Alexander, Brian M

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.

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.