Nonsynonymous Single-Nucleotide Variations on Some Posttranslational Modifications of Human Proteins and the Association with Diseases

Protein posttranslational modifications (PTMs) play key roles in a variety of protein activities and cellular processes. Different PTMs show distinct impacts on protein functions, and normal protein activities are consequences of all kinds of PTMs working together. With the development of high throughput technologies such as tandem mass spectrometry (MS/MS) and next generation sequencing, more and more nonsynonymous single-nucleotide variations (nsSNVs) that cause variation of amino acids have been identified, some of which result in the damage of PTMs. The damaged PTMs could be the reason of the development of some human diseases. In this study, we elucidated the proteome wide relationship of eight damaged PTMs to human inherited diseases and cancers. Some human inherited diseases or cancers may be the consequences of the interactions of damaged PTMs, rather than the result of single damaged PTM site

프로테오지노믹스 기법을 이용한 폐암 바이오마커 연구

학위논문 (박사)-- 서울대학교 대학원 : 수의과대학 수의학과, 2019. 2. 조제열.정밀의료 패러다임의 등장 이후, 질환의 진단 및 치료를 위해서 바이오마커에 대한 수요는 높아지고있다. 가설기반연구는 전통적으로 당연하게 사용되오던 연구수행체계이지만, 바이오마커 발굴에서 필연적으로 마주치게되는 광범위한 스크리닝 작업에서는 효율성의 한계를 드러낸다. 오믹스기술의 등장과 함께 질환연구의 패러다임은 증거기반 대규모 타겟발굴방식으로 변화하고 있다. 단백질은 생체 기능조절에 직접적으로 관여하는 물질이기 때문에 바이오마커로 활용할 수 있는 가장 이상적인 물질로 여겨진다. 질량분석기를 이용한 단백체분석은 단백질을 직접 정성 및 정량할 수 있을 뿐만 아니라 매우 생산성이 높아 질환 바이오마커 발굴에 유용하다. 이 논문에서는 질량분석기를 이용하여 폐암 바이오마커의 발굴을 위한 고도화된 분석기법인 프로테오지노믹스 기법의 적용과, 스크리닝된 바이오마커후보 단백질의 정량검증 및 폐암 감별진단 조합마커의 생성연구에 대하여 알아본다. CHAPTER I에서는 인간염색체기반 단백체프로젝트 (C-HPP)의 일환으로 수행된 염색체9번에 대한 단백체연구가 포함되어있다. 미확인 단백질과 유전단백체에서 발견되지 않았던 시그니처를 밝혀내기 위해 LC-MS/MS분석과 RNA-seq 차세대염기분석기법을 적용하여 샘암종 폐암환자 5명의 정상-종양조직을 분석하였다. 염색체중심-인간단백체프로젝트의 2013년 리포트에서는 neXtProt 인간단백체 데이터베이스를 기준으로 염색체 9번에서 170개의 미확인 단백질이 있는 것으로 알려졌으며, 본 논문의 연구가 진행된 2015년에는 133개가 계속 미확인상태로 남아있었다. 본 논문의 단백체분석에서는 19개의 미확인 단백질을 동정할 수 있었으며, 그 중에서 염색체9번에 해당하는 단백질은 SPATA31A4 한 개 였다. RNA-seq분석으로는 샘종폐암조직 5개에서 공통적으로 검출되면서 정상조직에서는 검출되지 않는nonsynonymous SNP 5개 (CDH17, HIST1H1T, SAPCD2, ZNF695) 그리고 synonymous SNP 3개를 발굴할 수 있었다. 프로테오지노믹 분석을 위해서 각 시료별 RNA-seq데이터를 가공하여 맞춤형 데이터베이스를 구축하였다. 이렇게 생성된 시료맞춤형 데이터베이스를 단백체 질량분석데이터 검색에 활용하여 5개 유전자(LTF, HDLBP, TF, HBD, HLA-DRB5)에 해당하는 7개의 돌연변이를 검출하였다. 두 개의 돌연변이는 정상조직에서는 검출되지 않고 암조직에서만 검출되었다. 또한, 이 결과에서는 정상-암조직 모두에서 위유전자 (EEF1A1P5) 펩티드를 검출할 수 있었다. CHAPTER II에서는 다중반응검지법 (MRM) 을 이용한 단백질 바이오마커 검증과 조합마커 구성에 대한 연구를 서술하였다. 폐암과 다른 폐질환은 감별이 어렵기 때문에 폐암은 오진단 위험이 큰 질병이다. 따라서 혈청기반의 폐암감별진단 바이오마커개발의 필요성은 널리 인정되고있다. 이 단원에서는 폐암환자와 대조군폐질환 환자 198명의 혈청시료를 활용하여 일곱개의 폐암바이오마커 후보단백질을 나노유속 액체크로마토그래피-다중반응검지법으로 정량하였다. 후보단백질을 개별로 분석하였을 때에는 SERPINA4만이 통계적으로 유의성있게 혈중농도가 감소하는 것으로 나타났다. 다중반응검지법 전체데이터를 임상정보와 함께 로지스틱회귀모델에 적용하여 하나의 조합마커로 만들 수 있었다. 이 과정에서 개별마커로는 통계적인 유의성이 두드러지지 않지만 간섭효과를 만들어낼 수 있는 변수를 고려하여 모델링을 진행하였다. 최종적으로 SERPINA4, PON1, 나이를 조합하였을 때 가장 최적의 조합마커가 생성되었다. 이 조합마커는 AUC 0.915 의 감별진단 성능을 보여주었으며, 모델을 만드는데 사용되었던 시료와는 별개의 검증군에서도 성능은 유지되었다. 이와 같이 통계모델을 이용하여 생성한 조합마커는 개별 분자마커를 이용했을 경우보다 개선된 폐암 감별진단능력을 보여줄 수 있음을 제시한다.Biomarkers have been in high demand for disease diagnosis and therapeutics. Traditional hypothesis-based research has been challenging due to massive screening studies. Together with the emergence of omics technologies, currently, the paradigm for disease research has been moving toward evidence-based large-scale discovery studies. Proteins, as key effector molecules, can serve as ideal biomarkers for various diseases because they catalyze every biological function. Proteomics, which is represented by mass spectrometry (MS) technologies, stands as a solution for disease diagnosis and drug target discovery. CHAPTER I includes a portion of a report from of the human proteome project (HPP) related to chromosome 9 (Chr 9). To identify missing proteins (MPs) and their potential features in regard to