• Molecules and Cells
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• v.45 no.6
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• pp.413-424
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• 2022

Suppressor of mothers against decapentaplegic homolog (SMAD) 4 is a pluripotent signaling mediator that regulates myriad cellular functions, including cell growth, cell division, angiogenesis, apoptosis, cell invasion, and metastasis, through transforming growth factor β (TGF-β)-dependent and -independent pathways. SMAD4 is a critical modulator in signal transduction and functions primarily as a transcription factor or cofactor. Apart from being a DNA-binding factor, the additional SMAD4 mechanisms in tumor suppression remain elusive. We previously identified methyl malonyl aciduria cobalamin deficiency B type (MMAB) as a critical SMAD4 binding protein using a proto array analysis. This study confirmed the interaction between SMAD4 and MMAB using bimolecular fluorescence complementation (BiFC) assay, proximity ligation assay (PLA), and conventional immunoprecipitation. We found that transient SMAD4 overexpression down-regulates MMAB expression via a proteasome-dependent pathway. SMAD4-MMAB interaction was independent of TGF-β signaling. Finally, we determined the effect of MMAB downregulation on cancer cells. siRNA-mediated knockdown of MMAB affected cancer cell metabolism in HeLa cells by decreasing ATP production and glucose consumption as well as inducing apoptosis. These findings suggest that SMAD4 controls cancer cell metabolism by regulating MMAB.

• BMB Reports
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• v.49 no.11
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• pp.607-611
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• 2016

The Cancer Genome Atlas (TCGA) has compiled genomic, epigenomic, and proteomic data from more than 10,000 samples derived from 33 types of cancer, aiming to improve our understanding of the molecular basis of cancer development. Availability of these genome-wide information provides an unprecedented opportunity for uncovering new key regulators of signaling pathways or new roles of pre-existing members in pathways. To take advantage of the advancement, it will be necessary to learn systematic approaches that can help to uncover novel genes reflecting genetic alterations, prognosis, or response to treatments. This minireview describes the updated status of TCGA project and explains how to use TCGA data.

• Genomics & Informatics
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• v.11 no.4
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• pp.180-185
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• 2013

Development of liver cancers is driven largely by genomic alterations that deregulate signaling pathways, influencing growth and survival of cancer cells. Because of the hundreds or thousands of genomic/epigenomic alterations that have accumulated in the cancer genome, it is very challenging to find and test candidate genes driving tumor development and progression. Systematic studies of the liver cancer genome have become available in recent years. These studies have uncovered new potential driver genes, including those not previously known to be involved in the development of liver cancer. Novel approaches combining multiple datasets from patient tissues have created an unparalleled opportunity to uncover potential new therapeutic targets and prognostic/predictive biomarkers for personalized therapy that can improve clinical outcomes of the patients with liver cancer.

• Genomics & Informatics
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• v.16 no.4
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• pp.32.1-32.7
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• 2018

Ovarian cancer is one of the leading causes of cancer-related deaths in gynecological malignancies. Over 70% of ovarian cancer cases are high-grade serous ovarian cancers and have high death rates due to their resistance to chemotherapy. Despite advances in surgical and pharmaceutical therapies, overall survival rates are not good, and making an accurate prediction of the prognosis is not easy because of the highly heterogeneous nature of ovarian cancer. To improve the patient's prognosis through proper treatment, we present a prognostic prediction model by integrating high-dimensional RNA sequencing data with their clinical data through the following steps: gene filtration, pre-screening, gene marker selection, integrated study of selected gene markers and prediction model building. These steps of the prognostic prediction model can be applied to other types of cancer besides ovarian cancer.

• Genomics & Informatics
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• v.18 no.4
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• pp.35.1-35.7
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• 2020

Identifying the patterns of gene expression in breast cancers is essential to understanding their pathophysiology and developing anticancer drugs. Breast cancer is a heterogeneous disease with different subtypes determined by distinct biological features. Luminal breast cancer is characterized by a relatively high expression of estrogen receptor (ER) and progesterone receptor (PR) genes, which are expressed in breast luminal cells. In ~25% of invasive breast cancers, human epidermal growth factor receptor 2 (HER2) is overexpressed; these cancers are categorized as the HER2 type. Triple-negative breast cancer (TNBC), in which the cancer cells do not express ER/PR or HER2, shows highly aggressive clinical outcomes. TNBC can be further classified into specific subtypes according to genomic mutations and cancer immunogenicity. Herein, we discuss the brief history of TNBC classification and its implications for promising treatments.

