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Mass Spectrometry-Based Protein Biomarker Discovery in Pancreatic Cancer

Zhou, Qimin LU orcid (2020) In Lund University, Faculty of Medicine Doctoral Dissertation Series
Abstract
Background: Pancreatic cancer has the lowest survival rate among all the major cancer types. Although recent decades have seen advances in diagnostic imaging, surgical techniques, perioperative care and oncological treatment, this has not been translated into major improvements in clinical outcome. The 5-year survival rate remains less than 10% for all stages. One important unmet clinical need is biomarkers of clinical utility that can be used for early detection, prognostication and guidance of treatment.

Aim: The aim of this thesis was to develop and validate protein biomarkers for diagnosis, prognosis and prediction of treatment response in pancreatic cancer.

Methods: Mass spectrometry (MS)-based proteomic profiling of... (More)
Background: Pancreatic cancer has the lowest survival rate among all the major cancer types. Although recent decades have seen advances in diagnostic imaging, surgical techniques, perioperative care and oncological treatment, this has not been translated into major improvements in clinical outcome. The 5-year survival rate remains less than 10% for all stages. One important unmet clinical need is biomarkers of clinical utility that can be used for early detection, prognostication and guidance of treatment.

Aim: The aim of this thesis was to develop and validate protein biomarkers for diagnosis, prognosis and prediction of treatment response in pancreatic cancer.

Methods: Mass spectrometry (MS)-based proteomic profiling of fresh frozen tissue specimens from pancreatic cancer patients and control subjects was conducted to identify potential protein biomarkers. These were subsequently verified by targeted proteomics (parallel reaction monitoring (PRM)) and bioinformatic analysis. Selected biomarker candidates were further validated in larger patient cohorts by tissue microarray-based immunohistochemistry studies, serum immunoassay measurements and in vitro experiments.

Results/conclusions:

(I) A proteolytic digestion protocol was optimised for MS-based proteomics studies. Urea in-solution digestion at room temperature (24 ± 2 °C) was found to be superior to traditional proteolysis at 37 °C, presenting several advantages such as fewer experimentally-induced post-translational modifications (carbamylation and pyroglutamic acid modifications), increased identification of peptides and proteins, and improved protein quantification by reducing coefficients of variations.

(II) Some 165 potential protein biomarkers were identified in pancreatic cancer tissues and a panel of 45 biomarker candidates was verified by targeted MS. The novel protein BASP1 was significantly associated with favourable survival and positive response to adjuvant chemotherapy in pancreatic cancer patients. Bioinformatic analysis indicated that BASP1 interacts with Wilms tumour protein WT1. Patients with negative BASP1 and high WT1 expression had the poorest outcomes.

(III) Prognostic analysis of YAP1 demonstrated a significant correlation with lower survival, at both mRNA expression levels (TCGA cohort) and protein expression levels (Lund cohort). Inhibiting the YAP1/TEAD interaction interfered with the expression of AREG, CTGF, CYR61 and MSLN in pancreatic cancer cells, which suggests that YAP1 transcriptional activity may affect the evolution and persistence of a fibrotic tumour microenvironment.

