Evidence map›Paper›PMID 24498002›Full record

ArticlePloS one2014

Transcriptome profiling of archived sectioned formalin-fixed paraffin-embedded (AS-FFPE) tissue for disease classification.

Kensuke Kojima, Craig April, Claudia Canasto-Chibuque, Xintong Chen, Manjeet Deshmukh, Anu Venkatesh, Poh Seng Tan, Masahiro Kobayashi, Hiromitsu Kumada, Jian-Bing Fan and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

29 citing papers in PubMed, 50 citations in OpenAlex.

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  18. Clinicopathological indices to predict hepatocellular carcinoma molecular classification.Liver international : official journal of the International Association for the Study of the Liver · 2016
    Article
  19. Article
  20. Molecular prognostic prediction in liver cirrhosis.World journal of gastroenterology · 2015
    Review
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

11 authors at 3 institutions in 2 countries.

Kensuke KojimaLiver Cancer Program, Tisch Cancer Institute, Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Craig AprilIllumina, Inc., San Diego, California, United States of America.
Claudia Canasto-ChibuqueLiver Cancer Program, Tisch Cancer Institute, Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Xintong ChenLiver Cancer Program, Tisch Cancer Institute, Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Manjeet DeshmukhLiver Cancer Program, Tisch Cancer Institute, Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Anu VenkateshLiver Cancer Program, Tisch Cancer Institute, Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Poh Seng TanLiver Cancer Program, Tisch Cancer Institute, Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Masahiro KobayashiDepartment of Hepatology, Toranomon Hospital, Tokyo, Japan.
Hiromitsu KumadaDepartment of Hepatology, Toranomon Hospital, Tokyo, Japan.
Jian-Bing FanIllumina, Inc., San Diego, California, United States of America.
Yujin HoshidaLiver Cancer Program, Tisch Cancer Institute, Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Icahn School of Medicine at Mount Sinai · USIllumina (United States) · USToranomon Hospital · JP

Funding

Molecular Prognostic Indicators in Liver Cirrhosis and CancerR01DK099558 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI HOSHIDA, YUJIN · 2013 to 2016
$2.6M
NIDDK NIH HHS 1R01DK099558NIDDK NIH HHS R01 DK099558
6 · The paper itself

Abstract

backgroundArchived tissues from previously completed prospective trials represent invaluable resource for biomarker development. However, such specimens are often stored as sections on glass slides, in which RNA is severely degraded due to prolonged air exposure. We evaluated whether a proportion of archived sectioned formalin-fixed paraffin-embedded (AS-FFPE) tissues yield transcriptome profiles comparable to freshly cut (FC) FFPE tissues, which can be used for retrospective class prediction analysis.

methodsGenome-wide transcriptome profiles of 6 to 7-year-old AS-FFPE tissue sections (generated from 5 to 16-year-old blocks) of 83 hepatocellular carcinoma (HCC) and 47 liver cirrhosis samples were generated by using whole-genome DASL assay (Illumina) and digital transcript counting (nCounter) assay (NanoString), and gene signature-based prediction of HCC subclasses and prognosis was compared with previously generated FC-FFPE profiles from the same tissue blocks.

resultsRNA quality and assay reproducibility of AS-FFPE RNA were comparable to intermediate to poor quality FC-FFPE samples (RNA Integrity Number: up to 2.50, R-square for technical replicates: up to 0.93). Analyzable transcriptome profiles were obtained in 64 (77%) HCC and 36 (77%) cirrhosis samples. Statistically more confident predictions based on random resampling-based method (nearest template prediction) were obtained in 37 (58%) HCC and 13 (36%) cirrhosis samples. Predictions made in FC-FFPE profiles were reproduced in 36 (97%) HCC and 11 (85%) cirrhosis AS-FFPE profiles. nCounter assay was tested in 24 cirrhosis samples, which yielded confident prediction in 15 samples (63%), of which 10 samples (67%) showed concordant predictions with FC-FFPE profiles.

conclusionsAS-FFPE tissues yielded poorer quality RNA and transcriptome profiles compared to FC-FFPE tissues. Statistically more confident class prediction was feasible in 37 of 83 HCC samples and 13 of 47 cirrhosis samples. These results suggest that AS-FFPE tissues can be regarded as a resource for retrospective transcriptome-based class prediction analysis when they are the only available materials.

Indexed as

Gene Expression ProfilingTranscriptomeCarcinoma, HepatocellularFixativesFormaldehydeHumansLiver CirrhosisLiver NeoplasmsParaffin EmbeddingPrognosisRNA, MessengerTissue FixationFixativesFormaldehydeRNA, Messenger

Identifiers

PMID24498002
PMCPMC3907407
OpenAlexW2053821592

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.