Tumor metastasis and recurrence prediction method and system based on TCGA database

Abstract

The invention discloses a tumor metastasis and recurrence prediction method and system based on a TCGA (The Cancer Genome Atlas) database. The tumor metastasis and recurrence prediction method includes the steps: obtaining transcriptome sequencing data of tumor tissues of tumor patients from the TCGA database; performing gene differential expression analysis according to the acquired transcriptomesequencing data of tumor tissues; performing construction of a tumor metastasis and recurrence prediction model by using a machine learning method according to results of gene differential expressionanalysis to obtain a tumor metastasis and recurrence model; and performing tumor metastasis and recurrence prediction on an object to be predicted according to the tumor metastasis and recurrence prediction model. The tumor metastasis and recurrence prediction method based on a TCGA database utilizes the machine learning method and the TCGA database to realize the fully automated management of the tumor metastasis and recurrence prediction, can directly provide a clear diagnosis and prognosis reference and guidance for tumor patients, and is more timely, accurate and efficient. The tumor metastasis and recurrence prediction method based on a TCGA database can be widely applied to the field of medical computer applications.

Description

technical field [0001] The invention relates to the field of medical computer applications, in particular to a method and system for predicting tumor metastasis and recurrence based on a TCGA database. Background technique [0002] At present, tumor metastasis is still a worldwide problem. For example, in colorectal cancer, about 50% of patients still die of metastatic disease within 5 years after radical resection (RO). Even in patients with node-negative (NO) disease, the recurrence rate reaches 10%. The prognosis of lung cancer is worse, with 60% RO and 40% NO patients dying of metastatic disease. After tumor resection, patients can only judge whether the tumor has recurred or has metastases through irregular reexamination. [0003] At present, the clinical diagnosis of metastasis and recurrence in tumor patients is achieved through high-resolution imaging technology or marker protein detection for early diagnosis of tumors. However, both methods have their limitations...

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Problems solved by technology

However, both methods have their limitations: it is often difficult to detect early metastasis of tumor cells through high-resolution imaging techniques, preventing effective early intervention, resulting in tumors that are often diagnosed and treated at an advanced stage, and the best time for treatment is missed ; However, the detection of marker proteins in the early diagnosis of tumors has a low abundance of marker proteins, which greatly reduces the accuracy of detection, and it is currently the only way to isolate very rare candidate tumor markers from the high-concentration complex mixture of blood proteins. a huge challenge

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