HLA Loss Detection via NGS Allele Thresholds
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Solution Overview
Problem
Current methods for detecting HLA Loss after hematopoietic stem cell transplantation are inefficient, inaccurate, and lack a reliable detection system, particularly for predicting relapse and guiding therapeutic regimens, as existing methods like fluorescent quantitative PCR only cover about 70% of the population and do not account for HLA Loss-caused relapses effectively.
Innovation Solution
An analysis method and apparatus that utilize Next Generation Sequencing (NGS) data to split and filter sample sequences, align them with reference genes, calculate allele sequence percentages, and determine HLA Loss by assessing HLA % and STR % thresholds, providing a negative or positive judgment on HLA Loss status post-transplantation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fluorescent quantitative PCR method is used for detection, then detection can be performed, but coverage is limited to about 70% of the population and accuracy is insufficient
Solution Approach 1:
The patent changes the detection parameters by switching from fluorescent quantitative PCR to NGS-based detection, which enables comprehensive coverage of all HLA gene types while maintaining high detection accuracy. The NGS method allows for simultaneous detection of multiple HLA loci with high throughput and precision, resolving the contradiction between accuracy and population coverage.
2Reliability
If conventional detection methods are used, then some HLA Loss cases can be detected, but early relapse prediction capability is insufficient
Solution Approach 1:
The patent implements preliminary detection of HLA Loss status before relapse occurs by analyzing NGS sequencing data for HLA gene abnormalities. By performing this detection early in the post-transplantation period, the system can predict potential relapse cases before they manifest clinically, enabling early intervention and improving treatment outcomes.
Solution Approach 2:
The patent establishes a feedback mechanism where NGS detection results are continuously monitored and analyzed to assess HLA Loss status. This feedback loop provides real-time information about potential relapse risks, allowing clinicians to adjust treatment strategies proactively based on detected HLA abnormalities, thereby enhancing both reliability and sensitivity of relapse prediction.
Data Source
AI summary
The present application belongs to the field of bioinformatic analysis, and discloses an analysis method and analysis processing apparatus for loss of heterozygosity (LOH) of human leukocyte antigen (HLA). Directed to the detection demands for relapse after transplantation caused by HLA Loss and based on Next Generation Sequencing (NGS) data, the present application provides an analysis method and analysis processing apparatus for HLA Loss, which is capable of conveniently achieving the flow and in-batch operation. The present application has low workload of artificial interpretation, and can accurately detect the presence of HLA Loss or not in a sample and thus has significant meaning to the relapse after transplantation caused by HLA Loss.