• Nutritional Sciences
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• v.8 no.1
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• pp.23-27
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• 2005

The major garlic component, Allicin [diallylthiosulfinate, or (R, S)-diallyldissulfid-S-oxide] is known for its medicinal effects, such as antihypertensive activity, microbicidal activity, and antitumor activity. Allicin and diallyldisulfide, which is a converted form of allicin, inhibited the cholesterol level in hepatocytes, in vivo and in vitro. The metabolism of allicin reportedly occurs in the microsomes of hepatocytes, predominantly with the contribution of cytochrome P-450. However, little is known about how allicin affects the genes involved in the activity of hepatocytes in vivo. In the present study, we used the short-term intravenous injection of allicin to examine the in vivo genetic profile of hepatocytes. Allicin up-regulate ten genes in the hepatocytes. For example, the interferon regulator 1 (IRF-I), the wingless-related MMTV (mouse mammary tumor virus) integration site 4 (wnt-4), and the fatty acid binding protein 1. However, allicin down-regulated three genes: namely, glutathione S-transferase mu6, a-2-HS glycoprotein, and the corticosteroid binding globulin of hepatocytes. The up-regulated wnt-4, IRF-1, and mannose binding lectin genes can enhance the growth factors, cytokines, transcription activators and repressors that are involved in the immune defense mechanism. These primary data, which were generated with the aid of the Atlas Plastic Mouse 5 K Microarray, help to explain the mechanism which enables allicin to act as a therapeutic agent, to enhance immunity, and to prevent cancer. The data suggest that these benefits of allicin are partly caused by the up-regulated or down-regulated gene profiles of hepatocytes. To evaluate the genetic profile in more detail, we need to use a more extensive mouse genome array.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.75-84
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• 2014

In this paper, we dealt with feature selection problem of large-scale and high-dimensional biological data such as omics data. For this problem, most of the previous approaches used simple score function to reduce the number of original variables and selected features from the small number of remained variables. In the case of methods that do not rely on filtering techniques, they do not consider the interactions between the variables, or generate approximate solutions to the simplified problem. Unlike them, by combining set covering and clustering techniques, we developed a new method that could deal with total number of variables and consider the combinatorial effects of variables for selecting good features. To demonstrate the efficacy and effectiveness of the method, we downloaded gene expression datasets from TCGA (The Cancer Genome Atlas) and compared our method with other algorithms including WEKA embeded feature selection algorithms. In the experimental results, we showed that our method could select high quality features for constructing more accurate classifiers than other feature selection algorithms.

• Molecules and Cells
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• v.41 no.5
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• pp.390-400
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• 2018

Studies have revealed that miR-103a-3p contributes to tumor growth in several human cancers, and high miR-103a-3p expression is associated with poor prognosis in advanced gastric cancer (GC) patients. Moreover, bioinformatics analysis has shown that miR-103a-3p is upregulated in The Cancer Genome Atlas (TCGA) stomach cancer cohort. These results suggest that miR-103a-3p may function as an oncogene in GC. The present study aimed to investigate the role of miR-103a-3p in human GC. miR-103a-3p expression levels were increased in 33 clinical GC specimens compared with adjacent nontumor stomach tissues. Gain- and loss-of-function studies were performed to identify the correlation between miR-103a-3p and tumorigenesis in human GC. Inhibiting miR-103a-3p suppressed GC cell proliferation and blocked the S-G2/M transition in MKN-45/SGC-7901 cells, whereas miR-103a-3p overexpression improved GC cell proliferation and promoted the S-G2/M transition in vitro. Bioinformatics and dual-luciferase reporter assays confirmed that ATF7 is a direct target of miR-103a-3p. Analysis of the TCGA stomach cancer cohort further revealed that miR-103a-3p expression was inversely correlated with ATF7 expression. Notably, silencing ATF7 showed similar cellular and molecular effects as miR-103a-3p overexpression, namely, increased GC cell proliferation, improved CDK2 expression and decreased P27 expression. ATF7 overexpression eliminated the effects of miR-103a-3p expression. These findings indicate that miR-103a-3p promotes the proliferation of GC cell by targeting and suppressing ATF7 in vitro.

• Radiation Oncology Journal
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• v.38 no.2
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• pp.99-108
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• 2020

Purpose: The probability of recurrence of cancer after adjuvant or definitive radiotherapy in patients with human papillomavirus-negative (HPV(-)) head and neck squamous cell carcinoma (HNSCC) varies for each patient. This study aimed to identify and validate radiation sensitivity signature (RSS) of patients with HPV(-) HNSCC to predict the recurrence of cancer after radiotherapy. Materials and Methods: Clonogenic survival assays were performed to assess radiosensitivity in 14 HNSCC cell lines. We identified genes closely correlated with radiosensitivity and validated them in The Cancer Genome Atlas (TCGA) cohort. The validated RSS were analyzed by ingenuity pathway analysis (IPA) to identify canonical pathways, upstream regulators, diseases and functions, and gene networks related to radiosensitive genes in HPV(-) HNSCC. Results: The survival fraction of 14 HNSCC cell lines after exposure to 2 Gy of radiation ranged from 48% to 72%. Six genes were positively correlated and 35 genes were negatively correlated with radioresistance, respectively. RSS was validated in the HPV(-) TCGA HNSCC cohort (n = 203), and recurrence-free survival (RFS) rate was found to be significantly lower in the radioresistant group than in the radiosensitive group (p = 0.035). Cell death and survival, cell-to-cell signaling, and cellular movement were significantly enriched in RSS, and RSSs were highly correlated with each other. Conclusion: We derived a HPV(-) HNSCC-specific RSS and validated it in an independent cohort. The outcome of adjuvant or definitive radiotherapy in HPV(-) patients with HNSCC can be predicted by analyzing their RSS, which might help in establishing a personalized therapeutic plan.

