Purpose Galunisertib, a TGF-β inhibitor, has demonstrated antitumor effects in preclinical and radiographic responses in some patients with malignant glioma. This Phase 1b/2a trial investigated the clinical benefit of combining galunisertib with temozolomide-based radiochemotherapy (TMZ/RTX) in patients with newly diagnosed malignant glioma (NCT01220271). Methods This is an open-label, 2-arm Phase 1b/2a study (N = 56) of galunisertib (intermittent dosing: 14 days on/14 days off per cycle of 28 days) in combination with TMZ/RTX (n = 40), versus a control arm (TMZ/RTX, n = 16). The primary objective of Phase 1b was to determine the safe and tolerable Phase 2 dose of galunisertib. The primary objective of Phase 2a was to confirm the tolerability and pharmacodynamic profile of galunisertib with TMZ/RTX, and the secondary objectives included determining the efficacy and pharmacokinetic (PK) profile of galunisertib with TMZ/RTX in patients with glioblastoma. This study also characterized the changes in the major T-cell subsets during TMZ/RTX plus galunisertib treatment. Results In the Phase 2a study, efficacy results for patients treated with galunisertib plus TMZ/RTX or TMZ/RTX were: median overall survival (18.2 vs 17.9 months), median progression-free survival (7.6 vs 11.5 months), and disease control rate (80% [32/40] vs 56% [9/16] patients) respectively. PK profile of galunisertib plus TMZ/RTX regimen was consistent with previously published PK data of galunisertib. The overall safety profile across treatment arms was comparable. Conclusion No differences in efficacy, safety or pharmacokinetic variables were observed between the two treatment arms.

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Background Transforming growth factor beta (TGF-β) signalling is involved in the development of hepatocellular carcinoma (HCC). We followed changes in biomarkers during treatment of patients with HCC with the TGF-βRI/ALK5 inhibitor galunisertib. Methods This phase 2 study (NCT01246986) enrolled second-line patients with advanced HCC into one of two cohorts of baseline serum alpha-fetoprotein (AFP): Part A (AFP �1.5x ULN) or Part B (AFP <1.5x ULN). Baseline and postbaseline levels of AFP, TGF-β1, E-cadherin, selected miRNAs, and other plasma proteins were monitored.

Identification of subgroups with differential treatment effects in randomized trials is attracting much attention. Many methods use regression tree algorithms. This article addresses 2 important questions arising from the subgroups: how to ensure that treatment effects in subgroups are not confounded with effects of prognostic variables and how to determine the statistical significance of treatment effects in the subgroups. We address the first question by selectively including linear prognostic effects in the subgroups in a regression tree model. The second question is more difficult because it falls within the subject of postselection inference. We use a bootstrap technique to calibrate normal-theory t intervals so that their expected coverage probability, averaged over all the subgroups in a fitted model, approximates the desired confidence level. It can also provide simultaneous confidence intervals for all subgroups. The first solution is implemented in the GUIDE algorithm and is applicable to data with missing covariate values, 2 or more treatment arms, and outcomes subject to right censoring. Bootstrap calibration is applicable to any subgroup identification method; it is not restricted to regression tree models. Two real examples are used for illustration: a diabetes trial where the outcomes are completely observed but some covariate values are missing and a breast cancer trial where the outcome is right censored.

Background The transforming growth factor β (TGF-β)–signaling pathway has emerged as a promising therapeutic target for many disease states including hepatocellular carcinoma (HCC). Because of the pleiotropic effects of this pathway, patient selection and monitoring may be important. TGF-β1 is the most prevalent isoform, and an assay to measure plasma levels of TGF-β1 would provide a rational biomarker to assist with patient selection. Therefore, the objective of this study was to analytically validate a colorimetric ELISA for the quantification of TGF-β1 in human plasma. Methods A colorimetric sandwich ELISA for TGF-β1 was analytically validated per Clinical and Laboratory Standards Institute protocols by assessment of precision, linearity, interfering substances, and stability. A reference range for plasma TGF-β1 was established for apparently healthy individuals and potential applicability was demonstrated in HCC patients. Results Precision was assessed for samples ranging from 633 to 10822 pg/mL, with total variance ranging from 28.4% to 7.2%. The assay was linear across the entire measuring range, and no interference of common blood components or similar molecules was observed. For apparently healthy individuals, the average TGF-β1 level was 1985 ± 1488 pg/mL compared to 4243 ± 2003 pg/mL for HCC patients. Additionally, the TGF-β1 level in plasma samples was demonstrated to be stable across all conditions tested, including multiple freeze–thaw cycles. Conclusions The ELISA described in this report is suitable for the quantification of TGF-β1 in human plasma and for investigational use in an approved clinical study.