Evidence map›Paper›PMID 27234232›Full record

ArticleBMC genomics2016

Fluorescence activated cell sorting followed by small RNA sequencing reveals stable microRNA expression during cell cycle progression.

Vince Kornél Grolmusz, Eszter Angéla Tóth, Kornélia Baghy, István Likó, Ottó Darvasi, Ilona Kovalszky, János Matkó, Károly Rácz, Attila Patócs

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

11 citing papers in PubMed, 21 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

9 authors at 3 institutions in 1 country.

Vince Kornél Grolmusz2nd Department of Medicine, Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary.
Eszter Angéla TóthDepartment of Immunology, Eötvös Loránd University, Pázmány Péter sétány 1/C, 1117, Budapest, Hungary.
Kornélia Baghy1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Üllői út 26, 1085, Budapest, Hungary.
István Likó"Lendület" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences, Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary.
Ottó Darvasi"Lendület" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences, Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary.
Ilona Kovalszky1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Üllői út 26, 1085, Budapest, Hungary.
János MatkóDepartment of Immunology, Eötvös Loránd University, Pázmány Péter sétány 1/C, 1117, Budapest, Hungary.
Károly Rácz2nd Department of Medicine, Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary.
Attila Patócs"Lendület" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences, Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary. patocs.attila@med.semmelweis-univ.hu.
Semmelweis University · HUEötvös Loránd University · HUHungarian Academy of Sciences · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreviously, drug-based synchronization procedures were used for characterizing the cell cycle dependent transcriptional program. However, these synchronization methods result in growth imbalance and alteration of the cell cycle machinery. DNA content-based fluorescence activated cell sorting (FACS) is able to sort the different cell cycle phases without perturbing the cell cycle. MiRNAs are key transcriptional regulators of the cell cycle, however, their expression dynamics during cell cycle has not been explored.

methodsFollowing an optimized FACS, a complex initiative of high throughput platforms (microarray, Taqman Low Density Array, small RNA sequencing) were performed to study gene and miRNA expression profiles of cell cycle sorted human cells originating from different tissues. Validation of high throughput data was performed using quantitative real time PCR. Protein expression was detected by Western blot. Complex statistics and pathway analysis were also applied.

resultsBeyond confirming the previously described cell cycle transcriptional program, cell cycle dependently expressed genes showed a higher expression independently from the cell cycle phase and a lower amplitude of dynamic changes in cancer cells as compared to untransformed fibroblasts. Contrary to mRNA changes, miRNA expression was stable throughout the cell cycle.

conclusionsCell cycle sorting is a synchronization-free method for the proper analysis of cell cycle dynamics. Altered dynamic expression of universal cell cycle genes in cancer cells reflects the transformed cell cycle machinery. Stable miRNA expression during cell cycle progression may suggest that dynamical miRNA-dependent regulation may be of less importance in short term regulations during the cell cycle.

Indexed as

Flow CytometryGene Expression RegulationSequence Analysis, RNACell CycleCell Line, TransformedCell Line, TumorCluster AnalysisGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansMicroRNAsOrgan SpecificityTranscriptomeMicroRNAsCell cycleDNA stainingDynamic expressionFluorescence-activated cell sorting (FACS)miRNA

Identifiers

PMID27234232
PMCPMC4884355
OpenAlexW2406488385

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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.