Chromosomal Interval Analysis for Non-Invasive CNS Cancer Detection
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Solution Overview
Problem
Current methods for diagnosing and monitoring central nervous system (CNS) cancers lack reliable biomarkers, leading to invasive procedures like neurosurgical biopsies due to low sensitivity and the inability to distinguish cancer from non-neoplastic processes, and existing imaging strategies are inadequate.
Innovation Solution
A method involving obtaining a DNA sample, analyzing chromosomal sequences, mapping nucleic acid sequences to reference chromosomes, dividing the DNA into genomic intervals, quantifying features, and comparing these features across intervals to detect chromosomal abnormalities, thereby identifying or monitoring CNS cancers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cytology on cerebrospinal fluid is used for diagnosis, then sensitivity can be improved with large volumes, but multiple lumbar punctures are required and the sensitivity remains as low as 2%
Solution Approach 1:
The patent replaces mechanical cytological examination with molecular sequencing technology. Instead of visually examining cells under a microscope (mechanical/optical system), the invention uses DNA sequencing and bioinformatic analysis to detect cancer-derived DNA fragments in CSF, achieving superior sensitivity without requiring multiple procedures
Solution Approach 2:
The invention changes the detection parameter from cellular morphology (cytology) to molecular genetic markers (chromosomal sequences, copy number variations, mutations). This parameter transformation enables detection of cancer at much lower concentrations of tumor cells in CSF, dramatically improving sensitivity while reducing the volume of CSF needed
2Object-affected harmful factors
If MRI imaging is used to detect CNS cancer, then non-invasive detection is achieved, but the ability to distinguish cancer from inflammatory or non-neoplastic processes is lost
Solution Approach 1:
The patent replaces anatomical imaging (MRI) with molecular genetic analysis. Instead of visualizing structural abnormalities that cannot distinguish cancer from inflammation, the invention sequences DNA to detect cancer-specific chromosomal alterations, achieving both non-invasiveness and high diagnostic specificity
Solution Approach 2:
The invention introduces cerebrospinal fluid as an intermediary medium containing tumor-derived DNA fragments. This intermediary carries molecular information from the tumor to the laboratory, enabling non-invasive detection of cancer-specific genetic markers that provide definitive diagnostic information
3Measurement precision
If neurosurgical biopsy is performed to diagnose CNS neoplasms, then definitive diagnosis is achieved, but surgical risks including neurological injury and hospitalization are incurred
Solution Approach 1:
The patent replaces surgical biopsy with molecular sequencing of CSF DNA. Instead of physically removing and examining tissue (invasive mechanical procedure), the invention analyzes DNA fragments in CSF to detect cancer-specific genetic alterations, achieving equivalent or superior diagnostic accuracy without surgical risks
Solution Approach 2:
The invention uses CSF DNA as an intermediary that carries diagnostic information from the tumor without requiring direct tissue sampling. The DNA fragments shed by tumor cells into the CSF serve as a surrogate for the tumor itself, enabling non-invasive definitive diagnosis
Data Source
AI summary
Provided herein are methods of identifying a subject as having a central nervous system (CNS) cancer that include (a) obtaining a DNA sample from the subject; (b) analyzing a plurality of chromosomal sequences in the DNA sample; (c) determining at least a portion of a nucleic acid sequence of one or more of the plurality of chromosomal sequences; (d) mapping the determined nucleic acid sequence to a reference chromosome; (e) dividing the DNA sample into a plurality of genomic intervals; (f) quantifying a plurality of features for the one or more nucleic acid sequences mapped to the genomic intervals; and (g) comparing the plurality of features in a first genomic interval with the plurality of features in one or more different genomic intervals and detecting a chromosomal abnormality in the DNA sample, thereby identifying the subject as having the CNS cancer.


