzumab, lenalidomide, bortezomib, dexamethasone, and autologous haematopoietic stem-cell transplantation for newly diagnosed multiple myeloma (GMMG-HD6): results from a randomised, phase 3 trial.

BACKGROUND: The aim of this trial was to investigate the addition of the anti-SLAMF7 monoclonal antibody elotuzumab to lenalidomide, bortezomib, and dexamethasone (RVd) in induction and consolidation therapy as well as to lenalidomide maintenance treatment in transplant-eligible patients with newly diagnosed multiple myeloma. METHODS: GMMG-HD6 was a phase 3, randomised trial conducted at 43 main trial sites and 26 associated trial sites throughout Germany. Adult patients (aged 18-70 years) with previously untreated, symptomatic multiple myeloma, and a WHO performance status of 0-3, with 3 being allowed only if caused by myeloma disease and not by comorbid conditions, were randomly assigned 1:1:1:1 to four treatment groups. Induction therapy consisted of four 21-day cycles of RVd (lenalidomide 25 mg orally on days 1-14; bortezomib 1·3 mg/m2 subcutaneously on days 1, 4, 8, and 11]; and dexamethasone 20 mg orally on days 1, 2, 4, 5, 8, 9, 11, 12, and 15 for cycles 1-2) or, RVd induction plus elotuzumab (10 mg/kg intravenously on days 1, 8, and 15 for cycles 1-2, and on days 1 and 11 for cycles 3-4; E-RVd). Autologous haematopoietic stem-cell transplantation was followed by two 21-day cycles of either RVd consolidation (lenalidomide 25 mg orally on days 1-14; bortezomib 1·3 mg/m2 subcutaneously on days 1, 8, and 15; and dexamethasone 20 mg orally on days 1, 2, 8, 9, 15, and 16) or elotuzumab plus RVd consolidation (with elotuzumab 10 mg/kg intravenously on days 1, 8, and 15) followed by maintenance with either lenalidomide (10 mg orally on days 1-28 for cycles 1-3; thereafter, up to 15 mg orally on days 1-28; RVd/R or E-RVd/R group) or lenalidomide plus elotuzumab (10 mg/kg intravenously on days 1 and 15 for cycles 1-6, and on day 1 for cycles 7-26; RVd/E-R or E-RVd/E-R group) for 2 years. The primary endpoint was progression-free survival analysed in a modified intention-to-treat (ITT) population. Safety was analysed in all patients who received at least one dose of trial medication. This trial is registered with ClinicalTrials.gov, NCT02495922, and is completed. FINDINGS: Between June 29, 2015, and on Sept 11, 2017, 564 patients were included in the trial. The modified ITT population comprised 559 (243 [43%] females and 316 [57%] males) patients and the safety population 555 patients. After a median follow-up of 49·8 months (IQR 43·7-55·5), there was no difference in progression-free survival between the four treatment groups (adjusted log-rank p value, p=0·86), and 3-year progression-free survival rates were 69% (95% CI 61-77), 69% (61-76), 66% (58-74), and 67% (59-75) for patients treated with RVd/R, RVd/E-R, E-RVd/R, and E-RVd/E-R, respectively. Infections (grade 3 or worse) were the most frequently observed adverse event in all treatment groups (28 [20%] of 137 for RVd/R; 32 [23%] of 138 for RVd/E-R; 35 [25%] of 138 for E-RVd/R; and 48 [34%] of 142 for E-RVd/E-R). Serious adverse events (grade 3 or worse) were observed in 68 (48%) of 142 participants in the E-RVd/E-R group, 53 (39%) of 137 in the RVd/R, 53 (38%) of 138 in the RVd/E-R, and 50 (36%) of 138 in the E-RVd/R (36%) group. There were nine treatment-related deaths during the study. Two deaths (one sepsis and one toxic colitis) in the RVd/R group were considered lenalidomide-related. One death in the RVd/E-R group due to meningoencephalitis was considered lenalidomide and elotuzumab-related. Four deaths (one pulmonary embolism, one septic shock, one atypical pneumonia, and one cardiovascular failure) in the E-RVd/R group and two deaths (one sepsis and one pneumonia and pulmonary fibrosis) in the E-RVd/E-R group were considered related to lenalidomide or elotuzumab, or both. INTERPRETATION: Addition of elotuzumab to RVd induction or consolidation and lenalidomide maintenance in patients with transplant-eligible newly diagnosed multiple myeloma did not provide clinical benefit. Elotuzumab-containing therapies might be reserved for patients with relapsed or refractory multiple myeloma. FUNDING: Bristol Myers Squibb/Celgene and Chugai.

