Effective osimertinib treatment in a patient with discordant T790 M mutation detection between liquid biopsy and tissue biopsy.

BACKGROUND:We report the successful treatment of the patient with osimertinib 80 mg/day following disease progression and a discordance in the detection of a mechanism of resistance epithelial growth factor receptor (EGFR) T790 M between liquid biopsy and tissue biopsy methods. CASE PRESENTATION:A 57-year-old Hispanic male patient initially diagnosed with an EGFR 19 deletion positive lung adenocarcinoma and clinically responded to initial erlotinib treatment. The patient subsequently progressed on erlotinib 150 mg/day and repeat biopsies both tissue and liquid were sent for next-generation sequencing (NGS). A T790 M EGFR mutation was detected in the blood sample using a liquid biopsy technique, but the tissue biopsy failed to show a T790 M mutation in a newly biopsied tissue sample. He was then successfully treated with osimertinib 80 mg/day, has clinically and radiologically responded, and remains on osimertinib treatment after 10 months. CONCLUSIONS:Second-line osimertinib treatment, when administered at 80 mg/day, is both well tolerated and efficacious in a patient with previously erlotinib treated lung adenocarcinoma and a T790 M mutation detected by liquid biopsy

Usefulness of Circulating Tumor DNA in Identifying Somatic Mutations and Tracking Tumor Evolution in Patients With Non-small Cell Lung Cancer

Background The usefulness of circulating tumor DNA (ctDNA) in detecting mutations and monitoring treatment response has not been well studied beyond a few actionable biomarkers in non-small cell lung cancer (NSCLC). Research Question How does the usefulness of ctDNA analysis compare with that of solid tumor biopsy analysis in patients with NSCLC? Methods We retrospectively evaluated 370 adult patients with NSCLC treated at the City of Hope between November 2015 and August 2019 to assess the usefulness of ctDNA in mutation identification, survival, concordance with matched tissue samples in 32 genes, and tumor evolution. Results A total of 1,688 somatic mutations were detected in 473 ctDNA samples from 370 patients with NSCLC. Of the 473 samples, 177 showed at least one actionable mutation with currently available Food and Drug Administration-approved NSCLC therapies. MET and CDK6 amplifications co-occurred with BRAF amplifications (false discovery rate [FDR], \u3c 0.01), and gene-level mutations were mutually exclusive in KRAS and EGFR (FDR, 0.0009). Low cumulative percent ctDNA levels were associated with longer progression-free survival (hazard ratio [HR], 0.56; 95% CI, 0.37-0.85; P = .006). Overall survival was shorter in patients harboring BRAF mutations (HR, 2.35; 95% CI, 1.24-4.6; P = .009), PIK3CA mutations (HR, 2.77; 95% CI, 1.56-4.9; P \u3c .001) and KRAS mutations (HR, 2.32; 95% CI, 1.30-4.1; P = .004). Gene-level concordance was 93.8%, whereas the positive concordance rate was 41.6%. More mutations in targetable genes were found in ctDNA than in tissue biopsy samples. Treatment response and tumor evolution over time were detected in repeated ctDNA samples. Interpretation Although ctDNA analysis exhibited similar usefulness to tissue biopsy analysis, more mutations in targetable genes were missed in tissue biopsy analyses. Therefore, the evaluation of ctDNA in conjunction with tissue biopsy samples may help to detect additional targetable mutations to improve clinical outcomes in advanced NSCLC

EPHA2 mutations with oncogenic characteristics in squamous cell lung cancer and malignant pleural mesothelioma.

Squamous cell carcinoma (SCC) and malignant pleural mesothelioma (MPM) are thoracic malignancies with very poor prognosis and limited treatment options. It is an established fact that most of the solid tumors have overexpression of EPHA2 receptor tyrosine kinase. EPHA2 is known to exhibit opposing roles towards cancer progression. It functions in inhibiting cancer survival and migration via a ligand and tyrosine kinase dependent signaling (Y772). Whereas it is known to promote tumor progression and cell migration through a ligand-independent signaling (S897). We analyzed the expression profile and mutational status of the ephrin receptor A2 (EPHA2) in SCC and MPM cell lines and primary patient specimens. The EPHA2 receptor was found to be either overexpressed, mutated or amplified in SCC and MPM. In particular, the EPHA2 mutants A859D and T647M were interesting to explore, A859D Y772 dead mutant exhibited lower levels of phosphorylation at Y772 compared to T647M mutant. Molecular Dynamics simulations studies suggested that differential changes in conformation might form the structural basis for differences in the level of EPHA2 activation. Consequently, A859D mutant cells exhibited increased proliferation as well as cell migration compared to controls and T647M mutant. Kinomics analysis demonstrated that the STAT3 and PDGF pathways were upregulated whereas signaling through CBL was suppressed. Considered together, the present work has uncovered the oncogenic characteristics of EPHA2 mutations in SSC and MPM reinstating the dynamics of different roles of EPHA2 in cancer. This study also suggests that a combination of doxazosin and other EPHA2 inhibitors directed to inhibit the pertinent signaling components may be a novel therapeutic strategy for MPM and Non-small cell lung cancer patients who have either EPHA2 or CBL alterations

Predicting Survival of NSCLC Patients Treated with Immune Checkpoint Inhibitors: Impact and Timing of Immune-related Adverse Events and Prior Tyrosine Kinase Inhibitor Therapy

