System for predicting prognosis of gastric cancer in subjects

A technology for subjects and gastric cancer, applied in medical data mining, pathological reference, instruments, etc., can solve the problems of great differences in clinical outcomes of patients

Active Publication Date: 2020-09-29
BEIJING CANCER HOSPITAL PEKING UNIV CANCER HOSPITAL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, even in the same pTNM stage and similar treatment regimens, the clinical outcomes of patients often vary greatly

Method used

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  • System for predicting prognosis of gastric cancer in subjects
  • System for predicting prognosis of gastric cancer in subjects
  • System for predicting prognosis of gastric cancer in subjects

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0106] Example 1 Study population and sample collection

[0107]The samples used in the examples of this application were obtained from patients treated with radical gastrectomy for gastric cancer or gastroesophagogastric junction between January 2000 and December 2012 at Peking University Cancer Hospital. Samples with histological identification of adenocarcinoma and available paraffin-embedded tissues (FFPE tissues) were selected. According to the histopathological classification system adopted by the World Health Organization (WHO), all hematoxylin and eosin (H&E) slides were centrally examined at the Pathology Department of Peking University Cancer Hospital to confirm the tumor type and degree of differentiation. A representative area of ​​each tissue sample was identified and carefully marked on the H&E-stained sections. Three representative core tissue samples (1 mm in diameter) were punched from corresponding single donor tissue blocks and rearranged in recipient block...

Embodiment 2

[0119] Embodiment 2 system model construction

[0120] Part of the clinical feature data, immune marker feature data, and protein expression data in the above-mentioned test samples were selected as the variables predicted by the present invention, and the gastric cancer prognosis risk value was used as the result to construct a system model.

[0121] Specifically, a system model was constructed for the above-mentioned clinical data, immune labeling characteristic data and protein expression data obtained in the training set in Example 1. In the process of building the model, the number and risk ratio of the selected feature data were studied, and it was found that the detection of 8 of the features was feasible under clinical conditions, and the risk ratio was equivalent to that of 8–12 features , so in order to balance the efficacy of the model and the convenience of testing clinical practice, 8 of the features were finally selected as the variables of the system model. The...

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PUM

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Abstract

The invention provides a system for predicting prognosis of gastric cancer of subjects. The system comprises: a data acquisition module, which is used for acquiring clinical characteristic data of thesubjects, immune marker characteristic data of the subjects and protein expression data of the subjects; a data processing module, which is used for further processing the data acquired in the data acquisition module; and a module for calculating the prognosis risk of the gastric cancer of the subjects, wherein the module utilizes the data processed in the data processing module to calculate theprognosis risk values of the gastric cancer of the subjects, and groups the subjects based on the risk values. According to the system and a method provided by the invention, eight characteristics, including five immunomarkers (CD3, CD4, PDL1, PAX5, and GZMB), an EMT protein marker (CDH1) and two clinical characteristics (pTNM and age), are selected to develop the system and the method that can significantly improve prognostic ability of gastric cancer patients. The system and the method may be applicable to patients with or without neoadjuvant chemotherapy and exhibit predicted values, and the patients may benefit from post-operative adjuvant chemotherapy.

Description

technical field [0001] The invention relates to a system for predicting the prognosis of gastric cancer of subjects, which is applicable to patients with or without neoadjuvant chemotherapy and predicts the prognosis of gastric cancer patients. Background technique [0002] Although the incidence of gastric cancer (GC) has decreased in recent decades, it remains the third most common cancer and the third leading cause of cancer death worldwide. More than half of these cases occurred in East Asia. Pathological Tumor-Node-Metastasis (pTNM) staging system and histological subtypes have been routinely used to predict the prognosis of GC and guide treatment strategies. However, even in the same pTNM stage and similar treatment regimens, the clinical outcomes of patients often vary greatly. Therefore, several studies have investigated prognostic biomarkers in the hope of enabling better outcome prediction. [0003] A number of signaling pathways and key regulators have been ide...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G16H50/20G16H50/70G16H70/60G16B25/00
CPCG16H50/30G16H50/20G16H50/70G16H70/60G16B25/00
Inventor 季加孚贾淑芹李子禹步召德邢晓芳
Owner BEIJING CANCER HOSPITAL PEKING UNIV CANCER HOSPITAL
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