proteogenomic view, both LC-MS/MS analysis and next-generation RNA sequencing (RNA-seq)-based tools were used for the clinical samples including adjacent non-tumor tissues. When the Chr 9 working group of the Chromosome-Centric Human Proteome Project (C-HPP) began this project, there were 170 remaining MPs encoded by Chr 9 (neXtProt 2013.09.26 rel.)currently, 133 MPs remain unidentified at present (neXtProt 2015.04.28 rel.). Proteome analysis in this study identified 19 missing proteins across all chromosomes and one MP (SPATA31A4) from Chr 9. RNA-seq analysis enable detection of RNA expression of 4 nonsynonymous (NS) SNPs (in CDH17, HIST1H1T, SAPCD2, and ZNF695) and 3 synonymous SNPs (in CDH17, CST1, and HNF1A) in all 5 tumor tissues but not in any of the adjacent normal tissues. By constructing a cancer patient sample-specific protein database based on individual RNA-seq data, and by searching the proteomics data from the same sample, 7 missense mutations in 5 genes (LTF, HDLBP, TF, HBD, and HLA-DRB5) were identified. Two of these mutations were found in tumor tissues but not in the paired normal tissues. Additionally, this study discovered peptides that were derived from the expression of a pseudogene (EEF1A1P5) in both tumor and normal tissues. In summary, this proteogenomic study of human primary lung tumor tissues enabled detection of additional missing proteins and revealed novel missense mutations and synonymous SNP signatures, some of which are predicted to be specific to lung cancer. CHAPTER II describes a study of the combination marker model using multiple reaction monitoring (MRM) quantitative data. Misdiagnosis of lung cancer remains a serious problem due to the difficulty of distinguishing lung cancer from other respiratory lung diseases. As a result, the development of serum-based differential diagnostic biomarkers is in high demand. In this study, 198 serum samples from non-cancer lung disease and lung cancer patients were analyzed using nLC-QqQ-MS to examine the diagnostic efficacy of seven lung cancer biomarker candidates. When the candidates were assessed individually, only SERPINEA4 showed statistically significant changes in the sera of cancer patient compared to those of control samples. The MRM results and clinical information were analyzed using logistic regression analysis to a select model for the best meta-marker, or combination of biomarkers for the differential diagnosis. Additionally, under consideration of statistical interaction, variables having a low significance as a single factor but statistically influencing the meta-marker model were selected. Using this probabilistic classification, the best meta-marker was determined to comprise two proteins SERPINA4 and PON1, with an age factor. This meta-marker showed an enhanced differential diagnostic capability (AUC=0.915) to distinguish the lung cancer from lung disease patient groups. These results suggest that a statistical model can determine optimal meta-markers, which may have better specificity and sensitivity than a single biomarker and may thus improve the differential diagnosis of lung cancer and lung disease patients.ABSTRACT_i CONTENTS_v LIST OF FIGURES_vii LIST OF TABLES_x ABBREVIATIONS_xii BACKGROUND_1 1. LUNG CANCER_1 2. BIOMARKER_7 3. MASS SPECTROMETRY BASED PROTEOMICS_12 4. PROTEOGENOMICS_24 5. TARGETED PROTEOMICS_33 CHAPTER I Proteogenomic Study: Variant Proteome and Transcriptome in Human Lung Adenocarcinoma Tissues_41 1. INTRODUCTION_42 2. MATERIALS AND METHODS_45 3. RESULTS AND DISCUSSION_53 4. CONCLUSION_81 CHAPTER II Multi-Panel Biomarker Development for the Efficient Discrimination of Lung Cancer for Other Lung Diseases_84 1. INTRODUCTION_85 2. MATERIALS AND METHODS_88 3. RESULTS_93 4. DISCUSSION_120 5. CONCLUSION_127 GENERAL CONCLUSION_129 REFERENCES_131 ABSTRACT IN KOREAN_154Docto

