A prognostic marker gene and random survival forest model for recurrence prediction of stage II colorectal cancer

Abstract

The invention discloses a prognostic marker gene and its application for predicting the recurrence of stage II colorectal cancer. The invention provides a model for predicting the recurrence risk of patients based on the gene expression information of tumors in patients with stage II colorectal cancer. The model predicts The AUC value of the 5-year recurrence risk of patients with stage II colorectal cancer is 0.993, which can significantly separate patients with high risk of recurrence and low risk of recurrence in the test set; regarding the establishment and selection of the model, the present invention uses a random survival forest model, and Screen variables according to the minimum depth value of the largest subtree where the variables are located, select important variables to re-establish the model, and greatly reduce the variable dimension of the model; use the random survival forest model in the test set to divide patients into high recurrence risk group and low recurrence risk group After the risk group, there was a significant difference in recurrence-free survival between the two groups.

Description

[0001] (1) Technical field [0002] The invention relates to a method for constructing a recurrence prediction model of stage II colorectal cancer and a prognostic marker gene. [0003] (2) Background technology [0004] The treatment of colorectal cancer is mainly surgical treatment, supplemented by comprehensive treatment methods such as chemotherapy, radiotherapy, targeted therapy, and immunotherapy. For patients with early colorectal cancer, high-quality radical surgery for colorectal cancer can bring significant benefits to patients. However, some patients with early colorectal cancer have local recurrence and metastatic recurrence after radical surgery. The prognosis of these recurrence patients is often poor, and some studies have found that the RFS (recurrence-free survival) of colorectal cancer patients after radical surgery is shorter, Its overall survival is also shorter. Therefore, the prediction of recurrence risk after radical surgery for early colorectal cancer...

AI Technical Summary

Problems solved by technology

However, many current clinical studies have found that the definition of high-risk stage II is not accurate. Many high-risk stage II patients have no recurrence, while some general-risk stage II patients have recurrence and metastasis. This may be related to the traditional high-risk factors. The clinicopathological characteristics of the patient are not considered, and the biological characteristics of the tumor itself are not considered. However, the current gene chip technology and high-throughput sequencing technology can allow researchers to better mine the gene expression information of the tumor, and then reflect the biology of the tumor. feature

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