Evidence map›Paper›PMID 29123093›Full record

ArticleNature communications2017

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 and 21 more

Abstract read
In one paragraph

Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
122citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

122 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  4. Impact of Tumor Genomic Profile on Adjuvant Chemotherapy Efficacy in Resected Pancreatic Adenocarcinoma: Results From the PRODIGE-24/CCTG PA6 Study.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2026
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62 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

31 authors.

Hyun-Tae ShinSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Yoon-La ChoiSamsung Advanced Institute of Health Science and Technology, Sungkyunkwan University, Seoul, 06351, Korea.
Jae Won YunSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Nayoung K D KimSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Sook-Young KimSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Hyo Jeong JeonSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Jae-Yong NamSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Chung LeeSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Daeun RyuSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Sang Cheol KimSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Kyunghee ParkSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Eunjin LeeSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Joon Seol BaeSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Dae Soon SonSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Je-Gun JoungSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea.
Jeeyun LeeDepartment of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Seung Tae KimDepartment of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Myung-Ju AhnDepartment of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Se-Hoon LeeDepartment of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Jin Seok AhnDepartment of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Woo Yong LeeDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Bo Young OhDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Yeon Hee ParkDepartment of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Jeong Eon LeeDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Kwang Hyuk LeeDivision of Gastroenterology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Hee Cheol KimDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Kyoung-Mee KimDepartment of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Young-Hyuck ImDepartment of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Keunchil ParkDepartment of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
Peter J ParkDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA. peter_park@hms.harvard.edu.ORCID http://orcid.org/0000-0001-9378-960X
Woong-Yang ParkSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, Korea. woongyang.park@samsung.com.ORCID http://orcid.org/0000-0003-4234-0380

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Gene FrequencyAgedAllelesClass I Phosphatidylinositol 3-KinasesErbB ReceptorsFemaleHigh-Throughput Nucleotide SequencingHumansLimit of DetectionMiddle AgedMolecular Targeted TherapyMutationNeoplasmsPrevalenceProto-Oncogene Proteins B-rafProto-Oncogene Proteins p21(ras)BRAF protein, humanClass I Phosphatidylinositol 3-KinasesEGFR protein, humanErbB ReceptorsKRAS protein, humanPIK3CA protein, humanProto-Oncogene Proteins B-rafProto-Oncogene Proteins p21(ras)

Identifiers

PMID29123093
PMCPMC5680209

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.