Purpose: We assessed the safety, maximum tolerated dose, and recommended phase 2 dose (RP2D), efficacy, pharmacokinetics, and pharmacodynamics of the nilotinib–paclitaxel combination in 44 patients with solid tumors. Patients and Methods: Paclitaxel was administered intravenously (days 1, 8, and 15), and nilotinib was administered twice daily orally beginning on cycle 1 day 2 (C1D2; escalation) or C1D3 (expansion) in 28-day cycles using a 3 + 3 dose escalation design. Pharmacodynamic biomarkers of drug action were assessed in paired tumor biopsies and circulating tumor cells at the RP2D. Results: The RP2D was 300 mg nilotinib twice daily with 80 mg/m2 paclitaxel. Grade 4 (Gr4) neutropenia and Gr3 rash, photosensitivity, and transaminase elevation were dose-limiting. The most common Gr3-4 toxicities were hematologic and hypophosphatemia; one patient (2%) experienced Gr3 peripheral neuropathy. Three patients [two with adult ovarian granulosa cell tumors (AOGCT) and one with endometrial carcinoma] had confirmed partial responses (cPR); the patients with AOGCT remained on study for 5 and 6+ years, and mesenchymal-like circulating tumor cells were measured prior to progression or during treatment holiday (patients 12 and 10, respectively). Conclusions: This study determined the maximum tolerated dose of this combination, demonstrated sustained cPRs in patients with AOGCT, and profiled molecular pharmacodynamic responses that will inform further mechanism-of-action studies. The rate of peripheral neuropathy suggests enhanced tolerability of this combination.

Proteomic data provide a direct readout of protein function, thus constituting an information-rich resource for prognostic and predictive modeling. However, protein array data may not fully capture pathway activity due to the limited number of molecules and incomplete pathway coverage compared to other high-throughput technologies. For the present study, our aim was to improve clinical outcome prediction compared to published pathway-dependent prognostic signatures for The Cancer Genome Atlas (TCGA) cohorts using the least absolute shrinkage and selection operator (LASSO). RPPA data is particularly well-suited to the LASSO due to the relatively low number of predictors compared to larger genomic data matrices. Our approach selected predictors regardless of their pathway membership and optimally combined their RPPA measurements into a weighted risk score. Performance was assessed and compared to that of the published signatures using two unbiased approaches: 1) 10 iterations of threefold cross-validation for unbiased estimation of hazard ratio and difference in 5-year survival (by Kaplan–Meier method) between predictor-defined high and low risk groups; and 2) a permutation test to evaluate the statistical significance of the cross-validated log-rank statistic. Here, we demonstrate strong stratification of 445 renal clear cell carcinoma tumors from The Cancer Genome Atlas (TCGA) into high and low risk groups using LASSO regression on RPPA data. Median cross-validated difference in 5-year overall survival was 32.8%, compared to 25.2% using a published receptor tyrosine kinase (RTK) prognostic signature (median hazard ratios of 3.3 and 2.4, respectively). Applicability and performance of our approach was demonstrated in three additional TCGA cohorts: ovarian serous cystadenocarcinoma (OVCA), sarcoma (SARC), and cutaneous melanoma (SKCM). The data-driven LASSO-based approach is versatile and well-suited for discovery of new protein/disease associations.

This file contains Supplementary Figure S1 (Correlation between downregulation of EGFR transcriptional target genes, and sensitivity to erlotinib at the high concentration after 6 hours); Supplementary Figure S2 (EGFR inhibitor and DNA damaging agents induce directionally opposing changes in EGR1 expression that are differentially associated with drug sensitivity); Supplementary Figure S3 (Representative 3D response surface plots for the gemcitabine-erlotinib combination in the indicated cell lines); Supplementary Figure S4 (Representative 3D response surface plots for the vorinostat-talazoparib combination in the indicated cell lines); Supplementary Table S1 (Validation of array-based measurements by qRT-PCR); Supplementary Table S2 (Genes with concerted changes in the same direction [upregulation or downregulation] 24 hours after treatment with each of the 15 drugs); and Supplementary Table S4 (Selected genes potentially mediating drug insensitivity to agents in the NCI TPW dataset).

Longitudinal tumor measurements in patients with cPR

Pharmacodynamic effect on tumor epithelial/mesenchymal phenotype

Representativeness of Study Participants