• Clinical Endoscopy
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• 제56권4호
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• pp.510-520
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• 2023

Background/Aims: We aimed to investigate (1) promising clinical findings for the recognition of focal type autoimmune pancreatitis (FAIP) and (2) the impact of endoscopic ultrasound (EUS)-guided tissue acquisition (EUS-TA) on the diagnosis of FAIP. Methods: Twenty-three patients with FAIP were involved in this study, and 44 patients with resected pancreatic ductal adenocarcinoma (PDAC) were included in the control group. Results: (1) Multivariate analysis revealed that homogeneous delayed enhancement on contrast-enhanced computed tomography was a significant factor indicative of FAIP compared to PDAC (90% vs. 7%, p=0.015). (2) For 13 of 17 FAIP patients (76.5%) who underwent EUS-TA, EUS-TA aided the diagnostic confirmation of AIPs, and only one patient (5.9%) was found to have AIP after surgery. On the other hand, of the six patients who did not undergo EUS-TA, three (50.0%) underwent surgery for pancreatic lesions. Conclusions: Homogeneous delayed enhancement on contrast-enhanced computed tomography was the most useful clinical factor for discriminating FAIPs from PDACs. EUS-TA is mandatory for diagnostic confirmation of FAIP lesions and can contribute to a reduction in the rate of unnecessary surgery for patients with FAIP.

• Mass Spectrometry Letters
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• 제15권2호
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• pp.69 -78
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• 2024

The advancement of high-throughput omics technologies and systems biology is essential for understanding complex biological mechanisms and diseases. The integration of proteomics and metabolomics provides comprehensive insights into cellular functions and disease pathology, driven by developments in mass spectrometry (MS) technologies, including electrospray ionization (ESI). These advancements are crucial for interpreting biological systems effectively. However, integrating these technologies poses challenges. Compared to genomic, proteomics and metabolomics have limitations in throughput, and data integration. This review examines developments in MS equipped electrospray ionization (ESI), and their importance in the effective interpretation of biological mechanisms. The review also discusses developments in sample preparation, such as Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX), analytical techniques, and data analysis, highlighting the application of these technologies in the study of cancer or Huntington's disease, underscoring the potential for personalized medicine and diagnostic accuracy. Efforts by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and integrative data analysis methods such as O2PLS and OnPLS extract statistical similarities between metabolomic and proteomic data. System modeling techniques that mathematically explain and predict system responses are also covered. This practical application also shows significant improvements in cancer research, diagnostic accuracy and therapeutic targeting for diseases like pancreatic ductal adenocarcinoma, non-small cell lung cancer, and Huntington's disease. These approaches enable researchers to develop standardized protocols, and interoperable software and databases, expanding multi-omics research application in clinical practice.

• Genomics & Informatics
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• 제20권2호
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• pp.23.1-23.9
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• 2022

A survival prediction model has recently been developed to evaluate the prognosis of resected nonmetastatic pancreatic ductal adenocarcinoma based on a Cox model using two nationwide databases: Surveillance, Epidemiology and End Results (SEER) and Korea Tumor Registry System-Biliary Pancreas (KOTUS-BP). In this study, we applied two machine learning methods-random survival forests (RSF) and support vector machines (SVM)-for survival analysis and compared their prediction performance using the SEER and KOTUS-BP datasets. Three schemes were used for model development and evaluation. First, we utilized data from SEER for model development and used data from KOTUS-BP for external evaluation. Second, these two datasets were swapped by taking data from KOTUS-BP for model development and data from SEER for external evaluation. Finally, we mixed these two datasets half and half and utilized the mixed datasets for model development and validation. We used 9,624 patients from SEER and 3,281 patients from KOTUS-BP to construct a prediction model with seven covariates: age, sex, histologic differentiation, adjuvant treatment, resection margin status, and the American Joint Committee on Cancer 8th edition T-stage and N-stage. Comparing the three schemes, the performance of the Cox model, RSF, and SVM was better when using the mixed datasets than when using the unmixed datasets. When using the mixed datasets, the C-index, 1-year, 2-year, and 3-year time-dependent areas under the curve for the Cox model were 0.644, 0.698, 0.680, and 0.687, respectively. The Cox model performed slightly better than RSF and SVM.

• Investigative Magnetic Resonance Imaging
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• 제20권3호
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• pp.185-190
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• 2016

Xanthogranulomatous inflammation is a rare benign condition involving various organs. However, its pancreas involvement is very rare. To the best of our knowledge, only 17 cases have been described in the literature. Interestingly, all reported 17 cases due to various causes underwent surgical resection. Here, we present a case of xanthogranulomatous pancreatitis in a 63-year-old man. He presented with epigastric pain and solid mass mimicking ductal adenocarcinoma in the body and tail of pancreas on magnetic resonance imaging. The patient was diagnosed as xanthogranulomatous pancreatitis via endoscopic ultrasound-guided fine needle aspiration. After that, he was followed up and monitored without any surgical treatment. Here, we show imaging findings and serial image changes of xanthogranulomatous pancreatitis for this case.

• Journal of Microbiology and Biotechnology
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• 제32권3호
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• pp.365-377
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• 2022

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.

• 생명과학회지
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• 제26권9호
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• pp.1056-1062
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• 2016

폐암은 전세계적으로 높은 발병율과 사망률을 보이는 암종으로 소세포암종과 비소세포암종으로 구분되어지며, 비소세포암이 75-80%를 차지하고 있다. miR-155의 유전자의 과 발현은 갑상선암, 유방암, 대장암, 자궁 경부암, 췌장선암(PDAC), 폐암 등의 고형암에서 관찰된다. 본 연구에서는 한국인 폐암 환자의 조직에서 특이적으로 발현되는 miRNA의 양상을 양성 폐질환자 와 비교 분석하고, 폐암환자의 임상병리학적 특성과의 상관성을 분석하여 miRNA가 암 진단의 생물표지자로서의 가능성을 조사하여 향후 암의 조기 진단 및 치료, 예후 연구에 기초 자료를 제공하고자 하였다. 파라핀 포매 된 비소세포폐암환자 및 양성 폐 질환자의 블록에서 total RN를의 분리하여, 정량 실시간연쇄중합반응을 통해 miR-155의 발현량을 정량 분석을 실시하였으며, miR-155의 발현과 폐암환자의 임상적 특징과의 상관관계를 분석하였다. 폐암 환자군과 양성 폐질환자의 miR-155의 △Ct 값을 분석한 결과 폐암환자군에서 유의하게 높게 발현되었다(p<0.001). 병리조직학적 분류에 따라서는 편평상피세포암종에서 선암종에 비해 높게 발현되었다. 분화도에 따라서는 저분화 암에서 고분화암에 비해 유의하게 높게 발현되었다(p=<0.001). 또한 miR-155의 과발현은 림프절 전이와도 통계적으로 유의성 나타내었다(p<0.05). 생존분석결과 miR-155의 과발현은 폐암환자의 생존률과 유의한 상관관계를 나타내었다(p<0.05). 본 연구의 결과로 miR-155의 발현은 폐암의 진행 및 전이에 중요한 역할을 할 것으로 생각되며, 폐암의 조기진단과 예후의 예측을 위하여 보다 다양한 종류의 miRNAs에 대한 연구가 이루어져야 할 것으로 판단된다.