Evidence map›Paper›PMID 35277789›Full record

ArticleMolecular biology reports2022

Identification of appropriate housekeeping genes for gene expression studies in human renal cell carcinoma under hypoxic conditions.

Luiz Felipe S Teixeira, Rodrigo Gigliotti, Luana da Silva Ferreira, Maria Helena Bellini

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Article in Molecular biology reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 60% 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

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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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 1 country.

Luiz Felipe S TeixeiraCentro de Biotecnologia, Instituto de Pesquisas Energéticas e Nucleares, São Paulo, Brazil.
Rodrigo GigliottiCentro de Pesquisa de Genética e Reprodução Animal, Instituto de Zootecnia (IZ), Nova Odessa, São Paulo, Brazil.
Luana da Silva FerreiraCentro de Biotecnologia, Instituto de Pesquisas Energéticas e Nucleares, São Paulo, Brazil.
Maria Helena BelliniCentro de Biotecnologia, Instituto de Pesquisas Energéticas e Nucleares, São Paulo, Brazil. mbmarumo@ipen.br.
Instituto de Pesquisas Energéticas e Nucleares · BRInstitute of Animal Science and Pastures · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypoxia pathways are deregulated in clear renal cell carcinoma (ccRCC) because of the loss of the von Hippel-Lindau tumor suppressor function. Quantitative PCR is a powerful tool for quantifying differential expression between normal and cancer cells. Reliable gene expression analysis requires the use of genes encoding housekeeping genes. Therefore, in this study, eight reference candidate genes were evaluated to determine their stability in 786-0 cells under normoxic and hypoxic conditions. METHODS AND

resultsFour different tools were used to rank the most stable genes-geNorm, NormFinder, BestKeeper, and Comparative Ct (ΔCt), and a general ranking was performed using RankAggreg. According to the four algorithms, the TFRC reference gene was identified as the most stable. There was no agreement among the results from the algorithms for the 2nd and 3rd positions. A general classification was then established using the RankAggreg tool. Finally, the three most suitable reference genes for use in 786-0 cells under normoxic and hypoxic conditions were TFRC, RPLP0, and SDHA.

conclusionsTo the best of our knowledge, this is the first study to identify reliable genes that can be used for gene expression analysis in ccRCC in a hypoxic environment.

Indexed as

Carcinoma, Renal CellGenes, EssentialKidney NeoplasmsTumor HypoxiaGene ExpressionGene Expression ProfilingHumansReal-Time Polymerase Chain ReactionReference StandardsEndogenous genesHypoxiaNormalizationRenal cell carcinoma

Identifiers

PMID35277789
OpenAlexW4220816980

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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.