Evidence map›Paper›PMID 28118322›Full record

ArticleBritish journal of cancer2017

Comparative mutational landscape analysis of patient-derived tumour xenografts.

Mariana Brait, Evgeny Izumchenko, Luciane T Kagohara, Samuel Long, Piotr T Wysocki, Brian Faherty, Elana J Fertig, Tin Oo Khor, Elizabeth Bruckheimer, Gilson Baia and 5 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in British journal of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

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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

15 authors.

Mariana BraitDepartment of Otolaryngology and Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
Evgeny IzumchenkoDepartment of Otolaryngology and Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
Luciane T KagoharaDepartment of Otolaryngology and Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
Samuel LongAIDS and Cancer Virus Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
Piotr T WysockiDepartment of Otolaryngology and Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
Brian FahertyDepartment of Otolaryngology and Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
Elana J FertigDepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
Tin Oo KhorChampions Oncology, Baltimore, MD 21205, USA.
Elizabeth BruckheimerChampions Oncology, Baltimore, MD 21205, USA.
Gilson BaiaChampions Oncology, Baltimore, MD 21205, USA.
Daniel CiznadijaChampions Oncology, Baltimore, MD 21205, USA.
Ido SlomaChampions Oncology, Baltimore, MD 21205, USA.
Ido Ben-ZviChampions Oncology, Baltimore, MD 21205, USA.
Keren PazChampions Oncology, Baltimore, MD 21205, USA.
David SidranskyDepartment of Otolaryngology and Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.

Funding

PQ1: Identification and characterization of genetic alterations for the progression of pre-neoplastic lung lesions by using novel PDx models and deep sequencingR01CA206027 · NCI · JOHNS HOPKINS UNIVERSITY · PI HOQUE, MOHAMMAD OBAIDUL, SIDRANSKY, DAVID · 2016 to 2020
$3.2M
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001ENCI NIH HHS R01 CA206027
6 · The paper itself

Abstract

backgroundScreening of patients for cancer-driving mutations is now used for cancer prognosis, remission scoring and treatment selection. Although recently emerged targeted next-generation sequencing-based approaches offer promising diagnostic capabilities, there are still limitations. There is a pressing clinical need for a well-validated, rapid, cost-effective mutation profiling system in patient specimens. Given their speed and cost-effectiveness, quantitative PCR mutation detection techniques are well suited for the clinical environment. The qBiomarker mutation PCR array has high sensitivity and shorter turnaround times compared with other methods. However, a direct comparison with existing viable alternatives are required to assess its true potential and limitations.

methodsIn this study, we evaluated a panel of 117 patient-derived tumour xenografts by the qBiomarker array and compared with other methods for mutation detection, including Ion AmpliSeq sequencing, whole-exome sequencing and droplet digital PCR.

resultsOur broad analysis demonstrates that the qBiomarker's performance is on par with that of other labour-intensive and expensive methods of cancer mutation detection of frequently altered cancer-associated genes, and provides a foundation for supporting its consideration as an option for molecular diagnostics.

conclusionsThis large-scale direct comparison and validation of currently available mutation detection approaches is extremely relevant for the current scenario of precision medicine and will lead to informed choice of screening methodologies, especially in lower budget conditions or time frame limitations.

Indexed as

HeterograftsAnimalsDNA Mutational AnalysisHigh-Throughput Nucleotide SequencingHumansMiceNeoplasmsNeoplasm TransplantationPolymerase Chain ReactionReproducibility of ResultsTumor Cells, Cultured

Identifiers

PMID28118322
PMCPMC5318980

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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.