Evidence map›Paper›PMID 28666423›Full record

ArticleBMC cancer2017

Precision oncology using a limited number of cells: optimization of whole genome amplification products for sequencing applications.

Shonan Sho, Colin M Court, Paul Winograd, Sangjun Lee, Shuang Hou, Thomas G Graeber, Hsian-Rong Tseng, James S Tomlinson

Abstract read
In one paragraph

Article in BMC cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Whole-Genome Amplification for Circulating Tumor Cells.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Review
  4. Review
  5. Review
  6. Theranostic Interpolation of Genomic Instability in Breast Cancer.International journal of molecular sciences · 2022
    Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Full Karyotype Interphase Cell Analysis.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2018
    Article
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

8 authors.

Shonan ShoDepartment of Surgery, University of California Los Angeles, 10833 Le Conte Ave, California, Los Angeles, 90095, USA. ssho@mednet.ucla.edu.ORCID http://orcid.org/0000-0002-1547-6402
Colin M CourtDepartment of Surgery, University of California Los Angeles, 10833 Le Conte Ave, California, Los Angeles, 90095, USA.
Paul WinogradDepartment of Surgery, University of California Los Angeles, 10833 Le Conte Ave, California, Los Angeles, 90095, USA.
Sangjun LeeDepartment of Molecular and Medical Pharmacology, University of California Los Angeles, 650 Charles E Young Dr S, California, Los Angeles, 90095, USA.
Shuang HouDepartment of Molecular and Medical Pharmacology, University of California Los Angeles, 650 Charles E Young Dr S, California, Los Angeles, 90095, USA.
Thomas G GraeberDepartment of Molecular and Medical Pharmacology, University of California Los Angeles, 650 Charles E Young Dr S, California, Los Angeles, 90095, USA.
Hsian-Rong TsengDepartment of Molecular and Medical Pharmacology, University of California Los Angeles, 650 Charles E Young Dr S, California, Los Angeles, 90095, USA.
James S TomlinsonDepartment of Surgery, University of California Los Angeles, 10833 Le Conte Ave, California, Los Angeles, 90095, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSequencing analysis of circulating tumor cells (CTCs) enables "liquid biopsy" to guide precision oncology strategies. However, this requires low-template whole genome amplification (WGA) that is prone to errors and biases from uneven amplifications. Currently, quality control (QC) methods for WGA products, as well as the number of CTCs needed for reliable downstream sequencing, remain poorly defined. We sought to define strategies for selecting and generating optimal WGA products from low-template input as it relates to their potential applications in precision oncology strategies.

methodsSingle pancreatic cancer cells (HPAF-II) were isolated using laser microdissection. WGA was performed using multiple displacement amplification (MDA), multiple annealing and looping based amplification (MALBAC) and PicoPLEX. Quality of amplified DNA products were assessed using a multiplex/RT-qPCR based method that evaluates for 8-cancer related genes and QC-scores were assigned. We utilized this scoring system to assess the impact of de novo modifications to the WGA protocol. WGA products were subjected to Sanger sequencing, array comparative genomic hybridization (aCGH) and next generation sequencing (NGS) to evaluate their performances in respective downstream analyses providing validation of the QC-score.

resultsSingle-cell WGA products exhibited a significant sample-to-sample variability in amplified DNA quality as assessed by our 8-gene QC assay. Single-cell WGA products that passed the pre-analysis QC had lower amplification bias and improved aCGH/NGS performance metrics when compared to single-cell WGA products that failed the QC. Increasing the number of cellular input resulted in improved QC-scores overall, but a resultant WGA product that consistently passed the QC step required a starting cellular input of at least 20-cells. Our modified-WGA protocol effectively reduced this number, achieving reproducible high-quality WGA products from ≥5-cells as a starting template. A starting cellular input of 5 to 10-cells amplified using the modified-WGA achieved aCGH and NGS results that closely matched that of unamplified, batch genomic DNA.

conclusionThe modified-WGA protocol coupled with the 8-gene QC serve as an effective strategy to enhance the quality of low-template WGA reactions. Furthermore, a threshold number of 5-10 cells are likely needed for a reliable WGA reaction and product with high fidelity to the original starting template.

Indexed as

GenomicsPrecision MedicineBiomarkers, TumorCell LineComparative Genomic HybridizationComputational BiologyDNA Mutational AnalysisGenome, HumanHigh-Throughput Nucleotide SequencingHumansLiquid BiopsyMutationNeoplasmsNeoplastic Cells, CirculatingNucleic Acid Amplification TechniquesQuality ControlBiomarkers, TumorMultiple displacement amplificationNext generation sequencingPrecision oncologySingle-cell sequencingWhole genome amplification

Identifiers

PMID28666423
PMCPMC5493892

What OpenQuestion holds

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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.