Trippa, Lorenzo

PURPOSE Integrating external control data into clinical trial designs and analyses has the potential to accelerate drug development processes. We reanalyzed the three experimental arms of the Individual Screening Trial of Innovative Glioblastoma Therapy (INSIGhT), a randomized phase II platform trial in newly diagnosed O 6 -methylguanine-DNA methyltransferase-unmethylated glioblastoma (ClinicalTrials.gov identifier: NCT02977780 ). To evaluate the validity of using external data sets, we compared treatment effect estimates based on internal INSIGhT control data and matched external control data. METHODS The three experimental arms of INSIGhT (abemaciclib [n = 72], neratinib [n = 80], and CC-115 [n = 12]) did not improve survival compared with internal controls (standard chemoradiation [n = 70]). We derived external control patient-level data from multiple real-world and clinical trial data sets. We applied propensity score matching and Cox proportional hazards models to estimate treatment effects with external controls. Additionally, using this glioblastoma (GBM) data collection, we specified simulation scenarios to evaluate trial designs that integrate external controls. RESULTS After matching to external controls, no survival benefit was observed for patients receiving abemaciclib (hazard ratio [HR], 1.00 [95% CI, 0.75 to 1.34]), neratinib (HR, 0.93 [95% CI, 0.70 to 1.24]), or CC-115 (HR, 0.88 [95% CI, 0.41 to 1.88]). Simulations, together with the INSIGhT data and a collection of GBM data sets, allowed us to examine efficiencies and risks of clinical trial designs that leverage external control data. CONCLUSION The use of carefully matched external controls, to replace or augment the internal controls of INSIGhT, produced treatment effect estimates that were similar to previously published analyses. Single-arm trial designs and hybrid randomized designs incorporating propensity score–matched external control data evaluated treatment effects in the early-phase testing of experimental therapies in newly diagnosed GBM. The validity of this approach and risks of bias depended on the availability of comprehensive and accurate data on all potential confounders, in the absence of unmeasured confounding.

Abstract INTRODUCTION Brigatinib is an oral ALK inhibitor that inhibits multiple tyrosine kinases. We previously published outcomes of patients with NF2-related schwannomatosis treated with brigatinib for a median of 10.4 months. We report updated results of these patients with extended follow-up. METHODS This multicenter, phase II, open-label study included participants ≥12 years with NF2-SWN and progressive target tumors (baskets: VS, NVS, meningioma, or ependymoma). Patients were treated with brigatinib 180 mg daily. Patients discontinued treatment upon progression of target tumors but could continue treatment with isolated progression of non-target tumors if deemed clinically acceptable by the treating team and patient. One target and up to 5 non-target tumors were followed in each participant. Tumor response was evaluated by MRI every 3 months in year 1 and every 6 months thereafter with radiographic response (RR) defined as ≥20% decrease in volume compared to baseline. RESULTS Forty participants were treated for a median of 23 months (range, 3-40 months). Updated imaging data is available on 162 tumors (45 VS, 59 non-VS, 53 meningiomas, and 5 ependymomas). RR rate for all tumors was 28% and was 31% for non-VS, 28% for meningioma, 22% for VS, and 60% for ependymomas. The 12-month freedom from tumor progression was 77.1% for all tumors, 81.5% for non-VS, 78.1% for meningioma, 69.2% for VS, and 100.0% for ependymoma. The 24-month freedom from tumor progression was 73% for all tumors, 81.3% for non-VS, 72.4% for meningioma, 62.4% for VS, and 100.0% for ependymoma. There were no grade 4/5 treatment-related adverse events (AEs). The most common AEs were diarrhea (65%), nausea (40%), muscle cramps (40%), hypertension (35%), increased LDH (35%), increased AST (33%), and increased ALT (25%). CONCLUSION Brigatinib treatment was associated with high rates of tumor stability at 24 months across multiple tumor types in patients with NF2-related schwannomatosis.