• International Journal of Stem Cells
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• v.16 no.2
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• pp.215-233
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• 2023

Background and Objectives: MYC, also known as an oncogenic reprogramming factor, is a multifunctional transcription factor that maintains induced pluripotent stem cells (iPSCs). Although MYC is frequently upregulated in various cancers and is correlated with a poor prognosis, MYC is downregulated and correlated with a good prognosis in lung adenocarcinoma. MYC and two other MYC family genes, MYCN and MYCL, have similar structures and could contribute to tumorigenic conversion both in vitro and in vivo. Methods and Results: We systematically investigated whether MYC family genes act as prognostic factors in various human cancers. We first evaluated alterations in the expression of MYC family genes in various cancers using the Oncomine and The Cancer Genome Atlas (TCGA) database and their mutation and copy number alterations using the TCGA database with cBioPortal. Then, we investigated the association between the expression of MYC family genes and the prognosis of cancer patients using various prognosis databases. Multivariate analysis also confirmed that co-expression of MYC/MYCL/MYCN was significantly associated with the prognosis of lung, gastric, liver, and breast cancers. Conclusions: Taken together, our results demonstrate that the MYC family can function not only as an oncogene but also as a tumor suppressor gene in various cancers, which could be used to develop a novel approach to cancer treatment.

• Journal of Microbiology and Biotechnology
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• v.34 no.5
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• pp.1164-1177
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• 2024

Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

• International Journal of Stem Cells
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• v.16 no.3
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• pp.315-325
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• 2023

Background and Objectives: Glioblastoma (GBM) is an aggressive primary brain tumor characterized by its heterogeneity and high recurrence and lethality rates. Glioblastoma stem cells (GSCs) play a crucial role in therapy resistance and tumor recurrence. Therefore, targeting GSCs is a key objective in developing effective treatments for GBM. The role of Parathyroid hormone-related peptide (PTHrP) in GBM and its impact on GSCs remains unclear. This study aimed to investigate the effect of PTHrP on GSCs and its potential as a therapeutic target for GBM. Methods and Results: Using the Cancer Genome Atlas (TCGA) database, we found higher expression of PTHrP in GBM, which correlated inversely with survival. GSCs were established from three human GBM samples obtained after surgical resection. Exposure to recombinant human PTHrP protein (rPTHrP) at different concentrations significantly enhanced GSCs viability. Knockdown of PTHrP using target-specific siRNA (siPTHrP) inhibited tumorsphere formation and reduced the number of BrdU-positive cells. In an orthotopic xenograft mouse model, suppression of PTHrP expression led to significant inhibition of tumor growth. The addition of rPTHrP in the growth medium counteracted the antiproliferative effect of siPTHrP. Further investigation revealed that PTHrP increased cAMP concentration and activated the PKA signaling pathway. Treatment with forskolin, an adenylyl cyclase activator, nullified the antiproliferative effect of siPTHrP. Conclusions: Our findings demonstrate that PTHrP promotes the proliferation of patient-derived GSCs by activating the cAMP/PKA signaling pathway. These results uncover a novel role for PTHrP and suggest its potential as a therapeutic target for GBM treatment.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.772-783
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• 2023

Objective: Imaging-based survival stratification of patients with gliomas is important for their management, and the 2021 WHO classification system must be clinically tested. The aim of this study was to compare integrative imaging- and pathology-based methods for survival stratification of patients with diffuse glioma. Materials and Methods: This study included diffuse glioma cases from The Cancer Genome Atlas (training set: 141 patients) and Asan Medical Center (validation set: 131 patients). Two neuroradiologists analyzed presurgical CT and MRI to assign gliomas to five imaging-based risk subgroups (1 to 5) according to well-known imaging phenotypes (e.g., T2/FLAIR mismatch) and recategorized them into three imaging-based risk groups, according to the 2021 WHO classification: group 1 (corresponding to risk subgroup 1, indicating oligodendroglioma, isocitrate dehydrogenase [IDH]-mutant, and 1p19q-codeleted), group 2 (risk subgroups 2 and 3, indicating astrocytoma, IDH-mutant), and group 3 (risk subgroups 4 and 5, indicating glioblastoma, IDHwt). The progression-free survival (PFS) and overall survival (OS) were estimated for each imaging risk group, subgroup, and pathological diagnosis. Time-dependent area-under-the receiver operating characteristic analysis (AUC) was used to compare the performance between imaging-based and pathology-based survival model. Results: Both OS and PFS were stratified according to the five imaging-based risk subgroups (P < 0.001) and three imaging-based risk groups (P < 0.001). The three imaging-based groups showed high performance in predicting PFS at one-year (AUC, 0.787) and five-years (AUC, 0.823), which was similar to that of the pathology-based prediction of PFS (AUC of 0.785 and 0.837). Combined with clinical predictors, the performance of the imaging-based survival model for 1- and 3-year PFS (AUC 0.813 and 0.921) was similar to that of the pathology-based survival model (AUC 0.839 and 0.889). Conclusion: Imaging-based survival stratification according to the 2021 WHO classification demonstrated a performance similar to that of pathology-based survival stratification, especially in predicting PFS.