Schenkein, David P.

Abstract Introduction: We investigated tumor gene expression profiling (PGx) to identify predictive classifiers of response and elucidate the mechanism of efficacy of proteasome inhibition in multiple myeloma (MM) by bortezomib, a first-in-class proteasome inhibitor. Analysis of 44 samples from the SUMMIT phase 2 trial identified predictive classifiers of response in patients (pts) with refractory MM (ASH 2002, Abstr 1519). We now report on the PGx analysis of the SUMMIT-derived classifier in an independent sample set from the APEX phase 3 trial, a multicenter randomized study of 669 pts that demonstrated the superiority of bortezomib to high-dose dex for relapsed MM following 1 to 3 prior therapies (Richardson NEJM 2005). As well, we report on a new classifier of response built by combining samples from SUMMIT and MLN34101-040 (040) (a study of bortezomib in pts who failed dex in APEX or were not eligible for APEX) and tested in the APEX samples. Methods: 93 participating clinical centers collected pretreatment bone marrow aspirates and enriched tumor cells on site before centralized RNA extraction and microarray analysis. Approximately 85% of pts consented to whole-genome analysis. Quality control for RNA integrity and quantity, microarray data quality, and tumor cell purity resulted in 129 patient samples from APEX evaluable for PGx; 67 were from the bortezomib arm and 62 from the dex arm. 48 samples were evaluable from 040. Patient characteristics of this subset were similar to those of the overall study population. Predictive classifiers were identified and tested via separate training and test datasets. Results: Consistent with the SUMMIT analysis, the APEX and 040 datasets exhibit biologic features expected of MM, including the overexpression of translocation target genes such as cyclin D1, MAF, and MMSET/FGFR3. Classifiers built using only the SUMMIT samples predict the outcome of pts in the APEX bortezomib arm with an overall accuracy of 51% (sensitivity [Sn] = 49%, specificity [Sp] = 55%; P = .81) and in the dex arm with an overall accuracy of 56% (Sn = 64%, Sp = 50%; P = .31). If the classifier was built using data from both the SUMMIT and 040 trials (87 total samples), the prediction of response in the APEX bortezomib arm was statistically significant (66% accuracy, Sn = 89%, Sp = 42%; P = .006). The same classifier only predicts the response of dex-treated pts with an overall accuracy of 46% (Sn = 72%, Sp = 28%; P = .88), suggesting specificity for bortezomib. Many of the overexpressed genes associated with bortezomib insensitivity relate to protein synthesis (EIF4B, RPL5) and RNA binding (SFRS10, CPSF6). Future Directions: This work highlights practical and scientific issues that inform future efforts to implement PGx in clinical trials. Predictive accuracy may be influenced by the clinical end point, limited sample size, and/or technical considerations associated with distinct trials and genomic data. The influence of study differences (relating to pts’ time from diagnosis, number of prior therapies, molecular subtypes, or hybridization characteristics) on the ability to build classifiers and identify biologic pathways related to response are being examined; these and potential insights on drug mechanisms will be presented.

