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      Identification of Biomarkers for Predicting Lymph Node Metastasis of Stomach Cancer Using Clinical DNA Methylation Data

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          Abstract

          Background

          Lymph node (LN) metastasis was an independent risk factor for stomach cancer recurrence, and the presence of LN metastasis has great influence on the overall survival of stomach cancer patients. Thus, accurate prediction of the presence of lymph node metastasis can provide guarantee of credible prognosis evaluation of stomach cancer patients. Recently, increasing evidence demonstrated that the aberrant DNA methylation first appears before symptoms of the disease become clinically apparent.

          Objective

          Selecting key biomarkers for LN metastasis presence prediction for stomach cancer using clinical DNA methylation based on a machine learning method.

          Methods

          To reduce the overfitting risk of prediction task, we applied a three-step feature selection method according to the property of DNA methylation data.

          Results

          The feature selection procedure extracted several cancer-related and lymph node metastasis-related genes, such as TP73, PDX1, FUT8, HOXD1, NMT1, and SEMA3E. The prediction performance was evaluated on the public DNA methylation dataset. The results showed that the three-step feature procedure can largely improve the prediction performance and implied the reliability of the biomarkers selected.

          Conclusions

          With the selected biomarkers, the prediction method can achieve higher accuracy in detecting LN metastasis and the results also proved the reliability of the selected biomarkers indirectly.

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          Most cited references24

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          Wrappers for feature subset selection

          Ron Kohavi, George H. John (1997)
          Article 0 comments Cited 1042 times – based on 0 reviews     Review now
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            HOX genes and their role in the development of human cancers.

            Seema Bhatlekar, Jeremy Fields, Bruce M. Boman (2014)
            In this review, we summarize published findings on the involvement of HOX genes in oncogenesis. HOX genes are developmental genes--they code for proteins that function as critical master regulatory transcription factors during embryogenesis. Many reports have shown that the protein products of HOX genes also play key roles in the development of cancers. Based on our review of the literature, we found that the expression of HOX genes is not only up- or downregulated in most solid tumors but also that the expression of specific HOX genes in cancers tends to differ based on tissue type and tumor site. It was also observed that HOXC family gene expression is upregulated in most solid tumor types, including colon, lung, and prostate cancer. The two HOX genes that were reported to be most commonly altered in solid tumors were HOXA9 and HOXB13. HOXA were often reported to have altered expression in breast and ovarian cancers, HOXB genes in colon cancers, HOXC genes in prostate and lung cancers, and HOXD genes in colon and breast cancers. It was found that HOX genes are also regulated at the nuclear-cytoplasmic transport level in carcinomas. Tumors arising from tissue having similar embryonic origin (endodermal), including colon, prostate, and lung, showed relatively similar HOXA and HOXB family gene expression patterns compared to breast tumors arising from mammary tissue, which originates from the ectoderm. The differential expression of HOX genes in various solid tumors thus provides an opportunity to advance our understanding of cancer development and to develop new therapeutic agents.
            Article 0 comments Cited 163 times – based on 0 reviews     Review now
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              Predicting lung cancer by detecting aberrant promoter methylation in sputum.

              F Gilliland, K Divine, G Saccomanno … (2000)
              Despite the promise of using DNA markers for the early detection of cancer, none has proven universally applicable to the most common and lethal forms of human malignancy. Lung carcinoma, the leading cause of tumor-related death, is a key example of a cancer for which mortality could be greatly reduced through the development of sensitive molecular markers detectable at the earliest stages of disease. By increasing the sensitivity of a PCR approach to detect methylated DNA sequences, we now demonstrate that aberrant methylation of the p16 and/or O6-methyl-guanine-DNA methyltransferase promoters can be detected in DNA from sputum in 100% of patients with squamous cell lung carcinoma up to 3 years before clinical diagnosis. Moreover, the prevalence of these markers in sputum from cancer-free, high-risk subjects approximates lifetime risk for lung cancer. The use of aberrant gene methylation as a molecular marker system seems to offer a potentially powerful approach to population-based screening for the detection of lung cancer, and possibly the other common forms of human cancer.
              Article 0 comments Cited 85 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Dis Markers
                Journal ID (iso-abbrev): Dis. Markers
                Journal ID (publisher-id): DM
                Title: Disease Markers
                Publisher: Hindawi
                ISSN (Print): 0278-0240
                ISSN (Electronic): 1875-8630
                Publication date (Print): 2017
                Publication date (Electronic): 29 August 2017
                Volume: 2017
                Electronic Location Identifier: 5745724
                Affiliations
                1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
                2Department of Automation, Shanghai Jiao Tong University, Shanghai, China
                3School of Communications and Electronics, Jiangxi Science & Technology Normal University, Nanchang, China
                4Charles L. Brown Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA
                Author notes

                Academic Editor: Yuen Yee Cheng

                Author information
                http://orcid.org/0000-0002-3381-2561
                http://orcid.org/0000-0002-4324-1088
                http://orcid.org/0000-0003-4192-5440
                http://orcid.org/0000-0002-6303-7260
                Article
                DOI: 10.1155/2017/5745724
                PMC ID: 5603126
                PubMed ID: 28951630
                SO-VID: b91a633e-042d-40f0-aabe-3fafce72be74
                Copyright © Copyright © 2017 Jun Wu et al.
                License:

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 25 May 2017
                Date revision received : 14 July 2017
                Date accepted : 24 July 2017
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 61603161
                Award ID: 31671299
                Funded by: State Key Development Program for Basic Research of China
                Award ID: 2013CB967402
                Categories
                Subject: Research Article

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