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Combined marker for predicting prognosis of liver cancer and application of combined marker

A liver cancer prognosis and combined biological technology, applied in the field of biomedicine, can solve problems affecting tumor cell growth and invasion, achieve high sensitivity and accuracy, shorten survival time, and improve accuracy

Pending Publication Date: 2022-06-07
QINGDAO MUNICIPAL HOSPITAL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It has been reported that the E2F family can participate in the regulation of tumor cell cycle, DNA damage response, cell differentiation and cell death by binding to consensus DNA binding sequences, thereby affecting the growth and invasion of tumor cells

Method used

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  • Combined marker for predicting prognosis of liver cancer and application of combined marker
  • Combined marker for predicting prognosis of liver cancer and application of combined marker
  • Combined marker for predicting prognosis of liver cancer and application of combined marker

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] Example 1TCGA database RNA-Seq sequencing data and download of patient clinicopathological data

[0030]Download the RNA-Seq sequencing data of liver cancer tissue and normal tissue next to cancer from the TCGGA database, and download the clinicopathological data of liver cancer patients at the download website: https: / / portal.gdc.cancer.gov / . In the TCGA database, 422 patients with liver cancer had clinical pathological data; 373 patients with liver cancer had RNA-Seq sequencing data of liver cancer tissue. A total of 369 patients with liver cancer had both clinical pathological data and hepatocellular carcinoma tissue sequencing data, of which 50 patients with liver cancer had RNA-Seq sequencing data of liver cancer tissue and normal liver tissue next to cancer. Since the expression profile data of mRNA has been standardized by TCGAs, no further standardization of these data will be carried out, and the pathological parameters of patients with liver cancer are shown in Ta...

Embodiment 2

[0033] Example 2 Screening of differentially expressed gene sets in patients with liver cancer

[0034] Using GSEA version 4.1.0, RNA-Seq sequencing data of liver cancer tissue and paracancerous normal liver tissue were used to analyze the differentially expressed gene sets in liver cancer tissue and paracancerous normal liver tissue. | NES|>1.5, NOM P-val<0.05 are the criteria for screening abnormally expressed gene sets in liver cancer tissues to determine gene sets that have predictive prognosis value in liver cancer treatment; | NES | represents the normalized enrichment analysis score, and NOM p-val represents the corrected p value, characterizing the credibility of the enrichment results; Among them, the transcription factor E2F gene contains 197 genes in the concentration, and its | NES | =2.071552 and NOM p-val=0.001961 are the gene sets with the largest differences among liver cancer tissues and paracancerous normal tissues (Table 2).

[0035] Table 2. Abnormally expresse...

Embodiment 3

[0037] Example 3 Construction of a prognosis model for liver cancer

[0038]Using univariate Cox regression analysis, the differential genes screened from GSEA affected the prognosis of liver cancer patients, and the PFigure 1 A), the present invention found that the high-risk group has a low overall survival time of the low-risk group, the high number of deaths ( Figure 1 B)。

[0039] Table 3.Multivariate COX analysis results of genes in liver cancer prognosis model

[0040]

[0041]

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Abstract

The invention discloses a group of combined markers for predicting liver cancer prognosis and application thereof, and belongs to the technical field of biological medicines. Liver cancer is one of the most common cancer-related death reasons in the world and is extremely poor in prognosis, and recognition of effective prognosis biomarkers of liver cancer has important clinical significance. The invention provides a model for prognosis determination and risk assessment of a liver cancer patient based on combined biomarkers. The related combined biomarkers comprise CDCA3, CDCA8, SSRP1, HN1 and KIF4A. The prognosis risk score is quantitatively calculated according to the expression condition of the combined biomarker in a case sample, the patient is divided into a high-risk group and a low-risk group according to the median value of the risk score of the patient, and the result shows that the prognosis of the patient in the low-risk group is obviously superior to that of the patient in the high-risk group; and the accuracy and specificity of the prognosis survival model are verified through a K-Mplot survival curve, an ROC curve and the survival time and state of the patient. Therefore, the prediction model is of great significance to prognosis prediction and targeted therapy of patients with liver cancer.

Description

[0001] Field of invention [0002] The present invention belongs to the biomedical field, specifically relates to a set of joint markers predicting the prognosis of liver cancer and its applications, specifically to a new set of transcription factor family E2F-associated gene sets, the gene set can be used as prognostic markers for liver cancer. Background [0003] Liver cancer is one of the most common malignancies in the clinic, with the third highest number of deaths among all cancers. It is difficult to detect early, and more than 70% of liver cancer patients are diagnosed at an advanced stage, so the prognosis of liver cancer patients is extremely poor. In addition, traditionally identifiable clinical and pathological symptoms are highly flawed in predicting liver cancer prognosis, and in order to prolong the overall survival rate of liver cancer patients, new methods need to be found to better predict prognosis. [0004] Liver cancer as a heterogeneous disease, not determined...

Claims

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Application Information

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IPC IPC(8): C12Q1/6886C12Q1/6851C12N15/11G16B25/00G16B50/30G16H50/30
CPCC12Q1/6886C12Q1/6851G16B25/00G16B50/30G16H50/30C12Q2600/118C12Q2600/158C12Q2561/113C12Q2563/107C12Q2531/113
Inventor 朱文静步向阳韩欢石杰
Owner QINGDAO MUNICIPAL HOSPITAL
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