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Biomarker Identification in Human Lung Adenocarcinoma

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Biomarker Identification in Human Lung Adenocarcinoma Research Collection Doctoral Thesis Activity-based proteomics biomarker identification in human lung adenocarcinoma Author(s): Wiedl, Thomas Publication Date: 2011 Permanent Link: https://doi.org/10.3929/ethz-a-006698733 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library Diss. ETH Nr. 19704 Activity-based proteomics: biomarker identification in human lung adenocarcinoma A dissertation submitted to the ETH Zurich for the degree of Doctor of Sciences (Dr. sc. ETH Zurich) presented by Thomas Wiedl Dipl. Ing., Vienna University of Technology, Austria Born March 30, 1981 Citizen of Austria accepted on the recommendation of Prof. Dr. Rudolf Aebersold (examiner) Prof. Dr. Walter Weder (co-examiner) Prof. Dr. Holger Moch (co-examiner) Prof. Dr. Stephan Sieber (co-examiner) 2011 Table of contents SUMMARY 6 ZUSAMMENFASSUNG 8 ACKNOWLEDGEMENTS 10 ABBREVIATIONS 12 1. INTRODUCTION 14 1.1 LUNG CANCER : CLASSIFICATION , EPIDEMIOLOGY AND PROGNOSIS 14 1.2 MOLECULAR EVOLUTION OF LUNG CANCER 16 1.3 LUNG CANCER AND THE BIOMARKER CONCEPT : STATUS QUO 18 1.4 MASS SPECTROMETRY (MS) BASED PROTEOMICS 20 1.5 ACTIVITY -BASED PROTEOMICS : A NOVEL STRATEGY FOR BIOMARKER DISCOVERY 23 1.6 THE SERINE HYDROLASE SUPERFAMILY 26 1.7 LUNG CANCER IN THE FUTURE 29 2. MATERIAL AND METHODS 30 2.1 SAMPLE COLLECTION 30 2.2 CELL CULTURE AND LYSIS 31 2.3 WESTERN BLOT 31 2.4 ACTIVITY -BASED PROBE 32 2.5 PROTEOME PREPARATION FOR LC-MS/MS ANALYSIS 33 2.6 LC-MS/MS ANALYSIS 35 2.7 DATABASE SEARCH AND LABEL -FREE QUANTIFICATION 36 2.8 STATISTICAL ANALYSIS 37 3. RESULTS 42 3.1 1D-SDS-PAGE DEPENDENT ACTIVITY -BASED PROTEOMICS 42 3.1.1 SH ACTIVITY PROFILES OF CALU-3 CELL EXTRACTS (MEMBRANE FRACTION ) 42 3.1.2 SH ACTIVITY PROFILES OF CALU-3 CELL EXTRACTS (SOLUBLE FRACTION ) 45 3.1.3 SH ACTIVITY PROFILES OF HUMAN LUNG ADENOCARCINOMA BIOPSIES 48 3.2 A MASS SPECTROMETRY (MS) DEPENDENT PLATFORM FOR ACTIVITY -BASED BIOMARKER DISCOVERY 50 3.2.1 CONSIDERATIONS FOR A SOLELY MS DEPENDENT ACTIVITY -BASED BIOMARKER DISCOVERY PLATFORM 50 3.2.2 ACTIVITY -BASED PROBES : FP-BIOTIN AND FP-1 51 3.2.3 DIRECTED IDENTIFICATION OF ACTIVE SH S IN COMPLEX PROTEOMES 53 3.2.4 LABEL -FREE QUANTIFICATION WITH PROGENESIS LC-MS 54 3.2.5 REPEATABILITY , REPRODUCIBILITY AND ROBUSTNESS 54 3.3 SH ACTIVITY PROFILES IN HUMAN LUNG ADENOCARCINOMA 58 3.4 BIOMARKER IDENTIFICATION 60 3.5 COMPARISON OF ACTIVITY- AND TRANSCRIPT -LEVELS OF ESD AND ABHD11 64 4. DISCUSSION 66 4.1 ACTIVITY -BASED PROTEOMIC STRATEGIES FOR THE INVESTIGATION OF SH ACTIVITIES IN COMPLEX PROTEOMES 66 4.1.1 AN ADVANCED STRATEGY FOR THE IDENTIFICATION OF SH ACTIVITIES IN COMPLEX PROTEOMES 67 4.1.2 LABEL -FREE QUANTIFICATION 69 4.1.3 REPEATABILITY , REPRODUCIBILITY AND ROBUSTNESS 70 4.1.4 ACTIVITY -BASED PROTEOMICS AND BIOMARKER DISCOVERY : TECHNICAL ASPECTS 72 4.2 SH ACTIVITIES AND HUMAN LUNG ADENOCARCINOMA 73 4.2.1 GLOBAL SH ACTIVITY PROFILES AS POTENTIAL BIOMARKERS FOR HUMAN LUNG ADENOCARCINOMA 73 4.2.2 SH ACTIVITIES ASSOCIATED WITH HUMAN LUNG ADENOCARCINOMA 77 4.2.3 IDENTIFICATION