Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Application of PINK1 as diagnostic marker in construction of lung squamous cell carcinoma prognosis prediction model

A technology of diagnostic markers and predictive models, applied in the field of biomedicine, to achieve high accuracy, high sensitivity, reduce treatment costs and discomfort experience

Pending Publication Date: 2021-06-04
JINSHAN HOSPITAL FUDAN UNIV
View PDF2 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There is no report about the application of PINK1 of the present invention as a diagnostic marker in the construction of a prognosis prediction model for lung squamous cell carcinoma

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Application of PINK1 as diagnostic marker in construction of lung squamous cell carcinoma prognosis prediction model
  • Application of PINK1 as diagnostic marker in construction of lung squamous cell carcinoma prognosis prediction model
  • Application of PINK1 as diagnostic marker in construction of lung squamous cell carcinoma prognosis prediction model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0023] Example 1 Model Construction and Effect Verification

[0024] 1. Method

[0025] 1.1 The training set comes from the RNA sequencing data and clinical data of 326 cases of lung squamous cell carcinoma from the TCGA database, and the expression profiles of autophagy-related genes (Autophagy-Related-Genes, ARGs) are obtained, and the verification set comes from the RNA sequencing data of 78 cases of lung squamous cell carcinoma from the GTO database , to obtain all RNA expression profiles and autophagy-related genes (Autophagy-Related-Genes, ARGs) expression profiles.

[0026] 1.2 The ARGs related to prognosis were screened out through survival analysis, and then the most critical survival-related ARGs (PINK1) were obtained by the random forest method, and a risk prediction model based on this gene was constructed through the deep machine learning method of the random forest. Patients were divided into low-risk and high-risk groups according to the model. The model was v...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the technical field of bio-medicine, in particular to application of PINK1 serving as a diagnostic marker in construction of a lung squamous cell carcinoma prognosis prediction model. The biomarker PINK1 and other clinical indexes are used in a combined mode, and lung squamous cell carcinoma prognosis detection can be assisted. According to the invention, screening and construction are carried out after full transcriptome sequencing and machine learning of a lung squamous cell carcinoma specimen based on large-sample anti-tumor immuno-therapy, so that the prognosis condition of a lung squamous cell carcinoma patient can be efficiently and accurately predicted; and meanwhile, according to the correlation between the risk and different immune cell infiltration levels, immune-related pathways, key immune checkpoint inhibitor expression levels and the like, comprehensive evaluation of the tumor immune micro-environment is achieved, effective guidance is provided for clinicians to make a treatment decision on lung squamous cell carcinoma patients, invalid treatment is reduced, and therefore, the treatment cost and discomfort experience of the patients are reduced.

Description

technical field [0001] The present invention relates to the technical field of biomedicine, specifically, the application of PINK1 as a diagnostic marker in constructing a prognosis prediction model of lung squamous cell carcinoma. Background technique [0002] Lung cancer is the most common cause of cancer-related death in the world today, and 80% of it is non-small cell lung cancer (NSCLC). TNM staging is a generally accepted clinical staging system, which is used to predict the prognosis and guide the treatment of patients with non-small cell lung cancer. However, the current TNM staging system is far from adequate to accurately predict the prognosis of NSCLC patients. For example, for lung cancer patients, even in clinical stage I, the recurrence rate of lung cancer is as high as 35-50%. In addition, a considerable number of patients can be cured only by surgery, and these patients should be able to avoid the extremely strong side effects of adjuvant chemotherapy based...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G16B5/00G16B40/00G16C20/50G16H50/30C12Q1/6886
CPCG16B5/00G16B40/00G16C20/50G16H50/30C12Q1/6886C12Q2600/158C12Q2600/118
Inventor 乔田奎罗露梦武多娇庄喜兵
Owner JINSHAN HOSPITAL FUDAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products