Targeted and explorative profiling of kallikrein proteases and global proteome biology of pancreatic ductal adenocarcinoma, chronic pancreatitis, and normal pancreas highlights disease-specific proteome remodelling

Werner, Janina; Bernhard, Patrick; Cosenza-Contreras, Miguel; Pinter, Niko; Fahrner, Matthias; Pallavi, Prama; Eberhard, Johannes; Bronsert, Peter; Rückert, Felix; Schilling, Oliver

doi:10.1016/j.neo.2022.100871

Cited by 14 publications

(16 citation statements)

References 69 publications

(99 reference statements)

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“…All measurements were done on a Q-Exactive Plus (Thermo Scientific, Bremen, Germany). Mass spectra were analyzed using DIANN [ 16 ] as described previously [ 17 ]. Peptide identification was performed using a human proteome database containing reviewed UniProt sequences without isoforms downloaded from Uniprot on 9th of January 2020.…”

Section: Methodsmentioning

confidence: 99%

The serum proteome of VA-ECMO patients changes over time and allows differentiation of survivors and non-survivors: an observational study

et al. 2023

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Background Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is applied in patients with refractory hemodynamic failure. Exposure of blood components to high shear stress and the large extracorporeal surfaces in the ECMO circuit trigger a complex inflammatory response syndrome and coagulopathy which are believed to worsen the already poor prognosis of these patients. Mass spectrometry-based proteomics allow a detailed characterization of the serum proteome as it provides the identity and concentration of large numbers of individual proteins at the same time. In this study, we aimed to characterize the serum proteome of patients receiving VA-ECMO. Methods Serum samples were collected on day 1 and day 3 after initiation of VA-ECMO. Samples underwent immunoaffinity based depletion for the 14 most abundant serum proteins, in-solution digestion and PreOmics clean-up. A spectral library was built with multiple measurements of a master-mix sample using variable mass windows. Individual samples were measured in data independent acquisition (DIA) mode. Raw files were analyzed by DIA-neural network. Unique proteins were log transformed and quantile normalized. Differential expression analysis was conducted with the LIMMA—R package. ROAST was applied to generate gene ontology enrichment analyses. Results Fourteen VA-ECMO patients and six healthy controls were recruited. Seven patients survived. Three hundred and fifty-one unique proteins were identified. One hundred and thirty-seven proteins were differentially expressed between VA-ECMO patients and controls. One hundred and forty-five proteins were differentially expressed on day 3 compared to day 1. Many of the differentially expressed proteins were involved in coagulation and the inflammatory response. The serum proteomes of survivors and non-survivors on day 3 differed from each other according to partial least-squares discriminant analysis (PLS-DA) and 48 proteins were differentially expressed. Many of these proteins have also been ascribed to processes in coagulation and inflammation (e.g., Factor IX, Protein-C, Kallikrein, SERPINA10, SEMA4B, Complement C3, Complement Factor D and MASP-1). Conclusion The serum proteome of VA-ECMO patients displays major changes compared to controls and changes from day 1 until day 3. Many changes in the serum proteome are related to inflammation and coagulation. Survivors and non-survivors can be differentiated according to their serum proteomes using PLS-DA analysis on day 3. Our results build the basis for future studies using mass-spectrometry based serum proteomics as a tool to identify novel prognostic biomarkers. Trial registration: DRKS00011106.

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Section: Methodsmentioning

confidence: 99%

The serum proteome of VA-ECMO patients changes over time and allows differentiation of survivors and non-survivors: an observational study

et al. 2023

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“…We integrated our data with treatment-naïve PDAC and noncancerous pancreas proteome profiles of the CPTAC, 19 and of a study by Werner et al 14 to enable a total of three proteomic comparisons (Figure 1A): (i) NCT vs treatment-naïve, (ii) NCRT vs treatment-naïve and (iii) NCT vs NCRT. Among all three studies, 3356 proteins were commonly identified.…”

Section: Integration Of Publicly Available Proteomics Data Of Treatme...mentioning

confidence: 99%

“…We analyzed formalin‐fixed and paraffin‐embedded (FFPE) tissue specimens. First, we compared the residual PDAC tumor after neoadjuvant treatment with treatment‐naïve PDAC published in a study by Werner et al 14 Afterwards, we performed a detailed comparison of both neoadjuvant treatments and correlated the proteome expression data with the survival time to identify potential prognostic candidate markers.…”

