A LC/MS-based Metabolomics Analysis on Cancer : The Path to Potential Biomarkers Discovery
- 주제(키워드) Liquid Chromatography-Mass Spectrometry , Metabolomics , Lung Cancer , Prostate Cancer , Biomarker
- 발행기관 고려대학교 대학원
- 지도교수 Youngja Hwang Park
- 발행년도 2017
- 학위수여년월 2017. 8
- 학위구분 석사
- 학과 대학원 약학과
- 원문페이지 66 p
- 실제URI http://www.dcollection.net/handler/korea/000000076430
- 본문언어 영어
- 제출원본 000045915583
초록/요약
The increasing number of lung and prostate cancer incidence and mortality has led to an increase in the number of studies investigating this malignancy. Determining the type of mutation (in this case, lung cancer) is important, as it is used to determine patient treatment. In addition, the need to develop a less invasive detection technique is important for aiding diagnosis, as cytologic or histologic detection is time-consuming. With the urgency of the issue mentioned above, a thorough analysis for discovering the solution was found to be necessary. Therefore, this study aimed to perform high-resolution metabolomics (HRM) using LC-MS to identify significant compounds that may induce lung cancer on Korean serum samples and their correlation with patient’s smoking habit (Study 1), to identify plasma biomarkers associated with mutations in exon 19 or 21 of EGFR, in order to facilitate the early detection and provide a minimally-invasive diagnosis of NSCLC (Study 2), and to detect significant compounds in serum samples that might influence prostate cancer development in Korean population (Study 3). Utilizing Korean Cancer Prevention Study-II participants and Korea University Guro hospital patients, those three study were conducted. The metabolic differences between control groups were compared with case group. Univariate analysis was performed, Manhattan plot with a false discovery rate of q=0.05, in order to identify significant metabolites between the two groups. In addition, hierarchical clustering analysis was performed to discriminate between the metabolic profiles of the two groups. The next analysis will cover about metabolites annotation and pathway analysis using several platforms, like METLIN & KEGG database, Mummichog, and MetaboAnalyst. Various significant metabolites were detected, complete with their potential explanation about their relationship with lung/prostate cancer development. In summary, HRM in combination with network and pathway analysis using significant metabolites detected from human samples provided information regarding potential biomarkers for disease, in this case, cancer. These findings may create opportunities for the development of new diagnostic tools.
more목차
Abstract i
Table of Contents ii
1 Introduction 1
1.1 Background 1
1.1.1 Cancer 1
1.1.2 Biomarker and Metabolomics 3
1.1.3 Liquid Chromatography – Mass Spectrometry 3
1.2 Statement of Problem 5
1.3 Research Objectives 6
1.4 Significance 6
1.5 Scope and Limitation 6
2 Materials and Methods 7
2.1 Materials 7
2.1.1 Samples Collection for Study 1 7
2.1.2 Samples Collection for Study 2 7
2.1.3 Samples Collection for Study 3 9
2.2 Methods 9
2.2.1 Study Design 9
2.2.2 Sample Preparation and LC/MS Measurements 10
2.2.3 Metabolic Profiling with Statistical Analysis 11
2.2.4 Data Annotation and Pathway Analysis 11
2.2.5 Relative Abundance Comparison of Significant Metabolites 13
3 Results and Discussion 13
3.1 Metabolomics Study Discovering Serum Biomarker on Korean
Lung Cancer Subjects 15
3.2 Metabolomics Study Discovering Plasma Biomarker on Korean
Lung Cancer Mutation Subjects 25
3.3 Metabolomics Study Discovering Serum Biomarker on Korean
Prostate Cancer Subjects 35
3.4 Comparison of Pathway Analysis Platforms 46
4 Conclusions & Summary 48
5 References 49
Acknowledgements 56