Abstract Accurate prediction of risk of progression from smoldering (SMM) to active multiple myeloma (MM) is paramount to individualized early therapeutic strategies with minimum risk of overtreatment. Current risk stratification models do not account for evolving biomarker trajectories. We assembled the largest cohort to date of 2,270 SMM patients from six international centers with longitudinal clinical and biological data to train and validate the PANGEA 2.0 risk models. Four evolving biomarkers were significantly associated with shorter time-to-progression: M-protein increase ≥0.2g/dL, involved:uninvolved serum free light chain ratio increase ≥20, creatinine increase >25%, and hemoglobin decrease ≥1.5g/dL. PANGEA 2.0 outperforms established models including the 20/2/20 and IMWG models by more accurately predicting progression (C-statistics=0.69–0.84), even without biomarker history (C-statistics=0.69–0.83) or recent bone marrow biopsy. PANGEA 2.0 is an easy-to-use, open-access tool (https://ghobrial.shinyapps.io/pangea_2_calculator) to improve and individualize SMM risk stratification. Validation tools are available to compare PANGEA 2.0 to established models (https://ghobrial.shinyapps.io/pangea_validation).

Abstract BACKGROUND Leveraging external data has the potential to increase efficiency and precision of drug development in glioblastoma by complementing or replacing data from in-trial controls. We used an external control arm (ECA) to re-analyze data of the abemaciclib, neratinib and CC-115 arms of the Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) trial. METHODS INSIGhT (NCT02977780) is an ongoing phase 2 adaptive platform trial in newly diagnosed MGMT unmethylated glioblastoma with a shared control arm of patients receiving radiation therapy with concurrent and maintenance temozolomide. The initial experimental arms (abemaciclib, neratinib, CC-115) have not shown a survival benefit relative to the shared control arm. We re-analyzed the experimental arm data and replaced the shared control arm with an ECA. The ECA was developed from a collection of trial datasets and real-world data available through the Glioblastoma External (GBM-X) Data Platform (). Propensity score matching was used to adjust for possible differences between pretreatment covariates (age, sex, resection, KPS) in the ECA and shared control arm. Cox proportional hazards models were used to estimate treatment effects. RESULTS On INSIGhT, patients were randomized to abemaciclib (n = 74), neratinib (n = 80), and CC-115 (n = 12). There were 687 unmethylated MGMT patients in the GBM-X ECA. After propensity score matching, there was no significant treatment effect associated with abemaciclib (HR 1.091, 95%CI:0.834-1.433, p = 0.536), neratinib (HR = 1.043, 95%CI:0.787-1.383, p = 0.770), or CC-115 (HR 1.088, 95%CI:0.834-1.433, p = 0.794) compared to the ECA. CONCLUSION In comparison to an ECA, there was no significant survival benefit with abemaciclib, neratinib and CC-115. Treatment effects estimates were similar to the primary analyses based on the original shared control arm of INSIGhT. The use of external control arms in early phase testing of new therapies is supported by our findings and could significantly reduce costs and time to conduct trials in newly diagnosed glioblastoma.

Abstract INTRODUCTION NF2-related schwannomatosis (NF2-SWN) predisposes affected individuals to vestibular schwannomas (VS), non-vestibular schwannomas (NVS), meningiomas, and ependymomas. The rarity of NF2-SWN and the presence of multiple tumor types has impeded clinical trials. We conducted a multi-center, adaptive, platform-basket trial to screen multiple drugs against progressive NF2-SWN tumors. We report the final analysis of the first treatment arm with brigatinib, an oral ALK inhibitor that inhibits multiple tyrosine kinases. METHODS This study enrolled participants ≥ 12 years with NF2-SWN and progressive target tumors (baskets: VS, NVS, meningioma, or ependymoma Radiographic response (RR) was defined as ≥ 20% decrease in target tumor volume from baseline. The primary outcome was RR rate. Secondary outcomes included safety, hearing response, and RR in non-target tumors. Tumor response was evaluated by MRI every 3 months in year 1 and every 6 months thereafter. In stage 1, 20 participants received brigatinib 180 mg daily. Interim analysis suggested activity in NVS and meningioma. Thus, an additional 20 participants with progressive meningioma or NVS were enrolled in stage 2. RESULTS Forty participants (median age 26 years, 12 pediatric, 28 female) were treated. Prior treatment included surgery (90%), radiation therapy (20%) and chemotherapy (55%). Target tumors included 10 VS, 9 NVS, 19 meningiomas, and 2 ependymomas. Overall RR rate was 10% for all target tumors (22% for non-VS, 11% for meningioma, 0% for VS, and 0% for ependymomas). There were no grade 4 or 5 treatment-related adverse events (AEs). The most common AEs were diarrhea (63%), nausea (40%), muscle cramps (33%), increased LDH (35%), increased AST (33%), and increased ALT (23%). CONCLUSION Brigatinib treatment was associated with RR in NVS and meningiomas in a heavily pretreated cohort of participants with progressing NF2-SWN tumors. This novel design provides unique ability to assess treatments for hereditary syndromes with multiple primary tumors.