Impact of Clonal Heterogeneity in Multiple Myeloma.

Multiple myeloma is characterized by a highly heterogeneous disease distribution within the bone marrow-containing skeletal system. In this review, we introduce the molecular mechanisms underlying clonal heterogeneity and the spatio-temporal evolution of myeloma. We discuss the clinical impact of clonal heterogeneity, which is thought to be one of the biggest obstacles to overcome therapy resistance and to achieve cure.

Sequence diversity of kappa light chains from patients with AL amyloidosis and multiple myeloma.

BACKGROUND: AL amyloidosis (AL) results from the misfolding of immunoglobulin light chains (IG LCs). Aim of this study was to comprehensively analyse kappa LC sequences from AL patients in comparison with multiple myeloma (MM). OBJECTIVE: We analysed IGKV/IGKJ usage and associated organ tropism and IGKV1/D-33 in terms of mutational analysis and theoretical biochemical properties. MATERIAL AND METHODS: cDNA and bulk RNA sequencing of the LCs of AL and MM patients. RESULTS: We studied 41 AL and 83 MM patients showing that IGKV1 was most expressed among kappa AL and MM, with higher frequency in AL (80% vs. 53%, p = .002). IGKV3 was underrepresented in AL (10% vs. 30%, p = .014). IGKJ2 was more commonly used in AL than in MM (39% vs. 29%). Patients with IGKV1/D-33 were associated with heart involvement (75%, p = .024). IGKV1/D-33-segments of AL had a higher mutation count (AL = 12.0 vs. MM = 10.0). FR3 and CDR3 were most frequently mutated in both, with a median mutation count in FR3 being the highest (AL = 4.0; MM = 3.5) and one mutation hotspot (FR3 (83I)) for IGKV1/D-33/IGKJ2 was associated with cardiac involvement. CONCLUSION: This study confirmed that germline usage has an influence on AL amyloidosis risk and organ involvement.

Genomic Classification and Individualized Prognosis in Multiple Myeloma.

PURPOSE: Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS: To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS: Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression-based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION: Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.

Sequential antigen loss and branching evolution in lymphoma after CD19- and CD20-targeted T-cell-redirecting therapy.

ABSTRACT: CD19 chimeric antigen receptor (CAR) T cells and CD20 targeting T-cell-engaging bispecific antibodies (bispecs) have been approved in B-cell non-Hodgkin lymphoma lately, heralding a new clinical setting in which patients are treated with both approaches, sequentially. The aim of our study was to investigate the selective pressure of CD19- and CD20-directed therapy on the clonal architecture in lymphoma. Using a broad analytical pipeline on 28 longitudinally collected specimen from 7 patients, we identified truncating mutations in the gene encoding CD20 conferring antigen loss in 80% of patients relapsing from CD20 bispecs. Pronounced T-cell exhaustion was identified in cases with progressive disease and retained CD20 expression. We also confirmed CD19 loss after CAR T-cell therapy and reported the case of sequential CD19 and CD20 loss. We observed branching evolution with re-emergence of CD20+ subclones at later time points and spatial heterogeneity for CD20 expression in response to targeted therapy. Our results highlight immunotherapy as not only an evolutionary bottleneck selecting for antigen loss variants but also complex evolutionary pathways underlying disease progression from these novel therapies.

Stem cell collection after lenalidomide, bortezomib and dexamethasone plus elotuzumab or isatuximab in newly diagnosed multiple myeloma patients: a single centre experience from the GMMG-HD6 and -HD7 trials.

