Panel Informativity Optimizer: An R Package to Improve Cancer Next-Generation Sequencing Panel Informativity

Area of Science:

• Genomics
• Bioinformatics
• Cancer Research

Background:

• Next-generation sequencing (NGS) is crucial for cancer diagnosis, but selecting optimal gene panels is challenging.
• Balancing panel informativity (patient mutation detection) with panel length (cost, sensitivity) is a key challenge.

Purpose of the Study:

• To introduce Panel Informativity Optimizer (PIO), an open-source R package with a graphical interface.
• To optimize cancer NGS panel informativity by selecting genomic intervals that maximize mutation detection while minimizing panel size.

Main Methods:

• Utilized patient-level mutational data from 91 cohorts across 31 cancer types.
• Developed PIO to select optimal genomic intervals (gene or exon level) using various optimization strategies.
• Included a panel tester function for benchmarking custom or commercial panels.

Main Results:

• PIO enables significant panel size reduction, up to 1000 kb.
• The software accurately predicts the performance of custom and commercial cancer gene panels.
• Demonstrated PIO's effectiveness using public and real-world cancer genomic data.

Conclusions:

• PIO provides an effective solution for optimizing cancer NGS panels.
• The tool aids in reducing sequencing costs and improving diagnostic sensitivity.
• PIO facilitates the design of more informative and cost-effective cancer gene panels.