Gene Fusion Detection in FFPE Tissue via Hybridization Capture
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Solution Overview
Problem
Current methods for detecting gene fusions and alternative spliced junctions in cancer, particularly in breast cancer, are not well-suited for analyzing formalin-fixed, paraffin-embedded (FFPE) tissue samples due to RNA degradation and low complexity of libraries generated from these samples.
Innovation Solution
A bioinformatics approach that utilizes multiplexed, whole genome sequencing to identify gene fusion and alternative spliced junctions in FFPE RNA-sequencing datasets, employing template sets to filter false positives and align reads accurately, and correlating expression levels to predict prognosis and recurrence risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current detection methods are used on FFPE tissue samples, then the analysis can be performed with standard clinical materials, but the RNA degradation and low library complexity prevent accurate identification of gene fusions and alternative spliced junctions
Solution Approach 1:
The method performs preliminary enrichment of fusion transcripts and alternative spliced junctions before sequencing by designing probes that specifically hybridize to these targets. This preliminary action compensates for the degraded RNA quality in FFPE samples by concentrating the rare intact fusion transcripts that remain, enabling accurate identification despite the overall RNA degradation in the sample
Solution Approach 2:
The invention changes the detection parameters by using targeted hybridization capture with specifically designed probes rather than whole transcriptome sequencing. This parameter change allows the method to work effectively with the low complexity and degraded nature of FFPE RNA by focusing sequencing resources on enriched target regions where fusion transcripts are concentrated
2Adaptability or versatility
If whole transcriptome sequencing is performed on FFPE samples, then comprehensive gene fusion detection is possible, but the low complexity and small insert sizes of FFPE libraries reduce detection sensitivity
Solution Approach 1:
The invention segments the whole transcriptome into targeted regions by using probe sets that specifically capture fusion transcripts and alternative spliced junctions. This segmentation allows the method to achieve comprehensive detection capability across multiple gene fusions while concentrating sequencing depth on these segmented targets, thereby maintaining high detection sensitivity despite the low complexity of FFPE libraries
Solution Approach 2:
The method adds a dimension of targeted enrichment before sequencing by implementing a two-step process: first enriching fusion transcripts through hybridization capture, then performing sequencing. This dimensional addition transforms the approach from direct whole transcriptome sequencing to an enriched targeted sequencing workflow, enabling both comprehensive detection and high sensitivity in degraded FFPE samples
3Ease of manufacture
If standard RNA sequencing protocols are used on FFPE samples, then the workflow remains simple and compatible with clinical materials, but the RNA degradation results in false positives and inaccurate alignment
Solution Approach 1:
The invention introduces an intermediary enrichment step using specifically designed probes that hybridize to fusion transcripts and alternative spliced junctions. This intermediary step acts as a mediator between the degraded FFPE RNA and the sequencing process, selectively capturing intact target molecules while excluding degraded background RNA, thereby improving read alignment accuracy without complicating the overall workflow
Solution Approach 2:
The method performs preliminary enrichment and validation steps before final sequencing and analysis. This preliminary action includes hybridization capture of fusion transcripts and quality control measures that eliminate false positives early in the workflow, maintaining simplicity while significantly improving measurement precision through pre-screening of the degraded FFPE RNA population
Data Source
AI summary
The present invention relates to gene fusions and alternative spliced junctions associated with breast cancer. The present invention also relates to novel methods of identifying gene fusions and alternative spliced junctions in RNA sequencing data. The present invention further relates to predicting prognosis of a breast cancer patient based on the number of gene fusion events.