Abstract 4610: A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors

2014 ◽  
Author(s):  
Nadine S. Jahchan ◽  
Joel T. Dudley ◽  
Pawel K. Mazur ◽  
Natasha Flores ◽  
Dian Yang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Neuroendocrine Tumors ◽  
Cell Lung Cancer ◽  
Tricyclic Antidepressants ◽  
Drug Repositioning ◽  
Small Cell ◽  
Small Cell Lung

Abstract IA02: A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer.

2014 ◽  
Vol 20 (2 Supplement) ◽  
pp. IA02-IA02
Author(s):  
Nadine Jahchan ◽  
Dudley Joel ◽  
Pawel Mazur ◽  
Joel Neal ◽  
Purvesh Khatri ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Tricyclic Antidepressants ◽  
Drug Repositioning ◽  
Small Cell ◽  
Small Cell Lung

Neuroendocrine Tumors of the Lung Other Than Small Cell Lung Cancer

2018 ◽  
pp. 555-568.e6
Author(s):  
Krista Noonan ◽  
Jules Derks ◽  
Janessa Laskin ◽  
Anne-Marie C. Dingemans
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Neuroendocrine Tumors ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung

scholarly journals P1-181: Clinical significance of the AKT pathway in small cell lung cancer and other neuroendocrine tumors

2007 ◽  
Vol 2 (8) ◽  
pp. S809
Author(s):  
Akihiko Yoshizawa ◽  
Junya Fukuoka ◽  
Konstantin Shilo ◽  
Teri J. Franks ◽  
Stephen M. Hewitt ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Clinical Significance ◽  
Neuroendocrine Tumors ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Akt Pathway ◽  
Small Cell Lung

Detection and Therapeutic Implications of c-Met Mutations in Small Cell Lung Cancer and Neuroendocrine Tumors

2012 ◽  
Vol 19 (5) ◽  
pp. 833-840 ◽  
Author(s):  
J. Voortman ◽  
T. Harada ◽  
R.P. Chang ◽  
J.K. Killian ◽  
M. Suuriniemi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Neuroendocrine Tumors ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Therapeutic Implications

Improving differential diagnosis of pulmonary large cell neuroendocrine carcinoma (LCNEC) and small cell lung cancer via a transcriptomic, biological pathway-based ridge regression model.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3065-3065
Author(s):  
Jun Hong ◽  
Likun Hou ◽  
Wei Zhang ◽  
Zhengwei Dong ◽  
Zhan Huang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prediction Model ◽  
Small Cell Lung Cancer ◽  
Neuroendocrine Tumors ◽  
Cell Lung Cancer ◽  
Ridge Regression ◽  
Disease Free Survival ◽  
Small Cell ◽  
Rna Seq ◽  
Small Cell Lung

3065 Background: In clinics, it can be challenging to make correct diagnosis of LCNEC, Small cell lung cancer (SCLC), if tissues, like needle biopsies, are insufficient or morphology was poorly preserved. In this study, a reliable classifier was constructed based on transcriptome data and machine learning (Ridge regression) to improve the diagnostic accuracy for LCNEC and SCLC. Methods: RNA-Seq data obtained from 3 public cohorts were collected as training set, including 60 NSCLC cases from The Cancer Genome Atlas (TCGA), 66 LCNEC cases from Julie George et al., Nature Communications 2018, and 33 SCLC cases from Julie George et al., Nature 2015. Another 80 NSCLC, 30 LCNEC and 15 SCLC cases published by Martin Peifer et al., Nature Genetics 2012 were used as validation set. Additionally, RNA-Seq data of 27 borderline samples which were hard to make diagnosis based on histology and Immunohistochemistry were used to test the accuracy of the prediction model. Results: 13,959 genes mapped to 186 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were included. Gene Set Variation Analysis (GSVA) algorithm was used to enrich and score each KEGG pathway. A prediction model based on GSVA score of each pathway was constructed via Ridge regression. This GSVA Score Model achieved ROC-AUC 0.949 and concordant rate of 0.75 for the entire prediction efficiency. Of the 27 borderline samples which were hard to make confirmed diagnosis, 17/27 (63.0%) were predicted as LCNEC, 7/27 were predicted as SCLC, and the remainder were predicted as NSCLC. While only 8 (29.6%) cases with LCNEC were diagnosed by pathologists, which was significantly lower than the results predicted by the model. Furthermore, cases with model predicted LCNEC had a significant longer disease-free survival than that with model predicted SCLC (median DFS,59 months for LCNEC vs 5 months for SCLC, p = 0.0043), which was in parallel with currently known prognostic difference of these two types of neuroendocrine tumors. Conclusions: This GSVA algorithm-based prediction model was able to make accurate diagnosis of LCNEC and SCLC. And it may provide valuable information for clinics to choose optimal therapeutic approach for patients with pulmonary neuroendocrine tumors.[Table: see text]

