Genome Biology (Apr 2021)

Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions

  • Binsheng Gong,
  • Dan Li,
  • Rebecca Kusko,
  • Natalia Novoradovskaya,
  • Yifan Zhang,
  • Shangzi Wang,
  • Carlos Pabón-Peña,
  • Zhihong Zhang,
  • Kevin Lai,
  • Wanshi Cai,
  • Jennifer S. LoCoco,
  • Eric Lader,
  • Todd A. Richmond,
  • Vinay K. Mittal,
  • Liang-Chun Liu,
  • Donald J. Johann,
  • James C. Willey,
  • Pierre R. Bushel,
  • Ying Yu,
  • Chang Xu,
  • Guangchun Chen,
  • Daniel Burgess,
  • Simon Cawley,
  • Kristina Giorda,
  • Nathan Haseley,
  • Fujun Qiu,
  • Katherine Wilkins,
  • Hanane Arib,
  • Claire Attwooll,
  • Kevin Babson,
  • Longlong Bao,
  • Wenjun Bao,
  • Anne Bergstrom Lucas,
  • Hunter Best,
  • Ambica Bhandari,
  • Halil Bisgin,
  • James Blackburn,
  • Thomas M. Blomquist,
  • Lisa Boardman,
  • Blake Burgher,
  • Daniel J. Butler,
  • Chia-Jung Chang,
  • Alka Chaubey,
  • Tao Chen,
  • Marco Chierici,
  • Christopher R. Chin,
  • Devin Close,
  • Jeffrey Conroy,
  • Jessica Cooley Coleman,
  • Daniel J. Craig,
  • Erin Crawford,
  • Angela del Pozo,
  • Ira W. Deveson,
  • Daniel Duncan,
  • Agda Karina Eterovic,
  • Xiaohui Fan,
  • Jonathan Foox,
  • Cesare Furlanello,
  • Abhisek Ghosal,
  • Sean Glenn,
  • Meijian Guan,
  • Christine Haag,
  • Xinyi Hang,
  • Scott Happe,
  • Brittany Hennigan,
  • Jennifer Hipp,
  • Huixiao Hong,
  • Kyle Horvath,
  • Jianhong Hu,
  • Li-Yuan Hung,
  • Mirna Jarosz,
  • Jennifer Kerkhof,
  • Benjamin Kipp,
  • David Philip Kreil,
  • Paweł Łabaj,
  • Pablo Lapunzina,
  • Peng Li,
  • Quan-Zhen Li,
  • Weihua Li,
  • Zhiguang Li,
  • Yu Liang,
  • Shaoqing Liu,
  • Zhichao Liu,
  • Charles Ma,
  • Narasimha Marella,
  • Rubén Martín-Arenas,
  • Dalila B. Megherbi,
  • Qingchang Meng,
  • Piotr A. Mieczkowski,
  • Tom Morrison,
  • Donna Muzny,
  • Baitang Ning,
  • Barbara L. Parsons,
  • Cloud P. Paweletz,
  • Mehdi Pirooznia,
  • Wubin Qu,
  • Amelia Raymond,
  • Paul Rindler,
  • Rebecca Ringler,
  • Bekim Sadikovic,
  • Andreas Scherer,
  • Egbert Schulze,
  • Robert Sebra,
  • Rita Shaknovich,
  • Qiang Shi,
  • Tieliu Shi,
  • Juan Carlos Silla-Castro,
  • Melissa Smith,
  • Mario Solís López,
  • Ping Song,
  • Daniel Stetson,
  • Maya Strahl,
  • Alan Stuart,
  • Julianna Supplee,
  • Philippe Szankasi,
  • Haowen Tan,
  • Lin-ya Tang,
  • Yonghui Tao,
  • Shraddha Thakkar,
  • Danielle Thierry-Mieg,
  • Jean Thierry-Mieg,
  • Venkat J. Thodima,
  • David Thomas,
  • Boris Tichý,
  • Nikola Tom,
  • Elena Vallespin Garcia,
  • Suman Verma,
  • Kimbley Walker,
  • Charles Wang,
  • Junwen Wang,
  • Yexun Wang,
  • Zhining Wen,
  • Valtteri Wirta,
  • Leihong Wu,
  • Chunlin Xiao,
  • Wenzhong Xiao,
  • Shibei Xu,
  • Mary Yang,
  • Jianming Ying,
  • Shun H. Yip,
  • Guangliang Zhang,
  • Sa Zhang,
  • Meiru Zhao,
  • Yuanting Zheng,
  • Xiaoyan Zhou,
  • Christopher E. Mason,
  • Timothy Mercer,
  • Weida Tong,
  • Leming Shi,
  • Wendell Jones,
  • Joshua Xu

DOI
https://doi.org/10.1186/s13059-021-02315-0
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 23

Abstract

Read online

Abstract Background Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing. Results All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5–20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden. Conclusion This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.

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