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Cancer precise chemotherapy typing marker screening method, chemotherapy sensitivity molecular typing method and application

A screening method and molecular typing technology, applied in the field of tumor clinical medicine, can solve problems such as unreliable answers, and achieve the effect of long storage time, large quantity, and complete follow-up information

Pending Publication Date: 2020-11-13
北京谷海天目生物医学科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the patent does not actually answer which patients are suitable for chemotherapy, what scheme is suitable, and the best use cycle and other pain points in the field of tumor medicine

Method used

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  • Cancer precise chemotherapy typing marker screening method, chemotherapy sensitivity molecular typing method and application
  • Cancer precise chemotherapy typing marker screening method, chemotherapy sensitivity molecular typing method and application
  • Cancer precise chemotherapy typing marker screening method, chemotherapy sensitivity molecular typing method and application

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0080] Example 1 Obtaining protein expression profile data of gastric cancer FFPE samples

[0081] Protein extraction and analysis were performed on 1020 FFPE samples of known gastric cancer cases, and the detailed steps were based on the steps described in the first part of Example 1 in the patent application CN110146636A.

[0082] Perform mass spectrometry detection on the sample, and for detection and analysis, refer to the specific implementation part of the patent application CN108445097A "3. Mass spectrometry detection of gastric cancer protein samples; 4. Mass spectrometry data analysis of gastric cancer protein samples":

[0083] Use the Firmiana computing platform to analyze mass spectrometry data, identify peptides and assemble proteins, and use the iBAQ algorithm for protein quantification to form protein expression profile data, including: protein identifiers, such as Protein GInumber, Accession or Gene Symbol; corresponding protein Quantitative expression values ​...

Embodiment 2

[0084] Example 2 Selection of typing markers

[0085] Based on the data in Example 1, the typing markers were selected, and the specific steps were as follows:

[0086] 1) Protein expression profile preprocessing and experimental filtering

[0087] a) High-confidence protein screening: Quantitative proteins are required to contain at least one unique peptide with an ion score greater than or equal to 20, and at least two peptides with an ion score greater than or equal to 20, or three ion scores Peptides with a value greater than or equal to 20.

[0088] b) Eliminate experiments with a protein identification frequency lower than 700 (this step can be adjusted according to the actual number of protein identifications in different cancers and different sample types).

[0089] c) Divide the 1020 samples into a discovery set (742 samples) and a validation set (278 samples).

[0090] d) Remove redundant proteins based on the discovery set composed of 742 samples: the sum of 5% p...

Embodiment 3

[0101] Example 3 Molecular classification of precision chemotherapy for gastric cancer

[0102] Part I: Molecular classification of precision chemotherapy

[0103] (1) Perform the following typing steps on the typing marker set obtained in Example 2:

[0104] a. Use log(1+x) to convert the FOT value of each protein in the typing marker set, where x is the FOT value of the protein; the converted data are shown in Table 2 below (in the table, the row is typing markers, columns are experiments):

[0105] Table 2

[0106]

[0107] b. Use the non-negative matrix factorization (NMF) consensus clustering method to classify the typing marker set, and assign an NMF typing label to each typing, as follows:

[0108] Load the R language package CancerSubtypes, use the ExecuteCNMF function to analyze the expression profile of the typing markers, set the parameter clusterNum to 2, and set nrun to 50.

[0109] The NMF typing results are shown in Table 3:

[0110] table 3

[0111] ...

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Abstract

The invention relates to a cancer precise chemotherapy typing marker screening method, a chemotherapy sensitivity molecular typing method and application. According to the method, a typing marker is obtained from a multi-center and large sample queue to discover molecular typing, and a classifier is constructed by using the typing marker or differential protein obtained based on a typing label asa selection characteristic; when the classifier carries out classification application, expression profile data of a collected sample is input; and after expression spectrum data preprocessing, classifier feature matching and logarithm conversion are performed, prediction is performed by the classifier constructed through a machine learning classification algorithm or an artificial intelligence model; and finally an output label of a chemotherapy sensitive group or a chemotherapy insensitive group is obtained, and molecular typing of accurate chemotherapy is performed, so that the problem of pain spots in the field of tumor medical treatment is solved, wherein the problems comprise: accurately judging whether chemotherapy is beneficial to people, providing first-line medication regimen optimal combination recommendation and providing chemotherapy regimen optimal period recommendation.

Description

technical field [0001] The present invention relates to the field of tumor clinical medicine, in particular to a method for screening cancer precision chemotherapy typing markers, a molecular typing method for chemotherapy sensitivity and an application thereof. Background technique [0002] According to the latest national cancer statistics released by the National Cancer Center of China in January 2019, cancer has become one of the major public health problems that seriously threaten the health of the Chinese population. Malignant tumor deaths account for 23.91% of all deaths among residents, and In the past ten years, the incidence and death of malignant tumors have continued to rise. The annual medical expenses caused by malignant tumors exceed 220 billion, and the prevention and control situation is severe. [0003] Taking gastric cancer as an example, gastric cancer is the fifth most common tumor in the world, and the third leading cause of cancer death after lung canc...

Claims

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Application Information

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IPC IPC(8): G16B20/00G16B35/20G16B40/00C12Q1/6886G01N33/574
CPCG16B20/00G16B35/20G16B40/00C12Q1/6886G01N33/57484G01N33/57446C12Q2600/106C12Q2600/112C12Q2600/158
Inventor 秦钧占冬冬黄文雯李亚卓郑乃仁汪宜沈琳陈凛赵青川王宏伟
Owner 北京谷海天目生物医学科技有限公司
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