Novel Mouse Cell Lines and In Vivo Models for Human High-Grade Neuroendocrine Lung Carcinoma, Small Cell Lung Carcinoma (SCLC), and Large Cell Neuroendocrine Carcinoma (LCNEC)

• Published in: International journal of molecular sciences Vol. 24; no. 20; p. 15284
• Main Authors: Recuero, Enrique, Lázaro, Sara, Lorz, Corina, Enguita, Ana Belén, Garcia-Escudero, Ramón, Santos, Mirentxu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 18.10.2023; MDPI
• Subjects: Adenoviruses; allograft; Cancer; cell lines; Cells; Cytoplasm; Disease; Immunocompetence; Immunotherapy; LCNEC; Lung cancer; Lungs; Lymphatic system; Medical prognosis; Metastasis; Morphology; Mutation; SCLC; syngeneic; Thyroid gland; Transcription factors; Tumors
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms242015284

There is a clear need to expand the toolkit of adequate mouse models and cell lines available for preclinical studies of high-grade neuroendocrine lung carcinoma (small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC)). SCLC and LCNEC are two highly aggressive tumor types with dismal prognoses and few therapeutic options. Currently, there is an extreme paucity of material, particularly in the case of LCNEC. Given the lack of murine cell lines and transplant models of LCNEC, the need is imperative. In this study, we generated and examined new models of LCNEC and SCLC transplantable cell lines derived from our previously developed primary mouse LCNEC and SCLC tumors. RNA-seq analysis demonstrated that our cell lines and syngeneic tumors maintained the transcriptome program from the original transgenic primary tumor and displayed strong similarities to human SCLC or LCNEC. Importantly, the SCLC transplanted cell lines showed the ability to metastasize and mimic this characteristic of the human condition. In summary, we generated mouse cell line tools that allow further basic and translational research as well as preclinical testing of new treatment strategies for SCLC and LCNEC. These tools retain important features of their human counterparts and address the lack of LCNEC disease models.