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Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer that is characterized by its poor prognosis, rapid progression and development of drug resistance. Chemotherapy is a vital treatment option for most of PDAC patients. Stratification of PDAC patients, who would have a higher likel...

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Autores principales: Peng, Hong, Chen, Ru, Brentnall, Teresa A., Eng, Jimmy K., Picozzi, Vincent J., Pan, Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636003/
https://www.ncbi.nlm.nih.gov/pubmed/31346328
http://dx.doi.org/10.1186/s12014-019-9251-3
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author Peng, Hong
Chen, Ru
Brentnall, Teresa A.
Eng, Jimmy K.
Picozzi, Vincent J.
Pan, Sheng
author_facet Peng, Hong
Chen, Ru
Brentnall, Teresa A.
Eng, Jimmy K.
Picozzi, Vincent J.
Pan, Sheng
author_sort Peng, Hong
collection PubMed
description BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer that is characterized by its poor prognosis, rapid progression and development of drug resistance. Chemotherapy is a vital treatment option for most of PDAC patients. Stratification of PDAC patients, who would have a higher likelihood of responding to chemotherapy, could facilitate treatment selection and patient management. METHODS: A quantitative proteomic study was performed to characterize the protein profiles in the plasma of PDAC patients undergoing chemotherapy to determine if specific biomarkers could be used to predict likelihood of therapeutic response. RESULTS: By comparing the plasma proteome of the PDAC patients with positive therapeutic response and longer overall survival (Good-responders) to those who did not respond as well with shorter survival time (Limited-responders), we identified differential proteins and protein variants that could effectively segregate Good-responders from Limited-responders. Functional clustering and pathway analysis further suggested that many of these differential proteins were involved in pancreatic tumorigenesis. Four proteins, including vitamin-K dependent protein Z (PZ), sex hormone-binding globulin (SHBG), von Willebrand factor (VWF) and zinc-alpha-2-glycoprotein (AZGP1), were further evaluated as single or composite predictive biomarker with/without inclusion of CA 19-9. A composite biomarker panel that consists of PZ, SHBG, VWF and CA 19-9 demonstrated the best performance in distinguishing Good-responders from Limited-responders. CONCLUSION: Based on the cohort investigated, our data suggested that systemic proteome alterations involved in pathways associated with inflammation, immunoresponse, coagulation and complement cascades may be reporters of chemo-treatment outcome in PDAC patients. For the majority of the patients involved, the panel consisting of PZ, SHBG, VWF and CA 19-9 was able to segregate Good-responders from Limited-responders effectively. Our data also showed that dramatic fluctuations of biomarker concentration in the circulating system of a PDAC patient, which might result from biological heterogeneity or confounding complications, could diminish the performance of a biomarker. Categorization of PDAC patients in terms of their tumor stages and histological types could potentially facilitate patient stratification for treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12014-019-9251-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-66360032019-07-25 Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy Peng, Hong Chen, Ru Brentnall, Teresa A. Eng, Jimmy K. Picozzi, Vincent J. Pan, Sheng Clin Proteomics Research BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer that is characterized by its poor prognosis, rapid progression and development of drug resistance. Chemotherapy is a vital treatment option for most of PDAC patients. Stratification of PDAC patients, who would have a higher likelihood of responding to chemotherapy, could facilitate treatment selection and patient management. METHODS: A quantitative proteomic study was performed to characterize the protein profiles in the plasma of PDAC patients undergoing chemotherapy to determine if specific biomarkers could be used to predict likelihood of therapeutic response. RESULTS: By comparing the plasma proteome of the PDAC patients with positive therapeutic response and longer overall survival (Good-responders) to those who did not respond as well with shorter survival time (Limited-responders), we identified differential proteins and protein variants that could effectively segregate Good-responders from Limited-responders. Functional clustering and pathway analysis further suggested that many of these differential proteins were involved in pancreatic tumorigenesis. Four proteins, including vitamin-K dependent protein Z (PZ), sex hormone-binding globulin (SHBG), von Willebrand factor (VWF) and zinc-alpha-2-glycoprotein (AZGP1), were further evaluated as single or composite predictive biomarker with/without inclusion of CA 19-9. A composite biomarker panel that consists of PZ, SHBG, VWF and CA 19-9 demonstrated the best performance in distinguishing Good-responders from Limited-responders. CONCLUSION: Based on the cohort investigated, our data suggested that systemic proteome alterations involved in pathways associated with inflammation, immunoresponse, coagulation and complement cascades may be reporters of chemo-treatment outcome in PDAC patients. For the majority of the patients involved, the panel consisting of PZ, SHBG, VWF and CA 19-9 was able to segregate Good-responders from Limited-responders effectively. Our data also showed that dramatic fluctuations of biomarker concentration in the circulating system of a PDAC patient, which might result from biological heterogeneity or confounding complications, could diminish the performance of a biomarker. Categorization of PDAC patients in terms of their tumor stages and histological types could potentially facilitate patient stratification for treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12014-019-9251-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-17 /pmc/articles/PMC6636003/ /pubmed/31346328 http://dx.doi.org/10.1186/s12014-019-9251-3 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Peng, Hong
Chen, Ru
Brentnall, Teresa A.
Eng, Jimmy K.
Picozzi, Vincent J.
Pan, Sheng
Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy
title Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy
title_full Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy
title_fullStr Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy
title_full_unstemmed Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy
title_short Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy
title_sort predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636003/
https://www.ncbi.nlm.nih.gov/pubmed/31346328
http://dx.doi.org/10.1186/s12014-019-9251-3
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