Evidence map›Paper›PMID 18618141›Full record

ArticleJournal of cancer research and clinical oncology2009

Molecular characterization of the DYX1C1 gene and its application as a cancer biomarker.

Yun-Ji Kim, Jae-Won Huh, Dae-Soo Kim, Min-In Bae, Ja-Rang Lee, Hong-Seok Ha, Kung Ahn, Tae-Oh Kim, Geun-Am Song, Heui-Soo Kim

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 18 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

10 authors at 3 institutions in 1 country.

Yun-Ji KimDivision of Biological Sciences, College of Natural Sciences, Pusan National University, Busan, 609-735, Republic of Korea.
Jae-Won Huh
Dae-Soo Kim
Min-In Bae
Ja-Rang Lee
Hong-Seok Ha
Kung Ahn
Tae-Oh Kim
Geun-Am Song
Heui-Soo Kim
Pusan National University · KRKorea Research Institute of Bioscience and Biotechnology · KRPusan National University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDYX1C1 has three alternatively spliced transcripts. Therefore, we expect that alternative transcripts of DYX1C1 are used as a biomarker to detect specific cancer.

methodsRT-PCR analysis is conducted in order to detect expression of the DYX1C1 gene and the PCR products were analyzed using the Image J program to compare the expression levels of each transcript.

resultsWe found one of the transcripts was directly associated with an HERV-H LTR element that could be translated into protein sequence. Four new alternative transcripts were identified by RT-PCR analysis with various human tissue samples including 10 normal and adjacent tumor tissue sets. Semi-quantitative RT-PCR analysis showed the transcriptional activity of V3 and V2 was higher in tumor than in normal tissue samples, especially in the colorectal tissue samples.

conclusionOur results indicated that alternatively spliced transcript variants of the DYX1C1 gene could be used as cancer biomarkers to detect colorectal cancer.

Indexed as

Alternative SplicingGene Expression Regulation, NeoplasticBiomarkers, TumorColorectal NeoplasmsCytoskeletal ProteinsFemaleGenetic VariationHumansMaleNeoplasmsNerve Tissue ProteinsNuclear ProteinsPregnancyReverse Transcriptase Polymerase Chain ReactionTranscription, GeneticBiomarkers, TumorCytoskeletal ProteinsDNAAF4 protein, humanNerve Tissue ProteinsNuclear Proteins

Identifiers

PMID18618141
PMCPMC12160286
OpenAlexW2083881409

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.