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Dissecting molecular, pathological, and clinical features associated with tumor neural/neuroendocrine heterogeneity.
Cai, Ling; DeBerardinis, Ralph J; Xiao, Guanghua; Minna, John D; Xie, Yang.
Afiliação
  • Cai L; Quantitative Biomedical Research Center, Peter O'Donnell School of Public Health, UT Southwestern Medical Center, Dallas, TX 75390, USA.
  • DeBerardinis RJ; Children's Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.
  • Xiao G; Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX 75390, USA.
  • Minna JD; Children's Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.
  • Xie Y; Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX 75390, USA.
iScience ; 26(6): 106983, 2023 Jun 16.
Article em En | MEDLINE | ID: mdl-37378310
ABSTRACT
Lineage plasticity, especially transdifferentiation between neural/neuroendocrine (NE) and non-NE lineage, has been observed in multiple cancer types and linked to increased tumor aggressiveness. However, existing NE/non-NE subtype classifications in various cancer types were established through ad hoc approaches in different studies, making it difficult to align findings across cancer types and extend investigations to new datasets. To address this issue, we developed a generalized strategy to generate quantitative NE scores and a web application to facilitate its implementation. We applied this method to nine datasets covering seven cancer types, including two neural cancers, two neuroendocrine cancers, and three non-NE cancers. Our analysis revealed significant NE inter-tumoral heterogeneity and identified strong associations between NE scores and molecular, histological, and clinical features, including prognosis in different cancer types. These results support the translational utility of NE scores. Overall, our work demonstrated a broadly applicable strategy for determining the NE properties of tumors.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article