Evidence map›Paper›PMID 26690524›Full record

ArticleJournal of genetics2015

CD133 and BMI1 expressions and its prognostic role in primary glioblastoma.

M K Sibin, C H Lavanya, Dhananjaya I Bhat, Narasinga Rao, N Geethashree, W Vibhuti, G K Chetan

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In one paragraph

Article in Journal of genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 36% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
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

7 authors at 2 institutions in 1 country.

M K SibinDepartment of Human Genetics, National Institute of Mental Health and Neurosciences, Bengaluru 560 029, India. drchetangk@gmail.com.
C H Lavanya
Dhananjaya I Bhat
Narasinga Rao
N Geethashree
W Vibhuti
G K Chetan
Centre For Human Genetics · INNational Institute of Mental Health and Neurosciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma is the most common malignant brain tumour, generated by bulk of malignant cancer stem cells, which express various stem cell factors like CD133, BMI1 and nestin. There are several studies which show the importance of CD133 in cancer, but the function and interaction with other major oncogenes and tumour suppressor genes is still not understood. This study aimed to analyse the expression of CD133 mRNA and its correlations with BMI1 protein expression and TP53 mutations in newly diagnosed glioblastoma patients and its role in prognosis. Overexpression of CD133 mRNA and BMI1 protein was found in 47.6 and 76.2% patients respectively and TP53 mutations was seen in 57.1% of patients in our study.There was no correlation among TP53 mutations and expressions of CD133 and BMI1. We found that high level of BMI1 expression was favourable for the patient survival (P=0.0075) and high CD133 mRNA expression was unfavourable for the patient survival (P=0.0226).CD133 mRNA and BMI1 protein expression could independently predict the glioblastoma patient survival in multivariate analysis. In conclusion, the overexpression of these stem cell markers is a common event in glioblastoma progression and could be used as potential prognostic markers.

Indexed as

AC133 AntigenAntigens, CDBrain NeoplasmsFemaleGlioblastomaGlycoproteinsHumansMaleMiddle AgedPeptidesPolycomb Repressive Complex 1PrognosisAC133 AntigenAntigens, CDBMI1 protein, humanGlycoproteinsPeptidesPolycomb Repressive Complex 1

Identifiers

PMID26690524
OpenAlexW2304009747

What OpenQuestion holds

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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.