OF ESD AND ABHD11 ACTIVITIES AS BIOMARKER CANDIDATES FOR HUMAN LUNG ADENOCARCINOMA 80 4.2.3.1 ESTERASE D (ESD) 80 4.2.3.2 ABHYDROLASE DOMAIN -CONTAINING PROTEIN 11 (ABHD11) 82 4.2.4 THE POTENTIAL OF ENZYMATIC ACTIVITIES AS CLINICAL BIOMARKERS : CHANCES AND LIMITATIONS 83 5. CONCLUSION 85 SUPPLEMENTARY DATA 88 PUBLICATIONS 104 REFERENCES 109 CURRICULUM VITAE 124 Summary 6 Summary Lung cancer is the leading cause of all cancer related deaths worldwide. The 5-year survival rate ranges from 80% in early stages to less than 5% in advanced disease. Non-small cell lung carcinoma (NSCLC) accounts for 80% of all lung malignancies, 40% of which are adenocarcinomas (ACs) representing one of the most common lung cancer subtypes. Currently, prognosis is mostly determined based on the extension of disease at diagnosis. Thereby it has become evident that predicted and real outcomes can vary significantly, even for patients with the same stage of disease. Thus, novel biomarkers that refine prognosis with a reliable clinical significance are clearly needed. In the genomic era biomarker studies typically aim at comparing transcript or protein abundances in malignant versus healthy tissues. However, taking into consideration that transcript and protein levels do not necessarily correlate with activity states, protein- and gene-expression profiling experiments might fail to detect changes in enzymatic activities caused by posttranslational events. Activity-based proteomics, a methodology that allows for the determination of enzymatic activity profiles of specific classes of enzymes even in complex proteomes, has become a valid option to circumvent this limitation. Based on the work of Prof. Cravatt, The Scripps Research Institute, USA and others an advanced activity-based proteomics platform for clinical biomarker discovery is presented in this PhD study. The implemented methodology was applied on 40 pairs of malignant and matching non- neoplastic human lung tissues to evaluate the potential of serine hydrolase (SH) activities, a large and diverse class of enzymes that have previously been linked to malignancies of the lung, as potential biomarker candidates for human lung adenocarcinoma. The implemented methodology represents a label-free, solely mass spectrometry (MS) dependent platform for relative quantification of enzymatic activities in complex proteomes. Key features of this platform include good repeatability and reproducibility on a qualitative level as well as high quantitative precision. The results of this study revealed that the SHs TPSB2 protein, LYPLA1, LYPLAL1, IAH1, ABHD10 and ABHD11 exhibited decreased or elevated activities in Summary 7 lung adenocarcinoma biopsies compared to matching non-neoplastic tissues in an almost exclusive manner, indicating that these enzymes play a general role in the pathogenesis of lung adenocarcinoma. On a transcript level, ESD , TPBS2 , IAH1 and ABHD10 did not show any differences in lung cancer biopsies compared to normal tissues of the respiratory system as determined with a publicly accessible gene expression database. These observations indicate that the found SH activity differences are not detectable on a transcript level. Furthermore, the