PURPOSE The Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) is a phase II platform trial that uses response adaptive randomization and genomic profiling to efficiently identify novel therapies for phase III testing. Three initial experimental arms (abemaciclib [a cyclin-dependent kinase [CDK]4/6 inhibitor], neratinib [an epidermal growth factor receptor [EGFR]/human epidermal growth factor receptor 2 inhibitor], and CC-115 [a deoxyribonucleic acid–dependent protein kinase/mammalian target of rapamycin inhibitor]) were simultaneously evaluated against a common control arm. We report the results for each arm and examine the feasibility and conduct of the adaptive platform design. PATIENTS AND METHODS Patients with newly diagnosed O 6 -methylguanine–DNA methyltransferase-unmethylated glioblastoma were eligible if they had tumor genotyping to identify prespecified biomarker subpopulations of dominant glioblastoma signaling pathways (EGFR, phosphatidylinositol 3-kinase, and CDK). Initial random assignment was 1:1:1:1 between control (radiation therapy and temozolomide) and the experimental arms. Subsequent Bayesian adaptive randomization was incorporated on the basis of biomarker-specific progression-free survival (PFS) data. The primary end point was overall survival (OS), and one-sided P values are reported. The trial is registered with ClinicalTrials.gov (identifier: NCT02977780 ). RESULTS Two hundred thirty-seven patients were treated (71 control; 73 abemaciclib; 81 neratinib; 12 CC-115) in years 2017-2021. Abemaciclib and neratinib were well tolerated, but CC-115 was associated with ≥ grade 3 treatment-related toxicity in 58% of patients. PFS was significantly longer with abemaciclib (hazard ratio [HR], 0.72; 95% CI, 0.49 to 1.06; one-sided P = .046) and neratinib (HR, 0.72; 95% CI, 0.50 to 1.02; one-sided P = .033) relative to the control arm but there was no PFS benefit with CC-115 (one-sided P = .523). None of the experimental therapies demonstrated a significant OS benefit ( P > .05). CONCLUSION The INSIGhT design enabled efficient simultaneous testing of three experimental agents using a shared control arm and adaptive randomization. Two investigational arms had superior PFS compared with the control arm, but none demonstrated an OS benefit. The INSIGhT design may promote improved and more efficient therapeutic discovery in glioblastoma. New arms have been added to the trial.

