Alexander, Brian M.

Abstract GBM AGILE(NCT03970447) is a phase 2/3 Bayesian adaptive registration platform trial testing multiple therapies against a common control. Paxalisib, a PI3K/mTOR inhibitor, is the 3rd arm in the trial to conclude evaluation. METHODS Paxalisib was open to patients with newly diagnosed unmethylated (NDU) and recurrent (RD) glioblastoma, with three possible signatures: NDU, RD, and All(NDU+RD). Arm enrollment occurred Dec2020 through May2022. Control patients were enrolled from study initiation (July2019) and were treated with temozolomide(NDU) or lomustine(RD). GBM AGILE investigational arms have 1 or 2 stages, with adaptive randomization in stage 1 and fixed randomization if arms continue to stage 2. Efficacy is based on OS hazard ratio(HR) of Arm/Control. Efficacy goal is final Bayesian probability ≥ 98% for HR<1.00 in combined Stages. An Arm continues to Stage 2 if Bayesian predictive power (PP) ≥ 0.8. An Arm stops accruing in Stage 1 if it reaches maximal sample size(N) or does not meet a minimum efficacy threshold (PP<0.25 for all signatures when N>50). Clinical cut-off is 12 months after accrual stops. The maximum N for paxalisib was approximately 150(Stage 1) and 50(Stage 2). RESULTS After paxalisib reached >150 patients in Stage 1, accrual stopped [Paxalisib/control N 54/75(NDU), 100/188(RD)]. Neither PP thresholds for moving to Stage 2 nor stopping for minimum efficacy were met. Following an unplanned public disclosure that the arm did not continue to stage 2, clinical cut-off for final analysis (planned May2023) was updated to public disclosure date (August2022). At final analysis mean HRs were 0.89(NDU), 1.25(RD), 1.05(All), probabilities of HR<1.00 of 0.72(NDU), 0.076(RD), 0.398(All). Model estimated median OS paxalisib/control (months) were 14.77/13.84(NDU) and 8.58/10.06(RD). CONCLUSION Paxalisib did not show survival benefit over cumulative control in final primary analysis; additional secondary analyses are being considered. GBM AGILE continues to rapidly and efficiently assess therapies in ND and RD glioblastoma.

AbstractMeningeal solitary fibrous tumors (SFT) are rare and have a high frequency of local recurrence and distant metastasis. In a cohort of 126 patients (57 female, 69 male; mean age at surgery 53.0 years) with pathologically confirmed meningeal SFTs with extended clinical follow‐up (median 9.9 years; range 15 days–43 years), we performed extensive molecular characterization including genome‐wide DNA methylation profiling (n = 80) and targeted TERT promoter mutation testing (n = 98). Associations were examined with NAB2::STAT6 fusion status (n = 101 cases; 51 = ex5‐7::ex16‐17, 26 = ex4::ex2‐3; 12 = ex2‐3::exANY/other and 12 = no fusion) and placed in the context of 2021 Central Nervous System (CNS) WHO grade. NAB2::STAT6 fusion breakpoints (fusion type) were significantly associated with metastasis‐free survival (MFS) (p = 0.03) and, on multivariate analysis, disease‐specific survival (DSS) when adjusting for CNS WHO grade (p = 0.03). DNA methylation profiling revealed three distinct clusters: Cluster 1 (n = 38), Cluster 2 (n = 22), and Cluster 3 (n = 20). Methylation clusters were significantly associated with fusion type (p < 0.001), with Cluster 2 harboring ex4::ex2‐3 fusion in 16 (of 20; 80.0%), nearly all TERT promoter mutations (7 of 8; 87.5%), and predominantly an “SFT” histologic phenotype (15 of 22; 68.2%). Clusters 1 and 3 were less distinct, both dominated by tumors having ex5‐7::ex16‐17 fusion (respectively, 25 of 33; 75.8%, and 12 of 18; 66.7%) and with variable histological phenotypes. Methylation clusters were significantly associated with MFS (p = 0.027), but not overall survival (OS). In summary, NAB2::STAT6 fusion type was significantly associated with MFS and DSS, suggesting that tumors with an ex5::ex16‐17 fusion may have inferior patient outcomes. Methylation clusters were significantly associated with fusion type, TERT promoter mutation status, histologic phenotype, and MFS.

