Evidence map›Paper›PMID 27756300›Full record

ArticleBMC medical genomics2016

Pitfalls of improperly procured adjacent non-neoplastic tissue for somatic mutation analysis using next-generation sequencing.

Lei Wei, Antonios Papanicolau-Sengos, Song Liu, Jianmin Wang, Jeffrey M Conroy, Sean T Glenn, Elizabeth Brese, Qiang Hu, Kiersten Marie Miles, Blake Burgher and 8 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
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

9 citing papers in PubMed, 12 citations in OpenAlex.

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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

18 authors at 1 institution in 1 country.

Lei WeiDepartment of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, USA. Lei.Wei@RoswellPark.org.ORCID 0000-0002-1881-8666
Antonios Papanicolau-SengosCenter for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, USA.
Song LiuDepartment of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, USA.
Jianmin WangDepartment of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, USA.
Jeffrey M ConroyCenter for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, USA.
Sean T GlennDepartment of Cancer Genetics, Roswell Park Cancer Institute, Buffalo, NY, USA.
Elizabeth BreseDepartment of Pathology, Roswell Park Cancer Institute, Buffalo, NY, USA.
Qiang HuDepartment of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, USA.
Kiersten Marie MilesCenter for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, USA.
Blake BurgherCenter for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, USA.
Maochun QinDepartment of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, USA.
Karen HeadDepartment of Pathology, Roswell Park Cancer Institute, Buffalo, NY, USA.
Angela R OmilianDepartment of Pathology, Roswell Park Cancer Institute, Buffalo, NY, USA.
Wiam BsharaDepartment of Pathology, Roswell Park Cancer Institute, Buffalo, NY, USA.
John KrolewskiCenter for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, USA.
Donald L TrumpDepartment of Medicine, Roswell Park Cancer Institute, Buffalo, NY, USA.
Candace S JohnsonDepartment of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, USA.
Carl D MorrisonCenter for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, USA. Carl.Morrison@RoswellPark.org.
Roswell Park Comprehensive Cancer Center · US

Funding

Two-Spirit Films in Indigenous Cancer HealthP30CA016056 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI Dean G. Tang · 1985 to 2026
$116.6M
NCI NIH HHS P30 CA016056
6 · The paper itself

Abstract

backgroundThe rapid adoption of next-generation sequencing provides an efficient system for detecting somatic alterations in neoplasms. The detection of such alterations requires a matched non-neoplastic sample for adequate filtering of non-somatic events such as germline polymorphisms. Non-neoplastic tissue adjacent to the excised neoplasm is often used for this purpose as it is simultaneously collected and generally contains the same tissue type as the neoplasm. Following NGS analysis, we and others have frequently observed low-level somatic mutations in these non-neoplastic tissues, which may impose additional challenges to somatic mutation detection as it complicates germline variant filtering.

methodsWe hypothesized that the low-level somatic mutation observed in non-neoplastic tissues may be entirely or partially caused by inadvertent contamination by neoplastic cells during the surgical pathology gross assessment or tissue procurement process. To test this hypothesis, we applied a systematic protocol designed to collect multiple grossly non-neoplastic tissues using different methods surrounding each single neoplasm. The procedure was applied in two breast cancer lumpectomy specimens. In each case, all samples were first sequenced by whole-exome sequencing to identify somatic mutations in the neoplasm and determine their presence in the adjacent non-neoplastic tissues. We then generated ultra-deep coverage using targeted sequencing to assess the levels of contamination in non-neoplastic tissue samples collected under different conditions.

resultsContamination levels in non-neoplastic tissues ranged up to 3.5 and 20.9 % respectively in the two cases tested, with consistent pattern correlated with the manner of grossing and procurement. By carefully controlling the conditions of various steps during this process, we were able to eliminate any detectable contamination in both patients.

conclusionThe results demonstrated that the process of tissue procurement contributes to the level of contamination in non-neoplastic tissue, and contamination can be reduced to below detectable levels by using a carefully designed collection method. A standard protocol dedicated for acquiring adjacent non-neoplastic tissue that minimizes neoplasm contamination should be implemented for all somatic mutation detection studies.

Indexed as

DNA Mutational AnalysisHigh-Throughput Nucleotide SequencingGenome, HumanHumansMutationNeoplasmsAdjacent normal tissuesSomatic mutationsTumor contamination

Identifiers

PMID27756300
PMCPMC5070097
OpenAlexW2537418151

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.