Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Biomarker for breast cancer typing and application thereof

A biomarker and breast cancer technology, applied in the field of medical detection, can solve problems such as poor differentiation and pathological judgment errors, and achieve the effect of convenient and precise treatment

Pending Publication Date: 2022-04-05
深圳康华君泰生物科技有限公司
View PDF2 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, limited tissue samples and the need to evaluate an increasing number of therapeutically targeted markers have greatly increased current diagnostic needs, and studies of histological diagnostic reproducibility have shown intra- and inter-pathologist variability : Wrong results of pathological judgment, poorly differentiated tumors and contradictory immunohistochemical results, etc., pose challenges to the accuracy of precision medicine in breast cancer

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
  • Biomarker for breast cancer typing and application thereof
  • Biomarker for breast cancer typing and application thereof
  • Biomarker for breast cancer typing and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] Based on the TCGA public database, a preliminary screening of variant gene markers for pathological subtypes of breast cancer was carried out.

[0060] The screening method is as follows.

[0061] 1. Obtain whole exome sequencing data of tumor tissue of breast cancer patients from TCGA database.

[0062] In this example, a total of 705 cases of breast cancer patients (including 490 cases of invasive ductal carcinoma and 215 cases of invasive lobular carcinoma) were downloaded from whole exome sequencing data, and seven different software were used: Samtools, SomaticSniper, Strelka and VarScan to detect points respectively Mutations; InDels were detected by VarScan, Pindel, GATK and Strelka, respectively.

[0063] 2. According to the difference analysis between the invasive ductal carcinoma group and the lobular carcinoma group.

[0064] The chi-square test was used for statistical analysis, and the variant genes with p≤0.05 and the genes investigated in the literature...

Embodiment 2

[0076] The latent markers obtained in Example 1 were used to train the model.

[0077]1. Using the information of all target markers obtained in Example 1, the TCGA and breast_msk_2018 data sets were combined to train the model, and one sample lacking CNV data was removed, that is, 1962 cases of ductal carcinoma and 603 cases of lobular carcinoma patient tissue samples for detection and judgment , using the random forest model for modeling analysis, the modeling process is as follows figure 1 As shown, according to the 7:3 segmentation, 20 repetitions are performed, and the model AUC is as high as 0.8685, such as figure 2 shown.

[0078] 2. Optimizing 111 markers: By using the random forest model for modeling analysis, 1962 cases of ductal carcinoma and 603 cases of lobular carcinoma were detected and judged, and 20 repetitions were performed according to the division of 7:3. The feature importance of the model in step 1, select the optimal combination of the top 20 MARKER,...

Embodiment 3

[0082] The biomarkers in Example 1 and the model in Example 2 were verified.

[0083] The verification process is as follows.

[0084] 1. Obtaining tissue samples: 897 cases of breast cancer (660 cases of invasive ductal carcinoma and 237 cases of invasive lobular carcinoma) were collected from Jinan University and related FFPE section samples were identified by relevant experts.

[0085] 2. Sample sequencing analysis:

[0086] FFPE tissue samples were analyzed by whole genome sequencing by a third party (Clearcode Biotechnology).

[0087] 3. Use the above 111 marker information to detect and judge the independent verification set, that is, patient tissue samples. According to the prediction test of the 20 marker models obtained in Example 2, the AUC in Example 3 can reach 0.9048, as Figure 6 shown.

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 a biomarker for breast cancer typing, and relates to the technical field of medical detection. When the biomarker is used for typing diagnosis of breast moistening ductal carcinoma or breast moistening lobular carcinoma, the biomarker comprises at least five genes such as CDH1, TP53, GATA3, CBFA2T3, MYC and the like, and the diagnostic power AUC can reach 0.8696; when the biomarker is used for breast cancer Luminal A type, breast cancer Luminal B type, breast cancer HER-2 overexpression type or basal sample breast cancer typing diagnosis, the biomarker comprises at least five genes such as TP53, ERBB2, PWWP2A, SPOP and RARA, the diagnostic power AUC can reach 0.8001, the biomarker has excellent diagnostic power, a molecular level-based discrimination method for different pathologies and molecular subtypes is provided, and the biomarker can be applied to diagnosis of breast cancer Luminal A type, breast cancer Luminal B type, breast cancer HER-2 overexpression type or basal sample breast cancer typing. And mutual verification is provided for pathological diagnosis results, so that case diagnosis results are ensured to be correct, and subsequent precise treatment is facilitated.

Description

technical field [0001] The invention relates to the technical field of medical detection, in particular to a biomarker for typing breast cancer and its application. Background technique [0002] Breast cancer is one of the most common high-incidence malignant tumors around the world, and it is also the malignant tumor with the fastest-rising global morbidity and mortality in the past half century. Among the female population in my country, the annual morbidity and mortality of breast cancer rank first among malignant tumors. [0003] Breast cancer is a heterogeneous disease. The current treatment options for breast cancer are mainly based on pathological classification and staging diagnosis. Pathological classification is generally determined by histology: breast cancer generally distinguishes between non-invasive and invasive, in which invasive breast cancer is advanced, the tumor develops rapidly, and the prognosis is poor. In invasive breast cancer, there are mainly The...

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
IPC IPC(8): C12Q1/6886C12Q1/6869G16B20/20G16B30/00
Inventor 刘鑫贾富建刘康
Owner 深圳康华君泰生物科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com