(IV) Expression of AGP1 in pancreatic cancer tissues is significantly correlated with poor survival. Circulating levels of AGP1 and CA 19-9 yielded a high diagnostic accuracy (AUC 0.963) for discrimination of resectable pancreatic cancer patients against healthy controls.
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Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Sund, Malin, Department of Surgical and Perioperative Sciences, Umeå University, Umeå, Sweden
organization
publishing date
type
Thesis
publication status
published
subject
keywords
pancreatic cancer, proteomics, mass spectrometry, biomarkers, diagnosis, prognosis, prediction, BASP1, WT1, YAP1, AGP1
in
Lund University, Faculty of Medicine Doctoral Dissertation Series
issue
2020:47
pages
84 pages
publisher
Lund University, Faculty of Medicine
defense location
Föreläsningssal 3, Centralblocket, Entrégatan 7, Skånes Universitetssjukhus i Lund
defense date
2020-04-28 13:00:00
ISSN
1652-8220
ISBN
978-91-7619-908-4
language
English
LU publication?
yes
id
0df25cdf-cdf8-465e-b398-0d27ab10e789
date added to LUP
2020-04-06 15:59:19
date last changed
2020-04-17 15:06:38
@phdthesis{0df25cdf-cdf8-465e-b398-0d27ab10e789,
  abstract     = {{Background: Pancreatic cancer has the lowest survival rate among all the major cancer types. Although recent decades have seen advances in diagnostic imaging, surgical techniques, perioperative care and oncological treatment, this has not been translated into major improvements in clinical outcome. The 5-year survival rate remains less than 10% for all stages. One important unmet clinical need is biomarkers of clinical utility that can be used for early detection, prognostication and guidance of treatment.<br/><br/>Aim: The aim of this thesis was to develop and validate protein biomarkers for diagnosis, prognosis and prediction of treatment response in pancreatic cancer.<br/><br/>Methods: Mass spectrometry (MS)-based proteomic profiling of fresh frozen tissue specimens from pancreatic cancer patients and control subjects was conducted to identify potential protein biomarkers. These were subsequently verified by targeted proteomics (parallel reaction monitoring (PRM)) and bioinformatic analysis. Selected biomarker candidates were further validated in larger patient cohorts by tissue microarray-based immunohistochemistry studies, serum immunoassay measurements and in vitro experiments.<br/><br/>Results/conclusions:<br/><br/>(I) A proteolytic digestion protocol was optimised for MS-based proteomics studies. Urea in-solution digestion at room temperature (24 ± 2 °C) was found to be superior to traditional proteolysis at 37 °C, presenting several advantages such as fewer experimentally-induced post-translational modifications (carbamylation and pyroglutamic acid modifications), increased identification of peptides and proteins, and improved protein quantification by reducing coefficients of variations.<br/><br/>(II) Some 165 potential protein biomarkers were identified in pancreatic cancer tissues and a panel of 45 biomarker candidates was verified by targeted MS. The novel protein BASP1 was significantly associated with favourable survival and positive response to adjuvant chemotherapy in pancreatic cancer patients. Bioinformatic analysis indicated that BASP1 interacts with Wilms tumour protein WT1. Patients with negative BASP1 and high WT1 expression had the poorest outcomes.<br/><br/>(III) Prognostic analysis of YAP1 demonstrated a significant correlation with lower survival, at both mRNA expression levels (TCGA cohort) and protein expression levels (Lund cohort). Inhibiting the YAP1/TEAD interaction interfered with the expression of AREG, CTGF, CYR61 and MSLN in pancreatic cancer cells, which suggests that YAP1 transcriptional activity may affect the evolution and persistence of a fibrotic tumour microenvironment.<br/><br/>(IV) Expression of AGP1 in pancreatic cancer tissues is significantly correlated with poor survival. Circulating levels of AGP1 and CA 19-9 yielded a high diagnostic accuracy (AUC 0.963) for discrimination of resectable pancreatic cancer patients against healthy controls.<br/>}},
  author       = {{Zhou, Qimin}},
  isbn         = {{978-91-7619-908-4}},
  issn         = {{1652-8220}},
  keywords     = {{pancreatic cancer; proteomics; mass spectrometry; biomarkers; diagnosis; prognosis; prediction; BASP1; WT1; YAP1; AGP1}},
  language     = {{eng}},
  number       = {{2020:47}},
  publisher    = {{Lund University, Faculty of Medicine}},
  school       = {{Lund University}},
  series       = {{Lund University, Faculty of Medicine Doctoral Dissertation Series}},
  title        = {{Mass Spectrometry-Based Protein Biomarker Discovery in Pancreatic Cancer}},
  url          = {{https://lup.lub.lu.se/search/files/78105474/Qimin_Zhou.pdf}},
  year         = {{2020}},
}