Inhibiting CDK4/6 in pancreatic ductal adenocarcinoma via microRNA-21

Mortoglou, M., Miralles, F., Mould, R., Sengupta, D. and Uysal Onganer, P. 2023. Inhibiting CDK4/6 in pancreatic ductal adenocarcinoma via microRNA-21. European Journal of Cell Biology. 102 (2) 151318. https://doi.org/10.1016/j.ejcb.2023.151318

TitleInhibiting CDK4/6 in pancreatic ductal adenocarcinoma via microRNA-21
TypeJournal article
AuthorsMortoglou, M., Miralles, F., Mould, R., Sengupta, D. and Uysal Onganer, P.
Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies, with a 5-year survival rate of 5–10 %. The high mortality rate is due to the asymptomatic progression of clinical features in metastatic stages of the disease, which renders standard therapeutic options futile. PDAC is characterised by alterations in several genes that drive carcinogenesis and limit therapeutic response. The two most common genetic aberrations in PDAC are the mutational activation of KRAS and loss of the tumour suppressor CDK inhibitor 2A (CDKN2A), which culminate the activation of the cyclin-dependent kinase 4 and 6 (CDK4/6), that promote G1 cell cycle progression. Therapeutic strategies focusing on the CDK4/6 inhibitors such as palbociclib (PD-0332991) may potentially improve outcomes in this malignancy. MicroRNAs (miRs/miRNAs) are small endogenous non-coding RNA molecules associated with cellular proliferation, invasion, apoptosis, and cell cycle. Primarily, miR-21 promotes cell proliferation and a higher proportion of PDAC cells in the S phase, while knockdown of miR-21 has been linked to cell cycle arrest at the G2/M phase and inhibition of cell proliferation. In this study, using a CRISPR/Cas9 loss-of-function screen, we individually silenced the expression of miR-21 in two PDAC cell lines and in combination with PD-0332991 treatment, we examined the synergetic mechanisms of CDK4/6 inhibitors and miR-21 knockouts (KOs) on cell survival and death. This combination reduced cell proliferation, cell viability, increased apoptosis and G1 arrest in vitro. We further analysed the mitochondrial respiration and glycolysis of PDAC cells; then assessed the protein content of these cells and revealed numerous Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with PD-0332991 treatment and miR-21 knocking out. Our results demonstrate that combined targeting of CDK4/6 and silencing of miR-21 represents a novel therapeutic strategy in PDAC.

Article number151318
JournalEuropean Journal of Cell Biology
Journal citation102 (2)
ISSN1618-1298
0171-9335
Year2023
PublisherElsevier
Publisher's version
License
CC BY-NC-ND 4.0
File Access Level
Open (open metadata and files)
Digital Object Identifier (DOI)https://doi.org/10.1016/j.ejcb.2023.151318
Web address (URL)https://www.sciencedirect.com/science/article/pii/S017193352300033X
Publication dates
Published online25 Apr 2023
Published in printJun 2023

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Grau, I., Nápoles, G., Sengupta, D., García Lorenzo, M.M. and Nowe, A. 2017. Training set edition using Rough Set Theory for Semi-supervised Classification. 2nd International Symposium on Fuzzy and Rough Sets. Villa Clara, Cuba 24 - 26 Oct 2017 Editorial Feijoó.

Prostate-specific PTen deletion in mice activates inflammatory microRNA expression pathways in the epithelium early in hyperplasia development
Dart Alwyn, D., Uysal-Onganer, P. and Jiang, W.G. 2017. Prostate-specific PTen deletion in mice activates inflammatory microRNA expression pathways in the epithelium early in hyperplasia development. Oncogenesis. 14 (6) 400. https://doi.org/10.1038/s41389-017-0007-5

