Peripheral and tumor-infiltrating immune cells are correlated with patient outcomes in ovarian cancer

被引:3
|
作者
Zhang, Weiwei [1 ,2 ]
Ling, Yawen [3 ]
Li, Zhidong [3 ]
Peng, Xingchen [1 ,4 ]
Ren, Yazhou [3 ,5 ]
机构
[1] Sichuan Univ, West China Hosp, Natl Clin Res Ctr Geriatr,Dept Biotherapy, Canc Ctr, Chengdu, Peoples R China
[2] Affiliated Fifth Peoples Hosp Chengdu Univ Tradit, Chengdu Peoples Hosp 5, Canc Prevent & Treatment Inst Chengdu, Dept Oncol,Clin Med Coll 2, Chengdu, Peoples R China
[3] Univ Elect Sci & Technol China, Shenzhen Inst Adv Study, Sch Comp Sci & Engn, Chengdu, Peoples R China
[4] Sichuan Univ, West China Hosp, Natl Clin Res Ctr Geriatr,Dept Biotherapy, Canc Ctr, Chengdu 610041, Peoples R China
[5] Univ Elect Sci & Technol China, Shenzhen Inst Adv Study, Sch Comp Sci & Engn, Chengdu 611731, Peoples R China
来源
CANCER MEDICINE | 2023年 / 12卷 / 08期
基金
中国国家自然科学基金;
关键词
machine learning; ovarian cancer; peripheral blood; tumor-infiltrating immune cells; LUNG-CANCER; EXPRESSION; NIVOLUMAB; IMMUNOTHERAPY; DOCETAXEL; CARCINOMA; MELANOMA; AXIS;
D O I
10.1002/cam4.5590
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
ObjectiveAt present, there is still a lack of reliable biomarkers for ovarian cancer (OC) to guide prognosis prediction and accurately evaluate the dominant population of immunotherapy. In recent years, the relationship between peripheral blood markers and tumor-infiltrating immune cells (TICs) with cancer has attracted much attention. However, the relationship between the survival of OC patients and intratumoral- or extratumoral-associated immune cells remains controversial. MethodsIn this study, four machine-learning algorithms were used to predict overall survival in OC patients based on peripheral blood indicators. To further screen out immune-related gene and molecular targets, we systematically explored the correlation between TICs and OC patient survival based on The Cancer Genome Atlas database. Using the TICs score method, patients were divided into a low immune infiltrating cell group and a high immune infiltrating cell group. ResultsThe results showed that there was a significant statistical significance between the peripheral blood indicators and the survival prognosis of OC patients. Survival analysis showed that TICs play a crucial role in the survival of OC patients. Four core genes, CXCL9, CD79A, MS4A1, and MZB1, were identified by cross-PPI and COX regression analysis. Further analysis found that these genes were significantly associated with both TICs and survival in OC patients. ConclusionsThese results suggest that both peripheral blood markers and TICs can be used as prognostic predictors in patients with OC, and CXCL9, CD79A, MS4A1, and MZB1 may be potential therapeutic targets for OC immunotherapy.
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页码:10045 / 10061
页数:17
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