Identification model for benign and malignant thyroid tumors and application thereof

A technique for identifying models of thyroid tumors, which is applied in the fields of molecular biology and computers, and can solve problems such as expensive, complicated diagnostic operations, and difficult diagnosis of thyroid tumors

Active Publication Date: 2020-07-03
SINGLERA GENOMICS (SHANGHAI) LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies in the prior art, such as the complex diagnostic operation and high price for the differentiation of benign and malignant follicular thyroid tumors, and the difficulty in diagnosing thyroid tumors with undetermined malignant potential, the present invention provides a model sui

Method used

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  • Identification model for benign and malignant thyroid tumors and application thereof
  • Identification model for benign and malignant thyroid tumors and application thereof
  • Identification model for benign and malignant thyroid tumors and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0203] Example 1, marker screening and model construction

[0204] Methylation detection: RRBS technology was used to perform methylation sequencing and library construction on samples from 33 patients with benign thyroid tumor (FTC) and 33 patients with malignant thyroid tumor (FTA).

[0205] Marker screening: compare the methylation detection results with the 147,888 nucleic acid fragments defined in Guo et al. (2017), and find out all detected fragments in the detected DNA samples. According to the mhl calculation method (mhl, mhl3, umhl, and pdr) and the pdr calculation method (Landau et al. (2014)), calculate the methylation score of each nucleic acid fragment and each calculation method in each sample, and screen out the methylation scores in each sample. There are significant differences (corrected p-value less than 0.05) between benign and malignant thyroid tumors and their corresponding algorithms, and 70 combinations of markers and algorithms are obtained.

[0206] ...

Embodiment 2

[0228] Embodiment 2, differentiation of benign and malignant thyroid

[0229] In this example, the model constructed in Example 1 was used to identify benign and malignant thyroid glands from 26 suspected follicular thyroid cancer samples. The process is as follows:

[0230] According to the method of Example 1, a sample-marker numerical matrix of 26 samples similar to Table 3 was constructed.

[0231] Open the R program package and import the numerical matrix of 26 samples-markers to be evaluated

[0232] valdata=read.delim("storage path of sample-marker matrix", sep="\t", as.is=T, row.names=1, header=T, check.names=F)

[0233] Transpose the matrix into a matrix with row names of sample names and columns of methylation marker names

[0234] input=t(valdata)

[0235] And use the adjacent value complement method to make up the NA value

[0236] library(DMwR)

[0237] imputed = knnImputation(imput)

[0238] Reimport the established assessment model of malignant thyroid ca...

Embodiment 3

[0249] Example 3, Assessment of Malignant Potential of Thyroid Tumors of Undetermined Malignant Potential

[0250] In this example, the model constructed in Example 1 was used to evaluate the malignant potential of thyroid tumors in 36 patients with thyroid tumors of undetermined malignant potential (UMP) diagnosed clinically and pathologically.

[0251] Sample processing: After the whole genome DNA is extracted with Qiagen tissue DNA extraction kit, a part of the DNA samples are tested for gene panel mutations formed by 18 malignant tumor genes, including TERT, EIF1AX, HRAS, NRAS, KRAS, BRAF, TP53, PIK3CA , All exon regions of PTEN, GNAS, TSHR, CTNNB1, AKT1 and ETV6, partial intron regions, and mutations in the promoter regions of some genes, as well as fusions of RET, PPARG, ALK and NTRK1. Additional DNA samples were subjected to methylation sequencing based on RRBS technology.

[0252] According to the method of Example 1, a sample-marker numerical matrix of UMP samples si...

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PUM

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Abstract

The invention relates to a methylation marker for identification of benign and malignant thyroid tumors and evaluation of follicular tumors with uncertain malignant potential, and a method for constructing an identification model for benign and malignant thyroid tumors. The method comprises the following steps of: (1) acquiring the methylation levels of candidate sites or fragments in genome DNAsof a tumor sample and a control sample; (2) processing the methylation levels of the sites or fragments by using at least one algorithm selected from a group consisting of mhl, mhl3, umhl and pdr; (3)screening out a site or fragment having significant difference between the processed methylation level of the tumor sample and the processed methylation level of the control sample, and screening outan optional corresponding algorithm, wherein the site or fragment is the methylation marker; and (4) constructing the model for identifying benign and malignant thyroid cancer according to the processed methylation levels of the methylation marker.

Description

technical field [0001] The invention relates to the fields of molecular biology technology and computer, and relates to a model for distinguishing benign and malignant thyroid tumors and a construction method and application thereof. Background technique [0002] Thyroid tumor is a very common tumor, which can be divided into benign and malignant. Benign tumors are divided into follicular thyroid adenoma (FTA) and papillary thyroid adenoma (PTA), among which FTA is the most common benign tumor, accounting for about 70% to 80% of thyroid adenomas. %. Malignant tumors are divided into papillary thyroid carcinoma (PTC), follicular thyroid carcinoma (FTC), anaplastic thyroid carcinoma and medullary thyroid carcinoma. The latter two types are relatively rare. PTC has a low degree of malignancy and a good prognosis, while FTC is a malignant tumor with a high degree of malignancy. In addition, clinically there is also a class of borderline tumors between benign and malignant tum...

Claims

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Application Information

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IPC IPC(8): G16H50/50C12Q1/6886
CPCC12Q1/6886C12Q2600/154G16B40/20G16B25/20G16B25/10
Inventor 刘蕊张桢珍苏志熙
Owner SINGLERA GENOMICS (SHANGHAI) LTD
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