Evidence map›Paper›PMID 27784341›Full record

ReviewGenome medicine2016

Technological considerations for genome-guided diagnosis and management of cancer.

Niall J Lennon, Viktor A Adalsteinsson, Stacey B Gabriel

Abstract readReview
In one paragraph

Review in Genome medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Nuclease Enrichment and qPCR Detection of Rare Nucleotide Variants.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. 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

3 authors.

Niall J LennonBroad Institute of MIT & Harvard, Cambridge, MA, 02142, USA. nlennon@broadinstitute.org.
Viktor A AdalsteinssonBroad Institute of MIT & Harvard, Cambridge, MA, 02142, USA.
Stacey B GabrielBroad Institute of MIT & Harvard, Cambridge, MA, 02142, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technological, methodological, and analytical advances continue to improve the resolution of our view into the cancer genome, even as we discover ways to carry out analyses at greater distances from the primary tumor sites. These advances are finally making the integration of cancer genomic profiling into clinical practice feasible. Formalin fixation and paraffin embedding, which has long been the default pathological biopsy medium, is now being supplemented with liquid biopsy as a means to profile the cancer genomes of patients. At each stage of the genomic data generation process-sample collection, preservation, storage, extraction, library construction, sequencing, and variant calling-there are variables that impact the sensitivity and specificity of the analytical result and the clinical utility of the test. These variables include sample degradation, low yields of nucleic acid, and low variant allele fractions (proportions of assayed molecules carrying variant allele(s)). We review here the most common pre-analytical and analytical factors relating to routine cancer patient genome profiling, some solutions to common challenges, and the major sample preparation and sequencing technology choices available today.

Indexed as

Cytological TechniquesGene Expression ProfilingGenome, HumanGenomicsHigh-Throughput Nucleotide SequencingHumansNeoplasmsReproducibility of ResultsSensitivity and SpecificitySystems Integration

Identifiers

PMID27784341
PMCPMC5080740

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.