Faculty Bibliography

BACKGROUND:Immunomodulatory derivatives (IMiDs), along with proteasome inhibitors, are key components of treatment regimens for multiple myeloma. Nonetheless, outcomes vary among treated individuals. Drug-specific gene-expression profile (GEP) signatures that aid the prediction of favourable and unfavourable outcomes can provide patients with the most effective therapy for their individual disease. We aimed to develop and validate a gene expression signature to suggest which patients would benefit most from IMiD-based therapies. METHODS:For this exploratory retrospective study, we selected a cohort of patients with newly diagnosed or relapsed or refractory multiple myeloma who were treated in clinical trials with IMiD-containing regimens. Cohorts were eligible if they had publicly available GEP data from patients' bone marrow plasma cells, with long-term follow-up and clinicopathological data. In the development stage of the model, we identified 176 IMiD response genes that were differentially expressed before and after IMiD exposure using pharmacogenomic GEP data from patients who had bone marrow samples taken before and 48 h after a test dose exposure with thalidomide (n=42), lenalidomide (n=18), or pomalidomide (n=18). 14 of these genes had p values less than 0·05 for associations with progression-free survival in patients who received thalidomide in induction and maintenance therapy in the Total Therapy (TT) 2 trial (ie, the training cohort). We combined the 14 genes to create a continuous IMiD-14 score and an optimal cutoff. The subgroup with an IMiD-14 score higher than the cutoff was deemed to be IMiD-resistant. We obtained validation cohorts from four studies of IMiD combination regimens: the TT3a trial (thalidomide in induction and maintenance), the TT3b trial (thalidomide in induction and lenalidomide in maintenance), the TT6 trial (thalidomide in induction and lenalidomide in maintenance), and the vincristine, doxorubicin, and dexamethasone (VAD) group of the HOVON65/GMMG-HD4 trial (thalidomide in maintenance). The primary endpoint was to show the prognostic value of the IMiD-14 gene signature for progression-free survival. FINDINGS/RESULTS:In the training cohort, progression-free survival was significantly shorter in the 83 patients with IMiD-14 high scores than in the 92 patients with IMiD-14 low scores; 3 year progression-free survival was 52% (95% CI 42-64) for the IMiD-14 high group versus 85% (78-92) for the IMiD-14 low group, with a hazard ratio (HR) of 2·51 (95% CI 1·72-3·66; p<0·0001). These findings were supported by the results in the validation cohorts, TT3a (115 patients with IMiD-14 high vs 160 patients with IMiD-14 low; 3 year progression-free survival 63% [95% CI 55-73] vs 87% [82-92]; HR 1·54 [1·11-2·15], p=0·010), TT3b (77 patients with IMiD-14 high vs 89 patients with IMiD-14 low; 62% [52-74] vs 80% [72-89]; HR 2·07 [1·28-3·34], p=0·0024), TT6 (20 patients with IMiD-14 high vs 36 patients with IMiD-14 low; 39% [22-68] vs 74% [61-90]; HR 2·40 [1·09-5·30], p=0·026), and the VAD group of HOVON65/GMMG-HD4 (65 patients with IMiD-14 high vs 77 patients with IMiD-14 low; 16% [9-28] vs 54% [44-67]; HR 2·29 [1·52-3·45], p<0·0001). INTERPRETATION/CONCLUSIONS:Our results suggest that the IMiD-14 model has prognostic value in patients with multiple myeloma who are treated with IMiDs. Some genes in the model could provide novel targets for IMiD resistance and therapeutic intervention. The IMiD-14 model warrants evaluation in prospective studies. FUNDING/BACKGROUND:Conquer Cancer Foundation ASCO Young Investigator Award and the Carolinas Myeloma Research Fund.

Monoclonal gammopathy of undetermined significance is a pre-malignant precursor of multiple myeloma with a 1% risk of progression per year. Although targeted analyses have shown the presence of specific genetic abnormalities such as IGH translocations, RB1 deletion, 1q gain, hyperdiploidy or RAS gene mutations, little is known about the molecular mechanism of malignant transformation. We performed whole exome sequencing together with comparative genomic hybridization plus single nucleotide polymorphism array analysis in 33 flow-cytometry-separated abnormal plasma cell samples from patients with monoclonal gammopathy of undetermined significance to describe somatic gene mutations and chromosome changes at the genome-wide level. Non-synonymous mutations and copy-number alterations were present in 97.0% and in 60.6% of cases, respectively. Importantly, the number of somatic mutations was significantly lower in monoclonal gammopathy of undetermined significance than in myeloma (P<10^-4) and we identified six genes that were significantly mutated in myeloma (KRAS, NRAS, DIS3, HIST1H1E, EGR1 and LTB) within the monoclonal gammopathy of undetermined significance dataset. We also found a positive correlation with increasing chromosome changes and somatic gene mutations. IGH translocations, comprising t(4;14), t(11;14), t(14;16) and t(14;20), were present in 27.3% of cases and in a similar frequency to myeloma, consistent with the primary lesion hypothesis. MYC translocations and TP53 deletions or mutations were not detected in samples from patients with monoclonal gammopathy of undetermined significance, indicating that they may be drivers of progression to myeloma. Data from this study show that monoclonal gammopathy of undetermined significance is genetically similar to myeloma, however overall genetic abnormalities are present at significantly lower levels in monoclonal gammopathy of undetermined significant than in myeloma.

