Evidence map›Paper›PMID 12101425›Full record

ArticleOncogene2002

Application of cDNA microarrays to generate a molecular taxonomy capable of distinguishing between colon cancer and normal colon.

Tong-Tong Zou, Florin M Selaru, Yan Xu, Valentina Shustova, Jing Yin, Yuriko Mori, David Shibata, Fumiaki Sato, Suma Wang, Andreea Olaru and 4 more

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PubMed Publisher
In one paragraph

Article in Oncogene, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Trial
  2. Article
  3. Iron metabolism in colorectal cancer: a balancing act.Cellular oncology (Dordrecht, Netherlands) · 2023
    Review
  4. Article
  5. Article
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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

14 authors.

Tong-Tong ZouDepartment of Medicine, Division of Gastroenterology and Greenebaum Cancer Center, University of Maryland School of Medicine and Baltimore VA Hospital, Baltimore, Maryland, MD 21201, USA.
Florin M Selaru
Yan Xu
Valentina Shustova
Jing Yin
Yuriko Mori
David Shibata
Fumiaki Sato
Suma Wang
Andreea Olaru
Elena Deacu
Thomas C Liu
John M Abraham
Stephen J Meltzer

Funding

Comprehensive Biomarker Development in early EsophagogasU01CA085069 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI MELTZER, STEPHEN J · 1999 to 2009
$4.8M
The Human Colorectal InstabilitomeR01CA077057 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI MELTZER, STEPHEN J · 1998 to 2007
$2.6M
Neoplastic Complications in Inflammatory Bowel DiseaseR01CA095323 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI MELTZER, STEPHEN J · 2003 to 2007
$1.4M
NEOPLASTIC COMPLICATIONS IN INFLAMMATORY BOWEL DISEASER01DK047717 · NIDDK · UNIVERSITY OF MARYLAND BALTIMORE · PI MELTZER, STEPHEN J · 1993 to 2001
$336k
NCI NIH HHS CA77057NCI NIH HHS CA85069NCI NIH HHS CA95323NIDDK NIH HHS DK47717
6 · The paper itself

Abstract

In order to discover global gene expression patterns characterizing subgroups of colon cancer, microarrays were hybridized to labeled RNAs obtained from seventeen colonic specimens (nine carcinomas and eight normal samples). Using a hierarchical agglomerative method, the samples grouped naturally into two major clusters, in perfect concordance with pathological reports (colon cancer versus normal colon). Using a variant of the unpaired t-test, selected genes were ordered according to an index of importance. In order to confirm microarray data, we performed quantitative, real-time reverse transcriptase-polymerase chain reaction (TaqMan RT-PCR) on RNAs from 13 colorectal tumors and 13 normal tissues (seven of which were matched normal-tumor pairs). RT-PCR was performed on the gro1, B-factor, adlican, and endothelin converting enzyme-1 genes and confirmed microarray findings. Two hundred and fifty genes were identified, some of which were previously reported as being involved in colon cancer. We conclude that cDNA microarraying, combined with bioinformatics tools, can accurately classify colon specimens according to current histopathological taxonomy. Moreover, this technology holds promise of providing invaluable insight into specific gene roles in the development and progression of colon cancer. Our data suggests that a large-scale approach may be undertaken with the purpose of identifying biomarkers relevant to cancer progression.

Indexed as

AgedCarcinomaColonColonic NeoplasmsComputational BiologyFemaleGene Expression ProfilingHumansMaleMiddle AgedOligonucleotide Array Sequence AnalysisReverse Transcriptase Polymerase Chain ReactionRNA, MessengerRNA, NeoplasmRNA, MessengerRNA, Neoplasm

Identifiers

PMID12101425

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.