Repeat-aware profiling of cell-free RNA

EP4552141A4Pending Publication Date: 2026-07-15RGT UNIV OF CALIFORNIA
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Patent Information

Authority / Receiving Office
EP · EP
Patent Type
Applications
Current Assignee / Owner
RGT UNIV OF CALIFORNIA
Filing Date
2023-07-06
Publication Date
2026-07-15

AI Technical Summary

Technical Problem

Current methods for analyzing cell-free RNA biomarkers face challenges in sensitivity and specificity for disease classification, particularly due to the diagnostic potential of repeat elements being underutilized in existing RNA analysis techniques.

Method used

A repeat-aware sequencing and analysis pipeline that aligns and quantifies cell-free RNA sequence reads using annotated repeat elements, generating repeat-aware features for incorporation into machine learning models for disease classification, prognosis, and treatment selection.

Benefits of technology

Enhances the detection and classification of diseases by leveraging repeat-derived cell-free RNA features, improving diagnostic accuracy and reducing computational complexity, while providing insights into disease prognosis and treatment strategies.

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Abstract

Disclosed herein are methods and systems of analyzing cell-free RNA (cfRNA) that comprises sequencing the cfRNA from a biological sample from a subject to produce cfRNA sequence reads; and aligning and quantifying the cfRNA sequence reads using a repeat-aware transcriptome annotation or a repeat-aware genome annotation. The aligning and quantifying the cfRNA sequence reads may comprise aligning the cfRNA sequence reads to an annotated reference to obtain gene or repeat annotations for the cfRNA sequence reads, quantifying the cfRNA sequence reads that align to a gene or to a repeat element, and aggregating the repeat-aligned cfRNA sequence reads to the repeat subfamily level to generate repeat-aware cfRNA features for disease classification using machine learning.
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