Sugar Alcohols Have a Key Role in Pathogenesis of Chronic Liver Disease and Hepatocellular Carcinoma in Whole Blood and Liver Tissues.

The major risk factors for hepatocellular carcinoma (HCC) are hepatitis C and B viral infections that proceed to Chronic Liver Disease (CLD). Yet, the early diagnosis and treatment of HCC are challenging because the pathogenesis of HCC is not fully defined. To better understand the onset and development of HCC, untargeted GC-TOF MS metabolomics data were acquired from resected human HCC tissues and their paired non-tumor hepatic tissues (n = 46). Blood samples of the same HCC subjects (n = 23) were compared to CLD (n = 15) and healthy control (n = 15) blood samples. The participants were recruited from the National Liver Institute in Egypt. The GC-TOF MS data yielded 194 structurally annotated compounds. The most strikingly significant alteration was found for the class of sugar alcohols that were up-regulated in blood of HCC patients compared to CLD subjects (p < 2.4 × 10-12) and CLD compared to healthy controls (p = 4.1 × 10-7). In HCC tissues, sugar alcohols were the most significant (p < 1 × 10-6) class differentiating resected HCC tissues from non-malignant hepatic tissues for all HCC patients. Alteration of sugar alcohol levels in liver tissues also defined early-stage HCC from their paired non-malignant hepatic tissues (p = 2.7 × 10-6). In blood, sugar alcohols differentiated HCC from CLD subjects with an ROC-curve of 0.875 compared to 0.685 for the classic HCC biomarker alpha-fetoprotein. Blood sugar alcohol levels steadily increased from healthy controls to CLD to early stages of HCC and finally, to late-stage HCC patients. The increase in sugar alcohol levels indicates a role of aldo-keto reductases in the pathogenesis of HCC, possibly opening novel diagnostic and therapeutic options after in-depth validation

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

Proteome Profiling of Breast Tumors by Gel Electrophoresis and Nanoscale Electrospray Ionization Mass Spectrometry

We have conducted proteome-wide analysis of fresh surgery specimens derived from breast cancer patients, using an approach that integrates size-based intact protein fractionation, nanoscale liquid separation of peptides, electrospray ion trap mass spectrometry, and bioinformatics. Through this approach, we have acquired a large amount of peptide fragmentation spectra from size-resolved fractions of the proteomes of several breast tumors, tissue peripheral to the tumor, and samples from patients undergoing noncancer surgery. Label-free quantitation was used to generate protein abundance maps for each proteome and perform comparative analyses. The mass spectrometry data revealed distinct qualitative and quantitative patterns distinguishing the tumors from healthy tissue as well as differences between metastatic and non-metastatic human breast cancers including many established and potential novel candidate protein biomarkers. Selected proteins were evaluated by Western blotting using tumors grouped according to histological grade, size, and receptor expression but differing in nodal status. Immunohistochemical analysis of a wide panel of breast tumors was conducted to assess expression in different types of breast cancers and the cellular distribution of the candidate proteins. These experiments provided further insights and an independent validation of the data obtained by mass spectrometry and revealed the potential of this approach for establishing multimodal markers for early metastasis, therapy outcomes, prognosis, and diagnosis in the future. © 2008 American Chemical Society

SITC cancer immunotherapy resource document: a compass in the land of biomarker discovery.

Since the publication of the Society for Immunotherapy of Cancer\u27s (SITC) original cancer immunotherapy biomarkers resource document, there have been remarkable breakthroughs in cancer immunotherapy, in particular the development and approval of immune checkpoint inhibitors, engineered cellular therapies, and tumor vaccines to unleash antitumor immune activity. The most notable feature of these breakthroughs is the achievement of durable clinical responses in some patients, enabling long-term survival. These durable responses have been noted in tumor types that were not previously considered immunotherapy-sensitive, suggesting that all patients with cancer may have the potential to benefit from immunotherapy. However, a persistent challenge in the field is the fact that only a minority of patients respond to immunotherapy, especially those therapies that rely on endogenous immune activation such as checkpoint inhibitors and vaccination due to the complex and heterogeneous immune escape mechanisms which can develop in each patient. Therefore, the development of robust biomarkers for each immunotherapy strategy, enabling rational patient selection and the design of precise combination therapies, is key for the continued success and improvement of immunotherapy. In this document, we summarize and update established biomarkers, guidelines, and regulatory considerations for clinical immune biomarker development, discuss well-known and novel technologies for biomarker discovery and validation, and provide tools and resources that can be used by the biomarker research community to facilitate the continued development of immuno-oncology and aid in the goal of durable responses in all patients

Non-coding RNAs in saliva: emerging biomarkers for molecular diagnostics.

