Functional profiling of venetoclax sensitivity can predict clinical response in multiple myeloma.
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ABSTRACT:
SUBMITTER: Matulis SM
PROVIDER: S-EPMC6891824 | biostudies-literature | 2019 May
REPOSITORIES: biostudies-literature
Publications
Functional profiling of venetoclax sensitivity can predict clinical response in multiple myeloma.
Matulis Shannon M SM Gupta Vikas A VA Neri Paola P Bahlis Nizar J NJ Maciag Paulo P Leverson Joel D JD Heffner Leonard T LT Lonial Sagar S Nooka Ajay K AK Kaufman Jonathan L JL Boise Lawrence H LH
Leukemia 20190124 5
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Project description:IntroductionMultiple myeloma (MM) is a heterogeneous disease where cancer-driver mutations and aberrant signaling may lead to disease progression and drug resistance. Drug responses vary greatly, and there is an unmet need for biomarkers that can guide precision cancer medicine in this disease.MethodsTo identify potential predictors of drug sensitivity, we applied integrated data from drug sensitivity screening, mutational analysis and functional signaling pathway profiling in 9 cell line models of MM. We studied the sensitivity to 33 targeted drugs and their association with the mutational status of cancer-driver genes and activity level of signaling proteins.ResultsWe found that sensitivity to mitogen-activated protein kinase kinase 1 (MEK1) and phosphatidylinositol-3 kinase (PI3K) inhibitors correlated with mutations in NRAS/KRAS, and PI3K family genes, respectively. Phosphorylation status of MEK1 and protein kinase B (AKT) correlated with sensitivity to MEK and PI3K inhibition, respectively. In addition, we found that enhanced phosphorylation of proteins, including Tank-binding kinase 1 (TBK1), as well as high expression of B cell lymphoma 2 (Bcl-2), correlated with low sensitivity to MEK inhibitors.DiscussionTaken together, this study shows that mutational status and signaling protein profiling might be used in further studies to predict drug sensitivities and identify resistance markers in MM.
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Project description:Venetoclax is a highly potent, selective BCL2 inhibitor capable of inducing apoptosis in cells dependent on BCL2 for survival. Most myeloma is MCL1-dependent; however, a subset of myeloma enriched for translocation t(11;14) is codependent on BCL2 and thus sensitive to venetoclax. The biology underlying this heterogeneity remains poorly understood. We show that knockdown of cyclin D1 does not induce resistance to venetoclax, arguing against a direct role for cyclin D1 in venetoclax sensitivity. To identify other factors contributing to venetoclax response, we studied a panel of 31 myeloma cell lines and 25 patient samples tested for venetoclax sensitivity. In cell lines, we corroborated our previous observation that BIM binding to BCL2 correlates with venetoclax response and further showed that knockout of BIM results in decreased venetoclax sensitivity. RNA-sequencing analysis identified expression of B-cell genes as enriched in venetoclax-sensitive myeloma, although no single gene consistently delineated sensitive and resistant cells. However, a panel of cell surface makers correlated well with ex vivo prediction of venetoclax response in 21 patient samples and may serve as a biomarker independent of t(11;14). Assay for transposase-accessible chromatin sequencing of myeloma cell lines also identified an epigenetic program in venetoclax-sensitive cells that was more similar to B cells than that of venetoclax-resistant cells, as well as enrichment for basic leucine zipper domain-binding motifs such as BATF. Together, these data indicate that remnants of B-cell biology are associated with BCL2 dependency and point to novel biomarkers of venetoclax-sensitive myeloma independent of t(11;14).
