Evidence map›Paper›PMID 31762958›Full record

ReviewComputational and structural biotechnology journal2019

Applications and analysis of targeted genomic sequencing in cancer studies.

Findlay Bewicke-Copley, Emil Arjun Kumar, Giuseppe Palladino, Koorosh Korfi, Jun Wang

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.

0numbers the graph read from it
0cells of the map it votes in
81citing 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

81 citing papers in PubMed.

  1. Exploratory Analysis of PTEN Deficiency by Immunohistochemistry from the Phase III CAPItello-291 Trial.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Trial
  2. The journal of liquid biopsy · 2026
    Review
  3. Review
  4. Liquid biopsy in solid tumours: expert opinion paper of the European society of pathology.Virchows Archiv : an international journal of pathology · 2026
    Review
  5. Article
  6. The Portable Microhaplotype Object and Tools.bioRxiv : the preprint server for biology · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Targeted Next-Generation Sequencing in Rare Diseases.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  17. Review
  18. The Evolution of Next-Generation Sequencing Technologies.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  19. Review
  20. Article

21 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

5 authors.

Findlay Bewicke-CopleyCentre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.
Emil Arjun KumarCentre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.
Giuseppe PalladinoCentre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.
Koorosh KorfiCentre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.
Jun WangCentre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Next Generation Sequencing (NGS) has dramatically improved the flexibility and outcomes of cancer research and clinical trials, providing highly sensitive and accurate high-throughput platforms for large-scale genomic testing. In contrast to whole-genome (WGS) or whole-exome sequencing (WES), targeted genomic sequencing (TS) focuses on a panel of genes or targets known to have strong associations with pathogenesis of disease and/or clinical relevance, offering greater sequencing depth with reduced costs and data burden. This allows targeted sequencing to identify low frequency variants in targeted regions with high confidence, thus suitable for profiling low-quality and fragmented clinical DNA samples. As a result, TS has been widely used in clinical research and trials for patient stratification and the development of targeted therapeutics. However, its transition to routine clinical use has been slow. Many technical and analytical obstacles still remain and need to be discussed and addressed before large-scale and cross-centre implementation. Gold-standard and state-of-the-art procedures and pipelines are urgently needed to accelerate this transition. In this review we first present how TS is conducted in cancer research, including various target enrichment platforms, the construction of target panels, and selected research and clinical studies utilising TS to profile clinical samples. We then present a generalised analytical workflow for TS data discussing important parameters and filters in detail, aiming to provide the best practices of TS usage and analyses.

Indexed as

Background errorBAM, Binary Alignment MapBWA, Burrows-Wheeler AlignerCancer genomicsClinical samplesCLL, Chronic Lymphocytic LeukaemiaCOSMIC, Catalogue of Somatic Mutations in CancerESP, Exome Sequencing ProjectFF, Fresh FrozenFFPE, Formalin Fixed Paraffin EmbeddedFL, Follicular LymphomaGATK, Genome Analysis ToolkitICGC, International Cancer Genome ConsortiumMBC, Molecular BarcodeNCCN, the National Comprehensive Cancer Network®NGS, Next Generation SequencingNHL, Non-Hodgkin LymphomaNSCLC, Non-Small Cell Lung CarcinomaPCR duplicatesQC, Quality ControlSAM, Sequence Alignment MapTargeted sequencingTCGA, The Cancer Genome AtlastFL, Transformed Follicular LymphomaTS, Targeted SequencingUMI, Unique Molecular IdentifiersVAF, Variant Allele FrequencyVariant callingWES, Whole Exome SequencingWGS, Whole Genome Sequencing

Identifiers

PMID31762958
PMCPMC6861594

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.