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Related Experiment Video

Updated: Sep 14, 2025

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Published on: July 5, 2019

Combining panel-based and whole-transcriptome-based gene fusion detection by long-read sequencing.

Karleena Rybacki¹, Feng Xu², Hannah M Deutsch³

¹Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Cell Reports Methods

|July 22, 2025

Summary

This study introduces a new workflow for detecting gene fusions (GFs) in cancer using long-read sequencing. The method combines targeted panels and whole-transcriptome analysis for faster and more comprehensive GF identification.

Keywords:

CP: cancer biology CP: genetics Oxford Nanopore Technologies computational pipeline gene fusions long-read sequencing transcriptome analysis

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Last Updated: Sep 14, 2025

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Published on: July 12, 2024

Area of Science:

Genomics
Cancer Research
Bioinformatics

Background:

Gene fusions (GFs) are critical drivers in various cancers.
Accurate detection of GFs is essential for targeted therapy.
Current methods may have limitations in sensitivity and scope.

Purpose of the Study:

To develop and validate a comprehensive gene fusion detection and analysis workflow.
To combine targeted panel-based and whole-transcriptome long-read sequencing for enhanced GF discovery.
To improve turnaround times and identify novel GFs in challenging cancer cases.

Main Methods:

Adaptation of a short-read cancer fusion panel for long-read sequencing (Oxford Nanopore Technologies).
Application of panel-based long-read sequencing for known GF detection.
Whole-transcriptome long-read sequencing analysis of panel-negative glioma samples.
Development of tailored computational pipelines for GF analysis.

Main Results:

Successful detection of known GFs using the adapted panel and long-read sequencing, with reduced turnaround times.
Identification of 20 novel candidate GFs in 24 panel-negative glioma samples.
Experimental validation of all identified candidate GFs.
Demonstrated compatibility of long-read sequencing for GF detection.

Conclusions:

The presented workflow integrates panel-based and whole-transcriptome long-read sequencing for comprehensive GF detection.
This approach enables fast and accurate identification of both known and novel gene fusions in cancer.
The workflow is effective for clinically challenging cases, including panel-negative samples.