Method for predicting prognosis based on combined analysis of rectal cancer transcriptome genes and methylation and model application

Abstract

The invention relates to the gene technology and medicine field, and in particular, relates to a method for predicting prognosis based on combined analysis of rectal cancer transcriptome genes and methylation and a model application. The invention provides an application of differentially expressed genes and differentially methylated genes in prognostic risk prediction of rectal cancer. The six special differentially expressed genes are TAMM41, AC022387.1, AP004609.1, GVQW3, AC245060.2 and AC027644.1. The seven special differential methylated genes are MIR7848, LRRC74B, MRPL13, SNRPD3, EMILIN2, NACAP1 and C8or87. The better choice is provided for early screening of rectal cancer, the accuracy of screening is improved, the mortality rate and local recurrence rate of rectal cancer patients are reduced, individualized and precise treatment is realized through the risk prediction model, and the prognosis of the patients is improved.

Description

technical field [0001] The invention relates to the fields of gene technology and medicine, in particular to a method and model application for predicting prognosis based on joint analysis of rectal cancer transcriptome gene and methylation. Background technique [0002] Colorectal cancer (CRC) is the third most commonly diagnosed malignancy worldwide and the fourth most common lethal tumor after lung, gastric, and liver cancers, with a poor prognosis. About one-third of people in developed countries die from the disease, and the five-year survival rate for rectal cancer in the United States is about 65 percent. Rectal cancer (RC) accounts for approximately 33% of colorectal cancer diagnoses and has a high rate of local recurrence. In general, the earlier the therapeutic intervention, the better the patient's prognosis. However, the lack of highly sensitive and specific biomarkers in current clinical work hinders the detection of patients with early rectal cancer to a cert...

AI Technical Summary

Problems solved by technology

However, there are still some problems with several existing screening methods: (1) Colonoscopy is invasive; (2) Single-gene prediction is not effective; (3) The clinical specificity of existing methylation markers and low sensitivity; (4) Lack of predictive models for joint analysis of transcriptome data and methylation data

But the compartmentalization studies used in the study did not detail specific genes, making it difficult to find new therapeutic targets when methylation serves as an entry point

At the same time, common DNA methylation signatures often lack specificity and are not altered in just one type of tumor

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