Abstract Neurofibromatosis type 2 (NF2) predisposes affected individuals to vestibular schwannomas (VS), non-vestibular schwannomas (NVS), meningiomas, and ependymomas. We developed an adaptive platform-basket trial to screen multiple drugs against any type of progressive NF2-related tumor. We report the interim analysis of the first treatment arm with brigatinib, an ALK inhibitor that inhibits multiple tyrosine kinases. We conducted a multicenter, phase II, open-label study for subjects ≥12 years old with NF2 and progressive target tumors (baskets: VS, NVS, meningioma, or ependymoma). Up to 5 non-target tumors were followed in each participant. In stage 1, 20 participants (minimum of 2 participants per basket) were treated with brigatinib 180 mg daily. Tumor response was evaluated by MRI every 3 months in year 1 and every 6 months thereafter. Radiographic response (RR) was defined as ≥20% decrease in target tumor volume from baseline. The primary outcome was RR rate. Per protocol, the brigatinib arm would be discontinued if no target tumor achieved a RR at interim analysis. Twenty subjects (median age=25 years, 7 pediatric, 12 females) were treated. Target tumors included 10 VS, 3 NVS, 5 meningiomas, and 2 ependymomas; non-target tumors included 18 VS, 36 NVS, and 14 meningiomas. RR rate for target and non-target tumors was 5% and 22%, respectively. By tumor basket, RR was 28% for meningioma, 26% for non-VS, 4% for VS, and 0% for ependymomas. Annualized tumor growth rates decreased for VS, NVS, and meningioma during treatment. Brigatinib was well tolerated with one dose reduction and one discontinuation due to grade 2 diarrhea. Brigatinib treatment was associated with RR in meningiomas, VS, and NVS. In stage 2, the study will enroll 20 participants in the two most promising baskets (meningioma and NVS). This novel design provides unique ability to assess treatments for hereditary syndromes with multiple primary tumors.

2012 Background: Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) trial is a phase II platform trial using response adaptive randomization and deep genomic profiling to more efficiently test experimental agents in MGMT unmethylated glioblastoma and potentially accelerate identification of novel therapies for phase III testing. We report on the feasibility and conduct of this approach. Methods: Tumor genotyping was performed prior to treatment assignment on eligible participants with newly diagnosed MGMT-unmethylated glioblastoma to identify biomarker signatures. Initial randomization was 1:1:1:1 between control (temozolomide) and 3 experimental arms (abemaciclib, CC-115, and neratinib). Subsequent randomization was adapted based on Bayesian estimation of biomarker-naïve and biomarker-specific probabilities of treatment impact on progression-free survival (PFS). Ineffective or toxic arms were discontinued by protocol amendment. The primary endpoint was overall survival (OS). Results: INSIGhT randomized 71 patients to the control arm, 73 patients to the abemaciclib arm, 12 patients to the CC-115 arm, and 81 patients to the neratinib arm between 2/9/2017 and 5/14/2021. Following the initial equal randomization period, early data were repeatedly analyzed during the study to capture early signals of treatment effects across the enrolled population or in specific biomarker subgroups. The results of these interim analyses influenced the randomization probability for future enrolled patients. In total, 77% of the participants were randomized before assessing their biomarker profile and 23% were biomarker randomized. The CC-115 arm opened and closed three times during the safety lead-in. The randomization probability to the CC-115 arm decreased based on poor early PFS results and the arm eventually closed after 12 patients due to toxicity. The randomization probability to the abemacicilb arm increased based on promising early PFS results. After the completion of accrual into the abemaciclib arm, the trial switched to block randomization to finish enrolling into the remaining neratinib and control arms. A total of 28 interim analyses and 32 randomization tables were created throughout the course of the trial with 4 adjustments (3 due to CC-115 closures and 1 due to completion of the abemaciclib arm). Biomarker association trends for neratinib and abemaciclib were similar to those seen in preclinical modeling of the trial. Conclusions: Relative to a standard randomization design, the adaptive platform design facilitated more efficient and economical testing of experimental arms by sharing a control arm, decreasing the probability of enrollment to potentially ineffective arms, and increasing the probability of enrollment to potentially effective arms. Additional future arms are planned on INSIGhT. Clinical trial information: NCT02977780.