A Framework for Morphological Feature Extraction of Organs from MR Images for Detection and Classification of Abnormalities
Villarini, B., Asaturyan, H., Thomas, E.L., Mould, R. and Bell, J.D. 2017. A Framework for Morphological Feature Extraction of Organs from MR Images for Detection and Classification of Abnormalities. Proceedings of the 30th IEEE International Symposium on Computer-Based Medical Systems (CBMS’17). Thessaloniki, Greece 22 - 24 Jun 2017 IEEE . https://doi.org/10.1109/CBMS.2017.49

Genomic Variant Classifier Tool
Grau, I., Sengupta, D., Farid, D.M., Manderick, B., Nowe, A., Garcia Lorenzo, M.M., Daneels, D., Bonduelle, M., Croes, D. and Van Dooren , S. 2016. Genomic Variant Classifier Tool. SAI Intelligent Systems Conference 2016. London 21 Sep 2016 Springer. https://doi.org/10.1007/978-3-319-56994-9_32

GeVaCT - Genomic Variant Classifier Tool
Daneels, D., Grau, I., Sengupta, D., Bonduelle, M.L., Farid, D., Croes, D., Nowé, A. and Van Dooren, S. 2016. GeVaCT - Genomic Variant Classifier Tool. European Journal of Human Genetics. 24 (E-Supplement 1), p. 341.

Grey-Box Model: An ensemble approach for addressing semi-supervised classification problems
Sengupta, D., Grau, I., Garcia Lorenzo, M.M. and Nowe, A. 2016. Grey-Box Model: An ensemble approach for addressing semi-supervised classification problems. Benelearn 2016: Belgian-Dutch Conference on Machine Learning. Katholieke Universiteit Leuven, Campus Kortrijk (KULAK) 12 - 13 Sep 2016

The interaction of Wnt-11 and signalling cascades in prostate cancer
Koushyar, S., Grant, G.H. and Uysal-Onganer, P. 2016. The interaction of Wnt-11 and signalling cascades in prostate cancer. Tumor Biology. 37 (10), pp. 13049-13057. https://doi.org/10.1007/s13277-016-5263-z

GEVACT: Genomic Variant Classifier Tool
Daneels, D., Grau, I., Sengupta, D., Bonduelle, M., Farid, D.M., Croes, D., Nowé, A. and Van Dooren, S. 2015. GEVACT: Genomic Variant Classifier Tool. BeSHG & NVHG First Joint Meeting “Genetics & Society”. Leuven, Belgium 04 - 05 Feb 2016

CliniPhenome: Clinical and Phenotypic Annotation Database
Sengupta, D., Croes, D., Van Dooren, S., Bonduelle, M. and Nowe, A. 2015. CliniPhenome: Clinical and Phenotypic Annotation Database. BeMGI Annual Meeting 2015. Ghent, Belgium

GeVaCT: Genomic Variant Classifier Tool
Grau, I., Daneels, D., Van Dooren, S., Bonduelle , M., Farid, D.M., Croes, D., Nowé, A. and Sengupta, D. 2015. GeVaCT: Genomic Variant Classifier Tool. 10th Benelux Bioinformatics Conference. University of Antwerp, Belgium 07 - 08 Dec 2015

CliniPhenome: Clinical and Phenotypic Annotation Database
Sengupta, D., Croes, D., Van Dooren, S., Bonduelle, M. and Nowe, A. 2015. CliniPhenome: Clinical and Phenotypic Annotation Database. 2nd International Conference on Health Informatics & Technology. Valencia, Spain 27 - 29 Jul 2015 OMICS Publishing Group.

Benchmarking pre-processing and batch effect removal methods for Insilico DB: Genomics Big Data Infrastructure
De Clerck, Q., Nowe, A., Coletta, A. and Sengupta, D. 2014. Benchmarking pre-processing and batch effect removal methods for Insilico DB: Genomics Big Data Infrastructure. 9th Benelux Bioinformatics Conference (BBC 2014). Novotel-Kirchberg, Luxembourg 08 - 09 Dec 2014

Homology Modeling of Bacteriocins: From sequence alignments to structural models
Atri, P., Sengupta, D., Verma, S., Ali, S. and Dey, G. 2014. Homology Modeling of Bacteriocins: From sequence alignments to structural models. International Journal of Scientific & Engineering Research. 5 (5), pp. 123-126.

Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor
Sengupta, D., Sood, M., Vijayvargia, P., Hota, S. and Naik, P.K. 2013. Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor. Bioinformation. 9 (11), pp. 555-559. https://doi.org/10.6026/97320630009555

Design of dimensional model for clinical data storage and analysis
Sengupta, D., Arora, P., Pant, S. and Naik, P.K. 2013. Design of dimensional model for clinical data storage and analysis. Applied Medical Informatics. 32 (2), pp. 47-53.

SN algorithm: analysis of temporal clinical data for mining periodic patterns and impending augury
Sengupta, D. and Naik, P.K. 2013. SN algorithm: analysis of temporal clinical data for mining periodic patterns and impending augury. Journal of Clinical Bioinformatics. 3 24. https://doi.org/10.1186/2043-9113-3-24

TpPred: A Tool for Hierarchical Prediction of Transport Proteins Using Cluster of Neural Networks and Sequence Derived Features
Jain, S., Ranjan, P., Sengupta, D. and Naik, P.K. 2012. TpPred: A Tool for Hierarchical Prediction of Transport Proteins Using Cluster of Neural Networks and Sequence Derived Features. International Journal for Computational Biology. 1 (1), pp. 28-36.

Distinct expression and activity of GSK-3α and GSK-3β in prostate cancer
Darrington, R.S., Campa, V.M., Walker, M.M., Bengoa-Vergniory, N., Gorrono-Etxebarria, I., Uysal-Onganer, P., Kawano, Y., Waxman, J. and Kypta, R.M. 2012. Distinct expression and activity of GSK-3α and GSK-3β in prostate cancer. International Journal of Cancer. 131 (6), p. E872–E883. https://doi.org/10.1002/ijc.27620

Mode of interaction of calcium oxalate crystal with human phosphate cytidylyltransferase 1: a novel inhibitor purified from human renal stone matrix
Pathak, P., Naik, P.K., Sengupta, D., Singh, S.K. and Tandon, C. 2011. Mode of interaction of calcium oxalate crystal with human phosphate cytidylyltransferase 1: a novel inhibitor purified from human renal stone matrix. Journal of Biomedical Science and Engineering. 4 (9), pp. 591-598. https://doi.org/10.4236/jbise.2011.49075

Secreted Frizzled-related protein-1 is a negative regulator of androgen receptor activity in prostate cancer
Kawano, Y., Diez, S., Uysal-Onganer, P., Darrington, R.S., Waxman, J. and Kypta, R.M. 2009. Secreted Frizzled-related protein-1 is a negative regulator of androgen receptor activity in prostate cancer. British Journal of Cancer. 100, pp. 1165-1174. https://doi.org/10.1038/sj.bjc.6604976

Docking-MM-GB/SA and ADME screening of HIV-1 NNRTI inhibitor: Nevirapine and its analogues
Sengupta, D., Verma, D. and Naik, P.K. 2008. Docking-MM-GB/SA and ADME screening of HIV-1 NNRTI inhibitor: Nevirapine and its analogues. In Silico Biology. 8 (3-4), pp. 275-289.

Epidermal growth factor upregulates motility of Mat-LyLu rat prostate cancer cells partially via voltage-gated Na+ channel activity
Ding, Y., Brackenbury, W.J., Uysal Onganer, P., Montano, Ximena, Porter, L.M., Bates, L.F. and Djamgoz, M.B.A. 2008. Epidermal growth factor upregulates motility of Mat-LyLu rat prostate cancer cells partially via voltage-gated Na+ channel activity. Journal of Cellular Physiology. 215 (1), pp. 77-81. https://doi.org/10.1002/jcp.21289

Binding Modes, binding Affinities and ADME Screening of HIV-1 NNRTI Inhibitor: Efavirnez and its analogues.
Sengupta, D. 2007. Binding Modes, binding Affinities and ADME Screening of HIV-1 NNRTI Inhibitor: Efavirnez and its analogues. Online Journal of Bioinformatics. 8 (1), pp. 99-114.