BACKGROUND: While quadruplet induction therapies deepen responses in newly diagnosed multiple myeloma patients, their impact on peripheral blood stem cell (PBSC) collection remains incompletely understood. This analysis aims to evaluate the effects of prolonged lenalidomide induction and isatuximab- or elotuzumab-containing quadruplet induction therapies on PBSC mobilization and collection. METHODS: A total of 179 transplant-eligible patients with newly diagnosed MM treated at a single academic center were included. The patients were evaluated based on PBSC mobilization and collection parameters, including overall collection results, CD34+ cell levels in peripheral blood, leukapheresis (LP) delays, overall number of LP sessions, and the rate of rescue mobilization with plerixafor. The patients underwent four different induction regimens: Lenalidomide, bortezomib, and dexamethasone (RVd, six 21-day cycles, n = 44), isatuximab-RVd (six 21-day cycles, n = 35), RVd (four 21-day cycles, n = 51), or elotuzumab-RVd (four 21-day cycles, n = 49). RESULTS: The patients' characteristics were well balanced across the different groups. Collection failures, defined as the inability to collect three sufficient PBSC transplants, were rare (n = 3, 2%), with no occurrences in the isatuximab-RVd and elotuzumab-RVd groups. Intensified induction with six 21-day cycles of RVd did not negatively impact the overall number of collected PBSCs (9.7 × 106/kg bw versus 10.5 × 106/kg bw, p = 0.331) compared to four 21-day cycles of RVd. Plerixafor usage was more common after six cycles of RVd compared to four cycles (16% versus 8%). Addition of elotuzumab to RVd did not adversely affect overall PBSC collection (10.9 × 106/kg bw versus 10.5 × 106/kg bw, p = 0.915). Patients treated with isatuximab-RVd (six cycles) had lower numbers of collected stem cells compared to those receiving RVd (six cycles) induction (8.8 × 106/kg bw versus 9.7 × 106/kg bw, p = 0.801), without experiencing significant delays in LP or increased numbers of LP sessions in a multivariable logistic regression analysis. Plerixafor usage was more common after isatuximab plus RVd compared to RVd alone (34% versus 16%). CONCLUSIONS: This study demonstrates that stem cell collection is feasible after prolonged induction with isatuximab-RVd without collection failures and might be further explored as induction therapy. TRIAL REGISTRATION: Patients were treated within the randomized phase III clinical trials GMMG-HD6 (NCT02495922, 24/06/2015) and GMMG-HD7 (NCT03617731, 24/07/2018). However, during stem cell mobilization and -collection, no study-specific therapeutic intervention was performed.

High-throughput electron tomography identifies centriole over-elongation as an early event in plasma cell disorders.

Plasma cell disorders are clonal outgrowths of pre-malignant or malignant plasma cells, characterized by extensive chromosomal aberrations. Centrosome abnormalities are a major driver of chromosomal instability in cancer but their origin, incidence, and composition in primary tumor cells is poorly understood. Using cutting-edge, semi-automated high-throughput electron tomography, we characterized at nanoscale 1386 centrioles in CD138pos plasma cells from eight healthy donors and 21 patients with plasma cell disorders, and 722 centrioles from different control populations. In plasma cells from healthy individuals, over-elongated centrioles accumulated with age. In plasma cell disorders, centriole over-elongation was notably frequent in early, pre-malignant disease stages, became less pronounced in overt multiple myeloma, and almost entirely disappeared in aggressive plasma cell leukemia. Centrioles in other types of patient-derived B cell neoplasms showed no over-elongation. In contrast to current belief, centriole length appears to be highly variable in long-lived, healthy plasma cells, and over-elongation and structural aberrations are common in this cell type. Our data suggest that structural centrosome aberrations accumulate with age in healthy CD138pos plasma cells and may thus play an important role in early aneuploidization as an oncogenic driver in plasma cell disorders.

Resolving the spatial architecture of myeloma and its microenvironment at the single-cell level.

