Evidence map›Paper›PMID 20533595›Full record

ArticleWorld journal of gastroenterology2010

Hydrophobic protein in colorectal cancer in relation to tumor stages and grades.

Lay-Chin Yeoh, Chee-Keat Loh, Boon-Hui Gooi, Manjit Singh, Lay-Harn Gam

Open access · hybridAbstract read
In one paragraph

Article in World journal of gastroenterology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Cell surface markers in colorectal cancer prognosis.International journal of molecular sciences · 2010
    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

5 authors at 1 institution in 1 country.

Lay-Chin YeohSchool of Pharmaceutical Sciences, Universiti Sains Malaysia, USM 11800, Penang, Malaysia.
Chee-Keat Loh
Boon-Hui Gooi
Manjit Singh
Lay-Harn Gam
Universiti Sains Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo identify differentially expressed hydrophobic proteins in colorectal cancer.

methodsEighteen pairs of colorectal cancerous tissues in addition to tissues from normal mucosa were analysed. Hydrophobic proteins were extracted from the tissues, separated using 2-D gel electrophoresis and analysed using Liquid Chromatography Tandem Mass Spectrometry (LC/MS/MS). Statistical analysis of the proteins was carried out in order to determine the significance of each protein to colorectal cancer (CRC) and also their relation to CRC stages, grades and patients' gender.

resultsThirteen differentially expressed proteins which were expressed abundantly in either cancerous or normal tissues were identified. A number of these proteins were found to relate strongly with a particular stage or grade of CRC. In addition, the association of these proteins with patient gender also appeared to be significant.

conclusionStomatin-like protein 2 was found to be a promising biomarker for CRC, especially in female patients. The differentially expressed proteins identified were associated with CRC and may act as drug target candidates.

Indexed as

Biomarkers, TumorAdultAgedAged, 80 and overBlood ProteinsChromatography, LiquidColorectal NeoplasmsElectrophoresis, Gel, Two-DimensionalFemaleHumansHydrophobic and Hydrophilic InteractionsMaleMembrane ProteinsMiddle AgedMolecular Sequence DataNeoplasm ProteinsBiomarkers, TumorBlood ProteinsMembrane ProteinsNeoplasm ProteinsSTOML2 protein, human

Identifiers

PMID20533595
PMCPMC2883131
OpenAlexW1965758446

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.