Evidence map›Paper›PMID 32316138›Full record

ArticleBiomolecules2020

3D Cell Culture-Based Global miRNA Expression Analysis Reveals miR-142-5p as a Theranostic Biomarker of Rectal Cancer Following Neoadjuvant Long-Course Treatment.

Linas Kunigenas, Vaidotas Stankevicius, Audrius Dulskas, Elzbieta Budginaite, Gediminas Alzbutas, Eugenijus Stratilatovas, Nils Cordes, Kestutis Suziedelis

Open access · goldAbstract read
In one paragraph

Article in Biomolecules, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.7field-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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. PARP9-PARP13-PARP14 axis tunes colorectal cancer response to radiotherapy.Journal of experimental & clinical cancer research : CR · 2025
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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

8 authors at 3 institutions in 2 countries.

Linas KunigenasNational Cancer Institute, LT-08660 Vilnius, Lithuania.
Vaidotas StankeviciusNational Cancer Institute, LT-08660 Vilnius, Lithuania.
Audrius DulskasNational Cancer Institute, LT-08660 Vilnius, Lithuania.ORCID 0000-0003-3692-8962
Elzbieta BudginaiteNational Cancer Institute, LT-08660 Vilnius, Lithuania.
Gediminas AlzbutasThermo Fisher Scientific, LT-02241 Vilnius, Lithuania.
Eugenijus StratilatovasNational Cancer Institute, LT-08660 Vilnius, Lithuania.
Nils CordesOncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine, Technische Universität, D-01307 Dresden, Germany.
Kestutis SuziedelisNational Cancer Institute, LT-08660 Vilnius, Lithuania.ORCID 0000-0002-9485-3674
Vilnius University · LTGerman Cancer Research Center · DENational Cancer Institute · LT

Funding

Research Council of Lithuania MIP-104/2015
6 · The paper itself

Abstract

Altered expression of miRNAs in tumor tissue encourages the translation of this specific molecular pattern into clinical practice. However, the establishment of a selective biomarker signature for many tumor types remains an inextricable challenge. For this purpose, a preclinical experimental design, which could maintain a fast and sensitive discovery of potential biomarkers, is in demand. The present study suggests that the approach of 3D cell cultures as a preclinical cancer model that is characterized to mimic a natural tumor environment maintained in solid tumors could successfully be employed for the biomarker discovery and validation. Subsequently, in this study, we investigated an environment-dependent miRNA expression changes in colorectal adenocarcinoma DLD1 and HT29 cell lines using next-generation sequencing (NGS) technology. We detected a subset of 16 miRNAs differentially expressed in both cell lines cultivated in multicellular spheroids compared to expression levels in cells grown in 2D. Furthermore, results of in silico miRNA target analysis showed that miRNAs, which were differentially expressed in both cell lines grown in MCS, are involved in the regulation of molecular mechanisms implicated in cell adhesion, cell-ECM interaction, and gap junction pathways. In addition, integrins and platelet-derived growth factor receptors were determined to be the most significant target genes of deregulated miRNAs, which was concordant with the environment-dependent gene expression changes validated by RT-qPCR. Our results revealed that 3D microenvironment-dependent deregulation of miRNA expression in CRC cells potentially triggers essential molecular mechanisms predominantly including the regulation of cell adhesion, cell-cell, and cell-ECM interactions important in CRC initiation and development. Finally, we demonstrated increased levels of selected miR-142-5p in rectum tumor tissue samples after neoadjuvant long course treatment compared to miR-142-5p expression levels in tumor biopsy samples collected before the therapy. Remarkably, the elevation of miR-142-5p expression remained in tumor samples compared to adjacent normal rectum tissue as well. Therefore, the current study provides valuable insights into the molecular miRNA machinery of CRC and proposes a potential miRNA signature for the assessment of CRC in further clinical research.

Indexed as

Cell Culture TechniquesGene Expression ProfilingNeoadjuvant TherapyPrecision MedicineAgedAged, 80 and overBiomarkers, TumorCell AdhesionCell Line, TumorCell ShapeComputer SimulationFemaleGap JunctionsGene Expression Regulation, NeoplasticHumansMaleBiomarkers, TumorMicroRNAsMIRN142 microRNA, human3D cell culturecancer biomarkerscell adhesioncolorectal carcinomamiR-142miRNAneoadjuvant therapyrectal cancertumor microenvironment

Identifiers

PMID32316138
PMCPMC7226077
OpenAlexW3017245853

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.