Prevalence and detection of low-allele-fraction variants in clinical cancer samples

Hyun-Tae Shin, Yoon-La Choi, Jae Won Yun, Nayoung K. D. Kim, Sook-Young Kim, Hyo Jeong Jeon, Jae-Yong Nam, Chung Lee, Daeun Ryu, Sang Cheol Kim, Kyunghee Park, Eunjin Lee, Joon Seol Bae, Dae Soon Son, Je-Gun Joung, Jeeyun Lee, Seung Tae Kim, Myung-Ju Ahn, Se-Hoon Lee, Jin Seok Ahn, Woo Yong Lee, Bo Young Oh, Yeon Hee Park, Jeong Eon Lee, Kwang Hyuk Lee, Hee Cheol Kim, Kyoung-Mee Kim, Young-Hyuck Im, Keunchil Park, Peter J. Park () and Woong-Yang Park ()
Additional contact information
Hyun-Tae Shin: Samsung Medical Center
Yoon-La Choi: Sungkyunkwan University
Jae Won Yun: Samsung Medical Center
Nayoung K. D. Kim: Samsung Medical Center
Sook-Young Kim: Samsung Medical Center
Hyo Jeong Jeon: Samsung Medical Center
Jae-Yong Nam: Samsung Medical Center
Chung Lee: Samsung Medical Center
Daeun Ryu: Samsung Medical Center
Sang Cheol Kim: Samsung Medical Center
Kyunghee Park: Samsung Medical Center
Eunjin Lee: Samsung Medical Center
Joon Seol Bae: Samsung Medical Center
Dae Soon Son: Samsung Medical Center
Je-Gun Joung: Samsung Medical Center
Jeeyun Lee: Sungkyunkwan University School of Medicine
Seung Tae Kim: Sungkyunkwan University School of Medicine
Myung-Ju Ahn: Sungkyunkwan University School of Medicine
Se-Hoon Lee: Sungkyunkwan University School of Medicine
Jin Seok Ahn: Sungkyunkwan University School of Medicine
Woo Yong Lee: Sungkyunkwan University School of Medicine
Bo Young Oh: Sungkyunkwan University School of Medicine
Yeon Hee Park: Sungkyunkwan University School of Medicine
Jeong Eon Lee: Sungkyunkwan University School of Medicine
Kwang Hyuk Lee: Sungkyunkwan University School of Medicine
Hee Cheol Kim: Sungkyunkwan University School of Medicine
Kyoung-Mee Kim: Sungkyunkwan University School of Medicine
Young-Hyuck Im: Sungkyunkwan University School of Medicine
Keunchil Park: Sungkyunkwan University School of Medicine
Peter J. Park: Harvard Medical School
Woong-Yang Park: Samsung Medical Center

Nature Communications, 2017, vol. 8, issue 1, 1-10

Abstract: Abstract Accurate detection of genomic alterations using high-throughput sequencing is an essential component of precision cancer medicine. We characterize the variant allele fractions (VAFs) of somatic single nucleotide variants and indels across 5095 clinical samples profiled using a custom panel, CancerSCAN. Our results demonstrate that a significant fraction of clinically actionable variants have low VAFs, often due to low tumor purity and treatment-induced mutations. The percentages of mutations under 5% VAF across hotspots in EGFR, KRAS, PIK3CA, and BRAF are 16%, 11%, 12%, and 10%, respectively, with 24% for EGFR T790M and 17% for PIK3CA E545. For clinical relevance, we describe two patients for whom targeted therapy achieved remission despite low VAF mutations. We also characterize the read depths necessary to achieve sensitivity and specificity comparable to current laboratory assays. These results show that capturing low VAF mutations at hotspots by sufficient sequencing coverage and carefully tuned algorithms is imperative for a clinical assay.

Date: 2017
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DOI: 10.1038/s41467-017-01470-y

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