Predicting the prognosis of esophageal cancer based on extensive analysis of new inflammatory response-related signature.

He, Hongbo; Zhang, Peng; Li, Feng; Zeng, Cheng; Liu, Donglei; Wu, Kai

He, Hongbo; Zhang, Peng; Li, Feng; Zeng, Cheng; Liu, Donglei; Wu, Kai.

Affiliation

He H; Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Henan, Zhengzhou, P. R. China.
Zhang P; Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Henan, Zhengzhou, P. R. China.
Li F; Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Henan, Zhengzhou, P. R. China.
Zeng C; Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Henan, Zhengzhou, P. R. China.
Liu D; Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Henan, Zhengzhou, P. R. China.
Wu K; Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Henan, Zhengzhou, P. R. China.

J Biochem Mol Toxicol ; 37(4): e23291, 2023 Apr.

Article de En | MEDLINE | ID: mdl-36536508

Sujet(s)
Mots clés

TCGA; bioinformatics; esophageal cancer; inflammatory response-related genes; prognostic signature

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Tumeurs de l'oesophage / Protéines précoces immédiates Type d'étude: Prognostic_studies / Risk_factors_studies Limites: Humans Langue: En Journal: J Biochem Mol Toxicol Sujet du journal: BIOLOGIA MOLECULAR / BIOQUIMICA / TOXICOLOGIA Année: 2023 Type de document: Article Pays de publication: États-Unis d'Amérique

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