In-silico TAT-PTD prediction for cell penetrating peptides
Tandon, C., Aggarwal, A., Goel, P., Sengupta, D. and Naik, P.K. 2007. In-silico TAT-PTD prediction for cell penetrating peptides. Online Journal of Bioinformatics. 8 (1), pp. 115-138.

Docking mode of delvardine and its analogues into the p66 domain of HIV-1 reverse transcriptase: Screening using molecular mechanics-generalized born/surface area and absorption, distribution, metabolism and excretion properties
Sengupta, D., Verma, D. and Naik, P.K. 2007. Docking mode of delvardine and its analogues into the p66 domain of HIV-1 reverse transcriptase: Screening using molecular mechanics-generalized born/surface area and absorption, distribution, metabolism and excretion properties. Journal of Biosciences. 32 (3), pp. 1307-1316. https://doi.org/10.1007/s12038-007-0140-y

Docking mode of delvardine and its analogues into the p66 domain of HIV-1 reverse transcriptase: screening using molecular mechanics-generalized born/surface area and absorption, distribution, metabolism and excretion properties
Sengupta, D., Verma, D. and Naik, P.K. 2007. Docking mode of delvardine and its analogues into the p66 domain of HIV-1 reverse transcriptase: screening using molecular mechanics-generalized born/surface area and absorption, distribution, metabolism and excretion properties. Journal of Biosciences. 32, pp. 1307-1316. https://doi.org/10.1007/s12038-007-0124-y

Clustering of HIV-I Subtype: Study of Molecular Diversity using Phylogenetic Analysis
Sengupta, D., Verma, D., Mishra, V.S. and Naik, P.K. 2006. Clustering of HIV-I Subtype: Study of Molecular Diversity using Phylogenetic Analysis. Bioinformatics Trends: A Journal of Bioinformatics and its Applications. 1 (1), pp. 1-12.

The expression and functional characterization of sigma (sigma) 1 receptors in breast cancer cell lines
Aydar, E., Uysal Onganer, P., Perrett, R., Djamgoz, M.B.A. and Palmer, C.P. 2006. The expression and functional characterization of sigma (sigma) 1 receptors in breast cancer cell lines. Cancer Letters. 242 (2), pp. 245-257. https://doi.org/10.1016/j.canlet.2005.11.011

An acetylcholinesterase-derived peptide inhibits endocytic membrane activity in a human metastatic breast cancer cell line
Uysal Onganer, P., Djamgoz, M.B.A., Whyte, K. and Greenfield, S.A. 2006. An acetylcholinesterase-derived peptide inhibits endocytic membrane activity in a human metastatic breast cancer cell line. Biochimica et Biophysica Acta: general subjects. 1760 (3), pp. 415-420. https://doi.org/10.1016/j.bbagen.2005.12.016

Small-cell lung cancer (human): potentiation of endocytic membrane activity by voltage-gated Na(+) channel expression in vitro
Uysal Onganer, P. and Djamgoz, M.B.A. 2005. Small-cell lung cancer (human): potentiation of endocytic membrane activity by voltage-gated Na(+) channel expression in vitro. Journal of Membrane Biology. 204, pp. 67-75. https://doi.org/10.1007/s00232-005-0747-6

Neuronal characteristics of small-cell lung cancer
Uysal Onganer, P., Seckl, M.J. and Djamgoz, M.B.A. 2005. Neuronal characteristics of small-cell lung cancer. British Journal of Cancer. 93, pp. 1197-1201. https://doi.org/10.1038/sj.bjc.6602857

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