Saliva is a complex body fluid that comprises secretions from the major and minor salivary glands, which are extensively supplied by blood. Therefore, molecules such as proteins, DNA, RNA, etc., present in plasma could be also present in saliva. Many studies have reported that saliva body fluid can be useful for discriminating several oral diseases, but also systemic diseases including cancer. Most of these studies revealed messenger RNA (mRNA) and proteomic biomarker signatures rather than specific non-coding RNA (ncRNA) profiles. NcRNAs are emerging as new regulators of diverse biological functions, playing an important role in oncogenesis and tumor progression. Indeed, the small size of these molecules makes them very stable in different body fluids and not as susceptible as mRNAs to degradation by ribonucleases (RNases). Therefore, the development of a non-invasive salivary test, based on ncRNAs profiles, could have a significant applicability to clinical practice, not only by reducing the cost of the health system, but also by benefitting the patient. Here, we summarize the current status and clinical implications of the ncRNAs present in human saliva as a source of biological information

Targeting LIF-mediated paracrine interaction for pancreatic cancer therapy and monitoring.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis largely owing to inefficient diagnosis and tenacious drug resistance. Activation of pancreatic stellate cells (PSCs) and consequent development of dense stroma are prominent features accounting for this aggressive biology1,2. The reciprocal interplay between PSCs and pancreatic cancer cells (PCCs) not only enhances tumour progression and metastasis but also sustains their own activation, facilitating a vicious cycle to exacerbate tumorigenesis and drug resistance3-7. Furthermore, PSC activation occurs very early during PDAC tumorigenesis8-10, and activated PSCs comprise a substantial fraction of the tumour mass, providing a rich source of readily detectable factors. Therefore, we hypothesized that the communication between PSCs and PCCs could be an exploitable target to develop effective strategies for PDAC therapy and diagnosis. Here, starting with a systematic proteomic investigation of secreted disease mediators and underlying molecular mechanisms, we reveal that leukaemia inhibitory factor (LIF) is a key paracrine factor from activated PSCs acting on cancer cells. Both pharmacologic LIF blockade and genetic Lifr deletion markedly slow tumour progression and augment the efficacy of chemotherapy to prolong survival of PDAC mouse models, mainly by modulating cancer cell differentiation and epithelial-mesenchymal transition status. Moreover, in both mouse models and human PDAC, aberrant production of LIF in the pancreas is restricted to pathological conditions and correlates with PDAC pathogenesis, and changes in the levels of circulating LIF correlate well with tumour response to therapy. Collectively, these findings reveal a function of LIF in PDAC tumorigenesis, and suggest its translational potential as an attractive therapeutic target and circulating marker. Our studies underscore how a better understanding of cell-cell communication within the tumour microenvironment can suggest novel strategies for cancer therapy

MALDI Mass Spectrometry Imaging for the Discovery of Prostate Carcinoma Biomarkers

The elucidation of new biological markers of prostate cancer (PCa) should aid in the detection, and prognosis of this disease. Diagnostic decision making by pathologists in prostate cancer is highly dependent on tissue morphology. The ability to localize disease-specific molecular changes in tissue would help improve this critical pathology decision making process. Direct profiling of proteins in tissue sections using MALDI imaging mass spectrometry (MALDI-IMS) has the power to link molecular detail to morphological and pathological changes, enhancing the ability to identify candidates for new specific biomarkers. However, critical questions remain regarding the integration of this technique with clinical decision making. To address these questions, and to investigate the potential of MALDI-IMS for the diagnosis of prostate cancer, we have used this approach to analyze prostate tissue for the determination of the cellular origins of different protein signals to improve cancer detection and to identify specific protein markers of PCa. We found that specific protein/peptide expression changes correlated with the presence or absence of prostate cancer as well as the presence of micro-metastatic disease. Additionally, the over-expression of a single peptide (m/z = 4355) was able to accurately define primary cancer tissue from adjacent normal tissue. Tandem mass spectrometry analysis identified this peptide as a fragment of MEKK2, a member of the MAP kinase signaling pathway. Validation of MEKK2 overexpression in moderately differentiated PCa and prostate cancer cell lines was performed using immunohistochemistry and Western Blot analysis. Classification algorithms using specific ions differentially expressed in PCa tissue and a ROC cut-off value for the normalized intensity of the MEKK2 fragment at m/z 4355 were used to classify a blinded validation set. Finally, the optimization of sample processing in a new fixative which preserves macromolecules has led to improved through-put of samples making MALDI-IMS more compatible with current histological applications, facilitating its implementation in a clinical setting. This study highlights the potential of MALDI-IMS to define the molecular events involved in prostate tumorigenesis and demonstrates the applicability of this approach to clinical diagnostics as an aid to pathological decision making in prostate cancer

