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Sensitively detecting copy number variations (CNVs) from circulating cell-free nucleic acid

A cell nucleic acid and copy number technology, applied in genomics, instrumentation, sequence analysis, etc., can solve the problem of reduced usefulness of RC method

Pending Publication Date: 2021-10-29
RGT UNIV OF CALIFORNIA +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the usefulness of the RC method will be reduced when the fraction of tumor-derived cfDNA in the sample is low

Method used

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  • Sensitively detecting copy number variations (CNVs) from circulating cell-free nucleic acid
  • Sensitively detecting copy number variations (CNVs) from circulating cell-free nucleic acid
  • Sensitively detecting copy number variations (CNVs) from circulating cell-free nucleic acid

Examples

Experimental program
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Effect test

Embodiment 1

[0211] Applying the cfCNV method to liver cancer samples to deconvolute tumor cfDNA and detect cancer

[0212] The cfCNV method is implemented as follows. In operations 1 and 2, a posterior probabilistic approach was used to classify and count tumor-derived sequencing reads among multiple sequencing reads obtained from cfDNA samples from liver cancer patients. In step 3, only leukocytes from the same blood sample were used to construct a control profile for normalization without taking into account other sources of experimental and technical bias. In step 4, the scores of blocks with abnormal log ratios were used as the final cancer indicator score.

[0213] To perform an example of a method according to a disclosed embodiment, whole genome bisulfite sequencing (WGBS) data of plasma cfDNA samples were collected from 15 liver cancer patients and 5 healthy subjects.

[0214] The performance of the cfCNV method was compared to that of a conventional sequencing read counting (RC...

Embodiment 2

[0218] Further improvements to the cfCNV method

[0219] The cfCNV method described herein can be improved by one or more of the following methods.

[0220] First, the cfCNV method can detect small CNVs. In general, using a block size of 1M base pairs ensures a sufficient number of tumor-derived sequencing reads for CNV detection, but flattens the signal of small CNVs. Therefore, advanced genome segmentation methods are suitable for automatically identifying CNV blocks with variable sizes.

[0221] Second, the cfCNV method can improve the correction of systematic bias by analyzing multiple cfDNA samples simultaneously. By modeling sequencing read counts from multiple samples per genomic region, some potential systematic biases that could not be identified in a single sample, such as poor-quality markers, were readily identified. Such a population-based strategy can fully utilize the information of multiple cfDNA samples and achieve higher performance CNV detection compared ...

Embodiment 3

[0224] Detection of prenatal disorders by inferring CNVs in placental / fetal DNA

[0225] The methods and systems described herein can be used to infer placental CNVs through methylation sequencing data analysis of maternal cfDNA to detect prenatal conditions (eg, diseases or conditions in a pregnant subject or a pregnant subject's fetus). Specifically, select its methylation pattern (see Figure 5 Three modes at different resolutions) specific genomic regions or single CpG sites that can distinguish the placenta from all other normal tissues and normal cfDNA samples as fetal methylation markers. The analysis steps remained the same (for the detection of CNVs in cancer) except that multiple placental methylation markers were used instead of cancer markers. Profiles of normalized placental read abundance were constructed and used to estimate CNV status in each genomic block. The inferred CNV status is then used to detect prenatal conditions such as fetal aneuploidy (eg Down sy...

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Abstract

The present disclosure provides methods and systems for detecting or inferring levels of Copy Number Variants (CNVs) in cell-free nucleic acid samples to detect or assess cancer and prenatal diseases. Cell-free nucleic acid methylation sequencing data may be utilized to distinguish tumor-derived or fetal-derived sequencing reads from normal cfDNA sequencing reads. Each cell-free nucleic acid sequencing read (e.g., containing tumor or fetal methylation markers) may be classified as corresponding to a tumor / fetal-derived or a normal-plasma cell-free nucleic acid, based on the methylation cfDNA sequencing data (e.g., obtained using Bisulfite sequencing or bisulfite-free sequencing methods) and tumor / fetal methylation markers. Next, a profile of the tumor / fetal-derived sequencing read counts may be constructed and then normalized. The CNV status (e.g., gain or loss) of each genomic region may be inferred, and a diagnosis or prognosis can be made based on a subject's inferred CNV profile.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of U.S. Provisional Patent Application No. 62 / 721,410, filed August 22, 2018, which is hereby incorporated by reference in its entirety. [0003] Government interests [0004] This invention was made with government support under HL108645 awarded by the National Institutes of Health. The government has certain rights in this invention. Background technique [0005] Circulating cell-free nucleic acids (e.g., cell-free DNA (cfDNA) and cell-free RNA (cfRNA)) (e.g., present in plasma) have been implicated in cancer and prenatal diagnosis and prognosis. A biomarker of great potential. Therefore, the detection and characterization of cfDNA and / or cfRNA represents a promising approach for cancer and prenatal diagnosis and prognosis. Furthermore, because cfDNA and / or cfRNA analysis involves performing liquid biopsies rather than traditional tissue biopsies, it allows for the diagnosis, pro...

Claims

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Application Information

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IPC IPC(8): G16B30/00G16B40/00G16B20/10
CPCG16B20/10G16B30/00G16B40/30G16B40/00
Inventor 向红·婕思敏·周李文渊李硕刘俊吉倪晓晖
Owner RGT UNIV OF CALIFORNIA
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