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SYM-6 : Young Scientists



Hee-Sung Ahn
Code / Date
SYM6-1 / March 29 (Fri)
Speaker
Hee-Sung Ahn   CV
Affiliation
Asan Medical Center
Title
Proteomics approach to discover the unrinary protein biomarkers to predict kidney function decline in type 2 diabetes
Abstract

The function of the kidney is to filter wastes from the blood and discharge it with urine which is the best specimen to detect kidney abnormalities. Proteins will be released into the urine due to the weakening of kidney function, especially albumin that is present in many parts of the blood is the current marker of diabetic nephropathy. However, albumin alone may make it harder for monitoring the progression of the patients with diabetic kidney disease (DKD) and type 2 diabetes. There may be other protein-monitoring markers that diagnose that diabetic nephropathy will worsen. In this study, we presented an analysis of the urinary proteome with liquid chromatography–tandem mass spectrometry (LC/MS/MS). The urine samples from patients who did not reach the chronic kidney disease (CKD) progression (Non-progression group, 45 cases) and the urine samples from patients who showed the accelerated eGFR decline and the development of CKD stage 3 or greater (Progression group, 19 cases) were investigated using label free quantitative proteomics approach. A total of 1381 proteins were identified in all samples. After identification and quantification of unirary proteins, variables were selected using random forest and the area under curve (AUCRF), which showed the difference between the two groups. As a result, five proteins were determined and AUC from the model showed to be 1.0 in random forest and 0.88 in support vector machine model. This study can be inferred that multi-protein panel showed improved values other than albuminuria (AUC=0.646) for predicting the progression of DKD in patients with type 2 diabetes.

 

Sohyun Kim
Code / Date
SYM6-2 / March 29 (Fri)
Speaker
Sohyun Kim   CV
Affiliation
Seoul National University
Title
Raft-localized CD147 with proximal proteins confers drug-resistance phenotype in cancer stemness
Abstract

Cancer stem cells are a specific sub-population of tumor cells that are exhibiting self-renewal ability, tumorigenesis, chemotherapy resistance and metastasis. As their unique stemness properties are enabling them to escape conventional anti-cancer therapies, CSCs have become a prime interest for the development of novel therapeutic strategies for cancer treatment. In the previous study, we have investigated the importance of CD147 which is involved in promoting anti-cancer drug resistance. Despite the critical role of CD147 in anti-cancer drug resistance, the mechanism in the regulatory functions in cancer cell stemness still remains to be elucidated. In an attempt to better understand the functions of CD147 in the context of cancer stemness in CSCs, we investigated the constituency of neighboring proteins of CD147 and compared their abundance with non-cancer stem cells to estimate their co-localization with CD147 by implementing a close-proximity labeling method. Also, we hypothesized that lateral interactions between cd147 and other oncogenic proteins residing within microdomain. We focused on the five candidates including CD133, CD44, Epithermal growth factor receptor (EGFR) and a novel protein among the proximal proteins of CD147 and we characterized the specific localization mechanism of microdomains. When the integrity of microdomains was disrupted in CSCs by specific chemical treatment, we found the assembly of candidates was dispersed. Therefore, based on the co-localization mechanism, we investigated the reactivity of drug-resistance according to the downstream signaling studies that can lead an aggressive phenotype of CSCs.

 

Shinyeong Ju
Code / Date
SYM6-3 / March 29 (Fri)
Speaker
Shinyeong Ju   CV
Affiliation
Korea Institute of Science and Technology
Title
iNrich, a rapid and robust method to enrich N-terminal proteome in a highly multiplexable platform
Abstract

