Multiplexed assays of variant effect for clinical variant interpretation

Area of Science:

• Genetics
• Genomic Medicine
• Biotechnology

Background:

• Clinical genetic testing identifies numerous genetic variants, but most remain unclassified.
• Unclassified variants hinder accurate disease diagnosis and personalized treatment strategies.
• Identifying oncogenic driver mutations is crucial for targeted cancer therapy, yet many tumor variants lack clear pathogenicity status.

Purpose of the Study:

• To provide an overview of multiplexed assays of variant effect (MAVEs) technologies.
• To highlight the increasing clinical implementation of MAVEs.
• To discuss the role of MAVEs in variant classification, understanding pathogenicity mechanisms, and guiding targeted therapies.

Main Methods:

• Overview of MAVE technologies from their historical development to current applications.
• Discussion of MAVE data generation for thousands of variants concurrently.
• Examination of MAVE data's utility in clinical variant classification.

Main Results:

• MAVEs enable massively scaled functional genomics experiments.
• Increased availability of MAVE data improves the classification of genetic variants.
• Guidance for using MAVE data in clinical settings is improving.

Conclusions:

• MAVEs are crucial for addressing the challenge of unclassified genetic variants.
• MAVE technology supports the clinical implementation of genetic testing.
• MAVEs play a key role in advancing targeted cancer therapy and drug development.