Metabolic response by FDG-PET to imatinib correlates with exon 11 KIT mutation and predicts outcome in patients with mucosal melanoma

Abstract Background In patients with metastatic melanoma and KIT amplifications and/or mutations, therapy with imatinib mesylate may prolong survival. 18F-labeled 2-fluoro-2-deoxy-D-glucose (18F-FDG) PET/CT may be used to assess metabolic response. We investigated associations of metabolic response, mutational status, progression-free survival and overall survival in this population. Methods Baseline and 4-week follow-up 18F-FDG-PET/CT were evaluated in 17 patients with metastatic melanoma and KIT amplifications and/or mutations treated with imatinib in a multicenter phase II clinical trial. The maximum standardized uptake values (SUVmax) were measured in up to 10 lesions on each scan. Metabolic response was classified using modified EORTC criteria. Each patient had a diagnostic CT or MR at baseline, after 6 weeks of therapy and then at intervals of 2 months and anatomic response was classified using RECIST 1.0. Median follow-up was 9.8 months. Results Partial metabolic response (PMR), stable metabolic disease (SMD) and progressive metabolic disease (PMD) was seen in 5 (29%), 5 (29%), and 7 (41%) patients respectively. Five patients (29%) had a KIT mutation in exon 11, four of whom (80%) had PMR while 1 (20%) had SMD. Twelve patients (71%) did not have a KIT mutation in exon 11, and only 1 (8%) had PMR, 4 (33%) had SMD and 7 (58%) had PMD. There was agreement of metabolic and anatomic classification in 12 of 17 patients (71%). Four of 17 patients (24%) had PR on both metabolic and anatomic imaging and all had a KIT mutation in exon 11. Survival of patients with PMD was lower than with SMD or PMR. Conclusions Metabolic response by 18F-FDG-PET/CT is associated with mutational status in metastatic melanoma patients treated with imatinib. 18F-FDG-PET/CT may be a predictor of outcome, although a larger study is needed to verify this. Clinical trial registration NCT0042451

Dabrafenib in patients with melanoma, untreated brain metastases, and other solid tumours: a phase 1 dose-escalation trial

BACKGROUND: Dabrafenib is an inhibitor of BRAF kinase that is selective for mutant BRAF. We aimed to assess its safety and tolerability and to establish a recommended phase 2 dose in patients with incurable solid tumours, especially those with melanoma and untreated, asymptomatic brain metastases. METHODS: We undertook a phase 1 trial between May 27, 2009, and March 20, 2012, at eight study centres in Australia and the USA. Eligible patients had incurable solid tumours, were 18 years or older, and had adequate organ function. BRAF mutations were mandatory for inclusion later in the study because of an absence of activity in patients with wild-type BRAF. We used an accelerated dose titration method, with the first dose cohort receiving 12 mg dabrafenib daily in a 21-day cycle. Once doses had been established, we expanded the cohorts to include up to 20 patients. On the basis of initial data, we chose a recommended phase 2 dose. Efficacy at the recommended phase 2 dose was studied in patients with BRAF-mutant tumours, including those with non-Val600Glu mutations, in three cohorts: metastatic melanoma, melanoma with untreated brain metastases, and non-melanoma solid tumours. This study is registered with ClinicalTrials.gov, number NCT00880321. FINDINGS: We enrolled 184 patients, of whom 156 had metastatic melanoma. The most common treatment-related adverse events of grade 2 or worse were cutaneous squamous-cell carcinoma (20 patients, 11%), fatigue (14, 8%), and pyrexia (11, 6%). Dose reductions were necessary in 13 (7%) patients. No deaths or discontinuations resulted from adverse events, and 140 (76%) patients had no treatment-related adverse events worse than grade 2. Doses were increased to 300 mg twice daily, with no maximum tolerated dose recorded. On the basis of safety, pharmacokinetic, and response data, we selected a recommended phase 2 dose of 150 mg twice daily. At the recommended phase 2 dose in 36 patients with Val600 BRAF-mutant melanoma, responses were reported in 25 (69%, 95% CI 51·9-83·7) and confirmed responses in 18 (50%, 32·9-67·1). 21 (78%, 57·7-91·4) of 27 patients with Val600Glu BRAF-mutant melanoma responded and 15 (56%, 35·3-74·5) had a confirmed response. In Val600 BRAF-mutant melanoma, responses were durable, with 17 patients (47%) on treatment for more than 6 months. Responses were recorded in patients with non-Val600Glu BRAF mutations. In patients with melanoma and untreated brain metastases, nine of ten patients had reductions in size of brain lesions. In 28 patients with BRAF-mutant non-melanoma solid tumours, apparent antitumour activity was noted in a gastrointestinal stromal tumour, papillary thyroid cancers, non-small-cell lung cancer, ovarian cancer, and colorectal cancer. INTERPRETATION: Dabrafenib is safe in patients with solid tumours, and an active inhibitor of Val600-mutant BRAF with responses noted in patients with melanoma, brain metastases, and other solid tumours. FUNDING: GlaxoSmithKline

