Marker group for predicting prognosis of gastric cancer

A marker and prognostic technology, applied in the medical field, can solve problems that have not been reported

Active Publication Date: 2022-07-22
SUN YAT SEN UNIV CANCER CENT
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  • Description
  • Claims
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Problems solved by technology

Various anti-tumor drugs against PDL1 have been developed, however, the use of PDL1 levels in patient blood samples to predict patient prognosis has not been reported

Method used

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  • Marker group for predicting prognosis of gastric cancer
  • Marker group for predicting prognosis of gastric cancer
  • Marker group for predicting prognosis of gastric cancer

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Experimental program
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Embodiment Construction

[0029] The technical scheme of the present invention is further described below in conjunction with experiments.

[0030] case screening

[0031] The inventors selected 247 patients as a sample of patients initially diagnosed with gastric cancer. During subsequent treatment, 34.4% (83 patients) died during the follow-up period.

[0032] ELISA detection of PDL1

[0033] PDL1 levels in serum of GC patients were detected by PDL1 ELISA kit (WEA788Hu-96T), which was purchased from Cloud Clone Company (CCC, Wuhan, China). For specimen collection, 3 ml of blood was collected from a blood collection tube containing EDTA-K2 anticoagulant, and centrifuged at 3000 r / min for 5 min at room temperature. ELISA Test Plasma specimens and ELISA kit were placed at room temperature in advance, and the operation was strictly in accordance with the instructions of the ELISA kit.

[0034] To evaluate the predictive ability of clinical indicators and blood biochemical indicators for prognosis in 2...

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Abstract

The invention discloses a marker group for predicting prognosis of gastric cancer, the inventor detects the concentration of PDL1 in sample plasma by using an ELISA method, discovers that a Nomogram model constructed by combining the concentration of PDL1 with the concentration of CEA can be used for predicting the prognosis of a gastric cancer patient, and an ROC curve analysis result shows that the area under the curve of the Nomogram model is 0.856. In the verification sequence, 68 cases of gastric cancer patients, the area under the curve of the Nomogram model is 0.910, and the five-year survival of the gastric cancer patients can be well predicted. In the aspect of prognosis prediction of gastric cancer, ROC curve analysis finds that the area under the curve of the Nomogram model constructed by the inventor is 0.856, the area under the curve of CEA is 0.676, the area under the curve of PDL1 is 0.67, and the area under the curve of distant metastasis is 0.647. The invention provides a novel high-sensitivity and high-specificity detection index for prognosis prediction of gastric cancer, and provides a novel way for judging and predicting prognosis of gastric cancer.

Description

technical field [0001] The invention belongs to the field of medicine, and particularly relates to a marker group for predicting the prognosis of gastric cancer. Background technique [0002] Gastric cancer (GC) is the second most common cancer in China. According to previous reports, GC has a poor prognosis and poses a great threat to human health. [0003] At present, the prognosis of GC is mainly predicted by the TNM staging system. However, prediction of patient prognosis based on TNM classification is far from enough. CEA is used for GC screening, clinical prognosis diagnosis and relapse monitoring. Carbohydrate antigen 19-9 (CA19-9) is a good prognostic factor in gastric cancer patients. However, the use of these tumor markers as an independent prognostic factor has been controversial due to their low sensitivity and high false-positive rate. [0004] Carcinoembryonic antigen (CEA) is a tumor-associated antigen first extracted from colon cancer and embryonic tissu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/531G01N33/574G01N33/68G01N21/76
CPCG01N33/531G01N33/6863G01N33/57473G01N21/76
Inventor 张琳狄田罗秋云杜勇杨大俊邱妙珍
Owner SUN YAT SEN UNIV CANCER CENT
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