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Molecular characterization of the DYX1C1 gene and its application as a cancer biomarker Yun-Ji Kim 1 *, Jae-Won Huh 1,2 *, Dae-Soo Kim 3, Min-In Bae 1,

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Presentation on theme: "Molecular characterization of the DYX1C1 gene and its application as a cancer biomarker Yun-Ji Kim 1 *, Jae-Won Huh 1,2 *, Dae-Soo Kim 3, Min-In Bae 1,"— Presentation transcript:

1 Molecular characterization of the DYX1C1 gene and its application as a cancer biomarker Yun-Ji Kim 1 *, Jae-Won Huh 1,2 *, Dae-Soo Kim 3, Min-In Bae 1, Tae-Oh Kim 4, Ja-Rang Lee 1, Hong-Seok Ha 1, Kung Ahn 1, Yu-Na Noh 1, Sang-Je Park 1, Jin-Han Bae 1, Yi-Deun Jung 1 and Heui-Soo Kim 1,3§ 1 Division of Biological Sciences, College of Natural Sciences, Pusan National University, Busan 609-735, Republic of Korea 2 National Primate Research Center (NPRC), KRIBB, Ochang, Chungbuk 363-883, Republic of Korea 3 PBBRC, Interdisciplinary Research Program of Bioinformatics, College of Natural Sciences, Pusan National University, Busan 609-735, Republic of Korea 4 Division of Gastroenterology Department of Internal Medicine, College of Medicine Pusan National University, Pusan National University Hospital, Busan 602-739, Republic of Korea http://www.primate.or.kr DYX1C1 has three alternatively spliced transcripts. So we expect that alternative transcripts of DYX1C1 are used as a biomarker to detect specific cancer. RT-PCR analysis is conducted in order to detect expression of the DYX1C1 gene and the PCR products were analyzed using the Image J program to compare the expression levels of each transcript. We found one of the transcripts was directly associated with an HERV-H LTR element that could be translated into protein sequence. Four new alternative transcripts were identified by RT-PCR analysis with various human tissue samples including 5 normal and adjacent tumor tissue sets. Semi-quantitative RT-PCR analysis showed the transcriptional activity of V3 and V2 was higher in normal than in tumor tissue samples, especially in the colorectal tissue samples. Our results indicated that alternatively spliced transcript variants of the DYX1C1 gene could be used as cancer biomarkers to detect colorectal cancer. ………………………………………………………………………………………………………………. Bioinformatics ( in silico analysis DYX1C1 gene ) PCR and RT - PCR Gene cloning and sequencing Alignment & Image J analysis marker adrenal gland cerebellumadult brain (whole) heart kidney liver lungtestistrachea bone marrow marker fetal brain fetal liver placenta prostate salivary gland sk-muscle spinal cord thymus thyroid uterus (a) Transcript related to HERV-H (b) Transcripts not related to HERV-H V3 V2 V1 V1-3 V1-4 V1-, V1-2 marker adrenal gland cerebellumadult brain (whole) heart kidney liver lungtestistrachea bone marrow marker fetal brainfetal liver placenta prostate salivary gland sk-muscle spinal cord thymus thyroid uterus GAPDH 120bp (a) M 1 2 3 4 5 6 7 8 9 10 GAPDH 120bp V1 V1-3 V1-4 V1-1,V1-2 (b) V3 V2 (a) M 1 2 3 4 5 6 7 8 9 10 GAPDH 120bp (b) * * 1. Adran A, Yoshida A, Ishikawa K, Goi T, Yamaguchi A, Ueda T, Inuzuka M. (2004) Identification of a novel splice variant of the human anti-apoptopsis gene survivin. Biochem Biophys Res Commun. 314: 902-7. 2. Brinkman BM. (2004) Splice variants as cancer biomarkers. Clin Biochem. 37: 584-94. Fig.1 Spliced variants of the DYX1C1 gene and their structural analysis Fig.4 Expression patterns of HERV-H LTR-associated (A) and - unassociated (B) DYX1C1 transcripts in normal human tissues. G3PDH indicates the positive control. Abstract IntroductionMaterials & Methods The identification of cancer biomarkers has been a major focus of investigation in the field of cancer research. However, effective and reproducible cancer biomarker developments are still far off and enormous efforts are needed in this area [Brinkman et al. 2004]. In cancerous cells, splicing mechanisms are significantly altered by defects in splice sites caused by frequent point mutations (Venables et al. 2004; Skotheim et al. 2007). Aberrant neuronal-specific splicing of amphiphysin 2 in non-neuronal cells may contribute to the progression human melanoma (Ge et al. 1999). Expression levels of alternatively spliced variants of survivin are not equal to each other in malignant breast tissues. In the case of breast cancer, different survivin transcripts show different functions in the progression of apoptosis (Ryan et al. 2005; Pajares et al. 2007). Our study focused on the application of cancer biomarkers using transcription variants. Biomarker Results and Discussion References Fig.2 Comparative analysis of HERV-H LTR-associated DYX1C1 transcripts (V1, V1-1, V1- 2, V1-3, V1-4) in normal and tumor tissue samples. G3PDH indicates the positive control. Fig.3 Comparative analysis of the other transcripts (V2, V3) in normal (N) and tumor (T) samples. G3PDH indicates the positive control The DYX1C1 gene is shown to have three alternatively spliced transcripts in the GenBank database. V1, V2, and V3 are the originally reported transcripts, and V1-1, V1-2, V1-3, and V1-4 are newly identified alternative transcripts. Fig. 3 - (B) RT-PCR was conducted three times and G3PDH was used as a control. PCR products were analyzed quantitatively using the Image-J program. The X-axis of the bar graph indicates normal (N)/tumor (T) tissue samples. Lanes: M, size marker; 1, colon (N); 2, colon (T); 3, liver (N); 4, liver (T); 5, uterus (N); 6, uterus (T); 7, breast (N); 8, breast (T); 9, stomach (N); 10, stomach (C) and the Y-axis of the bar graph indicates the relative expression levels of 2 transcripts (V2 and V3). P < 0.05 in Student’s t-test is indicated by *. (A) Lanes: M, size marker; 1, colon (N); 2, colon (T); 3, liver (N); 4, liver (T); 5, uterus (N); 6, uterus (T); 7, breast (N); 8, breast (T); 9, stomach (N); 10, stomach (C). 8% LTR : long terminal repeat LINE : long integrated nuclear element SINE : short integrated nuclear element HERV : Human endogenous retro-virus RNase Viral RNA Capsid : core proteins Receptor binding proteins Lipid envelope transformation Plasmid isolation ligation Electrophoresis PCR, RT-PCR Human genomic DNA inoculation DNA vector Bioinformatics Sequencing analysis


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