A personalized prognostic assessment method for liver cancer based on multi-gene expression profiles

A Prognostic Assessment, Personalized Technology, Applied in Biotechnology and Medicine

Active Publication Date: 2022-04-15
KUNMING INST OF ZOOLOGY CHINESE ACAD OF SCI
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  • Claims
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Problems solved by technology

However, most reports only use single or several genes, can only classify a group, and can only qualitatively divide the individual survival period (such as two indicators of good prognosis and poor prognosis)

Method used

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  • A personalized prognostic assessment method for liver cancer based on multi-gene expression profiles
  • A personalized prognostic assessment method for liver cancer based on multi-gene expression profiles
  • A personalized prognostic assessment method for liver cancer based on multi-gene expression profiles

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Embodiment Construction

[0064] The implementation of the present invention will be described in detail below with examples, so as to fully understand and implement the implementation process of how the present invention uses technical means to solve technical problems and achieve technical effects.

[0065] The invention discloses a method for evaluating the individualized prognosis of liver cancer based on a polygene expression profile, which comprises the following steps:

[0066] Step 1. Obtain the liver cancer prognosis risk gene list and gene weight, specifically:

[0067] Step 1.1, download the tumor tissue and paracancerous tissue transcriptome data and clinical data of liver cancer patients from the Genomic Data Commons Data Portal database, and obtain the tumor tissue gene expression profile FPKM of liver cancer patients ( F fragments P er K ilobase of transcript per M million fragments mapped) values, logarithmic transformation (log2).

[0068] Step 1.2. Let the total number of samples ...

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Abstract

The invention discloses a liver cancer individualized prognosis assessment method based on multi-gene expression profile, comprising the following steps: obtaining a list of liver cancer prognosis risk genes and gene weights; constructing a prognosis assessment model by using tumor tissue transcriptome and survival data of liver cancer patients; The gene expression profile of the tumor tissue of liver cancer patients is used to calculate the patient's risk score; the patient's annual survival probability is calculated based on the patient's risk score. The annual survival probability of patients with liver cancer obtained by the method of the present invention is highly consistent with the actual annual survival ratio (linear correlation R 2 = 0.992, P-value = 6.18E‑37). It is confirmed that the method has high prediction accuracy, which is highly consistent with the actual survival status. At the same time, for each tumor patient, the present invention can provide the specific survival probability curve of the patient.

Description

technical field [0001] The invention belongs to the fields of biotechnology and medicine, and in particular relates to a method for evaluating the individualized prognosis of liver cancer based on a polygene expression profile. Background technique [0002] Liver cancer is a malignant tumor with high incidence in China and the world. The incidence and death rate in developing countries such as China are generally higher than those in developed countries. Globally, the incidence and mortality of liver cancer in men are higher than those in women. Global Burden of Disease (GBD) data shows that in 2016, the number of people suffering from liver cancer worldwide reached 1 million, of which 670,000 were in China. In 2016, the number of deaths of liver cancer patients worldwide was 830,000, accounting for 1.52% of the total deaths. In 2016, the number of patients who died in China exceeded 420,000, accounting for 4.42% of the total number of deaths. Statistics show that from 19...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H50/30G16B25/10
CPCG16B25/00G16H50/30
Inventor 李文兴李功华黄京飞赵旭东代绍兴
Owner KUNMING INST OF ZOOLOGY CHINESE ACAD OF SCI
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