activities of ESD predicted the presence of high-grade tumors and the activities of ABHD11 predicted the development of distant metastases, both in a statistically significant model (p<0.05). Importantly, neither ESD nor ABHD11 have previously been associated with NSCLC. Although data validation with an increased sample set will be required to perform clinically more relevant statistical analysis, we anticipate that ESD and / or ABHD11 activities have the potential to develop into molecular predictors with a reliable clinical significance. We conclude that the implemented activity-based proteomics platform represents a powerful tool in the search for novel disease biomarkers and that SH activities bear predictive potential for human lung adenocarcinoma. Zusammenfassung 8 Zusammenfassung Das Lungenkarzinom ist weltweit die häufigste Ursache aller krebsbedingten Todesfälle. Ausgehend vom Zeitpunkt der Diagnosestellung erstreckt sich die 5- Jahres-Überlebensrate von 80% in frühen Stadien bis hin zu 5% bei fortgeschrittener Erkrankung. Das nicht-kleinzellige Lungenkarzinom (NSCLC) repräsentiert dabei 80% aller Lungenkarzinome, 40% davon werden dem Subtyp Adenokarzinom (AC) zugeordnet, einer der häufigsten Histologien des Lungenkarzinoms. Zurzeit basiert die Krankheitsprognose auf der Einschätzung des Ausmasses der Krebserkrankung bei Diagnosestellung. Dabei stellte sich heraus, dass sich der prediktierte und tatsächliche Krankheitsverlauf signifikant unterscheiden können, selbst bei Patienten mit initial identischer Prognose. Um die Prediktion der Krankheitsverläufe zu verbessern werden molekulare Biomarker mit einer zuverlässigen klinischen Relevanz benötigt. Im Zeitalter der Genomik zielen Biomarkerstudien typischerweise darauf ab, Transkript- oder Proteinabundanzen in gesundem und malignem Gewebe zu vergleichen. Wenn man bedenkt, dass Transkript- oder Proteinabundanzen nicht unbedingt mit enzymatischen Aktivitäten korrelieren, besteht die Möglichkeit, dass durch konventionelle Protein- und Genexpressionsstudien Differenzen in Enzymaktivitäten aufgrund von posttranslationalen Modifikationen nicht detektiert werden. Durch direkte Messung von Aktivitätszuständen bestimmter Enzymklassen selbst in komplexen Proteomen, bietet die Methode der aktivitäts-basierenden Proteomik die Möglichkeit diese Einschränkung zu umgehen. Aufbauend auf der Arbeit von Prof. Cravatt, The Scripps Research Institute, USA und anderen stellen wir im Rahmen dieser Doktorarbeit eine weiterentwickelte, auf der Messung von Enzymaktivitäten basierende Plattform für die Identifikation von klinischen Biomarkern vor. Mit der implementierten Methode wurden 40 humane Lungen- Adenokarzinom Biopsien und korrespondierende normale Lungengewebe untersucht, um das Potential von Serinhydrolase (SH) Aktivitäten hinsichtlich ihrer Eignung als Biomarker zu eruieren. Für diese Studie stellten SHs eine interessante Gruppe von Proteinen dar, da einzelne Mitglieder dieser Enzymfamilie bereits mit dem Lungenkarzinom in Verbindung gebracht wurden. Zusammenfassung 9 Die in dieser Doktorarbeit vorgestellte Methode stellt eine auf Massenspektrometrie (MS) basierende Analyseplattform
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