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.

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 Meningeal solitary fibrous tumor (SFT) is a rare tumor with high propensity to recur and metastasize, even late in the course of disease. The WHO 2021 classification of CNS tumors divides SFT in 3 grades, based on mitotic index and necrosis. We re-examined our cohort of 126 patients (57 F, 69 M; mean age 53.0 years) with SFT, confirmed by STAT6 nuclear positivity and/or NAB2::STAT6 fusion, with extended follow-up (median 7.6 years; range 4 days-26.6 years). Tumors included 76 grade 1, 36 grade 2 and 14 grade 3 according to 2021 WHO criteria, evaluated at primary resection (n=90), recurrence (n=35), or metastasis (n=1). Fifty-six patients had one or more post-surgical events, the earliest event being local recurrence (n=41) or metastasis (n=15). Forty patients died (29 of disease; 9 of other causes; 2 unknown). Overall survival (OS), and progression-free survival (PFS, recurrence and/or metastasis) from time of primary resection (n=90) were not significantly associated with grade; however, risk of metastasis differed significantly (5-year estimates: 4.1%, 15.3%, and 37.8% for grades 1, 2, and 3 SFT, respectively; p=0.005). NAB2::STAT6 fusion status was known in 101 cases (51 = ex5-7-ex16-17, 26 = ex4_ex2-3; 12 = ex2-3_exANY/other and 12 =no fusion). Disease specific 5-year survival in primary tumors with molecular data (n = 75) was 80.0% in patients whose tumors harbored ex5-7_ex16-17 compared to 93.3% in all others combined (p=0.014). Targeted TERT promoter mutation testing was performed in 98 patients, revealing patients with tumors lacking TERT promoter mutation (n = 88) were younger at time of surgery than those harboring a mutation (n=10; p = 0.022), and none with a mutation harboring concurrent ex5-7_ex16-17 fusion (p = 0.0009). In summary, WHO 2021 grade is associated with risk of metastasis. Patients whose tumors harbor ex5-7_ex16-17 fusion have a higher risk of dying from the disease.

AbstractBackgroundKnown risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.MethodsSingle nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer–related cell types.ResultsWe identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P &lt; .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P &lt; .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.ConclusionsCNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

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 BACKGROUND The Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) is a phase II platform trial with Bayesian adaptive randomization and deep genomic profiling to more efficiently test experimental agents in newly diagnosed glioblastoma and to prioritize therapies for late-stage testing. METHODS In the ongoing INSIGhT trial, patients with newly diagnosed MGMT-unmethylated glioblastoma are randomized to the control arm or one of three experimental therapy arms (CC-115, abemaciclib, and neratinib). The control arm therapy is radiotherapy with concomitant and adjuvant temozolomide, and primary endpoint is overall survival. Randomization has been adapted based on Bayesian estimation of biomarker-specific probability of treatment impact on progression-free survival (PFS). All tumors undergo detailed molecular sequencing, and this is facilitated with the companion ALLELE protocol. To evaluate feasibility of this approach, we assessed the status of this ongoing trial. RESULTS Since INSIGhT was activated 4.3 years ago, it has expanded to include 12 sites across the United States. A total of 247 patients have been enrolled. Randomization probabilities have been repeatedly adjusted over time based upon early PFS results to alter the randomization ratio from standard 1:1:1:1 randomization. All three arms have completed accrual and efficacy estimates are available based upon comparison to the common control arm in context of relevant biomarkers. There are 87 patients alive and in follow-up, and there are ongoing plans to add additional arms to evaluate further treatments in the future. CONCLUSION The INSIGhT trial demonstrates that a multi-center Bayesian adaptive platform trial is a feasible and effective approach to help prioritize therapies and biomarkers for newly diagnosed GBM. The trial has maintained robust accrual, and the simultaneous testing of multiple agents, sharing a common control arm and adaptive randomization serve as features to increase trial efficiency relative to traditional clinical trial designs.