The recent discovery of fMet/N-end rule in Saccharomyces cerevisiae suggests digging deeper into N-terminome is a new opportunity of the discovery of the degradation system in eukaryotes. However, the terminal proteomics is limited in that it is optimized for large scale analysis consisting of multistep processes including profound liquid chromatography system. Here, we present an integrated N-terminal peptide enrichment method (iNrich) that can handle as little as 25 µg cell lysate via a single-stage encapsulated solid phase extraction column. iNrich enables simple, rapid (nine hours) and reproducible sample processing, treatment of wide range of protein amount (25 µg ~ 1 mg), multiplexed parallel sample preparation, and in-stage sample prefractionation through the use of a mixed anion exchanger filter. We show, as an example, the results of ~11,000 N-terminal sites identified from only 100 µg human cell lysate including novel Nt-formyl proteins. Multiplexed sample preparation enabled quantitatively robust enrichment of N-terminome on a maximum of 20 reactions. We further developed the method to use isobaric tags, in this case, the tandem mass tags (TMT). As a result, the peptides with non-canonical translation initiation site (TIS) which could be in the process of degradation are highly increased in ER stress-induced cell while the peptides with canonical TIS showed cellular response against stress-inducer, that is UPR (unfolded protein response) analyzed by reactome analysis. iNrich facilitates high-throughput N-terminomics and degradomics studies, especially understanding low-concentration molecules such as Nt-formyl proteins which could lose during bulky methods that are currently available.

 

Hyoung-Min Park
Code / Date
SYM6-4 / March 29 (Fri)
Speaker
Hyoung-Min Park   CV
Affiliation
Seoul National University
Title
Novel protein markers for both human and canine breast tumors in plasma
Abstract

Plasma protein has been a viable source of finding and implementing cancer markers. Potential marker candidates can be easily tested and detected with plasma samples. However, identifying protein markers within plasma samples is a difficult task due to abundant proteins such as albumin and various immunoglobulins. In this study various cancer upregulated proteins were identified including 2 common protein markers using both canine and human plasma samples. An intensive 36 fraction method was used to find plasma protein after removing 2 highly abundant proteins albumin and IgG. Using bioinformatics to identify solid cancer protein marker candidates, validation was processed through MRM. Furthermore, heavy labeled peptides and western blots were implemented to precisely measure protein amounts within each plasma sample. As a result, both canine and human common cancer protein markers were highly enriched within cancer plasma.

 

Kwang Hoe Kim
Code / Date
SYM6-5 / March 29 (Fri)
Speaker
Kwang Hoe Kim   CV
Affiliation
Korea Basic Science Institute
Title
N-Glycoprotein Biomarkers for Detection of Hepatocellular Carcinoma by Parallel Reaction Monitoring
Abstract

The N-glycosylation of proteins is one of the most important post-translational modifications (PTMs) relevant to various biological functions. Therefore, the differences of N-glycoprotein level in human serum or plasma can be used for detecting of cancers. Hepatocellular carcinoma (HCC) is the leading cause of cancer-related deaths worldwide. Usually, most HCC patients do not have any noticeable symptoms in the early stages of primary liver cancer. Thus, effective detection method using biomarkers is needed to improve detection ability of HCC. In this study, we selected N-glycoproteins [α-fetoprotein (AFP), vitronectin (VTN), and α-1-antichymotrypsin (AACT)] that are abnormally fucosylated in HCC and has been known to be HCC biomarker candidates. These N-glycoproteins were used to investigate the feasibility of analyzing N-glycoproteins using multiplexed immunoprecipitation to detect HCC. To that end, their tryptic N-glycopeptides were selected to determine the percentages of fucosylated N-glycopeptides using Y ions, which include glycopeptide fragments with amino acid sequences. These N-glycopeptides were analyzed by the liquid chromatography-mass spectrometry (LC-MS)-based parallel reaction monitoring (PRM). Finally, we confirmed that the area under the receiver operating characteristic curve (AUC = 0.944) for the combination of AFP and VTN increased more so than for a single glycopeptide with respect to discriminating between HCC and cirrhosis. This study shows that an LC-PRM method using multiplexed immunoprecipitation of N-glycoproteins from serum could be applied to develop and verify cancer biomarkers.

 

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