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Featured lincRNA expression profile combination and early stage prediction method for renal clear cell carcinoma

A technology of renal clear cell carcinoma and prediction method, which is applied in the field of characteristic lincRNA expression profile combination and early prediction of renal clear cell carcinoma, and can solve problems such as difficulty in defining critical values

Inactive Publication Date: 2020-10-23
FOSHAN UNIVERSITY
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Problems solved by technology

Due to the overlapping expression distribution of individual lincRNA molecules in tumors and normal populations, it is difficult to define the cut-off value for early prediction

Method used

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  • Featured lincRNA expression profile combination and early stage prediction method for renal clear cell carcinoma
  • Featured lincRNA expression profile combination and early stage prediction method for renal clear cell carcinoma
  • Featured lincRNA expression profile combination and early stage prediction method for renal clear cell carcinoma

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Embodiment 1

[0117] A method for early prediction of clear cell renal cell carcinoma based on a combination of characteristic lincRNA expression profiles, comprising the following steps:

[0118] Step 1. Obtain stable and differentially expressed lincRNA (characteristic lincRNA) in patients with early-stage clear cell renal cell carcinoma. For details, see figure 1 .

[0119] Step 1.1. Download the tumor tissue and paracancerous tissue transcriptome data and clinical data of clear cell renal cell carcinoma patients from the Genomic Data Commons Data Portal database, and obtain the read counts of the tumor tissue gene expression profiles of clear cell renal cell carcinoma patients, and perform logarithmic transformation.

[0120] Step 1.2: Select lincRNAs with a certain expression abundance, that is, the readcounts of lincRNAs in all samples are greater than or equal to 10, see formula (1) for details.

[0121] Step 1.3: Select patients with clear cell renal cell carcinoma whose disease st...

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Abstract

The invention discloses a featured lincRNA expression profile combination and an early stage prediction method for a renal clear cell carcinoma. The nucleotide probe sequence of the lincRNA is disclosed by SEQ ID NO.1-26. The early-stage risk assessment of the renal clear cell carcinoma on the basis of the characteristics of the lincRNA expression profile combination has high precision and accuracy (ROC (Receiver Operating Curve) ACU (Area Under The Curve) is equal to 0.964). Only the relative expression quantities of the above 26 types of lincRNA need to be obtained, an early stage illness probability of the renal clear cell carcinoma is given through a support vector machine model, and the early stage illness probability can be taken as a reference basis for the early stage prediction ofthe renal clear cell carcinoma.

Description

technical field [0001] The invention belongs to the fields of biotechnology and medicine, and in particular relates to a combination of characteristic lincRNA expression profiles and an early prediction method for renal clear cell carcinoma. Background technique [0002] Kidney renal clear cell carcinoma accounts for about 70%-80% of renal cell carcinomas. Clear cell renal cell carcinoma is often asymptomatic in the early stage, or only has systemic symptoms such as fever and fatigue, so early diagnosis is difficult. Global Burden of Disease (GBD) data shows that in 2017, the number of people suffering from kidney cancer worldwide exceeded 2.1 million, of which about 270,000 were in China. In 2017, the number of deaths from kidney cancer worldwide was about 140,000, accounting for 0.25% of the total number of deaths. The number of patients who died in China in 2017 was about 17,000, accounting for 0.16% of the total number of deaths. The statistical results show that from...

Claims

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Application Information

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IPC IPC(8): C12Q1/6886G16B25/10G16B35/00G16B5/00G16B40/00G16H50/20
CPCC12Q1/6886C12Q2600/112C12Q2600/158C12Q2600/178G16H50/20G16B5/00G16B25/10G16B35/00G16B40/00
Inventor 亓飞孙婷婷刘玮刘大海李文兴
Owner FOSHAN UNIVERSITY
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