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Lung cancer recurrence prediction method based on DNA methylation of tissue-specific enhancement subregion

A tissue-specific, predictive method technology, applied in the field of biomedicine, can solve the problems of unreasonable prediction of recurrence of non-small cell lung cancer, and achieve good prediction efficiency and good uniformity

Active Publication Date: 2021-09-24
WEST CHINA HOSPITAL SICHUAN UNIV
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Problems solved by technology

[0007] The technical problem to be solved by the present invention is: to provide a method for predicting recurrence of lung cancer based on DNA methylation in tissue-specific enhancer regions, to solve the current non-small cell Lung cancer recurrence model is unreasonable in predicting the recurrence of non-small cell lung cancer

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  • Lung cancer recurrence prediction method based on DNA methylation of tissue-specific enhancement subregion
  • Lung cancer recurrence prediction method based on DNA methylation of tissue-specific enhancement subregion
  • Lung cancer recurrence prediction method based on DNA methylation of tissue-specific enhancement subregion

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Embodiment

[0051] Embodiment A method for predicting recurrence of lung cancer based on DNA methylation of tissue-specific enhancer regions, the specific process is as follows:

[0052] (1), such as figure 1 As shown, stage IB / IIA non-small cell lung cancer cases, including relapsed and non-relapsed patients with matched clinical information, were collected, DNA samples were extracted, and simplified bisulfite sequencing was performed.

[0053] (2) In order to enable the lung cancer recurrence model to be applied to the 450K chip platform at the same time, we screened the methylation sites that can be detected by the chip probes for subsequent model establishment. It should be noted that theoretically, this model can be applied to any technology that can detect methylation sites / intervals, so in addition to 450K, the same can be achieved in other methylation detection technologies (such as RRBS, WGBS and 850K). Purpose.

[0054] (3) We divided the samples into high-risk group and low-r...

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Abstract

The invention relates to the field of biomedicine, discloses a lung cancer recurrence prediction method based on DNA methylation of a tissue-specific enhancement subregion, and is used for solving the problem that an existing non-small cell lung cancer recurrence model is unreasonable in non-small cell lung cancer recurrence prediction. The method comprises the following steps: firstly, extracting DNA of a lung cancer patient, and carrying out DNA methylation detection to obtain a beta value of a DNA methylation site of a tissue specific enhancer region; wherein the DNA (deoxyribonucleic acid) methylation sites comprise chr1: 170667082, chr12: 85280518, chr17: 76561412, chr11: 9759297, chr15: 91915828, chr16: 1079990, chr2: 226797988, and chr7: 150477419; and then substituting the beta value of the DNA methylation site into a pre-constructed lung cancer recurrence model, calculating a model score, and obtaining a prediction result according to the model score and a plurality of score thresholds. The method is suitable for predicting the recurrence of the early non-small cell lung cancer.

Description

technical field [0001] The invention relates to the field of biomedicine, in particular to a method for predicting recurrence of lung cancer based on DNA methylation in a tissue-specific enhancer region. Background technique [0002] Non-small cell lung cancer is the leading cause of death from cancer worldwide. Low-dose CT can screen out early-stage lung cancer patients in the population. Surgical resection and postoperative adjuvant therapy for these patients can significantly improve their overall survival rate, but still more than 25% of early-stage (T2N0M0) patients will experience postoperative recurrence , and postoperative recurrence is the main cause of poor prognosis. Considering the extensive heterogeneity of lung cancer, it is an important scientific issue to accurately identify the high-recurrence population among early-stage lung cancer patients. The latest National Comprehensive Cancer Network (NCCN) guidelines recommend six high-risk factors, including tumo...

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Application Information

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IPC IPC(8): G16H50/30G06Q10/04C12Q1/6886
CPCG16H50/30G06Q10/04C12Q1/6886C12Q2600/118C12Q2600/154
Inventor 刘伦旭邓雨岚邓森议陈楠苏雨桃夏粱
Owner WEST CHINA HOSPITAL SICHUAN UNIV
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