• BMB Reports
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• v.57 no.3
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• pp.125-134
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• 2024

Whole-genome doubling (WGD), characterized by the duplication of an entire set of chromosomes, is commonly observed in various tumors, occurring in approximately 30-40% of patients with different cancer types. The effect of WGD on tumorigenesis varies depending on the context, either promoting or suppressing tumor progression. Recent advances in genomic technologies and large-scale clinical investigations have led to the identification of the complex patterns of genomic alterations underlying WGD and their functional consequences on tumorigenesis progression and prognosis. Our comprehensive review aims to summarize the causes and effects of WGD on tumorigenesis, highlighting its dualistic influence on cancer cells. We then introduce recent findings on WGD-associated molecular signatures and genetic aberrations and a novel subtype related to WGD. Finally, we discuss the clinical implications of WGD in cancer subtype classification and future therapeutic interventions. Overall, a comprehensive understanding of WGD in cancer biology is crucial to unraveling its complex role in tumorigenesis and identifying novel therapeutic strategies.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.8003-8008
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• 2015

Background: The aim of this study was to investigate whether family history of cancer is associated with head and neck cancer risk in a Chinese population. Materials and Methods: This case-control study included 921 cases and 806 controls. Recruitment was from December 2010 to January 2015 in eight centers in East Asia. Controls were matched to cases with reference to sex, 5-year age group, ethnicity, and residence area at each of the centers. Results: We observed an increased risk of head and neck cancer due to first degree family history of head and neck cancer, but after adjustment for tobacco smoking, alcohol drinking and betel quid chewing the association was no longer apparent. The adjusted OR were 1.10 (95% CI=0.80-1.50) for family history of tobacco-related cancer and 0.96 (95%CI=0.75-1.24) for family history of any cancer with adjustment for tobacco, betel quid and alcohol habits. The ORs for having a first-degree relative with HNC were higher in all tobacco/alcohol subgroups. Conclusions: We did not observe a strong association between family history of head and neck cancer and head and neck cancer risk after taking into account lifestyle factors. Our study suggests that an increased risk due to family history of head and neck cancer may be due to shared risk factors. Further studies may be needed to assess the lifestyle factors of the relatives.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4229-4233
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• 2012

With the advances in modern diagnostic expertise for cancer, certain approaches allowing scanning of the complete genome and the proteome are becoming very useful for researchers. These high throughput techniques have already proven power, over traditional detection methods, in differentiating disease sub-types and identifying specific genetic events during progression of cancer. This paper introduces major branches of omics-technology and their applications in the field of cancer. It also addresses current road blocks that need to be overcome and future possibilities of these methods in oncogenic detection.

• Genomics & Informatics
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• v.3 no.2
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• pp.77-80
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• 2005

Targeting of complex system such as human cells rather than biochemically pure molecules will be a useful approach to massively identify ligands specific for the markers associated with human disease such as cancer and simultaneously discover the specific molecular markers. In this study, we developed in vitro selection method to identify nuclease-resistant nucleic acid ligands called RNA aptamers that are specific for human cancer cells. This method is based on the combination of the cell-based selection and subtractive systematic evolution of ligands by exponential enrichment (SELEX) method. These aptamers will be useful for cancer-specific ligands for proteomic research to identify cancer-specific molecular markers as well as tumor diagnosis and therapy.

• Genomics & Informatics
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• v.18 no.4
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• pp.36.1-36.9
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• 2020

Since lung cancer is a major causative for cancer-related deaths, the investigations for discovering biomarkers to diagnose at an early stage and to apply therapeutic strategies have been continuously conducted. Recently, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are being exponentially studied as promising biomarkers of lung cancer. Moreover, supportive evidence provides the competing endogenous RNA (ceRNA) network between lncRNAs and miRNAs participating in lung tumorigenesis. This review introduced the oncogenic or tumor-suppressive roles of lncRNAs and miRNAs in lung cancer cells and summarized the involvement of the lncRNA/miRNA ceRNA networks in carcinogenesis and therapeutic resistance of lung cancer.