Evidence map›Paper›PMID 22266856›Full record

ArticleOncogene2012

A general method to derive robust organ-specific gene expression-based differentiation indices: application to thyroid cancer diagnostic.

G Tomás, M Tarabichi, D Gacquer, A Hébrant, G Dom, J E Dumont, X Keutgen, T J Fahey, C Maenhaut, V Detours

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Article in Oncogene, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed, 3 pooled it
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1 · What the graph read from it

What it found

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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

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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

91 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Deciphering radiological stable disease to immune checkpoint inhibitors.Annals of oncology : official journal of the European Society for Medical Oncology · 2022
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31 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

10 authors.

G TomásIRIBHM, Université Libre de Bruxelles (ULB), Campus Erasme, Brussels, Belgium.
M Tarabichi
D Gacquer
A Hébrant
G Dom
J E Dumont
X Keutgen
T J Fahey
C Maenhaut
V Detours

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Differentiation is central to development, while dedifferentiation is central to cancer progression. Hence, a quantitative assessment of differentiation would be most useful. We propose an unbiased method to derive organ-specific differentiation indices from gene expression data and demonstrate its usefulness in thyroid cancer diagnosis. We derived a list of thyroid-specific genes by selecting automatically those genes that are expressed at higher level in the thyroid than in any other organ in a normal tissue's genome-wide gene expression compendium. The thyroid index of a tissue was defined as the median expression of these thyroid-specific genes in that tissue. As expected, the thyroid index was inversely correlated with meta-PCNA, a proliferation metagene, across a wide range of thyroid tumors. By contrast, the two indices were positively correlated in a time course of thyroid-stimulating hormone (TSH) activation of primary thyrocytes. Thus, the thyroid index captures biological information not integrated by proliferation rates. The differential diagnostic of follicular thyroid adenomas and follicular thyroid carcinoma is a notorious challenge for pathologists. The thyroid index discriminated them as accurately as did machine-learning classifiers trained on the genome-wide cancer data. Hence, although it was established exclusively from normal tissue data, the thyroid index integrates the relevant diagnostic information contained in tumoral transcriptomes. Similar results were obtained for the classification of the follicular vs classical variants of papillary thyroid cancers, that is, tumors dedifferentiating along a different route. The automated procedures demonstrated in the thyroid are applicable to other organs.

Indexed as

AdenomaAlgorithmsArea Under CurveCarcinomaCarcinoma, PapillaryCell DedifferentiationCell ProliferationCell Transformation, NeoplasticDecision TreesDiagnosis, DifferentialOligonucleotide Array Sequence AnalysisOrgan SpecificityProliferating Cell Nuclear AntigenROC CurveSupport Vector MachineThyroid Cancer, PapillaryProliferating Cell Nuclear AntigenThyrotropin

Identifiers

PMID22266856

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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.