Biomarker for predicting survival time of patient with lung cancer and related product

A biomarker, lung cancer technology, applied in the field of disease diagnosis, which can solve problems such as the limitation of the prediction ability of the TNM staging system

Pending Publication Date: 2021-09-10
BEIJING MEDINTELL BIOMED CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the prediction ability of TNM staging system is also limited, so there is an urgent need for new markers that can accurately predict the prognosis of lung cancer patients (Shi X, Li R, Dong X et al. IRGS: an immune-related gene classifier for lung adenocarcinomaprognosis. Journal of translational medicine, 18(1), 55(2020).)

Method used

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  • Biomarker for predicting survival time of patient with lung cancer and related product
  • Biomarker for predicting survival time of patient with lung cancer and related product
  • Biomarker for predicting survival time of patient with lung cancer and related product

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0084] Example Gene markers associated with diagnosis and prognosis of lung cancer

[0085] 1. Data download

[0086] Obtain the RNA-seq data and clinical information of lung cancer from the TCGA database, remove the samples with missing survival information and 0 survival period, and include a sample size of 496 as the training set; obtain the chip sequencing data and clinical information of lung cancer from the GEO database, remove the survival data For samples with missing information and 0 survival period, 226 samples were included as the validation set.

[0087] 2. Data standardization

[0088] For TCGA RNA-seq data, the Voom method was used for normalization, and for GEO chip data, the RMA method was used for normalization.

[0089] 3. Single factor Cox analysis

[0090] Univariate Cox analysis was performed on the genes in the training set and the validation set, and the genes associated with the survival of lung adenocarcinoma patients in both data sets were screene...

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Abstract

The invention discloses a biomarker for predicting the survival time of a patient with lung cancer and related products. The biomarker comprises ARRB1, GRIA1, HDC and/or KRT8. By detecting the expression level of the biomarker, the prognosis of the patient with lung cancer can be effectively predicted, and guidance is provided for clinicians to carry out individualized treatment.

Description

technical field [0001] The present invention relates to the field of disease diagnosis, more specifically, the present invention relates to biomarkers and related products for predicting the survival period of lung cancer patients. Background technique [0002] Lung cancer is the most common malignant tumor in the world, and its morbidity and mortality rank first among men and women (Bray F, Ferlay J, et al. Global cancer mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians, 68(6), 394-424(2018)). Lung cancer is divided into small cell lung cancer (small cell lung cancer, SCLC) and non-small cell lung cancer (non-small cell lung cancer, NSCLC), 80-85% of lung cancer patients are NSCLC. NSCLC is mainly divided into three histological types, namely lung adenocarcinoma, lung squamous cell carcinoma and large cell carcinoma, among which lung adenocarcinoma is the main histological type, accounting for about 40% (Bender E. Epidemiology: The do...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/6886G01N33/574G16H50/30G16B40/00
CPCC12Q1/6886G01N33/57423G01N33/57488G16H50/30G16B40/00C12Q2600/118C12Q2600/158G01N2800/52
Inventor 杨承刚李雨晨
Owner BEIJING MEDINTELL BIOMED CO LTD
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