Viral Modulation of Host Translation and Implications for Vaccine Development

Translation of mRNAs into protein is an essential mechanism of regulating gene expression—and a step exploited by viruses for their own propagation. In this article, we review mechanisms that govern translation and provide an overview of the translation machinery, discuss some of the components involved in this process, and discuss how viruses modulate host translational controls and implications in vaccine design

Human germline and pan-cancer variomes and their distinct functional profiles

Identification of non-synonymous single nucleotide variations (nsSNVs) has exponentially increased due to advances in Next-Generation Sequencing technologies. The functional impacts of these variations have been difficult to ascertain because the corresponding knowledge about sequence functional sites is quite fragmented. It is clear that mapping of variations to sequence functional features can help us better understand the pathophysiological role of variations. In this study, we investigated the effect of nsSNVs on more than 17 common types of post-translational modification (PTM) sites, active sites and binding sites. Out of 1 705 285 distinct nsSNVs on 259 216 functional sites we identified 38 549 variations that significantly affect 10 major functional sites. Furthermore, we found distinct patterns of site disruptions due to germline and somatic nsSNVs. Pan-cancer analysis across 12 different cancer types led to the identification of 51 genes with 106 nsSNV affected functional sites found in 3 or more cancer types. 13 of the 51 genes overlap with previously identified Significantly Mutated Genes (Nature. 2013 Oct 17;502(7471)). 62 mutations in these 13 genes affecting functional sites such as DNA, ATP binding and various PTM sites occur across several cancers and can be prioritized for additional validation and investigations