Abstract Introduction: Multiple Myeloma (MM) is an incurable plasma cell malignancy commonly preceded by the asymptomatic stage smoldering multiple myeloma (SMM). MM is characterized with significant genomic heterogeneity of chromosomal gains and losses (CNVs), translocations, and point mutations (SNVs); alterations that are also observed in SMM patients. However, current SMM risk models rely solely on clinical markers and do not accurately capture progression risk. While incorporating some genomic biomarkers improves prediction, using all MM genomic features to comprehensively stratify patients may increase risk stratification precision in SMM. Methods: We obtained a total of 214 patient samples at SMM diagnosis. We performed whole-exome sequencing on 166 tumors; of these, RNA sequencing was performed on 100. Targeted capture was done on 48 additional tumors. Upon binarization of DNA features, we performed consensus non-negative matrix factorization to identify distinct molecular clusters. We then trained a random forest classifier on translocations, SNVs, and CNVs. The predicted clinical outcomes for the molecular subtypes were further validated in an independent SMM cohort of 74 patients. Results: We identified six genomic subtypes, four with hyperdiploidy (>48 chromosomes, HMC, HKR, HNT, HNF) and two with IgH translocations (FMD, CND) (Table 1). In multivariate analysis accounting for IMWG (20-2-20) clinical risk stages, high-risk (HMC, FMD, HKR) and intermediate-risk (HNT, HNF) genetic subtypes were independent predictors of progression (Hazards ratio [HR]: 3.8 and 5.5, P = 0.016 and 0.001, respectively). The low-risk, CND subtype harboring translocation (11;14) was enriched for the previously defined CD-2 MM signature defined by the B cell markers CD20 and CD79A (FDR = 0.003 ), showed upregulation of CCND1, E2F1, and E2F7 (FDR = 0.01, 0.0004, 0.08), and was enriched for G2M checkpoint, heme metabolism, and monocyte cell signature (FDR = 0.003, 0.003, 0.003, respectively). The FMD subtype with IgH translocations (4;14) and (14;16) was enriched for P53, mTORC1, unfolded protein signaling pathways and plasmacytoid dendritic cell signatures (FDR = 0.01, 0.005, 0.008, respectively). The HKR tumors were enriched for inflammatory cytokine signaling, MYC target genes, T regulatory cell signature, and the MM proliferative (PR) signatures (FDR = 0.02, 0.03, 0.007, 0.02, respectively). The APOBEC mutational signature was enriched in HMC and FMD tumors (P = 0.005), while there was no statistical difference across subtypes in the AID signature. The median follow-up for the primary cohort is 7.1 years. Median TTP for patients in HMC, FMD, and HKR was 3.8, 2.6, and 2.2 years, respectively; TTP for HNT and HNF was 4.3 and 5.2, respectively, while it was 11 years in CND patients (P = 0.007). Moreover, by analyzing the changes in MM clinical biomarkers over time, we found that patients from high-risk subgroups had higher odds of developing evolving hemoglobin and monoclonal protein levels over time (P = 0.01 and 0.002, respectively); Moreover, the absolute increase in M-protein was significantly higher in patients from the high-risk genetic subtypes at one, two, and five years from diagnosis (P = 0.001, 0.03, and 0,01, respectively). Applying the classifier to the external cohort replicated our findings where intermediate and high-risk genetic subgroups conferred increased risk of progression to MM in multivariate analysis after accounting for IMWG staging (HR: 5.5 and 9.8, P = 0.04 and 0.005, respectively). Interestingly, within the intermediate-risk clinical group in the primary cohort, patients in the high-risk genetic subgroups had increased risk of progression (HR: 5.2, 95% CI 1.5 - 17.3, P = 0.007). In the validation cohort, these patients also had an increased risk of progression to MM (HR: 6.7, 95% CI 1.2 - 38.3, P = 0.03), indicating that molecular classification improves the clinical risk-stratification models. Conclusion: We identified and validated in an independent dataset six SMM molecular subgroups with distinct DNA alterations, transcriptional profiles, dysregulated pathways, and risks of progression to active MM. Our results underscore the importance of molecular classification in addition to clinical evaluation in better identifying high-risk SMM patients. Moreover, these subgroups may be used to identify tumor vulnerabilities and target them with precision medicine efforts. Figure 1 Figure 1. Disclosures Bustoros: Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria. Casneuf: Janssen: Current Employment. Kastritis: Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Walker: Bristol Myers Squibb: Research Funding; Sanofi: Speakers Bureau. Davies: Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Dimopoulos: Amgen: Honoraria; BMS: Honoraria; Takeda: Honoraria; Beigene: Honoraria; Janssen: Honoraria. Bergsagel: Genetech: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; GSK: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Yong: BMS: Research Funding; Autolus: Research Funding; Takeda: Honoraria; Janssen: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; GSK: Honoraria; Amgen: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.