Introduction: Immune checkpoint inhibitors (ICIs) produce a broad spectrum of immune-related adverse events (irAEs) affecting various organ systems. While ICIs are established as a therapeutic option in non-small cell lung cancer (NSCLC) treatment, most patients receiving ICI relapse. Additionally, the role of ICIs on survival in patients receiving prior targeted tyrosine kinase inhibitor (TKI) therapy has not been well-defined. Objective: To investigate the impact of irAEs, the relative time of occurrence, and prior TKI therapy to predict clinical outcomes in NSCLC patients treated with ICIs. Methods: A single center retrospective cohort study identified 354 adult patients with NSCLC receiving ICI therapy between 2014 and 2018. Survival analysis utilized overall survival (OS) and real-world progression free survival (rwPFS) outcomes. Model performance matrices for predicting 1-year OS and 6-month rwPFS using linear regression baseline, optimal, and machine learning modeling approaches. Results: Patients experiencing an irAE were found to have a significantly longer OS and rwPFS compared to patients who did not (median OS 25.1 vs. 11.1 months; hazard ratio [HR] 0.51, confidence interval [CI] 0.39- 0.68, P-value \u3c0.001, median rwPFS 5.7 months vs. 2.3; HR 0.52, CI 0.41- 0.66, P-value \u3c0.001, respectively). Patients who received TKI therapy before initiation of ICI experienced significantly shorter OS than patients without prior TKI therapy (median OS 7.6 months vs. 18.5 months; P-value \u3c 0.01). After adjusting for other variables, irAEs and prior TKI therapy significantly impacted OS and rwPFS. Lastly, the performances of models implementing logistic regression and machine learning approaches were comparable in predicting 1-year OS and 6-month rwPFS. Conclusion: The occurrence of irAEs, the timing of the events, and prior TKI therapy were significant predictors of survival in NSCLC patients on ICI therapy. Therefore, our study supports future prospective studies to investigate the impact of irAEs, and sequence of therapy on the survival of NSCLC patients taking ICIs

Differentiating Peripherally-Located Small Cell Lung Cancer From Non-small Cell Lung Cancer Using a CT Radiomic Approach

Lung cancer can be classified into two main categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), which are different in treatment strategy and survival probability. The lung CT images of SCLC and NSCLC are similar such that their subtle differences are hardly visually discernible by the human eye through conventional imaging evaluation. We hypothesize that SCLC/NSCLC differentiation could be achieved via computerized image feature analysis and classification in feature space, as termed a radiomic model. The purpose of this study was to use CT radiomics to differentiate SCLC from NSCLC adenocarcinoma. Patients with primary lung cancer, either SCLC or NSCLC adenocarcinoma, were retrospectively identified. The post-diagnosis pre-treatment lung CT images were used to segment the lung cancers. Radiomic features were extracted from histogram-based statistics, textural analysis of tumor images and their wavelet transforms. A minimal-redundancy-maximal-relevance method was used for feature selection. The predictive model was constructed with a multilayer artificial neural network. The performance of the SCLC/NSCLC adenocarcinoma classifier was evaluated by the area under the receiver operating characteristic curve (AUC). Our study cohort consisted of 69 primary lung cancer patients with SCLC (n = 35; age mean ± SD = 66.91± 9.75 years), and NSCLC adenocarcinoma (n = 34; age mean ± SD = 58.55 ± 11.94 years). The SCLC group had more male patients and smokers than the NSCLC group (P \u3c 0.05). Our SCLC/NSCLC classifier achieved an overall performance of AUC of 0.93 (95% confidence interval = [0.85, 0.97]), sensitivity = 0.85, and specificity = 0.85). Adding clinical data such as smoking history could improve the performance slightly. The top ranking radiomic features were mostly textural features. Our results showed that CT radiomics could quantitatively represent tumor heterogeneity and therefore could be used to differentiate primary lung cancer subtypes with satisfying results. CT image processing with the wavelet transformation technique enhanced the radiomic features for SCLC/NSCLC classification. Our pilot study should motivate further investigation of radiomics as a non-invasive approach for early diagnosis and treatment of lung cancer

Precision Medicine and Actionable Alterations in Lung Cancer: A Single Institution Experience

OBJECTIVES: Oncology has become more reliant on new testing methods and a greater use of electronic medical records, which provide a plethora of information available to physicians and researchers. However, to take advantage of vital clinical and research data for precision medicine, we must initially make an effort to create an infrastructure for the collection, storage, and utilization of this information with uniquely designed disease-specific registries that could support the collection of a large number of patients. MATERIALS AND METHODS: In this study, we perform an in-depth analysis of a series of lung adenocarcinoma patients (n = 415) with genomic and clinical data in a recently created thoracic patient registry. RESULTS: Of the 415 patients with lung adenocarcinoma, 59% (n = 245) were female; the median age was 64 (range, 22-92) years with a median OS of 33.29 months (95% CI, 29.77-39.48). The most common actionable alterations were identified in EGFR (n = 177/415 [42.7%]), ALK (n = 28/377 [7.4%]), and BRAF V600E (n = 7/288 [2.4%]). There was also a discernible difference in survival for 222 patients, who had an actionable alteration, with a median OS of 39.8 months as compared to 193 wild-type patients with a median OS of 26.0 months (P CONCLUSION: The use of patient registries, focused genomic panels and the appropriate use of clinical guidelines in community and academic settings may influence cohort selection for clinical trials and improve survival outcomes