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies

ABSTRACTBiologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration–time curve (AUC0–672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL

Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma

Gastroesophageal adenocarcinoma (GEA) is a lethal disease where targeted therapies, even when guided by genomic biomarkers, have had limited efficacy. A potential rea-son for the failure of such therapies is that genomic profiling results could commonly differ between the primary and metastatic tumors. To evaluate genomic heterogeneity, we sequenced paired primary GEA and synchronous metastatic lesions across multiple cohorts, finding extensive differences in genomic alterations, including discrepancies in potentially clinically relevant alterations. Multiregion sequencing showed significant discrepancy within the primary tumor (PT) and between the PT and disseminated disease, with oncogene amplification profiles commonly discordant. In addition, a pilot analysis of cell-free DNA (cfDNA) sequencing demonstrated the feasibility of detecting genomic amplifications not detected in PT sampling. Lastly, we profiled paired primary tumors, metastatic tumors, and cfDNA from patients enrolled in the personalized antibodies for GEA (PANGEA) trial of targeted therapies in GEA and found that genomic biomarkers were recurrently discrepant between the PT and untreated metastases. Divergent primary and metastatic tissue profiling led to treatment reassignment in 32% (9/28) of patients. In discordant primary and metastatic lesions, we found 87.5% concordance for targetable alterations in metastatic tissue and cfDNA, suggesting the potential for cfDNA profiling to enhance selection of therapy. SIGNIFICANCE: We demonstrate frequent baseline heterogeneity in targetable genomic alterations in GEA, indicating that current tissue sampling practices for biomarker testing do not effectively guide precision medicine in this disease and that routine profiling of metastatic lesions and/or cfDNA should be systematically evaluated

Genomic heterogeneity as a barrier to precision medicine in gastroesophageal adenocarcinoma

Gastroesophageal adenocarcinoma (GEA) is a lethal disease where targeted therapies, even when guided by genomic biomarkers, have had limited efficacy. A potential rea-son for the failure of such therapies is that genomic profiling results could commonly differ between the primary and metastatic tumors. To evaluate genomic heterogeneity, we sequenced paired primary GEA and synchronous metastatic lesions across multiple cohorts, finding extensive differences in genomic alterations, including discrepancies in potentially clinically relevant alterations. Multiregion sequencing showed significant discrepancy within the primary tumor (PT) and between the PT and disseminated disease, with oncogene amplification profiles commonly discordant. In addition, a pilot analysis of cell-free DNA (cfDNA) sequencing demonstrated the feasibility of detecting genomic amplifications not detected in PT sampling. Lastly, we profiled paired primary tumors, metastatic tumors, and cfDNA from patients enrolled in the personalized antibodies for GEA (PANGEA) trial of targeted therapies in GEA and found that genomic biomarkers were recurrently discrepant between the PT and untreated metastases. Divergent primary and metastatic tissue profiling led to treatment reassignment in 32% (9/28) of patients. In discordant primary and metastatic lesions, we found 87.5% concordance for targetable alterations in metastatic tissue and cfDNA, suggesting the potential for cfDNA profiling to enhance selection of therapy. SIGNIFICANCE: We demonstrate frequent baseline heterogeneity in targetable genomic alterations in GEA, indicating that current tissue sampling practices for biomarker testing do not effectively guide precision medicine in this disease and that routine profiling of metastatic lesions and/or cfDNA should be systematically evaluated