MET Fusions in NSCLC: Clinicopathologic Features and Response to MET Inhibition.

INTRODUCTION: MET fusions have been described only rarely in NSCLC. Thus, data on patient characteristics and treatment response are limited. We here report histopathologic data, patient demographics, and treatment outcome including response to MET tyrosine kinase inhibitor (TKI) therapy in MET fusion-positive NSCLC. METHODS: Patients with NSCLC and MET fusions were identified mostly by RNA sequencing within the routine molecular screening program of the national Network Genomic Medicine, Germany. RESULTS: We describe a cohort of nine patients harboring MET fusions. Among these nine patients, two patients had been reported earlier. The overall frequency was 0.29% (95% confidence interval: 0.15-0.55). The tumors were exclusively adenocarcinoma. The cohort was heterogeneous in terms of age, sex, or smoking status. We saw five different fusion partner genes (KIF5B, TRIM4, ST7, PRKAR2B, and CAPZA2) and several different breakpoints. Four patients were treated with a MET TKI leading to two partial responses, one stable disease, and one progressive disease. One patient had a BRAF V600E mutation as acquired resistance mechanism. CONCLUSIONS: MET fusions are very rare oncogenic driver events in NSCLC and predominantly seem in adenocarcinomas. They are heterogeneous in terms of fusion partners and breakpoints. Patients with MET fusion can benefit from MET TKI therapy.

Effects of Whole-Body Vibration and Manually Assisted Locomotor Therapy on Neurotrophin-3 Expression and Microglia/Macrophage Mobilization Following Thoracic Spinal Cord Injury in Rats.

Microglial cells play an important role in neuroinflammation and secondary damages after spinal cord injury (SCI). Progressive microglia/macrophage inflammation along the entire spinal axis follows SCI, and various factors may determine the microglial activation profile. Neurotrophin-3 (NT-3) is known to control the survival of neurons, the function of synapses, and the release of neurotransmitters, while also stimulating axon plasticity and growth. We examined the effects of whole-body vibration (WBV) and forms of assisted locomotor therapy, such as passive flexion-extension (PFE) therapy, at the neuronal level after SCI, with a focus on changes in NT-3 expression and on microglia/macrophage reaction, as they play a major role in the reconstitution of CNS integrity after injury and they may critically account for the observed structural and functional benefits of physical therapy. More specifically, the WBV therapy resulted in the best overall functional recovery when initiated at day 14, while inducing a decrease in Iba1 and the highest increase in NT-3. Therefore, the WBV therapy at the 14th day appeared to be superior to the PFE therapy in terms of recovery. Functional deficits and subsequent rehabilitation depend heavily upon the inflammatory processes occurring caudally to the injury site; thus, we propose that increased expression of NT-3, especially in the dorsal horn, could potentially be the mediator of this favorable outcome.

Resistance to MET inhibition in MET-dependent NSCLC and therapeutic activity after switching from type I to type II MET inhibitors.

OBJECTIVES: Resistance to MET inhibition occurs inevitably in MET-dependent non-small cell lung cancer and the underlying mechanisms are insufficiently understood. We describe resistance mechanisms in patients with MET exon 14 skipping mutation (METΔex14), MET amplification, and MET fusion and report treatment outcomes after switching therapy from type I to type II MET inhibitors. MATERIALS AND METHODS: Pre- and post-treatment biopsies were analysed by NGS (next generation sequencing), digital droplet PCR (polymerase chain reaction), and FISH (fluorescense in situ hybridization). A patient-derived xenograft model was generated in one case. RESULTS: Of 26 patients with MET tyrosine kinase inhibitor treatment, eight had paired pre- and post-treatment biopsies (Three with MET amplification, three with METΔex14, two with MET fusions (KIF5B-MET and PRKAR2B-MET).) In six patients, mechanisms of resistance were detected, whereas in two cases, the cause of resistance remained unclear. We found off-target resistance mechanisms in four cases with KRAS mutations and HER2 amplifications appearing. Two patients exhibited second-site MET mutations (p.D1246N and p. Y1248H). Three patients received type I and type II MET tyrosine kinase inhibitors sequentially. In two cases, further progressive disease was seen hereafter. The patient with KIF5B-MET fusion received three different MET inhibitors and showed long-lasting stable disease and a repeated response after switching therapy, respectively. CONCLUSION: Resistance to MET inhibition is heterogeneous with on- and off-target mechanisms occurring regardless of the initial MET aberration. Switching therapy between different types of kinase inhibitors can lead to repeated responses in cases with second-site mutations. Controlled clinical trials in this setting with larger patient numbers are needed, as evidence to date is limited to preclinical data and case series.

