MUC16 as a serum-based prognostic indicator of prometastatic gastric cancer

被引:1
|
作者
Lee, Jieun [1 ]
Lee, Sang Wook [2 ]
Kang, So Hyun [1 ]
Seol, Donghyeok [1 ]
Yoo, Mira [1 ]
Hwang, Duyeong [1 ]
Lee, Eunju [3 ]
Park, Young Suk [1 ]
Ahn, Sang-Hoon [1 ]
Suh, Yun-Suhk [1 ]
Park, Kyoung Un [4 ,5 ]
Kwon, Nak-Jung [2 ]
Kim, Hyung-Ho [1 ,5 ,6 ,7 ]
机构
[1] Seoul Natl Univ, Bundang Hosp, Dept Surg, Seongnam Si 17382, South Korea
[2] Macrogen Inc, Precis Med Inst, 254 Beotkkot Ro, Seoul, South Korea
[3] Chung Ang Univ, Dept Surg, Gwangmyeong Hosp, Gwangmyeong Si, South Korea
[4] Seoul Natl Univ, Bundang Hosp, Dept Lab Med, Seongnam Si, South Korea
[5] Seoul Natl Univ, Coll Med, Dept Lab Med, Seoul, South Korea
[6] Chung Ang Univ, Gwang Myeong Hosp, Gwangmyeong Si, South Korea
[7] Chung Ang Univ, Coll Med, Seoul, South Korea
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
基金
新加坡国家研究基金会;
关键词
Gastric cancer; Metastasis; Serum-based prognostic marker; Olink; MUC16; CARBONIC-ANHYDRASE IX; ANTIGEN;
D O I
10.1038/s41598-024-64798-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Metastatic gastric cancer (GC) presents significant clinical challenges due to its poor prognosis and limited treatment options. To address this, we conducted a targeted protein biomarker discovery study to identify markers predictive of metastasis in advanced GC (AGC). Serum samples from 176 AGC patients (T stage 3 or higher) were analyzed using the Olink Proteomics Target panels. Patients were retrospectively categorized into nonmetastatic, metastatic, and recurrence groups, and differential protein expression was assessed. Machine learning and gene set enrichment analysis (GSEA) methods were applied to discover biomarkers and predict prognosis. Four proteins (MUC16, CAIX, 5'-NT, and CD8A) were significantly elevated in metastatic GC patients compared to the control group. Additionally, GSEA indicated that the response to interleukin-4 and hypoxia-related pathways were enriched in metastatic patients. Random forest classification and decision-tree modeling showed that MUC16 could be a predictive marker for metastasis in GC patients. Additionally, ELISA validation confirmed elevated MUC16 levels in metastatic patients. Notably, high MUC16 levels were independently associated with metastatic progression in T3 or higher GC. These findings suggest the potential of MUC16 as a clinically relevant biomarker for identifying GC patients at high risk of metastasis.
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页数:11
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