Kit and system for prognosis prediction of metastatic colorectal cancer

A colorectal cancer and prediction system technology, applied in the field of biomedicine, can solve problems such as the limitations of molecular heterogeneity in metastatic colorectal cancer, and achieve good prediction results

Active Publication Date: 2019-09-17
THE SIXTH AFFILIATED HOSPITAL OF SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Current prognostic models that use clinical parameters of tissue to predict individual patients have limitations in capturing molecular heterogeneity in metastatic colorectal cancer

Method used

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  • Kit and system for prognosis prediction of metastatic colorectal cancer
  • Kit and system for prognosis prediction of metastatic colorectal cancer
  • Kit and system for prognosis prediction of metastatic colorectal cancer

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0044] Construction of a prognosis prediction model for metastatic colorectal cancer

[0045] (1) Gene expression profiles of frozen colorectal cancer tumor tissue samples from 4 public cohorts were analyzed, including datasets from TCGA CRC and 3 microarray datasets (GSE39582, GSE39084, and GSE17536) obtained from Gene Expression Omnibus . In this example, 192 metastatic colorectal cancer patients with valid survival information were included, and 18113 genes were analyzed. First, 4172 genes were obtained by filtering the median absolute deviation, that is, Median Absolute Deviation greater than 0.5. Further sampling and analysis were carried out by using sampling technology, and 197 prognostic genes were obtained. Finally, a prognostic gene signature (PGS) consisting of 15 genes associated with the prognosis of metastatic colorectal cancer was constructed using the LASSO Cox model. The 15 genes associated with the prognosis of metastatic colorectal cancer are: ACOT11, C12...

Embodiment 2

[0051] Prediction of Prognosis in Metastatic Colorectal Cancer

[0052] (1) qPCR reaction detection

[0053] Detect the expression levels of the following target genes in patients with metastatic colorectal cancer to be predicted, that is, the Ct value of mRNA: ACOT11, C12orf45, CHDH, COX17, CTNNB1, CYP2S1, DDTL, DUSP18, FAM221A, FGFR4, KLC4, LARS2, PFDN6, SLC27A3 and TNFRSF11A.

[0054] Use qPCR technology to detect the expression level of the target gene:

[0055] Use the primer pairs of the genes in the following table 1 to detect the expression level of the corresponding genes

[0056] Table 1 Primer sequences for detection of genes related to prognosis of metastatic colorectal cancer

[0057]

[0058]

[0059] a) qPCR reaction system:

[0060] Prepare the mixture of template RNA and primers as follows:

[0061]

[0062] *The reaction system can be scaled up

[0063] *Oligo(dT)15Primer and Random Primer are used at the same time, which can effectively improv...

Embodiment 3

[0080] This embodiment provides a metastatic colorectal cancer prognosis prediction device, the prediction device includes: a gene expression level information acquisition module, a risk value calculation module and a prediction module;

[0081] The gene expression level information acquisition module is used to obtain the expression level information of the target gene in patients with metastatic colorectal cancer.

[0082] Among them, the target genes include the following genes:

[0083] ACOT11, C12orf45, CHDH, COX17, CTNNB1, CYP2S1, DDTL, DUSP18, FAM221A, FGFR4, KLC4, LARS2, PFDN6, SLC27A3, and TNFRSF11A.

[0084] The risk value calculation module is used to substitute the expression level information of the target gene into the prediction model to calculate the risk value;

[0085] The calculation formula of the prediction model is as follows:

[0086] Risk value=-0.073×expACOT11+0.152×expC12orf45-0.179×expCHDH+0.518×expCOX17-0.054×expCTNNB1-0.065×expCYP2S1-0.001×expDDT...

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Abstract

The invention discloses a kit and system for prognosis prediction of a metastatic colorectal cancer and relates to the field of biomedicine. The kit comprises a reagent for detecting the expression level of a target gene, wherein the target gene is selected from one or more genes in the group consisting of ACOT11, C12orf45, CHDH, COX17, CTNNB1, CYP2S1, DDTL, DUSP18, FAM221A, FGFR4, KLC4, LARS2, PFDN6, SLC27A3 and TNFRSF11A, the expression levels of the target genes are detected by using the kit, the prognosis condition of the metastatic colorectal cancer can be stably predicted according to the detection result, the prediction result is reliable, the kit has a clinical application prospect, and a new prediction thought or strategy is provided for the prognosis of the metastatic colorectal cancer.

Description

technical field [0001] The invention relates to the field of biomedicine, in particular to a kit and system for prognosis prediction of metastatic colorectal cancer. Background technique [0002] Metastatic colorectal cancer (mCRC) is the third most common cause of cancer death worldwide, and the incidence of metastatic colorectal cancer is increasing, especially in younger patients. Despite the emergence of new treatment options, the prognosis of patients with metastatic colorectal cancer varies from curable oligometastatic disease to rapidly progressive fatal disease. In recent years, studies have suggested that this is mainly caused by the molecular heterogeneity of cancer patients. [0003] Gene molecular markers refer to the establishment of mathematical models based on the expression of a group of genes through machine learning to predict specific clinical targets. In recent years, gene expression detection methods have been quite mature, including high-throughput RN...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/6886G16H50/30G16B40/00
CPCC12Q1/6886G16B40/00G16H50/30C12Q2600/118
Inventor 邹一丰高峰吴小剑柯嘉谈应鑫
Owner THE SIXTH AFFILIATED HOSPITAL OF SUN YAT SEN UNIV
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