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Peng H, Chen R, Brentnall TA, et al. Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy. Clin Proteomics. 2019;16:31doi: 10.1186/s12014-019-9251-3.
Peng, H., Chen, R., Brentnall, T. A., Eng, J. K., Picozzi, V. J., & Pan, S. (2019). Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy. Clinical proteomics, 1631. https://doi.org/10.1186/s12014-019-9251-3
Peng, Hong, et al. "Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy." Clinical proteomics vol. 16 (2019): 31. doi: https://doi.org/10.1186/s12014-019-9251-3
Peng H, Chen R, Brentnall TA, Eng JK, Picozzi VJ, Pan S. Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy. Clin Proteomics. 2019 Jul 17;16:31. doi: 10.1186/s12014-019-9251-3. eCollection 2019. PMID: 31346328; PMCID: PMC6636003.
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Clin Proteomics. 2019 Jul 17;16:31. doi: 10.1186/s12014-019-9251-3. eCollection 2019.

Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy.

Clinical proteomics

Hong Peng, Ru Chen, Teresa A Brentnall, Jimmy K Eng, Vincent J Picozzi, Sheng Pan

Affiliations

  1. 1Institute of Molecular Medicine, the University of Texas Health Science Center at Houston, Houston, TX 77030 USA.
  2. 2Division of Gastroenterology, Department of Medicine, Baylor College of Medicine, Houston, TX 77030 USA.
  3. 3Division of Gastroenterology, Department of Medicine, The University of Washington, Seattle, WA 98195 USA.
  4. 4Proteomics Resource, The University of Washington, Seattle, WA 98109 USA.
  5. 5Virginia Mason Medical Center, Seattle, WA 98101 USA.

PMID: 31346328 PMCID: PMC6636003 DOI: 10.1186/s12014-019-9251-3

Abstract

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.

Keywords: Biomarker; Chemotherapy; Mass spectrometry; Pancreatic cancer; Plasma; Proteomics

Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

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