Rebiopsy in advanced non-small cell lung cancer, clinical relevance and prognostic implications.

INTRODUCTION: Rebiopsies of non-small cell lung cancers (NSCLC) are mainly performed to (i) cover the evolution of potentially amenable resistance mechanisms against a targeted therapy, and (ii) to identify new therapeutic targets which were not detected in the initial diagnostic biopsy. Comprehensive systematic analyses evaluating the value of rebiopsies are missing. METHODS: Clinical databases from two large comprehensive cancer center networks were queried following prespecified criteria to identify prospectively entered NSCLC cases with at least one rebiopsy at disease progression. Clinicopathological and biomarker findings including multigene sequencing were correlated with clinical outcomes. RESULTS: From a total of 17,477 stage IV NSCLC patients, a cohort of 403 evaluable patients undergoing at least one rebiopsy of a primary tumor or metastasis was retrieved. Changes in biomarker profiles as compared to baseline were observed in 48.9%. In 31.3% of cases, findings of potential therapeutic relevance were revealed, including 18 patients (4.4%) with a targetable marker only detected at rebiopsy. New findings were more frequent (greater than50%) in NSCLC with EGFR/ALK/ROS1 alterations, including mutations of the dominant oncogene, TP53 mutations, and MET or ERBB2 amplifications. Patients undergoing rebiopsy exhibited superior overall survival compared to a control group, irrespective of presence (HR 0.28) or absence (HR 0.20, both p < 0.001) of a therapeutically targetable aberration. CONCLUSIONS: Rebiopsies at progression of advanced NSCLC are strongly supported by a high rate of clinically relevant findings. Current clinical practice selects a patient population with exceptional outcomes, which merits further characterization.

Clonal dynamics of BRAF-driven drug resistance in EGFR-mutant lung cancer.

Activation of MAPK signaling via BRAF mutations may limit the activity of EGFR inhibitors in EGFR-mutant lung cancer patients. However, the impact of BRAF mutations on the selection and fitness of emerging resistant clones during anti-EGFR therapy remains elusive. We tracked the evolution of subclonal mutations by whole-exome sequencing and performed clonal analyses of individual metastases during therapy. Complementary functional analyses of polyclonal EGFR-mutant cell pools showed a dose-dependent enrichment of BRAFV600E and a loss of EGFR inhibitor susceptibility. The clones remain stable and become vulnerable to combined EGFR, RAF, and MEK inhibition. Moreover, only osimertinib/trametinib combination treatment, but not monotherapy with either of these drugs, leads to robust tumor shrinkage in EGFR-driven xenograft models harboring BRAFV600E mutations. These data provide insights into the dynamics of clonal evolution of EGFR-mutant tumors and the therapeutic implications of BRAF co-mutations that may facilitate the development of treatment strategies to improve the prognosis of these patients.

Real-world efficacy of docetaxel plus nintedanib after chemo-immunotherapy failure in advanced pulmonary adenocarcinoma.

