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DNA methylated biomarker related to prognosis of renal clear cell carcinoma

A technology of renal clear cell carcinoma and biomarkers, which can be applied in the field of biomedicine to solve problems such as affecting physiological and pathological activities and affecting gene expression.

Pending Publication Date: 2021-12-07
FUDAN UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This is a modification method that does not change the primary structure of DNA, but can cause changes in chromatin structure, DNA conformation, DNA stability, and the interaction between DNA and proteins, thereby affecting gene expression and affecting physiological and pathological activities [6,7,8]

Method used

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  • DNA methylated biomarker related to prognosis of renal clear cell carcinoma
  • DNA methylated biomarker related to prognosis of renal clear cell carcinoma
  • DNA methylated biomarker related to prognosis of renal clear cell carcinoma

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0060] Example 1. Analysis of whole-genome DNA methylation

[0061]DNA methylation basic data collection: 320 clear cell renal cell carcinoma samples were downloaded from the TCGA database, including the following information: clinicopathological factors, such as age and stage at diagnosis, lymph node status, and race and ethnicity, etc.:

[0062] Microarray data: The gene expression dataset (GSE66272) was analyzed using the Gene Expression Profile (GEO, https: / / www.ncbi.nlm.nih.gov / geo / ) of the National Center for Biotechnology (NCBI). Among them, GSE66272 includes 27 pairs of renal clear cell carcinoma tissues and their adjacent normal tissues (platform: GPL96 Affymetrix Human GenomeU133A Array).

Embodiment 2

[0063] Example 2. Analysis of the relationship between differentially expressed CpG sites and differentially expressed genes between ccRCC and adjacent normal tissues

[0064] Methylation data processing: use the TCGA level-3 database to analyze the β value of the relevant CpG site and the location and chromosome of the CpG site;

[0065] The β value is calculated by (M / M+U), and its numerical range is from 0 to 1, wherein, M represents methylation, U represents unmethylation, and the present invention removes the CpG probe on chromosome X and Y In order to eliminate gender differences, the methylation level of 102 samples was detected at the CpG site and gene level, and the 102 samples included 51 primary tumor tissues and 51 normal tissues;

[0066] Differential methylation site analysis: All probes including CpG single nucleotides within 10 bp in length are removed, when the β value between the primary tumor and normal tissue samples is greater than or equal to 0.14, and th...

Embodiment 3

[0072] Example 3. Screen out CpG sites as biomarkers and analyze their relationship with survival

[0073] LASSO regression analysis: For high-dimensional data, LASSO is used to optimize the selection of genes to prevent overfitting and obtain higher diagnostic and prognostic values. LASSO makes the coefficient value close to 0 by eliminating redundant variables. LASSO regression analysis was performed using R software version 3.0.3 and the "glmnet" package;

[0074] Data analysis: use R software to analyze the data, the significant feature is that the two-sided P value is <0.05, and the data is represented by the mean ± standard deviation or the median. In the regression analysis, the P value is calculated by the likelihood ratio test , using T-test to analyze continuous data, chi-square test to compare proportions;

[0075] Use non-zero coefficients in LASSO logistic regression to identify candidate CpG sites;

[0076] Use the single factor Cox proportional hazards regress...

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Abstract

The invention belongs to the technical field of biomedicine, and relates to a marker for prognosis of renal clear cell carcinoma and application of the marker. According to the invention, comparative analysis is carried out on the whole genome methylation level, differential methylation sites and differential methylation regions among tumor tissues and adjacent normal tissues by performing testing observation on the relationship between the change of DNA methylation related markers in renal clear cell carcinoma and the prognosis condition of diseases, and by utilizing an LASSO-Cox regression model, biological markers related to prognosis of renal clear cell carcinoma are determined to be TP73 (cg00295572, cg07382920, cg20611911 and cg01915516) and CTBP2 (cg05749728) respectively. The DNA methylation related markers disclosed by the invention can be used for preparing a product for evaluating the prognosis of the renal clear cell carcinoma.

Description

technical field [0001] The invention belongs to the technical field of biomedicine and relates to a DNA methylation biomarker, in particular to a marker for the prognosis of renal clear cell carcinoma and an application thereof. Background technique [0002] The prior art discloses that kidney cancer is one of the 15 common malignant tumors in humans, with more than 270,000 cases increasing every year [1] . Among them, clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, accounting for about 70% of all renal tumors. [2] . Clinical studies have shown that although the 5-year survival rate of patients with localized clear cell renal cell carcinoma is 91%, the onset of renal cancer is relatively insidious, and about 20% to 30% of patients have developed distant metastasis at the time of treatment, and about 20% of them have developed distant metastasis. % of patients with localized clear cell renal cell carcinoma will develop metastases after surgery....

Claims

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Application Information

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IPC IPC(8): C12Q1/6886C12N15/11
CPCC12Q1/6886C12Q2600/118C12Q2600/154
Inventor 张雪梅陶杰何佳琪辛宏朱宇丹
Owner FUDAN UNIV
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