The outcomes for the majority of patients with myeloma have improved over recent decades, driven by treatment advances. However, there is a subset of patients considered to have high-risk disease who have not benefited. Understanding how high-risk disease evolves from more therapeutically tractable stages is crucial if we are to improve outcomes. This can be accomplished by identifying the genetic mechanisms and mutations driving the transition of a normal plasma cell to one with the features of the following disease stages: monoclonal gammopathy of undetermined significance, smouldering myeloma, myeloma and plasma cell leukaemia. Although myeloma initiating events are clonal, subsequent driver lesions often occur in a subclone of cells, facilitating progression by Darwinian selection processes. Understanding the co-evolution of the clones within their microenvironment will be crucial for therapeutically manipulating the process. The end stage of progression is the generation of a state associated with treatment resistance, increased proliferation, evasion of apoptosis and an ability to grow independently of the bone marrow microenvironment. In this Review, we discuss these end-stage high-risk disease states and how new information is improving our understanding of their evolutionary trajectories, how they may be diagnosed and the biological behaviour that must be addressed if they are to be treated effectively.

In multiple myeloma malignant plasma cells expand within the bone marrow. Since this site is well-perfused, a rapid dissemination of "fitter" clones may be anticipated. However, an imbalanced distribution of multiple myeloma is frequently observed in medical imaging. Here, we perform multi-region sequencing, including iliac crest and radiology-guided focal lesion specimens from 51 patients to gain insight into the spatial clonal architecture. We demonstrate spatial genomic heterogeneity in more than 75% of patients, including inactivation of CDKN2C and TP53, and mutations affecting mitogen-activated protein kinase genes. We show that the extent of spatial heterogeneity is positively associated with the size of biopsied focal lesions consistent with regional outgrowth of advanced clones. The results support a model for multiple myeloma progression with clonal sweeps in the early phase and regional evolution in advanced disease. We suggest that multi-region investigations are critical to understanding intra-patient heterogeneity and the evolutionary processes in multiple myeloma.In multiple myeloma, malignant cells expand within bone marrow. Here, the authors use multi-region sequencing in patient samples to analyse spatial clonal architecture and heterogeneity, providing novel insight into multiple myeloma progression and evolution.

Immunoglobulin light chain (AL) amyloidosis is characterized by tissue deposition of amyloid fibers derived from immunoglobulin light chain. AL amyloidosis and multiple myeloma (MM) originate from monoclonal gammopathy of undetermined significance. We wanted to characterize germline susceptibility to AL amyloidosis using a genome-wide association study (GWAS) on 1229 AL amyloidosis patients from Germany, UK and Italy, and 7526 healthy local controls. For comparison with MM, recent GWAS data on 3790 cases were used. For AL amyloidosis, single nucleotide polymorphisms (SNPs) at 10 loci showed evidence of an association at P<10^-5 with homogeneity of results from the 3 sample sets; some of these were previously documented to influence MM risk, including the SNP at the IRF4 binding site. In AL amyloidosis, rs9344 at the splice site of cyclin D1, promoting translocation (11;14), reached the highest significance, P=7.80 × 10^-11; the SNP was only marginally significant in MM. SNP rs79419269 close to gene SMARCD3 involved in chromatin remodeling was also significant (P=5.2 × 10^-8). These data provide evidence for common genetic susceptibility to AL amyloidosis and MM. Cyclin D1 is a more prominent driver in AL amyloidosis than in MM, but the links to aggregation of light chains need to be demonstrated.

Light chain deposition disease (LCDD) is characterized by monotypic immunoglobulin depositions which will eventually lead to loss of organ function if left untreated. While the kidney is almost always affected, the presence and degree of LCDD in other organs vary. Ten to thirty percent of LCDD patients have underlying Multiple Myeloma (MM), yet outcome and prognostic markers in this particular patient group are still lacking. Here, we analyzed 69 patients with MM and biopsy proven LCDD and report on renal and extra-renal involvement and its impact on prognosis as well as renal response depending on hematologic response. Coexisting light chain diseases such as AL amyloid and cast nephropathy were found in 30% of patients; those with LCDD and concurrent amyloid tended to have shorter survival. Cardiac involvement by LCDD was seen in one-third of our patients and was associated with shorter overall survival; such patients also had a significantly higher risk of treatment-related mortality (TRM) after stem cell transplant (SCT) compared to LCDD patients without cardiac involvement. This study highlights that MM patients with LCDD present with different clinical features compared to previously reported LCDD cohorts. Rapid initiation of treatment is necessary to prevent progressive renal disease and worse outcome. Coexisting light chain diseases and cardiac involvement are more common than previously reported and confer worse clinical outcome, emphasizing the need for careful patient careful patient evaluation and treatment selection.

¹⁸F-Fluorodeoxyglucose (FDG)-positron emission tomography (PET) and diffusion-weighted magnetic resonance imaging with background signal suppression (DWIBS) are 2 powerful functional imaging modalities in the evaluation of malignant plasma cell (PC) disease multiple myeloma (MM). Preliminary observations have suggested that MM patients with extensive disease according to DWIBS may be reported as being disease-free on FDG-PET ("PET false-negative"). The aim of this study was to describe the proportion of PET false-negativity in a representative set of 227 newly diagnosed MM patients with simultaneous assessment of FDG-PET and DWIBS, and to identify tumor-intrinsic features associated with this pattern. We found the incidence of PET false-negativity to be 11%. Neither tumor load-associated parameters, such as degree of bone marrow PC infiltration, nor the PC proliferation rate were associated with this subset. However, the gene coding for hexokinase-2, which catalyzes the first step of glycolysis, was significantly lower expressed in PET false-negative cases (5.3-fold change, P < .001) which provides a mechanistic explanation for this feature. In conclusion, we demonstrate a relevant number of patients with FDG-PET false-negative MM and a strong association between hexokinase-2 expression and this negativity: a finding which may also be relevant for clinical imaging of other hematological cancers.