Section: Introductionmentioning

confidence: 99%

Neoadjuvant chemo‐ or chemo‐radiation‐therapy of pancreatic ductal adenocarcinoma differentially shift ECM composition, complement activation, energy metabolism and ribosomal proteins of the residual tumor mass

Stillger,

Kurowski,

Bronsert

et al. 2024

Intl Journal of Cancer

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Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed at stages that dis‐qualify for surgical resection. Neoadjuvant therapies offer potential tumor regression and improved resectability. Although features of the tumor biology (e.g., molecular markers) may guide adjuvant therapy, biological alterations after neoadjuvant therapy remain largely unexplored. We performed mass spectrometry to characterize the proteomes of 67 PDAC resection specimens of patients who received either neoadjuvant chemo (NCT) or chemo‐radiation (NCRT) therapy. We employed data‐independent acquisition (DIA), yielding a proteome coverage in excess of 3500 proteins. Moreover, we successfully integrated two publicly available proteome datasets of treatment‐naïve PDAC to unravel proteome alterations in response to neoadjuvant therapy, highlighting the feasibility of this approach. We found highly distinguishable proteome profiles. Treatment‐naïve PDAC was characterized by enrichment of immunoglobulins, complement and extracellular matrix (ECM) proteins. Post‐NCT and post‐NCRT PDAC presented high abundance of ribosomal and metabolic proteins as compared to treatment‐naïve PDAC. Further analyses on patient survival and protein expression identified treatment‐specific prognostic candidates. We present the first proteomic characterization of the residual PDAC mass after NCT and NCRT, and potential protein candidate markers associated with overall survival. We conclude that residual PDAC exhibits fundamentally different proteome profiles as compared to treatment‐naïve PDAC, influenced by the type of neoadjuvant treatment. These findings may impact adjuvant or targeted therapy options.

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“…In addition, KLK6 hydrolyzes myelin basic protein (MBP) [4], and when its enzymatic activity is blocked with antibodies, there is a reduction in the severity of symptoms caused by central nervous system inflammation, a model for multiple sclerosis, in mice [5]. KLK6 also plays an important role in several cancers as component of the tumor microenvironment [6]. Recent studies have shown that inhibition of KLK6 reduced the invasiveness of pancreatic cancer cells [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…KLK6 also plays an important role in several cancers as component of the tumor microenvironment [6]. Recent studies have shown that inhibition of KLK6 reduced the invasiveness of pancreatic cancer cells [6,7]. As a result, this enzyme may represent an attractive target for therapeutic development.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Performance of Docking, FEP, and MM/GBSA Methods on a Series of KLK6 Inhibitors

Silva

Freitas

2023

Preprint

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Kallikrein 6 (KLK6) is an attractive drug target for the treatment of neurological diseases and for various cancers. Herein, we explore the accuracy and efficiency of different computational methods and protocols to predict the free energy of binding (ΔGbind) of a series of KLK6 inhibitors. We found that the performance of the methods varied strongly with the tested system. For only one of the three KLK6 datasets, the docking scores were in good agreement (R2 ≥ 0.5) with experimental values of ΔGbind. A similar result was obtained with MM/GBSA calculations based on single minimized structures. Improved binding affinity predictions were obtained with the free energy perturbation (FEP) method, with an overall MUE and RMSE of 0.53 and 0.68 kcal/mol, respectively. This result indicates that FEP can be a promising tool for the structure-based optimization of KLK6 inhibitors.

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Targeted and explorative profiling of kallikrein proteases and global proteome biology of pancreatic ductal adenocarcinoma, chronic pancreatitis, and normal pancreas highlights disease-specific proteome remodelling

Cited by 14 publications

References 69 publications

The serum proteome of VA-ECMO patients changes over time and allows differentiation of survivors and non-survivors: an observational study

The serum proteome of VA-ECMO patients changes over time and allows differentiation of survivors and non-survivors: an observational study

Neoadjuvant chemo‐ or chemo‐radiation‐therapy of pancreatic ductal adenocarcinoma differentially shift ECM composition, complement activation, energy metabolism and ribosomal proteins of the residual tumor mass

Assessing the Performance of Docking, FEP, and MM/GBSA Methods on a Series of KLK6 Inhibitors

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