Oncogenic Splice Variant Detection via Baseline Comparison
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Solution Overview
Problem
Traditional methods for determining oncogenic splice variants require multiple samples, leading to increased costs and reagent consumption, as they involve sequencing both tumor and non-tumor samples to identify differences in gene expression.
Innovation Solution
A method and system that analyze a single biological sample by determining sample splice junctions, comparing them to a set of baseline splice junctions from healthy samples, and identifying filtered sample splice junctions that do not overlap with the baseline junctions, which are potential oncogenic events, thereby reducing the need for multiple samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple samples (tumor and non-tumor) are sequenced to identify splice variants, then measurement precision is improved, but cost and reagent consumption increase
Solution Approach 1:
The patent extracts only the tumor sample for sequencing while using a reference database of normal tissue splice junctions for comparison. This eliminates the need to sequence normal tissue samples from each patient, directly reducing reagent consumption while maintaining the ability to identify oncogenic splice variants through differential analysis against the reference database.
Solution Approach 2:
The patent performs preliminary action by pre-constructing a comprehensive reference database of splice junctions from normal tissues before patient sample analysis. This reference database is created once and reused across multiple patient samples, eliminating the need to repeatedly sequence normal tissues and significantly reducing overall reagent consumption while enabling accurate identification of abnormal splice variants.
2Reliability
If multiple samples are sequenced per patient, then reliability of oncogenic event detection is improved, but cost increases
Solution Approach 1:
The patent creates a universal reference database that serves multiple functions: it represents normal tissue splice junctions across diverse populations, provides a baseline for comparing all patient samples, and enables reliable detection of oncogenic variants. This single reference resource replaces the need for individual normal tissue sequencing for each patient, reducing costs while maintaining detection reliability.
Solution Approach 2:
The patent uses a copied reference version of normal tissue splice junctions stored in a database rather than requiring the original normal tissue samples for each patient. This copying approach allows unlimited reuse of the reference data across numerous patient samples without additional reagent consumption, maintaining reliability through consistent comparison while dramatically reducing per-sample costs.
3Measurement precision
If traditional de-novo splice transcript identification is performed, then comprehensive splice variant detection is achieved, but computational complexity increases
Solution Approach 1:
The patent extracts and focuses analysis specifically on splice junction regions rather than performing comprehensive de-novo assembly of entire splice transcripts. By targeting only the junction points and comparing them against a reference database of normal junctions, the method achieves effective oncogenic variant detection with significantly reduced computational complexity compared to full transcript reconstruction.
Solution Approach 2:
The patent applies partial action by performing splice junction analysis rather than complete de-novo transcript assembly. This partial approach focuses computational resources on the most critical regions for oncogenic detection (the splice junctions themselves) while relying on the reference database for contextual information, achieving effective detection with reduced computational burden.
Data Source
AI summary
Presented herein are systems and methods for identifying splice variants. The techniques include determining one or more sample splice junctions from a plurality of RNA sequence reads from a single biological sample, retrieving a set of baseline splice junctions determined from a plurality of healthy RNA samples and comparing the one or more sample splice junctions to the set of baseline splice junctions to identify one or more filtered sample splice junctions comprising sample splice junctions that do not overlap with the baseline splice junctions, wherein the one or more filtered sample splice junctions are candidate oncogenic events.