Multi-source data fusion framework for revealing breast cancer immune escape regulation mechanism

Abstract

The invention relates to the field of data mining in bioinformatics, in particular to a multi-source data fusion framework for revealing a breast cancer immune escape regulation mechanism. The framework is implemented mainly according to the following steps of: (1) collecting related data of breast cancer samples and normal samples; (2) clustering the breast cancer samples by using NMF (Non-negative Matrix Factorization) to obtain sample subgroup types; (3) comparing the breast cancer samples with the normal samples obtained from GTEx, and finding out differentially expressed related genes; (4) designing a regulation and control analysis algorithm based on ATAC-SEQ data to find immune related genes; (5) verifying the relationship between the TF and the immune gene by using five general databases; and (6) analyzing whether the immune gene obtained according to the framework affects the survival of the patient. The invention provides a multi-source data fusion framework for revealing a breast cancer immune escape regulation mechanism, and the framework has important significance for researching drug relocation and realizing precise medical treatment. The biological significance of the research process and the research result can be effectively improved. More importantly, the single-sample law analysis method can be used for deeply exploring the heterogeneity of a tumor, and has important significance on precise medical practice.

Description

technical field [0001] The invention relates to the field of data mining in bioinformatics, in particular to a multi-source data fusion framework for revealing the regulatory mechanism of breast cancer immune escape. Background technique [0002] Precision medicine is an emerging cancer prevention and treatment strategy that takes into account the individual variability in each patient's genetic basis. With the help of next-generation high-throughput sequencing technology, researchers are becoming more and more familiar with the details of genome-wide mutations, and the overall relationship between different omics data is becoming more and more systematic. For precision medicine, it is very necessary to understand the immune escape mechanism of tumors, especially when the heterogeneity of tumors significantly affects the effect of immunotherapy. Identifying subtypes of breast cancer based on immune-related genes will help to understand the immune escape pathways dominated b...

AI Technical Summary

Problems solved by technology

Although previous studies have clustered breast cancer samples collected by TCGA, it is still unclear how most of the mechanisms of tumor cells regulate the expression of immune genes to escape the killing of immune cells. At the same time, although TCGA also collects non-malignant adjacent cancer patients normal tissue samples, but such normal samples face two major limitations: the number of matched normal samples is too small, and normal samples from cancer patients still cannot fully replace true normal tissue samples from non-cancer individuals

[0004] To sum up, the existing methods have shortcomings in the study of tumor immune escape mechanisms, and each database has its own defects. Few studies have been conducted on the regulatory mechanism of breast cancer cells in the context of multi-source data.

Images