An open-label phase 1b/2 study of surufatinib in combination with tislelizumab in subjects with advanced solid tumors.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. TPS2677-TPS2677
Author(s):  
Arvind Dasari ◽  
John S. Kauh ◽  
Christopher Tucci ◽  
Shivani Nanda ◽  
Marek K. Kania ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Antitumor Activity ◽  
Adverse Events ◽  
Small Cell Lung Cancer ◽  
Solid Tumors ◽  
Neuroendocrine Tumors ◽  
Cell Lung Cancer ◽  
Primary Objective ◽  
Small Cell ◽  
Small Cell Lung

TPS2677 Background: Surufatinib (S) is an inhibitor of VEGFR1, 2, & 3; FGFR1; and CSF-1R. In two phase 3 randomized trials (SANET-ep; NCT02588170 & SANET-p; NCT02589821) S demonstrated a manageable safety profile and statistically significant efficacy. Patients (pts) with extrapancreatic neuroendocrine tumors (epNETs) achieved a median progression free survival (PFS) of 9.2 v 3.8 months (mo) (hazard ratio [HR] 0.334; p<0.0001), and pts with pancreatic NETs (pNETs) achieved a median PFS of 10.9 v 3.7 mo (HR 0.491; p=0.0011), with S v placebo, respectively. S was recently approved for the treatment of pts with epNET in China. Tislelizumab (T) is a humanized immunoglobulin G4 anti-PD-1 monoclonal antibody engineered to minimize binding to Fc-gamma-receptor on macrophages. T is approved in China in combination with chemotherapy for squamous non-small cell lung cancer and has conditional approval for Hodgkin’s lymphoma and locally advanced or metastatic urothelial carcinoma with PD-L1 high expression. The objective of this study is to evaluate the safety and efficacy of combination therapy with S and T, which may have synergistic effects, where inhibition of angiogenesis along with stimulation of an immune response may enhance the overall antitumor activity. Methods: This study (NCT04579757) will include pts, ≥18 years of age, with advanced metastatic solid tumors, who have an Eastern Cooperative Oncology Group performance status of 0 or 1 and have progressed on or are intolerant to standard therapies. The primary objective of part 1 (dose escalation) will be to evaluate the safety and tolerability of S and T to determine the recommended phase 2 dose of the combination. The starting dose in part 1 will be 250 mg of S, orally, daily, and 200mg of T, intravenously, every 3 weeks. The dose of S will be escalated during part 1, while the dose of T will remain fixed. Endpoints include dose limiting toxicities, treatment emergent adverse events, serious adverse events, adverse events leading to discontinuation, electrocardiograms, clinical laboratory abnormalities and vital signs. Antitumor activity will be evaluated as a secondary objective. Six to 12 pts will be enrolled. The primary objective of part 2 (dose expansion) will be to evaluate the objective response rate (ORR) of S in combination with T per RECIST v1.1. The endpoint will be ORR at 12 weeks. Key secondary endpoints include PFS, disease control rate, duration of response, safety endpoints, and PK parameters. Approximately 95 pts with indications of interest will be enrolled: colorectal cancer, neuroendocrine tumors (thoracic and gastroenteropancreatic), small-cell lung cancer, gastric cancer, and soft tissue sarcoma (undifferentiated pleomorphic sarcoma and alveolar soft part sarcoma). Enrollment in the United States is open and ongoing, and enrollment in Europe is planned for fourth quarter 2021. Clinical trial information: NCT04579757.

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