Abstract Background: Targeted therapies against specific driver mutations of cancer progression have been used to improve survival of lung adenocarcinoma patients. In KRAS mutant NSCLC specifically, however, after some initial improvement in lung cancer patients, targeted therapies often fail due to acquired drug resistance. To uncover mechanisms of resistance and to discover new drivers, genome-scale sequencing of lung cancers has identified candidate genes, but these data have not rapidly translated in preclinical validation. A major obstacle in lung cancer research has been the deficiencies of standard in vitro models. Methods: To address the deficiencies within standard models we have developed an in vitro 3-dimensional, KRAS-mutated “organoid” model of lung adenocarcinoma that surpasses both in vitro and in vivo models by possessing the tractability of cell lines and the 3-dimensional architecture and morphology of animal models. We have engineered a p53 knockout and KRAS mutation on top of normal wild-type lung epithelium to achieve oncogenicity. Result: Through an optimized growth period in the presence of drug, an organoid model of resistance has been developed through which de novo genetic events underlying acquired resistance can be studied. Conclusion: The highly defined genetic background of the KRAS-mutated 3-D organoid model serves as a tabula rasa upon which stochastic secondary genetic and epigenetic changes can be identified and mechanistically studied by forward and reverse genetics approaches in order to rapidly identify mechanisms of acquired drug resistance and validate therapeutic options. Citation Format: Navika D. Shukla, Ameen A. Salahudeen, Sukhmani K. Padda, Joel W. Neal, Heather A. Wakelee, Calvin J. Kuo. Three-dimensional organoid model for acquired drug resistance in non-small cell lung cancer [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr B30.
Advanced thymic epithelial tumors pose a clinical dilemma for surgeons and medical oncologists. Given the prognostic importance of obtaining a complete resection, interventions that improve resectability may have profound implications. The documented chemosensitivity and radiosensitivity of thymic tumors present an opportunity to use these therapies in the neoadjuvant setting to reduce tumor burden and improve the likelihood of achieving a complete resection. The current evidence available is limited to institutional case-series, large retrospective multi-institutional databases, and phase II clinical trials. The primary objective of considering induction therapy should be facilitating a complete resection; other endpoints such as down-staging or pathologic response have not been shown to result in meaningful improvements in long-term outcomes. There are certain high-risk tumor characteristics that may aid clinicians in appropriately selecting patients for induction therapy. The selection of candidates for induction therapy should take place in a multidisciplinary tumor board including medical oncologist, surgeon, and radiation oncologist with experience in managing advanced thymic malignancies. Without randomized controlled trials, it is unlikely the thymic medical community will arrive at a consensus on the utility of induction therapy. This review will summarize the existing literature and provide insight into the role of induction therapy for advanced thymic malignancies.
Background
Limited treatment options exist for patients with thymic malignancies (TM), and chemotherapy efficacy is often restricted by cumulative toxicity such as neuropathy (taxanes) and cardiomyopathy (anthracyclines). Single agent amrubicin, a third generation anthracycline and topoisomerase II inhibitor with minimal cardiac toxicity, was investigated in TM patients in this trial.
8519 Background: Identifying localized non-small cell lung cancer (NSCLC) patients with residual disease following curative intent therapy is difficult due to normal tissue changes caused by surgery or radiation and an inability to detect microscopic disease. Analysis of circulating tumor DNA (ctDNA) might enable identification of molecular residual disease (MRD) and personalization of adjuvant treatment approaches but has not been explored in lung cancer. Methods: We applied CAPP-Seq, an ultra-sensitive next-generation sequencing based ctDNA quantitation method, to pre- and post-treatment blood samples from a cohort of 41 patients treated with chemoradiation, radiotherapy or surgery for stage I-III primary lung cancer. Detection of ctDNA at a single MRD time-point within 4 months of treatment completion was compared with surveillance by cross-sectional imaging. Furthermore, we developed an approach for identification of tumor mutation burden based on mutations detected in plasma, leveraging whole exome sequencing data from 1,177 NSCLCs sequenced by TCGA. Results: Median follow-up time was 35 months. Pre-treatment ctDNA was detected in 38 (93%) patients and 19 (46%) had detectable post-treatment ctDNA MRD. MRD+ patients displayed significantly inferior 3-year freedom from progression (0% vs. 92%; HR 38; P < 0.0001) and 3-year overall survival (8% vs. 75%; HR 12; P < 0.0001) than MRD- patients. Detection of ctDNA MRD had positive and negative predictive values for disease progression of 100% and 93%, respectively. Furthermore, we non-invasively identified activating EGFR mutations or high mutational burden (≥5 CAPP-Seq non-synonymous mutations, corresponding to > 200 non-synonymous mutations per exome or > 4 single nucleotide variants per megabase of exome) in 47% of patients with detectable ctDNA MRD, suggesting potentially favorable responses to TKIs and immune checkpoint inhibitors, respectively. Conclusions: Our results indicate that ctDNA analysis accurately detects MRD in localized lung cancer patients and could facilitate personalized adjuvant treatment at early time-points when disease burden is minimal.
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