ArticleClinical proteomics2019
Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy.
Article in Clinical proteomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 19 citations in OpenAlex.
- Development of a multiplex assay for early detection of pancreatic cancer in high-risk groups.BMC cancer · 2026Article
- Proteomics in pancreatic cancer.Biomarker research · 2025Review
- Blood-based biomarkers in pancreatic ductal adenocarcinoma: developments over the last decade and what holds for the future- a review.Frontiers in oncology · 2025Review
- Proteomics-Driven Biomarkers in Pancreatic Cancer.Proteomes · 2023Review
- Article
- An Integrated Proteomic and Glycoproteomic Investigation Reveals Alterations in theInternational journal of molecular sciences · 2022Article
- Article
- Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review.International journal of molecular sciences · 2022Review
- Molecular advances in pancreatic cancer: A genomic, proteomic and metabolomic approach.World journal of gastroenterology · 2021Review
- Novel Gene Signatures Predictive of Patient Recurrence-Free Survival and Castration Resistance in Prostate Cancer.Cancers · 2021Article
- Genome-wide association study of pancreatic fat: The Multiethnic Cohort Adiposity Phenotype Study.PloS one · 2021Article
- Implementation of MALDI Mass Spectrometry Imaging in Cancer Proteomics Research: Applications and Challenges.Journal of personalized medicine · 2020Review
- Systemic Proteome Alterations Linked to Early Stage Pancreatic Cancer in Diabetic Patients.Cancers · 2020Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundPancreatic 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.
methodsA 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.
resultsBy 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.
conclusionBased 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.
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