In multiple myeloma spatial differences in the subclonal architecture, molecular signatures and composition of the microenvironment remain poorly characterized. To address this shortcoming, we perform multi-region sequencing on paired random bone marrow and focal lesion samples from 17 newly diagnosed patients. Using single-cell RNA- and ATAC-seq we find a median of 6 tumor subclones per patient and unique subclones in focal lesions. Genetically identical subclones display different levels of spatial transcriptional plasticity, including nearly identical profiles and pronounced heterogeneity at different sites, which can include differential expression of immunotherapy targets, such as CD20 and CD38. Macrophages are significantly depleted in the microenvironment of focal lesions. We observe proportional changes in the T-cell repertoire but no site-specific expansion of T-cell clones in intramedullary lesions. In conclusion, our results demonstrate the relevance of considering spatial heterogeneity in multiple myeloma with potential implications for models of cell-cell interactions and disease progression.

Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma.

PURPOSE: [18F]FDG PET/CT is an imaging modality of high performance in multiple myeloma (MM). Nevertheless, the inter-observer reproducibility in PET/CT scan interpretation may be hampered by the different patterns of bone marrow (BM) infiltration in the disease. Although many approaches have been recently developed to address the issue of standardization, none can yet be considered a standard method in the interpretation of PET/CT. We herein aim to validate a novel three-dimensional deep learning-based tool on PET/CT images for automated assessment of the intensity of BM metabolism in MM patients. MATERIALS AND METHODS: Whole-body [18F]FDG PET/CT scans of 35 consecutive, previously untreated MM patients were studied. All patients were investigated in the context of an open-label, multicenter, randomized, active-controlled, phase 3 trial (GMMG-HD7). Qualitative (visual) analysis classified the PET/CT scans into three groups based on the presence and number of focal [18F]FDG-avid lesions as well as the degree of diffuse [18F]FDG uptake in the BM. The proposed automated method for BM metabolism assessment is based on an initial CT-based segmentation of the skeleton, its transfer to the SUV PET images, the subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, six different SUV thresholds (Approaches 1-6) were applied for the definition of pathological tracer uptake in the skeleton [Approach 1: liver SUVmedian × 1.1 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 2: liver SUVmedian × 1.5 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 3: liver SUVmedian × 2 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 4: ≥ 2.5. Approach 5: ≥ 2.5 (axial skeleton), ≥ 2.0 (extremities). Approach 6: SUVmax liver]. Using the resulting masks, subsequent calculations of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in each patient were performed. A correlation analysis was performed between the automated PET values and the results of the visual PET/CT analysis as well as the histopathological, cytogenetical, and clinical data of the patients. RESULTS: BM segmentation and calculation of MTV and TLG after the application of the deep learning tool were feasible in all patients. A significant positive correlation (p < 0.05) was observed between the results of the visual analysis of the PET/CT scans for the three patient groups and the MTV and TLG values after the employment of all six [18F]FDG uptake thresholds. In addition, there were significant differences between the three patient groups with regard to their MTV and TLG values for all applied thresholds of pathological tracer uptake. Furthermore, we could demonstrate a significant, moderate, positive correlation of BM plasma cell infiltration and plasma levels of ß2-microglobulin with the automated quantitative PET/CT parameters MTV and TLG after utilization of Approaches 1, 2, 4, and 5. CONCLUSIONS: The automated, volumetric, whole-body PET/CT assessment of the BM metabolic activity in MM is feasible with the herein applied method and correlates with clinically relevant parameters in the disease. This methodology offers a potentially reliable tool in the direction of optimization and standardization of PET/CT interpretation in MM. Based on the present promising findings, the deep learning-based approach will be further evaluated in future prospective studies with larger patient cohorts.

(Smoldering) multiple myeloma: mismatch between tumor load estimated from bone marrow biopsy at iliac crest and tumor load shown by MRI.

In multiple myeloma and its precursor stages, precise quantification of tumor load is of high importance for diagnosis, risk assessment, and therapy response evaluation. Both whole-body MRI, which allows to investigate the complete bone marrow of a patient, and bone marrow biopsy, which is commonly used to assess the histologic and genetic status, are relevant methods for tumor load assessment in multiple myeloma. We report on a series of striking mismatches between the plasma cell infiltration estimating the tumor load from unguided biopsies of the bone marrow at the posterior iliac crest and the tumor load assessment from whole-body MRI.

Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis.

Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.