UGT pharmacogenomics in drug metabolism and diseases

Glucuronidation, mediated by UDP-glucuronosyltransferase enzymes (UGTs), is a major phase II biotransformation pathway and, complementary to phase I metabolism and membrane transport, one of the most important cellular defense mechanism responsible for the inactivation of therapeutic drugs, other xenobiotics and numerous endogenous molecules. Individual variability in UGT enzymatic pathways is significant and may have profound pharmacological and toxicological implications. Several genetic and genomic processes are underlying this variability and are discussed in the context of drug metabolism and diseases such as cancer

Identification and functional characterization of genetic variants in the human indoleamine 2, 3-dioxygenase (INDO) gene

Indiana University-Purdue University Indianapolis (IUPUI)Indoleamine 2,3-dioxygenase (IDO) is a rate limiting enzyme in tryptophan catabolism that has been implicated in the pathogenesis of a number of diseases. Large interindividual variability in IDO activity in the absence of stimuli and as the result of therapy induced changes has been reported. This variability has the potential to contribute to susceptibility to disease and to interindividual variability in therapeutic response. To identify genetic variations that might contribute to interindividual variability in IDO activity, we resequenced the exons, intron/exon borders and 1.3 kb of the 5’-flanking region of the INDO gene in 48 African-American (AA) and 48 Caucasian-American (CA) subjects from the Coriell DNA Repository. A total of 24 INDO variants were identified. Seventeen of these were in exons, introns, or exon/intron boundries, while seven were within 1.3 kb upstream of the translation start site. Seventeen are novel and 7 were previously identified. When transiently expressed in COS-7 or HEK293 cells the amino acid sequence change in Arg77His resulted in significant decrease in activity, and it reduced the Vmax of IDO. The Arg77His variant and the 9 bp deletion resulted in nearly complete loss of enzyme activity and a lack of detectable protein expression. The function of the Arg77His variant IDO was restored in a dose dependent manner by the heme analog hemin; but there was no associated increase in IDO protein. Cellular heme concentration was higher in cells transfected with the wild type and Ala4Thr variant constructs, but not in cells transfected with the Arg77His variant. The heme synthesis inhibitor, succinylacetone (SA), blocked IDO activity in cells transfected with Arg77His. We identified 22 putative transcription binding sites within the 1.3 kb upstream of the translation start site. Two of the SNPs were located in GATA3 and FOXC1 sites. A specific 3-SNP haplotype reduced promoter activity when transiently transfected into 2 different cell lines. We conclude that there are naturally occurring genetic variants in the INDO gene which affect both expression and activity. These results make clear that interindividual variability in IDO activity at baseline or in response to therapy may be in part due to inherited genetic variability

Graves' disease: introducing new genetic and epigenetic contributors

Autoimmune thyroid disease (AITD) accounts for 90% of all thyroid diseases and affects 2-5% of the population with remarkable familial clustering. Among AITDs, Graves' disease (GD) is a complex disease affecting thyroid function. Over the l ast two decades, casecontrol studies using cutting-edge gene sequencing techniques have detected various susceptible loci that may predispose individuals to GD. It has been presumed that all likely associated genes, variants, and polymorphisms might be responsible for 75-80% of the heritability of GD. As a result, there are implications concerning the potential contribution of environmental and epigenetic factors in the pathogenesis of GD, including its initiation, progression, and development. Numerous review studies have summarized the contribution of genetic factors in GD until now, but there are still some key questions and notions that have not been discussed concerning the interplay of genetic, epigenetic, and immunological factors. With this in mind, this review discusses some newly-identified loci and their potential roles in the pathogenicity of GD. This may lead to the identification of new, promising therapeutic targets. Here, we emphasized principles, listed all the reported disease-associated genes and polymorphisms, and also summarized the current understanding of the epigenetic basis of GD