Dissecting molecular, pathological, and clinical features associated with tumor neural/neuroendocrine heterogeneity
Ling Cai,
Ralph J. DeBerardinis,
Guanghua Xiao,
John D. Minna,
Yang Xie
Affiliations
Ling Cai
Quantitative Biomedical Research Center, Peter O’Donnell School of Public Health, UT Southwestern Medical Center, Dallas, TX 75390, USA; Children’s Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA; Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX 75390, USA; Corresponding author
Ralph J. DeBerardinis
Children’s Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA; Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX 75390, USA; Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
Guanghua Xiao
Quantitative Biomedical Research Center, Peter O’Donnell School of Public Health, UT Southwestern Medical Center, Dallas, TX 75390, USA; Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX 75390, USA; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
John D. Minna
Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX 75390, USA; Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Pharmacology, UT Southwestern Medical Center, Dallas, TX 75390, USA; Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
Yang Xie
Quantitative Biomedical Research Center, Peter O’Donnell School of Public Health, UT Southwestern Medical Center, Dallas, TX 75390, USA; Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX 75390, USA; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Corresponding author
Summary: 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.
