Cargando…
Analysis of EVs from patients with advanced pancreatic cancer identifies antigens and miRNAs with predictive value
The identification of predictive factors for treatment of pancreatic cancer (PC) is an unmet clinical need. In the present work, we analyzed blood-derived extracellular vesicles (EVs) from patients with advanced PC in order to find a molecular signature predictive of response to therapy. We analyzed...
Autores principales: | , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Gene & Cell Therapy
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238807/ https://www.ncbi.nlm.nih.gov/pubmed/37273899 http://dx.doi.org/10.1016/j.omtm.2023.05.009 |
_version_ | 1785053360354754560 |
---|---|
author | Vannini, Ivan Rossi, Tania Melloni, Mattia Valgiusti, Martina Urbini, Milena Passardi, Alessandro Bartolini, Giulia Gallio, Chiara Azzali, Irene Bandini, Sara Ancarani, Valentina Montanaro, Lorenzo Frassineti, Giovanni Luca Fabbri, Francesco Rapposelli, Ilario Giovanni |
author_facet | Vannini, Ivan Rossi, Tania Melloni, Mattia Valgiusti, Martina Urbini, Milena Passardi, Alessandro Bartolini, Giulia Gallio, Chiara Azzali, Irene Bandini, Sara Ancarani, Valentina Montanaro, Lorenzo Frassineti, Giovanni Luca Fabbri, Francesco Rapposelli, Ilario Giovanni |
author_sort | Vannini, Ivan |
collection | PubMed |
description | The identification of predictive factors for treatment of pancreatic cancer (PC) is an unmet clinical need. In the present work, we analyzed blood-derived extracellular vesicles (EVs) from patients with advanced PC in order to find a molecular signature predictive of response to therapy. We analyzed samples from 21 patients with advanced PC, all receiving first-line treatment with gemcitabine + nab-paclitaxel. Isolated EVs have been analyzed, and the results of laboratory have been matched with clinical data in order to investigate possible predictive factors. EV concentration and size were similar between responder and non-responder patients. Analysis of 37 EV surface epitopes showed a decreased expression of SSEA4 and CD81 in responder patients. We detected more than 450 expressed miRNAs in EVs. A comparative survey between responder and non-responder patients showed that at least 44 miRNAs were differently expressed. Some of these miRNAs have already been observed in relation to the survival and gemcitabine sensitivity of tumor cells. In conclusion, we showed the ability of our approach to identify EV-derived biomarkers with predictive value for therapy response in PC. Our findings are worthy of further investigation, including the analysis of samples from patients treated with different schedules and in different settings. |
format | Online Article Text |
id | pubmed-10238807 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Society of Gene & Cell Therapy |
record_format | MEDLINE/PubMed |
spelling | pubmed-102388072023-06-04 Analysis of EVs from patients with advanced pancreatic cancer identifies antigens and miRNAs with predictive value Vannini, Ivan Rossi, Tania Melloni, Mattia Valgiusti, Martina Urbini, Milena Passardi, Alessandro Bartolini, Giulia Gallio, Chiara Azzali, Irene Bandini, Sara Ancarani, Valentina Montanaro, Lorenzo Frassineti, Giovanni Luca Fabbri, Francesco Rapposelli, Ilario Giovanni Mol Ther Methods Clin Dev Original Article The identification of predictive factors for treatment of pancreatic cancer (PC) is an unmet clinical need. In the present work, we analyzed blood-derived extracellular vesicles (EVs) from patients with advanced PC in order to find a molecular signature predictive of response to therapy. We analyzed samples from 21 patients with advanced PC, all receiving first-line treatment with gemcitabine + nab-paclitaxel. Isolated EVs have been analyzed, and the results of laboratory have been matched with clinical data in order to investigate possible predictive factors. EV concentration and size were similar between responder and non-responder patients. Analysis of 37 EV surface epitopes showed a decreased expression of SSEA4 and CD81 in responder patients. We detected more than 450 expressed miRNAs in EVs. A comparative survey between responder and non-responder patients showed that at least 44 miRNAs were differently expressed. Some of these miRNAs have already been observed in relation to the survival and gemcitabine sensitivity of tumor cells. In conclusion, we showed the ability of our approach to identify EV-derived biomarkers with predictive value for therapy response in PC. Our findings are worthy of further investigation, including the analysis of samples from patients treated with different schedules and in different settings. American Society of Gene & Cell Therapy 2023-05-11 /pmc/articles/PMC10238807/ /pubmed/37273899 http://dx.doi.org/10.1016/j.omtm.2023.05.009 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Original Article Vannini, Ivan Rossi, Tania Melloni, Mattia Valgiusti, Martina Urbini, Milena Passardi, Alessandro Bartolini, Giulia Gallio, Chiara Azzali, Irene Bandini, Sara Ancarani, Valentina Montanaro, Lorenzo Frassineti, Giovanni Luca Fabbri, Francesco Rapposelli, Ilario Giovanni Analysis of EVs from patients with advanced pancreatic cancer identifies antigens and miRNAs with predictive value |
title | Analysis of EVs from patients with advanced pancreatic cancer identifies antigens and miRNAs with predictive value |
title_full | Analysis of EVs from patients with advanced pancreatic cancer identifies antigens and miRNAs with predictive value |
title_fullStr | Analysis of EVs from patients with advanced pancreatic cancer identifies antigens and miRNAs with predictive value |
title_full_unstemmed | Analysis of EVs from patients with advanced pancreatic cancer identifies antigens and miRNAs with predictive value |
title_short | Analysis of EVs from patients with advanced pancreatic cancer identifies antigens and miRNAs with predictive value |
title_sort | analysis of evs from patients with advanced pancreatic cancer identifies antigens and mirnas with predictive value |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238807/ https://www.ncbi.nlm.nih.gov/pubmed/37273899 http://dx.doi.org/10.1016/j.omtm.2023.05.009 |
work_keys_str_mv | AT vanniniivan analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT rossitania analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT mellonimattia analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT valgiustimartina analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT urbinimilena analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT passardialessandro analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT bartolinigiulia analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT galliochiara analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT azzaliirene analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT bandinisara analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT ancaranivalentina analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT montanarolorenzo analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT frassinetigiovanniluca analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT fabbrifrancesco analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue AT rapposelliilariogiovanni analysisofevsfrompatientswithadvancedpancreaticcanceridentifiesantigensandmirnaswithpredictivevalue |