Aim: This real-world analysis evaluated docetaxel plus nintedanib in patients with advanced pulmonary adenocarcinoma after chemotherapy and immune checkpoint inhibitor failure, for whom treatment options are limited. Methods: Data were sourced retrospectively from seven German centers. Results: Of 93 patients, overall response rate was 41.4% (disease control rate: 75.9%). Of 57 patients given third-line docetaxel plus nintedanib, overall response rate was 50.0% (disease control rate: 82.7%). Median overall survival following third-line docetaxel plus nintedanib was 8.4 months. Adverse events were consistent with the known safety profile of docetaxel plus nintedanib. Conclusion: To date, this was the largest retrospective, real-world analysis of docetaxel plus nintedanib after chemotherapy-immunotherapy failure, indicating that docetaxel plus nintedanib offers meaningful clinical benefits in this setting.

Lay abstract The standard of care for patients with lung adenocarcinoma has advanced with the introduction of immunotherapy in the first-line setting. However, limited clinical data are available to help guide treatment decisions after failure of chemotherapy and immunotherapy. Nintedanib is an oral antiangiogenic agent that is approved in the EU and other countries in combination with docetaxel for the treatment of patients with advanced/metastatic lung adenocarcinoma after first-line chemotherapy. This study is a retrospective, real-world analysis of docetaxel plus nintedanib in 93 patients with advanced lung adenocarcinoma who progressed on immunotherapy (either in sequence or in combination with chemotherapy). The results suggest that docetaxel plus nintedanib offers a meaningful clinical benefit in this setting. Safety findings were generally consistent with the known safety profile of docetaxel plus nintedanib.

Fully Automated MR Detection and Segmentation of Brain Metastases in Non-small Cell Lung Cancer Using Deep Learning.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the most common tumor entity spreading to the brain and up to 50% of patients develop brain metastases (BMs). Detection of BMs on MRI is challenging with an inherent risk of missed diagnosis. PURPOSE: To train and evaluate a deep learning model (DLM) for fully automated detection and 3D segmentation of BMs in NSCLC on clinical routine MRI. STUDY TYPE: Retrospective. POPULATION: Ninety-eight NSCLC patients with 315 BMs on pretreatment MRI, divided into training (66 patients, 248 BMs) and independent test (17 patients, 67 BMs) and control (15 patients, 0 BMs) cohorts. FIELD STRENGTH/SEQUENCE: T1 -/T2 -weighted, T1 -weighted contrast-enhanced (T1 CE; gradient-echo and spin-echo sequences), and FLAIR at 1.0, 1.5, and 3.0 T from various vendors and study centers. ASSESSMENT: A 3D convolutional neural network (DeepMedic) was trained on the training cohort using 5-fold cross-validation and evaluated on the independent test and control sets. Three-dimensional voxel-wise manual segmentations of BMs by a neurosurgeon and a radiologist on T1 CE served as the reference standard. STATISTICAL TESTS: Sensitivity (recall) and false positive (FP) findings per scan, dice similarity coefficient (DSC) to compare the spatial overlap between manual and automated segmentations, Pearson's correlation coefficient (r) to evaluate the relationship between quantitative volumetric measurements of segmentations, and Wilcoxon rank-sum test to compare the volumes of BMs. A P value <0.05 was considered statistically significant. RESULTS: In the test set, the DLM detected 57 of the 67 BMs (mean volume: 0.99 ± 4.24 cm3 ), resulting in a sensitivity of 85.1%, while FP findings of 1.5 per scan were observed. Missed BMs had a significantly smaller volume (0.05 ± 0.04 cm3 ) than detected BMs (0.96 ± 2.4 cm3 ). Compared with the reference standard, automated segmentations achieved a median DSC of 0.72 and a good volumetric correlation (r = 0.95). In the control set, 1.8 FPs/scan were observed. DATA CONCLUSION: Deep learning provided a high detection sensitivity and good segmentation performance for BMs in NSCLC on heterogeneous scanner data while yielding a low number of FP findings. Level of Evidence 3 Technical Efficacy Stage 2.