Cargando…
Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer
Colorectal cancer represents a leading cause of cancer-related morbidity and mortality. Despite improvements, chemotherapy remains the backbone of colorectal cancer treatment. The aim of this study is to investigate the variation of circulating microRNA expression profiles and the response to irinot...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9820223/ https://www.ncbi.nlm.nih.gov/pubmed/36613487 http://dx.doi.org/10.3390/ijms24010046 |
_version_ | 1784865415896236032 |
---|---|
author | Pliakou, Evangelia Lampropoulou, Dimitra Ioanna Dovrolis, Nikolas Chrysikos, Dimosthenis Filippou, Dimitrios Papadimitriou, Christos Vezakis, Antonios Aravantinos, Gerasimos Gazouli, Maria |
author_facet | Pliakou, Evangelia Lampropoulou, Dimitra Ioanna Dovrolis, Nikolas Chrysikos, Dimosthenis Filippou, Dimitrios Papadimitriou, Christos Vezakis, Antonios Aravantinos, Gerasimos Gazouli, Maria |
author_sort | Pliakou, Evangelia |
collection | PubMed |
description | Colorectal cancer represents a leading cause of cancer-related morbidity and mortality. Despite improvements, chemotherapy remains the backbone of colorectal cancer treatment. The aim of this study is to investigate the variation of circulating microRNA expression profiles and the response to irinotecan-based treatment in metastatic colorectal cancer and to identify relevant target genes and molecular functions. Serum samples from 95 metastatic colorectal cancer patients were analyzed. The microRNA expression was tested with a NucleoSpin miRNA kit (Machnery-Nagel, Germany), and a machine learning approach was subsequently applied for microRNA profiling. The top 10 upregulated microRNAs in the non-responders group were hsa-miR-181b-5p, hsa-miR-10b-5p, hsa-let-7f-5p, hsa-miR-181a-5p, hsa-miR-181d-5p, hsa-miR-301a-3p, hsa-miR-92a-3p, hsa-miR-155-5p, hsa-miR-30c-5p, and hsa-let-7i-5p. Similarly, the top 10 downregulated microRNAs were hsa-let-7d-5p, hsa-let-7c-5p, hsa-miR-215-5p, hsa-miR-143-3p, hsa-let-7a-5p, hsa-miR-10a-5p, hsa-miR-142-5p, hsa-miR-148a-3p, hsa-miR-122-5p, and hsa-miR-17-5p. The upregulation of microRNAs in the miR-181 family and the downregulation of those in the let-7 family appear to be mostly involved with non-responsiveness to irinotecan-based treatment. |
format | Online Article Text |
id | pubmed-9820223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98202232023-01-07 Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer Pliakou, Evangelia Lampropoulou, Dimitra Ioanna Dovrolis, Nikolas Chrysikos, Dimosthenis Filippou, Dimitrios Papadimitriou, Christos Vezakis, Antonios Aravantinos, Gerasimos Gazouli, Maria Int J Mol Sci Article Colorectal cancer represents a leading cause of cancer-related morbidity and mortality. Despite improvements, chemotherapy remains the backbone of colorectal cancer treatment. The aim of this study is to investigate the variation of circulating microRNA expression profiles and the response to irinotecan-based treatment in metastatic colorectal cancer and to identify relevant target genes and molecular functions. Serum samples from 95 metastatic colorectal cancer patients were analyzed. The microRNA expression was tested with a NucleoSpin miRNA kit (Machnery-Nagel, Germany), and a machine learning approach was subsequently applied for microRNA profiling. The top 10 upregulated microRNAs in the non-responders group were hsa-miR-181b-5p, hsa-miR-10b-5p, hsa-let-7f-5p, hsa-miR-181a-5p, hsa-miR-181d-5p, hsa-miR-301a-3p, hsa-miR-92a-3p, hsa-miR-155-5p, hsa-miR-30c-5p, and hsa-let-7i-5p. Similarly, the top 10 downregulated microRNAs were hsa-let-7d-5p, hsa-let-7c-5p, hsa-miR-215-5p, hsa-miR-143-3p, hsa-let-7a-5p, hsa-miR-10a-5p, hsa-miR-142-5p, hsa-miR-148a-3p, hsa-miR-122-5p, and hsa-miR-17-5p. The upregulation of microRNAs in the miR-181 family and the downregulation of those in the let-7 family appear to be mostly involved with non-responsiveness to irinotecan-based treatment. MDPI 2022-12-20 /pmc/articles/PMC9820223/ /pubmed/36613487 http://dx.doi.org/10.3390/ijms24010046 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pliakou, Evangelia Lampropoulou, Dimitra Ioanna Dovrolis, Nikolas Chrysikos, Dimosthenis Filippou, Dimitrios Papadimitriou, Christos Vezakis, Antonios Aravantinos, Gerasimos Gazouli, Maria Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer |
title | Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer |
title_full | Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer |
title_fullStr | Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer |
title_full_unstemmed | Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer |
title_short | Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer |
title_sort | circulating mirna expression profiles and machine learning models in association with response to irinotecan-based treatment in metastatic colorectal cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9820223/ https://www.ncbi.nlm.nih.gov/pubmed/36613487 http://dx.doi.org/10.3390/ijms24010046 |
work_keys_str_mv | AT pliakouevangelia circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer AT lampropouloudimitraioanna circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer AT dovrolisnikolas circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer AT chrysikosdimosthenis circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer AT filippoudimitrios circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer AT papadimitriouchristos circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer AT vezakisantonios circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer AT aravantinosgerasimos circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer AT gazoulimaria circulatingmirnaexpressionprofilesandmachinelearningmodelsinassociationwithresponsetoirinotecanbasedtreatmentinmetastaticcolorectalcancer |