Abstract NF-κB is a transcriptional factor promoting tumor cell growth and inhibition of apoptosis via regulating expression of proteins modulating cell cycle and anti-apoptosis. NF-κB is constitutively associated with an inhibitor (IκB), which is phosphorylated by IκB kinase (IKK) upon cell stimulation (ie, TNFα) and subsequently degraded by ubiquitin-proteasome pathway, thereby allowing NF-κB to translocate to nucleus. We have previously shown that an IKK inhibitor PS-1145 partially (20–50%) inhibits MM cell proliferation; however, it inhibits both IL-6 secretion from BMSCs triggered by MM cell adhesion and proliferation of MM cells adherent to BMSCs. Targeting IKKβ is therefore a possible therapeutic option for inhibition of MM cell growth in the bone marrow microenvironment by downregulating NF-κB activity. In this study, we further delineated the biologic significance of IKK inhibition in MM cells using IKKβ specific inhibitor MLN120B (Millennium Pharmaceuticals, Cambridge, MA). MLN120B induced 60–90% growth inhibition in cells from the MM cell lines RPMI8226, RPMI/Dox40, RPMI/LR5, U266, and INA-6; on the other hand, it induced only 25–30% inhibition in MM.1S and MM.1R cells, assessed by 72 h tritiated-thymidine uptake. Importantly, neither IL-6 nor IGF-1 overcomes the growth inhibitory effect of MLN120B in both MM.1S and U266 cells. Interestingly, MLN120B significantly augmented TNFα-induced cytotoxicity in MM.1S cells. We next examined whether MLN120B could enhance the cytotoxicity of other agents. MLN120B augmented growth inhibition triggered by doxorubicin and melphalan in RPMI8226 and IL-6 dependent INA-6 cell line. We therefore studied growth inhibitory effect of MLN120B in the presence of bone marrow stromal cells (BMSCs). MLN120B inhibited 70–80% of constitutive IL-6 secretion from BMSCs, without toxicity. Importantly, MLN120B almost completely blocked stimulation of MM.1S, U266 and INA-4 cell growth and IL-6 secretion from BMSCs induced by binding of tumor cells to BMSCs. Finally, MLN120B overcame the protective effect of BMSCs, cell adhesion mediated drug resistance, against dexamethasone in MM.1S cells. Taken together, our data demonstrate that an IKKβ inhibitor induces cytotoxicity in MM cells in the BM milieu, providing the framework for clinical trials of these novel agents to improve patient outcome in MM.

Abstract Initial analysis of the Assessment of Proteasome Inhibition for Extending Remissions (APEX) trial of relapsed multiple myeloma patients showed significantly longer time to progression, higher response rate, and improved survival with single-agent bortezomib versus high-dose dexamethasone. In this updated analysis (median follow-up: 22 months), survival was assessed in both arms, and efficacy updated for the bortezomib arm. Median survival was 29.8 months for bortezomib versus 23.7 months for dexamethasone, a 6-month benefit, despite substantial crossover from dexamethasone to bortezomib. Overall and complete response rates with bortezomib were 43% and 9%, respectively; among responding patients, 56% improved response with longer therapy beyond initial response, leading to continued improvement in overall quality of response. Higher response quality (100% M-protein reduction) was associated with longer response duration; response duration was not associated with time to response. These data confirm the activity of bortezomib and support extended treatment in relapsed multiple myeloma patients tolerating therapy. This study is registered at http://clinicaltrials.gov (Study ID NCT00048230).

Abstract The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents.

Abstract Bortezomib, a potent and reversible proteasome inhibitor, affects the myeloma cell and its microenvironment, resulting in down-regulation of growth and survival signaling pathways and durable responses in patients with relapsed and refractory myeloma. Potential associations between baseline parameters and outcomes with bortezomib were explored in 202 patients who received bortezomib 1.3 mg/m2 twice weekly for 2 weeks every 3 weeks for up to 8 cycles in a phase 2 trial. Using European Group for Blood and Marrow Transplantation criteria, the response rate (complete or partial response) to bortezomib alone was 27% and was not associated with sex, race, performance status, isotype, chromosome 13 deletion, number or type of previous therapies, or concentration of hemoglobin or β2-microglobulin. By multivariate analysis, factors associated with lower response were being age 65 or older versus younger than 65 (19% vs 32%; P < .05) and plasma-cell infiltration in bone marrow greater than 50% versus 50% or less (20% vs 35%; P < .05). Factors that may be indicative of tumor burden (bone marrow plasma-cell infiltration greater than 50%, hypoalbuminemia, thrombocytopenia) were predictive of overall survival. Chromosome 13 deletion and elevated β2-microglobulin, generally considered poor prognostic factors, were not predictive of poor outcome with bortezomib in this study.