Abstract BACKGROUND EGFR is amplified in over 50% of glioblastoma and 20-30% have EGFRvIII mutations. Neratinib is a potent inhibitor of EGFR/HER2 approved for metastatic HER2+ breast cancer. To efficiently evaluate the potential impact of neratinib on overall survival (OS) in newly-diagnosed glioblastoma and to simultaneously develop information regarding potential genomic biomarker associations, neratinib was included as an arm on the Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) trial. INSIGhT 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 accelerate identification of novel therapies for phase III testing. Initial randomization was equal between neratinib, control, and two other experimental arms but subsequent randomization was adapted based on efficacy as determined by progression-free survival (PFS). We report preliminary results for the neratinib arm. METHODS Patients with newly diagnosed MGMT-unmethylated glioblastoma were randomized to receive either radiotherapy with concomitant and adjuvant temozolomide or standard radiochemotherapy followed by adjuvant neratinib (240 mg daily). Treatment continued until progression or development of unacceptable toxicities. The primary endpoint was OS. Association between neratinib efficacy and EGFR amplification was also investigated. RESULTS There were 144 patients (70 control; 74 neratinib). Neratinib was reasonably well-tolerated with no new toxicity signals identified. PFS was compared (HR 0.84; p=0.38, logrank test – not significant) between the neratinib (median 6.05 months) and control (median 5.82 months) arms. For patients EGFR pathway activation the PFS HR was 0.53 (p-value=0.03 – significant, median PFS: neratinib, 6.21 months, control, 5.26 months). However, there was no significant improvement in OS in EGFR amplified/mutated patients (HR 1.05; p-value 0.87) between neratinib (median 14.2) compared to the control arm (median 14.6). CONCLUSION Neratinib prolonged PFS in the EGFR positive subpopulation but there was no overall PFS benefit, or any OS improvement.

PURPOSE Combined hepatocellular cholangiocarcinoma (cHCC-CCA) is a rare, aggressive primary liver carcinoma, with morphologic features of both hepatocellular carcinomas (HCC) and liver cholangiocarcinomas (CCA). METHODS The genomic profiles of 4,975 CCA, 1,470 HCC, and 73 cHCC-CCA cases arising from comprehensive genomic profiling in the course of clinical care were reviewed for genomic alterations (GA), tumor mutational burden, microsatellite instability status, genomic loss of heterozygosity, chromosomal aneuploidy, genomic ancestry, and hepatitis B virus status. RESULTS In cHCC-CCA, GA were most common in TP53 (65.8%), TERT (49.3%), and PTEN (9.6%), and 24.6% cHCC-CCA harbored potentially targetable GA. Other GA were predominantly associated with either HCC or CCA, including, but not limited to, TERT, FGFR2, IDH1, and presence of hepatitis B virus. On the basis of these features, a machine learning (ML) model was trained to classify a cHCC-CCA case as CCA-like or HCC-like. Of cHCC-CCA cases, 16% (12/73) were ML-classified as CCA-like and 58% (42/73) cHCC-CCA were ML-classified as HCC-like. The ML model classified more than 70% of cHCC-CCA as CCA-like or HCC-like on the basis of genomic profiles, without additional clinico-pathologic input. CONCLUSION These findings demonstrate the use of ML for classification as based on a targeted exome panel used during routine clinical care. Classification of cHCC-CCA by genomic features alone creates insights into the biology of the disease and warrants further investigation for relevance to clinical care.