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Prognosis and Immunotherapy Response With a Novel Golgi Apparatus Signature-Based Formula in Lung Adenocarcinoma.
Jiang, Yupeng; Ouyang, Wenhao; Zhang, Chenzi; Yu, Yunfang; Yao, Herui.
Afiliación
  • Jiang Y; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medical Oncology, Center of Phase I Clinical Trial, Center of Breast Tumor, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Ouyang W; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medical Oncology, Center of Phase I Clinical Trial, Center of Breast Tumor, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Zhang C; Department of Hematology, Xiangya Hospital, Central South University, Changsha Hunan, China.
  • Yu Y; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medical Oncology, Center of Phase I Clinical Trial, Center of Breast Tumor, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Yao H; Artificial Intelligence & Digital Media Concentration Program, Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai, China.
Front Cell Dev Biol ; 9: 817085, 2021.
Article en En | MEDLINE | ID: mdl-35127727
The Golgi apparatus (GA) is a cellular organelle that participates in the packaging, modification, and transport of proteins and lipids from the endoplasmic reticulum to be further fabricated before being presented to other cellular components. Recent studies have demonstrated that GA facilitates numerous cellular processes in cancer development. Therefore, this study aimed to establish a novel lung adenocarcinoma (LUAD) risk evaluation model based on GA gene signatures. In this study, we used TCGA-LUAD (n = 500) as the training cohort and GSE50081 (n = 127), GSE68465 (442), and GSE72094 (398) as the validation cohorts. Two immunotherapy datasets (GSE135222 and GSE126044) were also obtained from a previous study. Based on machine algorithms and bioinformatics methods, a GA gene-related risk score (GARS) was established. We found that the GARS independently predicted the prognosis of LUAD patients and remained effective across stages IA to IIIA. Then, we identified that the GARS was highly correlated with mutations in P53 and TTN. Further, this study identified that GARS is related to multiple immune microenvironmental characteristics. Furthermore, we investigated GSE135222 and GSE126044 and found that a lower GARS may be indicative of an improved therapeutic effect of PD-1/PD-L1 therapy. We also found that high GARS may lead to a better response to multiple anticancer drugs. Finally, we established a nomogram to better guide clinical application. To our knowledge, this is the first study to demonstrate a novel GA signature-based risk score formula to predict clinical prognosis and guide the treatment of LUAD patients.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Cell Dev Biol Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Cell Dev Biol Año: 2021 Tipo del documento: Article País de afiliación: China