Evidence map›Paper›PMID 39702719›Full record

GuidelineMethods in molecular biology (Clifton, N.J.)2025

A Practical Guideline for MicroRNA Sequencing Data Analysis in Chronic Lymphocytic Leukemia.

Tuulikki Suomela, Liang Zhang, Julio Vera, Heiko Bruns, Xin Lai

Abstract readPractice Guideline
PubMed Publisher
In one paragraph

Guideline in Methods in molecular biology (Clifton, N.J.), 2025. 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
–field-weighted citation impact
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.

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

5 authors.

Tuulikki SuomelaFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Liang ZhangFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Julio VeraDepartment of Dermatology, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
Heiko BrunsDepartment of Internal Medicine 5, Universitätsklinikum Erlangen, Erlangen, Germany.
Xin LaiFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland. xin.lai@tuni.fi.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. They have been associated with several diseases and cancers, including chronic lymphocytic leukemia (CLL). CLL is the most common form of adult leukemia, and its pathogenesis is driven by the deletion of miRNAs, such as the miR-15a/16-1 cluster. In addition to initiating the development of CLL, the function of miRNAs in regulating the progression of this tumor remains to be investigated. Here, we present a computational pipeline, from the processing of miRNA sequencing files to functional analysis, including differential gene expression and gene set enrichment analysis.We exemplified the utility of the pipeline by applying it to genome-wide small RNA sequencing data from a cohort of CLL patients. The analysis revealed dysregulated expression profiles of miRNAs in CLL. The target genes of these miRNAs are not only associated with the response of CLL patients to current therapies but also involved in several cancer hallmarks, including the avoidance of cell death, the deregulation of cellular energetics, the activation of invasion and metastasis, and genome instability. The identified miRNA-gene interactions offer valuable insights for developing targeted therapies for CLL. In addition, we underscored the importance of a practical and robust computational pipeline to ensure the reliability and reproducibility of miRNA sequencing data analysis.

Indexed as

Computational BiologyGene Expression ProfilingLeukemia, Lymphocytic, Chronic, B-CellMicroRNAsGene Expression Regulation, LeukemicGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingHumansSequence Analysis, RNAMicroRNAsBioinformaticsChronic lymphocytic leukemiaMicroRNANetwork biologySystems medicine

Identifiers

PMID39702719

What OpenQuestion holds

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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.