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Project description:Venetoclax (ABT-199), a specific inhibitor of the anti-apoptotic protein Bcl-2, is currently in phase I clinical trials for multiple myeloma. The results suggest that venetoclax is only active in a small cohort of patients therefore we wanted to determine its efficacy when used in combination. Combining venetoclax with melphalan or carfilzomib produced additive or better cell death in four of the five cell lines tested. The most striking results were seen with dexamethasone (Dex). Co-treatment of human myeloma cell lines and primary patient samples, with Dex and venetoclax, significantly increased cell death over venetoclax alone in four of the five cell lines, and in all patient samples tested. The mechanism by which this occurs is an increase in the expression of both Bcl-2 and Bim upon addition of Dex. This results in alterations in Bim binding to anti-apoptotic proteins. Dex shifts Bim binding towards Bcl-2 resulting in increased sensitivity to venetoclax. These data suggest that knowledge of drug-induced alterations of Bim-binding patterns may help inform better combination drug regimens. Furthermore, the data indicate combining this novel therapeutic with Dex could be an effective therapy for a broader range of patients than would be predicted by single-agent activity.
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Project description:The BCL-2 antagonist venetoclax is highly effective in multiple myeloma (MM) patients exhibiting the 11;14 translocation, the mechanistic basis of which is unknown. In evaluating cellular energetics and metabolism of t(11;14) and non-t(11;14) MM, we determine that venetoclax-sensitive myeloma has reduced mitochondrial respiration. Consistent with this, low electron transport chain (ETC) Complex I and Complex II activities correlate with venetoclax sensitivity. Inhibition of Complex I, using IACS-010759, an orally bioavailable Complex I inhibitor in clinical trials, as well as succinate ubiquinone reductase (SQR) activity of Complex II, using thenoyltrifluoroacetone (TTFA) or introduction of SDHC R72C mutant, independently sensitize resistant MM to venetoclax. We demonstrate that ETC inhibition increases BCL-2 dependence and the 'primed' state via the ATF4-BIM/NOXA axis. Further, SQR activity correlates with venetoclax sensitivity in patient samples irrespective of t(11;14) status. Use of SQR activity in a functional-biomarker informed manner may better select for MM patients responsive to venetoclax therapy.
| S-EPMC7060223 | biostudies-literature
Project description:Genomic characterization of cancer has enabled identification of numerous molecular targets, which has led to significant advances in personalized medicine. However, with few exceptions, precision medicine approaches in the plasma cell malignancy multiple myeloma (MM) have had limited success, likely owing to the subclonal nature of molecular targets in this disease. Targeted therapies against FGFR3 have been under development for the past decade in the hopes of targeting aberrant FGFR3 activity in MM. FGFR3 activation results from the recurrent transforming event of t(4;14) found in ∼15% of MM patients, as well as secondary FGFR3 mutations in this subgroup. To evaluate the effectiveness of targeting FGFR3 in MM, we undertook a phase 2 clinical trial evaluating the small-molecule FGFR1-4 inhibitor, erdafitinib, in relapsed/refractory myeloma patients with or without FGFR3 mutations (NCT02952573). Herein, we report on a single t(4;14) patient enrolled on this study who was identified to have a subclonal FGFR3 stop-loss deletion. Although this individual eventually progressed on study and succumbed to their disease, the intended molecular response was revealed through an extensive molecular characterization of the patient's tumor at baseline and on treatment using single-cell genomics. We identified elimination of the FGFR3-mutant subclone after treatment and expansion of a preexisting clone with loss of Chromosome 17p. Altogether, our study highlights the utility of single-cell genomics in targeted trials as they can reveal molecular mechanisms that underlie sensitivity and resistance. This in turn can guide more personalized and targeted therapeutic approaches, including those that involve FGFR3-targeting therapies.
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Project description:Whole genome sequencing studies have identified several oncogenic mutations in multiple myeloma (MM). As MM progresses, it evolves genetically underscoring the need to have tools for rapid detection of targetable mutations to optimize individualized treatment. Massachusetts General Hospital (MGH) has developed a Clinical Laboratory Improvement Amendments (CLIA)-approved, high-throughput, genotyping platform to determine the mutation status of a panel of known oncogenes. Sequence analysis using SNaPshot on DNA extracted from bone marrow and extramedullary plasmacytomas is feasible and leads to the detection of potentially druggable mutations. Screening MM patients for somatic mutations in oncogenes may provide novel targets leading to additional therapies for this patient population.
