Evidence map›Paper›PMID 35978291›Full record

ArticleBMC genomics2022

Low-cost and clinically applicable copy number profiling using repeat DNA.

Sam Abujudeh, Sebastian S Zeki, Meta C J van Lanschot, Mark Pusung, Jamie M J Weaver, Xiaodun Li, Ayesha Noorani, Andrew J Metz, Jan Bornschein, Lawrence Bower and 4 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 89% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Trial
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

14 authors at 3 institutions in 1 country.

Sam Abujudeh *Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK. samer.abujudeh@gmail.com.ORCID http://orcid.org/0000-0002-1127-4299
Sebastian S Zeki *Medical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK. sebastianzeki0@gmail.com.
Meta C J van LanschotMedical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK.
Mark PusungMedical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK.
Jamie M J WeaverMedical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK.
Xiaodun LiMedical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK.
Ayesha NooraniMedical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK.
Andrew J MetzMedical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK.
Jan BornscheinMedical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK.
Lawrence BowerCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
Ahmad MiremadiMedical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK.
Rebecca C Fitzgerald *Medical Research Council (MRC) Cancer Unit, University of Cambridge, Cambridge, UK. rcf29@mrc-cu.cam.ac.uk.
Edward R Morrissey *Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK. edward.morrissey@imm.ox.ac.uk.
Andy G Lynch *Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK. andy.lynch@st-andrews.ac.uk.
University of Cambridge · GBGuy's and St Thomas' NHS Foundation Trust · GBUniversity of St Andrews · GB

Funding

Cancer Research UK RG66287Wellcome TrustWellcome Trust RG73199
6 · The paper itself

Abstract

backgroundSomatic copy number alterations (SCNAs) are an important class of genomic alteration in cancer. They are frequently observed in cancer samples, with studies showing that, on average, SCNAs affect 34% of a cancer cell's genome. Furthermore, SCNAs have been shown to be major drivers of tumour development and have been associated with response to therapy and prognosis. Large-scale cancer genome studies suggest that tumours are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Despite the frequency of SCNAs and their clinical relevance, the use of genomics assays in the clinic is biased towards targeted gene panels, which identify SNVs but provide limited scope to detect SCNAs throughout the genome. There is a need for a comparably low-cost and simple method for high-resolution SCNA profiling.

resultsWe present conliga, a fully probabilistic method that infers SCNA profiles from a low-cost, simple, and clinically-relevant assay (FAST-SeqS). When applied to 11 high-purity oesophageal adenocarcinoma samples, we obtain good agreement (Spearman's rank correlation coefficient, r

conclusionsWe show that conliga provides high-resolution SCNA profiles using a convenient, low-cost assay. We believe conliga makes FAST-SeqS a more clinically valuable assay as well as a useful research tool, enabling inexpensive and fast copy number profiling of pre-malignant and cancer samples.

Indexed as

DNA Copy Number VariationsNeoplasmsBase SequenceDNAHigh-Throughput Nucleotide SequencingHumansDNABarrett’s oesophagusBayesian nonparametricsCancerCopy number profilingFAST-SeqSMCMCOesophageal adenocarcinomaProbabilistic modelSomatic copy number alterationsSticky HDP-HMMTumour purity

Identifiers

PMID35978291
PMCPMC9386984
OpenAlexW4292261449

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.