Early Assessment of Chemotherapy Response in Advanced Non-Small Cell Lung Cancer with Circulating Tumor DNA.

Monitoring treatment efficacy early during therapy could enable a change in treatment to improve patient outcomes. We report an early assessment of response to treatment in advanced NSCLC using a plasma-only strategy to measure changes in ctDNA levels after one cycle of chemotherapy. Plasma samples were collected from 92 patients with Stage IIIB-IV NSCLC treated with first-line chemo- or chemoradiation therapies in an observational, prospective study. Retrospective ctDNA analysis was performed using next-generation sequencing with a targeted 198-kb panel designed for lung cancer surveillance and monitoring. We assessed whether changes in ctDNA levels after one or two cycles of treatment were associated with clinical outcomes. Subjects with ≤50% decrease in ctDNA level after one cycle of chemotherapy had a lower 6-month progression-free survival rate (33% vs. 58%, HR 2.3, 95% CI 1.2 to 4.2, log-rank p = 0.009) and a lower 12-month overall survival rate (25% vs. 70%, HR 4.3, 95% CI 2.2 to 9.7, log-rank p < 0.001). Subjects with ≤50% decrease in ctDNA level after two cycles of chemotherapy also had shorter survival. Using non-invasive liquid biopsies to measure early changes in ctDNA levels in response to chemotherapy may help identify non-responders before standard-of-care imaging in advanced NSCLC.

Plasma-based longitudinal mutation monitoring as a potential predictor of disease progression in subjects with adenocarcinoma in advanced non-small cell lung cancer.

BACKGROUND: Identifying and tracking somatic mutations in cell-free DNA (cfDNA) by next-generation sequencing (NGS) has the potential to transform the clinical management of subjects with advanced non-small cell lung cancer (NSCLC). METHODS: Baseline tumor tissue (n = 47) and longitudinal plasma (n = 445) were collected from 71 NSCLC subjects treated with chemotherapy. cfDNA was enriched using a targeted-capture NGS kit containing 197 genes. Clinical responses to treatment were determined using RECIST v1.1 and correlations between changes in plasma somatic variant allele frequencies and disease progression were assessed. RESULTS: Somatic variants were detected in 89.4% (42/47) of tissue and 91.5% (407/445) of plasma samples. The most commonly mutated genes in tissue were TP53 (42.6%), KRAS (25.5%), and KEAP1 (19.1%). In some subjects, the allele frequencies of mutations detected in plasma increased 3-5 months prior to disease progression. In other cases, the allele frequencies of detected mutations declined or decreased to undetectable levels, indicating clinical response. Subjects with circulating tumor DNA (ctDNA) levels above background had significantly shorter progression-free survival (median: 5.6 vs 8.9 months, respectively; log-rank p = 0.0183). CONCLUSION: Longitudinal monitoring of mutational changes in plasma has the potential to predict disease progression early. The presence of ctDNA mutations during first-line treatment is a risk factor for earlier disease progression in advanced NSCLC.

Disease Monitoring Using Post-induction Circulating Tumor DNA Analysis Following First-Line Therapy in Patients with Metastatic Colorectal Cancer.

PURPOSE: We assessed plasma circulating tumor DNA (ctDNA) level as a prognostic marker for progression-free survival (PFS) following first-line metastatic colorectal cancer (mCRC) therapy. EXPERIMENTAL DESIGN: The Sequencing Triplet With Avastin and Maintenance (STEAM) was a randomized, phase II trial investigating efficacy of bevacizumab (BEV) plus 5-fluorouracil/leucovorin/oxaliplatin (FOLFOX) and 5-fluorouracil/leucovorin/irinotecan (FOLFIRI), administered concurrently or sequentially, versus FOLFOX-BEV in first-line mCRC. Evaluation of biomarkers associated with treatment outcomes was an exploratory endpoint. Patients in the biomarker-evaluable population (BEP) had 1 tissue sample, 1 pre-induction plasma sample, and 1 post-induction plasma sample collected ≤60 days of induction from last drug date. RESULTS: Among the 280 patients enrolled in STEAM, 183 had sequenced and evaluable tumor tissue, 118 had matched pre-induction plasma, and 54 (BEP) had ctDNA-evaluable sequencing data for pre- and post-induction plasma. The most common somatic variants in tumor tissue and pre-induction plasma were TP53, APC, and KRAS. Patients with lower-than-median versus higher-than-median post-induction mean allele fraction (mAF) levels had longer median PFS (17.7 vs. 7.5 months, HR, 0.33; 95% confidence interval, 0.17-0.63). Higher levels of post-induction mAF and post-induction mean mutant molecules per milliliter (mMMPM), and changes in ctDNA (stratified by a 10-fold or 100-fold reduction in mAF between pre- and post-induction plasma), were associated with shorter PFS. Post-induction mAF and mMMPM generally correlated with each other (ρ = 0.987, P < 0.0001). CONCLUSIONS: ctDNA quantification in post-induction plasma may serve as a prognostic biomarker for mCRC post-treatment outcomes.

