| Autor: |
Meng Xia Wei, Zheng Yang, Pan Pan Wang, Xue Ke Zhao, Xin Song, Rui Hua Xu, Jing Feng Hu, Kan Zhong, Ling Ling Lei, Wen Li Han, Miao Miao Yang, Fu You Zhou, Xue Na Han, Zong Min Fan, Jia Li, Ran Wang, Bei Li, Li Dong Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Cancer Medicine, Vol 13, Iss 5, Pp n/a-n/a (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2045-7634 |
| DOI: |
10.1002/cam4.7015 |
| Popis: |
Abstract Background Gastric cardia adenocarcinoma (GCA) is classified as Siewert type II adenocarcinoma at the esophagogastric junction in Western countries. The majority of GCA patients do not exhibit early warning symptoms, leading to over 90% of diagnoses at an advanced stage, resulting in a grim prognosis, with less than a 20% 5‐year survival rate. Method Metabolic features of 276 GCA and 588 healthy controls were characterized through a widely‐targeted metabolomics by UPLC‐MS/MS analysis. This study encompasses a joint pathway analysis utilizing identified metabolites, survival analysis in both early and advanced stages, as well as high and negative and low expression of HER2 immunohistochemistry staining. Machine learning techniques and Cox regression models were employed to construct a diagnostic panel. Results A total of 25 differential metabolites were consistently identified in both discovery and validation sets based on criteria of p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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