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Project description:BackgroundNecroptosis is an inflammatory cell death mode, and its association with multiple myeloma (MM) remains unclear.MethodsThis prospective study first analyzed the association between necroptosis-related signature as well as prognosis and chemotherapy sensitivity in MM using the necroptosis score. Consensus clustering was used to identify necroptosis-related molecular clusters. Least absolute shrinkage and selection operator analysis and multivariate Cox regression analysis were performed to establish the prognostic model of necroptosis-related genes (NRGs).ResultsA high necroptosis score was associated with poor prognosis and abundant immune infiltration. Two molecular clusters (clusters A and B) significantly differed in terms of prognosis and tumor microenvironment. Cluster B had a worse prognosis and higher tumor marker pathway activity than cluster A. The risk score model based on four NRGs can accurately predict the prognosis of patients with MM, which was validated in two validation cohorts. Receiver operating characteristic curve analysis showed that the area under the curves of the risk score in predicting the 1-, 3-, and 5-year survival rates were 0.710, 0.758, and 0.834, respectively. Further, the activity of pathways related to proliferation and genetic regulation in the high-risk group significantly increased. The drug prediction results showed that the low-risk score group was more sensitive to bortezomib, cytarabine, and doxorubicin than the high-risk score group. Meanwhile, the high-risk score group was more sensitive to lenalidomide and vinblastine than the low-risk score group. Finally, the upregulation of model genes CHMP1A, FAS, JAK3, and HSP90AA1 in clinical samples collected from patients with MM was validated via real-time polymerase chain reaction.ConclusionA systematic analysis of NRGs can help identify potential necroptosis-related mechanisms and provide novel biomarkers for MM prognosis prediction, tumor microenvironment evaluation, and personalized treatment planning.
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Project description:Providing treatment sensitivity stratification at the time of cancer diagnosis allows better allocation of patients to alternative treatment options. Despite many clinical and biological risk markers having been associated with variable survival in cancer, assessing the interplay of these markers through Machine Learning (ML) algorithms still remains to be fully explored. Here, we present a Multi Learning Training approach (MuLT) combining supervised, unsupervised and self-supervised learning algorithms, to examine the predictive value of heterogeneous treatment outcomes for Multiple Myeloma (MM). We show that gene expression values improve the treatment sensitivity prediction and recapitulates genetic abnormalities detected by Fluorescence in situ hybridization (FISH) testing. MuLT performance was assessed by cross-validation experiments, in which it predicted treatment sensitivity with 68.70% of AUC. Finally, simulations showed numerical evidences that in average 17.07% of patients could get better response to a different treatment at the first line.
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Project description:Multiple myeloma (MM) is a heterogeneous haematological disease that remains clinically challenging. Increased activity of the epigenetic silencer EZH2 is a common feature in patients with poor prognosis. Previous findings have demonstrated that metabolic profiles can be sensitive markers for response to treatment in cancer. While EZH2 inhibition (EZH2i) has proven efficient in inducing cell death in a number of human MM cell lines, we hereby identified a subset of cell lines that despite a global loss of H3K27me3, remains viable after EZH2i. By coupling liquid chromatography-mass spectrometry with gene and miRNA expression profiling, we found that sensitivity to EZH2i correlated with distinct metabolic signatures resulting from a dysregulation of genes involved in methionine cycling. Specifically, EZH2i resulted in a miRNA-mediated downregulation of methionine cycling-associated genes in responsive cells. This induced metabolite accumulation and DNA damage, leading to G2 arrest and apoptosis. Altogether, we unveiled that sensitivity to EZH2i in human MM cell lines is associated with a specific metabolic and gene expression profile post-treatment.
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Project description:The historical lack of pre-clinical models reflecting the genetic heterogeneity of multiple myeloma (MM) hampers advancing therapeutic discoveries. To circumvent this limitation, we have generated fifteen genetically diverse models that developed bone marrow tumors fulfilling MM pathogenesis. Transcriptomic analysis of tumor plasma cells revealed that MYC activation regulates time to progression. Bone marrow cell composition analysis classified myeloma tumors into immune-cold and inflamed categories, which condition immune checkpoint blockade responses in mouse multiple myeloma models.
2023-03-17 | GSE205644 | GEO