Concordance of Genomic Alterations by Next-Generation Sequencing in Tumor Tissue versus Cell-Free DNA in Stage I-IV Non-Small Cell Lung Cancer.

Molecular biomarkers hold promise for personalization of cancer treatment. However, a typical tumor biopsy may be difficult to acquire and may not capture genetic variations within or across tumors. Given these limitations, tumor genotyping using next-generation sequencing of plasma-derived circulating tumor (ct)-DNA has the potential to transform non-small cell lung cancer (NSCLC) management. Importantly, mutations detected in biopsied tissue must also be detected in plasma-derived ctDNA at different disease stages. Using the AVENIO ctDNA Surveillance kit (research use only), mutations in ctDNA from NSCLC subjects were compared with those identified in matched tumor tissue samples, retrospectively. Plasma and tissue samples were collected from 141 treatment-naïve NSCLC subjects (stage I, n = 48; stage II, n = 37; stage III, n = 33; stage IV, n = 23). In plasma samples, the median numbers of variants per subject were 4, 6, 8, and 9 in those with stage I, II, III, and IV disease, respectively. The corresponding values in tissue samples were 5, 5, 6, and 4. The overall tissue-plasma concordance of stage II through IV was 62.2% by AVENIO software call. On multivariate analysis, concordance was positively and significantly associated with tumor size and cancer stage. Next-generation sequencing-based analyses with the AVENIO ctDNA Surveillance kit could be an alternative approach to detecting genetic variations in plasma-derived ctDNA isolated from NSCLC subjects.

Population pharmacokinetics and dosing implications for cobimetinib in patients with solid tumors.

PURPOSE: To characterize cobimetinib pharmacokinetics and evaluate impact of clinically relevant covariates on cobimetinib pharmacokinetics. METHODS: Plasma samples (N = 4886) were collected from 487 patients with various solid tumors (mainly melanoma) in three clinical studies (MEK4592g, NO25395, GO28141). Cobimetinib was administered orally, once daily on either a 21-day-on/7-day-off, 14-day-on/14-day-off or 28-day-on schedule in a 28-day dosing cycle as single agent or in combination with vemurafenib. Cobimetinib doses ranged from 2.1 to 125 mg. NONMEM was used for pharmacokinetic analysis. RESULTS: A linear two-compartment model with first-order absorption, lag time and first-order elimination described cobimetinib pharmacokinetics. The typical estimates (inter-individual variability) of apparent clearance (CL/F), central volume of distribution (V2/F) and terminal half-life were 322 L/day (58 %), 511 L (49 %) and 2.2 days, respectively. Inter-occasion variability on relative bioavailability was estimated at 46 %. CL/F decreased with age. V2/F increased with body weight (BWT). However, the impact of age and BWT on cobimetinib steady-state exposure (peak and trough concentrations and AUC following the recommended daily dose of 60 mg 21-day-on/7-day-off) was limited (<25 % changes across the distribution of age and BWT). No significant difference in cobimetinib pharmacokinetics or steady-state exposure was observed between patient subgroups based on sex, renal function, ECOG score, hepatic function tests, race, region, cancer type, and co-administration of moderate and weak CYP3A inducers or inhibitors and vemurafenib. CONCLUSION: A population pharmacokinetic model was developed for cobimetinib in cancer patients. Covariates had minimal impact on steady-state exposure, suggesting no need for dose adjustments and supporting the recommended dose for all patients.