Early detection of colorectal cancer: biomarker discovery

Colorectal cancer (CRC) is the third most common cancer worldwide, with about 1.2 million new cases diagnosed each year. CRC derived from the gradual accumulation of both genetic and epigenetic changes that transform the normal intestinal glandular epithelium into invasive cancer. While the genetic alterations are already used as prognostic and predictive markers, epigenetic alterations are currently the subject of intense research in the biomedical field because are considered as common and early molecular events in carcinogenesis that potentially could be used as molecular markers. The aims of this study were: to identify the alterations that characterize the CRC methylome; verify that these changes represent early events in the development of CRCs; explore the use of ultra-sensitive molecular techniques to track these alterations in biological matrices suitable for a non-invasive assessment (blood and stool); correlate the methylation alterations with the associated genes expression. The methylome analysis, conducted by Infinium HumanMethylation450 BeadChip on CRC and adenoma samples, has allowed us to delineate both the CRC methylation profile and that associated with precancerous stages. The gene-set/pathway enrichment analysis conducted by Toppgene and based on case/control differential methylation analysis results of CRCs and adenomas, allowed the identification of pathways involved in CRC carcinogenesis. The contribution of these pathways had never been widely emphasized and discussed in the literature. A very important result, emerged from the comparison of the genes belonging to the most altered significant pathways both in CRCs and adenomas, has been the identification of methylation alterations of regions, known as CpG islands, since the earliest stages of precancerous lesion suggesting that the alteration of specific pathways can lead the tumorigenic process. The selection of these regions has allowed us to identify a panel of biomarkers that can discriminate, with high specificity and sensitivity, CRCs and adenomas from peritumoral / normal counterpart. This panel has been extensively validated in silico in over 600 samples. We also evaluated the gene expression associated with these regions; more than 70% of hypermethylated CpG islands correlated with a downregulation in tumor tissue. To evaluate the usefulness of these biomarkers as a potential tool for non-invasive early diagnosis of CRC in clinical practice, we tried to trace through the use of ultra-sensitive techniques (methyl_BEAMING), the hypermethylation of three selected biomarkers in DNA extract from blood and stool. The hypermethylation of these regions, due to the presence of tumoral DNA, has been traced with great sensitivity and specificity in both matrices confirming the usefulness of these regions as possible biomarkers for the early diagnosis and traceability of residual disease of CRC

Identification of Novel High-Frequency DNA Methylation Changes in Breast Cancer

Recent data have revealed that epigenetic alterations, including DNA methylation and chromatin structure changes, are among the earliest molecular abnormalities to occur during tumorigenesis. The inherent thermodynamic stability of cytosine methylation and the apparent high specificity of the alterations for disease may accelerate the development of powerful molecular diagnostics for cancer. We report a genome-wide analysis of DNA methylation alterations in breast cancer. The approach efficiently identified a large collection of novel differentially DNA methylated loci (∼200), a subset of which was independently validated across a panel of over 230 clinical samples. The differential cytosine methylation events were independent of patient age, tumor stage, estrogen receptor status or family history of breast cancer. The power of the global approach for discovery is underscored by the identification of a single differentially methylated locus, associated with the GHSR gene, capable of distinguishing infiltrating ductal breast carcinoma from normal and benign breast tissues with a sensitivity and specificity of 90% and 96%, respectively. Notably, the frequency of these molecular abnormalities in breast tumors substantially exceeds the frequency of any other single genetic or epigenetic change reported to date. The discovery of over 50 novel DNA methylation-based biomarkers of breast cancer may provide new routes for development of DNA methylation-based diagnostics and prognostics, as well as reveal epigenetically regulated mechanism involved in breast tumorigenesis