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Method for constructing mathematical model for detecting breast cancer in vitro, and application thereof

A mathematical model, breast cancer technology, applied in the field of medical diagnosis, to achieve the effect of improving precision and accuracy

Pending Publication Date: 2020-09-11
HANGZHOU GUANGKEANDE BIOTECHNOLOGY CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, for now, no screening method is perfect and 100% accurate

Method used

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  • Method for constructing mathematical model for detecting breast cancer in vitro, and application thereof
  • Method for constructing mathematical model for detecting breast cancer in vitro, and application thereof
  • Method for constructing mathematical model for detecting breast cancer in vitro, and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] Using the self-made chemiluminescence detection kit or the self-made flow cytometry fluorescence luminescence detection kit, the concentrations of 11 breast cancer protein markers (CA15-3, TIMP-1, PAI, NMP66, OPN, CEACAM6, RARA, IGFBP1, GRM1, GRIK1, S100A8), the concentration of 13 breast cancer molecular markers (UHRF1, BRCA1, FGFR2, HER-2 / neu, STAT3, Ki-67, PIK3CA, CCNB1 (Cyclin B1), MYBL2, ACTB (b-actin), CTSL2 (Cathepsin L2), CD68, BAG1), the concentrations of 12 breast cancer-related DNA methylation markers (PITX2P2, GSTP1, RASSF1A, RAR-β2, DNMT1, DMAP1, MeCP2, MBD1, CDKN2B, CDKN2A, p21WAF1 / CIP1, RARβ2).

[0031] Perform logistic regression analysis on the test concentrations of the above-mentioned relevant markers to obtain Logit(P)=constant+λ1*P1+λ2*P2+η3*P3+η4*P4...

[0032] Then test the concentration of each marker in the unknown blood sample and substitute it into the regression model. According to the calculated Logit (P) and the judgment standard of the re...

Embodiment 2

[0035] Use the purchased or self-made chemiluminescence method kit to test the concentration of 6 breast cancer protein markers (CA15-3, TIMP-1, OPN, CEACAM6, CEA, IGFBP1) in the blood sample, and use the fluorescence in situ hybridization method to test the concentration of the six breast cancer protein markers in the blood sample. 9 molecular markers of breast cancer (miR-21, miR-20a, miR-214, miR-181a, miR-1304, miR-141, miR-200a / c, miR-203, miR-210), with purchased The concentration of 13 breast cancer autoantibodies (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) in blood samples was detected by immunofluorescence method, and urine by flow cytometry method or 11 breast cancer-associated exosomes (miR-27a, miR-451, miR-21-5p, miR-21, miR-221, TGF-β1, HMGB1, CagA, GKN1, UBR2, TRIM3) in blood, using Fluorescence flow method to detect 7 related inflammatory factors and growth factors in urine or blood: (CRP, Ch17CEP, sHER2, MAD...

Embodiment 3

[0040] Breast cancer protein markers are CA15-3, TIMP-1, uPA, PAI, NMP66, OPN, CEACAM6, Bc1, IGFBP1, breast cancer molecular diagnostic markers are UHRF1, BRCA1, BRCA2, FGFR2, STAT3, PIK3CA, MYBL2, GAPDH , RPLPO, BCL2, breast cancer-related DNA methylation markers are PITX2P2, APC, GSTP1, RASSF1A, RAR-β2, DNMT1, obtain the concentration values ​​of these markers in the sample, perform natural logarithmic transformation, and eliminate After no contributing markers, the resulting regression model is: Logit(P)=-2.43+1.012*Ln(CA15-3)+0.452*Ln(uPA)+0.785*Ln(OPN)+0.652*Ln(CEACAM6) +0.741*Ln(IGFBP1)+1.210*Ln(UHRF1)+0.471*Ln(BRCA1)+0.723*Ln(FGFR2)+0.457*Ln(PIK3CA)+0.789*Ln(RASSF1A)+0.354*Ln(PITX2P2)+ 0.987*Ln(APC)+0.541*Ln(GSTP1), where Ln is the natural logarithm.

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Abstract

The invention provides a method for constructing a mathematical model for detecting breast cancer in vitro. The method comprises the following steps: obtaining concentrations of at least two breast cancer markers from a sample, and carrying out logistic regression on the measured concentration value of each marker, substituting the detected concentration into a logistic regression model to obtainan analysis result, and carrying out comprehensive breast cancer analysis by using the concentration of each marker and the logistic regression analysis result. The invention further provides an application of the method.

Description

technical field [0001] The present application relates to the technical field of medical diagnosis, in particular to a method for constructing a mathematical model for in vitro detection of breast cancer and its application. Background technique [0002] The female mammary gland is composed of skin, fibrous tissue, mammary glands and fat. Breast cancer is a malignant tumor that occurs in the mammary gland epithelial tissue. 99% of breast cancers occur in women and only 1% in men. [0003] The mammary gland is not an important organ to maintain human life activities, and breast cancer in situ is not fatal; but because breast cancer cells lose the characteristics of normal cells, the connections between cells are loose and easy to fall off. Once the cancer cells fall off, the free cancer cells can spread throughout the body with the blood or lymph fluid, forming metastasis, which is life-threatening. At present, breast cancer has become a common tumor that threatens women's ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B40/20G16H50/30
CPCG16B40/20G16H50/30
Inventor 高俊莉高俊顺高金波
Owner HANGZHOU GUANGKEANDE BIOTECHNOLOGY CO LTD
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