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Prognosis marker for lung cancer, method for anticipating lung cancer prognosis by using marker and application of marker

A prognostic marker and marker technology, applied in the field of biomedicine, can solve problems such as loss of data, achieve high clinical application value and save medical costs.

Active Publication Date: 2016-11-16
广州万德基因医学科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these censored data cannot be deleted, because this not only loses data, but also causes bias

Method used

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  • Prognosis marker for lung cancer, method for anticipating lung cancer prognosis by using marker and application of marker
  • Prognosis marker for lung cancer, method for anticipating lung cancer prognosis by using marker and application of marker
  • Prognosis marker for lung cancer, method for anticipating lung cancer prognosis by using marker and application of marker

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] Taking lung adenocarcinoma as an example, the establishment of a prognosis prediction model for lung adenocarcinoma:

[0056] 1) Download lung adenocarcinoma data from TCGA, including transcriptome data and clinical survival data, a total of 515 samples;

[0057] 2) Remove samples with incomplete clinical data, such as incomplete follow-up data, leaving 464 samples; the follow-up survival time data of patients included in the present invention is the earliest from 1986, and the latest is 2016;

[0058] 3) Use the DESeq R package to compare the gene expression between normal people and cancer patients (screening conditions: |log2FC|>2, padj<0.001), and get 1618 differentially expressed genes; the main code for DESeq to find differential genes is as follows:

[0059] >library("DESeq")

[0060] >group=c(rep("normal",num1),rep("tumor",num2))

[0061] >design = factor(group)

[0062] >newTab = newCountDataSet( data, design )

[0063] >newTab = estimateSizeFactors(newTab)...

Embodiment 2

[0079] The prognostic markers of lung adenocarcinoma include the following gene combinations: RP11-89K21.1, CDH17, GRIA1, CENPF, AP000438.2, HMMR, RP11-434D9.1, ADH1B, TPX2, OR7E47P, and the sequences of the genes are SEQ ID NO: 1-10.

[0080] According to Example 1, we have screened out the above prognostic markers, and the prognostic prediction model of lung cancer is:

[0081] S=∑Pi * Ci

[0082] Among them, S is the prognostic risk value of lung cancer, Pi is the quantitative expression value of the i-th gene, and Ci represents the COX regression coefficient of the i-th gene, i=1,2,3,4...10.

[0083] In the prognosis prediction model of lung cancer, the COX regression coefficient corresponding to each gene is selected from the following table:

[0084]

[0085] A method for predicting the prognosis of lung cancer, comprising the following steps:

[0086] 1) Collect samples from lung cancer patients, detect and obtain the expression levels of prognostic markers of lun...

Embodiment 3

[0093] Prognostic markers for lung adenocarcinoma included the following gene combinations: RP11-89K21.1, CDH17, GRIA1, CENPF, AP000438.2, HMMR, RP11-434D9.1, ADH1B, TPX2, OR7E47P, GPR37, HABP2, the The sequences are SEQ ID NO: 1-12 in turn.

[0094] In the prognosis prediction method of lung cancer, the reference value is 1.02.

[0095] According to Example 1, we have screened out the above prognostic markers, and the prognostic prediction model of lung cancer is:

[0096] S=∑Pi * Ci

[0097] Among them, S is the prognostic risk value of lung cancer, Pi is the quantitative expression value of the i-th gene, and Ci represents the COX regression coefficient of the i-th gene, i=1,2,3,4...12.

[0098] In the prognosis prediction model of lung cancer, the COX regression coefficient corresponding to each gene is selected from the following table:

[0099]

[0100] A method for predicting the prognosis of lung cancer, comprising the following steps:

[0101] 1) Collect sample...

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Abstract

The invention discloses a prognosis marker for lung cancer, a method for anticipating lung cancer prognosis by using the marker and application of the marker. The marker comprises the following gene combinations: RP11-89K21.1, CDH17, GRIA1, CENPF, AP000438.2, HMMR, RP11-434D9.1, ADH1B, TPX2 and OR7E47P. The prognosis marker for lung cancer overcomes the defect that the difference between lung cancer treatment reaction and prognosis is big, resulting in inaccuracy and inconvenience in prognosis, and the prognosis marker for lung cancer rapidly, accurately and conveniently anticipates lung cancer prognosis through the marker and detection of the marker, realizes classification and stratification of high and low lung cancer hazards on the molecular level, and remarkably separates patients with high risk from patients with low risk, thereby guiding individualized treatment, having higher clinical application value and saving medical treatment cost.

Description

technical field [0001] The invention belongs to the field of biomedicine, and in particular relates to a prognostic marker of lung cancer and a method and application of using the marker to predict the prognosis of lung cancer. Background technique [0002] Lung cancer is one of the malignant tumors with the fastest-growing morbidity and mortality and the greatest threat to the health and life of the population. In the past 50 years, many countries have reported that the morbidity and mortality of lung cancer have increased significantly. The incidence and mortality of lung cancer in men rank first among all malignant tumors, and the incidence and mortality of lung cancer occupy the second place in women. [0003] In recent years, with the emergence of large-scale sequencing and microarray data, there have been many cases of predicting patient prognosis at the molecular level. In breast cancer, breast cancer 21 gene detection (OncotypeDx) refers to the detection of the expr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/68C12N15/11
CPCC12Q1/6886C12Q2600/118C12Q2600/158
Inventor 张洁霞乐小兵陈梦麟黄凯铃刘艳卉骆颖筠史晓舜
Owner 广州万德基因医学科技有限公司
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