Evidence map›Paper›PMID 29339835›Full record

ArticleLaboratory investigation; a journal of technical methods and pathology2018

Obtaining high quality transcriptome data from formalin-fixed, paraffin-embedded diagnostic prostate tumor specimens.

Liesel M FitzGerald, Chol-Hee Jung, Ee Ming Wong, JiHoon E Joo, Jodee A Gould, Vivien Vasic, Julie K Bassett, Neil O'Callaghan, Tim Nottle, John Pedersen and 2 more

Open access · bronzeAbstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Laboratory investigation; a journal of technical methods and pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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

12 authors at 5 institutions in 1 country.

Liesel M FitzGeraldCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
Chol-Hee Jung *Melbourne Bioinformatics, The University of Melbourne, Parkville, VIC, Australia.ORCID http://orcid.org/0000-0002-2992-3162
Ee Ming Wong *Department of Pathology, The University of Melbourne, Parkville, VIC, Australia.
JiHoon E JooDepartment of Pathology, The University of Melbourne, Parkville, VIC, Australia.
Jodee A GouldMonash Health Translation Precinct, Medical Genomics Facility, Hudson Institute of Medical Research, Clayton, VIC, Australia.
Vivien VasicMonash Health Translation Precinct, Medical Genomics Facility, Hudson Institute of Medical Research, Clayton, VIC, Australia.
Julie K BassettCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
Neil O'CallaghanDepartment of Pathology, The University of Melbourne, Parkville, VIC, Australia.
Tim NottleTissuPath Specialist Pathology, Mount Waverley, VIC, Australia.
John PedersenTissuPath Specialist Pathology, Mount Waverley, VIC, Australia.
Graham G GilesCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
Melissa C SoutheyCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia. msouthey@unimelb.edu.au.
The University of Melbourne · AUHudson Institute of Medical Research · AUTissuPath · AUCancer Council Victoria · AUUniversity of Tasmania · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prognostic genomic biomarkers that can be measured at diagnosis to aid choice of treatment options are unavailable for most common cancers. This is due in part to the poor quality and quantity of available diagnostic specimens for discovery research and to limitations in genomic technologies. Recent technical advances now enable high-density molecular analyses using suboptimal biological specimens. Here we describe the optimization of a transcriptome-specific protocol for use with formalin-fixed, paraffin-embedded (FFPE) diagnostic prostate cancer (PrCa) specimens. We applied the Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq Kit) to RNA samples extracted from 36 tumor-enriched and 16 adjacent normal tissues (ADJ

Indexed as

AdenocarcinomaGene Expression ProfilingHumansMaleParaffin EmbeddingProstatic NeoplasmsSpecimen Handling

Identifiers

PMID29339835
OpenAlexW2783294164

What OpenQuestion holds

Textmetadata
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.