Michelle Davis and Ruba Deeb's poster examining the use of the Gene Expression Omnibus database to identify genetic protein biomarkers of epithelial ovarian cancer

Davis, Michelle

Deeb, Ruba S.

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Michelle Davis, Ruba S. Deeb *#Department of Biomedical EngineeringUniversity of Bridgeport, Bridgeport, CT *Advisor, # Poster Advisor A comparison of the dominant key genes using GEO2R that are transformed in ovarian cancer promoting epithelium cell proliferation and cell differentiation Using the Gene Expression Omnibus database (GEO), identify four genes that are associated with common factors of epithelial ovarian cancer and compare them with the ”Gold-standard,” CA125 (MUC16)I n t r o d u c t i o n: Human epithelial ovarian cancer (EOC) is the most lethal of the gynecological malignancies of the female reproductive system1-2 It is imperative to find a detection or therapeutic strategy that is specific and sensitive enough to accurately detect early-staged ovarian cancer cells when the cancer cell is still small and confined to the ovary The current standard diagnostic approved by the US FDA is the CA-125 test coupled with the transvaginal ultrasound2-3 The CA-125 test cannot be categorized as a screening assay for cancer detection in the general population The CA-125 test cannot be used as a single diagnostic test to clinically confirm EOC because an increase in CA-125 can be seen in other conditions such as endometriosis and ovarian cysts3 When the CA-125 test is combined with the transvaginal ultrasound (TVU), a predictive value (PPD) of 40% was obtained. A high PPD was achieved in patients with advanced stage EOC, where three out of the four tumors displayed in early-stage cancer came back with a normal prognosis9 Using the GEO2R Gene Expression Omnibus database, data analysis compared samples with differential genes expression under the conditions of risk prediction, depression, Transforming Growth Factor Beta (TGFβ) Receptor 3 signaling disruption, in addition to the cell niche under various experimental conditions AnalyzeGeo Series NumberTop Protein Gene ExpressedKeywordsMain Topic of ChoiceOvarian Cancer Cell ProliferationRisk predictionNuclear transport factor 2 like export factor 1 [NXT1]4GSE9116Gene expression differs in tissues from individuals with high vs low symptoms of psychological depression4Transforming Growth Factor Beta Receptor 3 [TGFBR2]Ninjurin 2 [NINJ2] & LIM and Cysteine Rich Domains 1 [LMCD1]5GSE40266TGF-beta can modulate ovarian cancer cell growth in an indirect manner through cancer-associated fibroblasts (CAFs)5LIM and Cysteine Rich Domains 1 [LMCD1]6GSE6653Normal  ovarian cancer cells respond to the addition of TGF-β (growth inhibition)Cell nicheNeural EGFL like 2 [NELL2]7GSE144072000 genes are significantly differentially expressed between the surface epithelial and cancer samples.7S t u d y  D e s i g n: G E O  D a t a b a s e  S e a r c hS t u d y  D e s i g n: G e n e  I n f o r m a t i o n  C h a r tTop Gene ExpressionHow Genes Alter Cell Behavior and Cell FunctionNuclear transport factor 2 like export factor 1 [NXT1]4• Risk factors such as depression can effect theNeuroendocrine system, which effects the activityof tumor cells4• Patients with depressive symptoms show anincrease in transcription factors, such as NXT1,which also showed an elevation in norepinephrine4Ninjurin 2 [NINJ2]5• Transforming Growth Factor Beta Receptor 3 [TGFBR2] influences ovarian cancer metastasis by the way of cancer-associated fibroblasts (CAFs)5• Transcriptional profiling of normal ovarian cell tissues treated with TGF-β have shown a key CAF gene expression, versican (VCAN)5LIM and Cysteine Rich Domains 1 [LMCD1]6• When  TGF-β is activated, LMCD1 was one of the identified transcriptional factors containing SMAD4 in promoter regions6• Increases in LMCD1 regulates cancer cell invasion and metastasis8Neural EGFL like 2 [NELL2]7• Expression differs greatly between normal ovarian tissues and cancer tissues • Nell2 is significantly upregulated in normal     ovarian tissues• Nell2 downregulation indicates an ovarian adenocarcinoma Experimental data analysis using GEO allows the discovery of other than MUC16 that are expressed in association with EOC  These four revealed genes are not addressed in the literature and require further investigation and recognition due to their significant differential expression levels in sample comparison studies Depression, TGFBR2 signaling disruption, and the cell niche are potential confounding factors in epithelial ovarian cancer proliferation Molecular mechanisms for each EOC factor are significantly expressed through four genes R e s e a r c h  G o a l s:C o n c l u s i o n:R e f e r e n c e s :1. Y Zhang BMC Bioinformatics. 2008, 9: 40.2. Natanzon, Y., Goode, E. L., & Cunningham, J. M. (2018). Epigenetics in ovarian cancer. Seminars in Cancer Biology, 51, 160-169. doi:https://doi.org/10.1016/j.semcancer.2017.08.0033. E.L. Moss, et al.Views of general practitioners on the role of CA125 in primary care to diagnose ovarian cancer. BMC Womens Health, 13 (8) (2013), pp. 2-7 4. Lutgendorf, S. K., DeGeest, K., Sung, C. Y., Arevalo, J. M., Penedo, F., Lucci, J., Goodheart, M., Lubaroff, D., Farley, D. M., Sood, A. K., … Cole, S. W. (2008). Depression, social support, and beta-adrenergic transcription control in human ovarian cancer. Brain, behavior, and immunity, 23(2), 176-83.5. Yeung, T. L., Leung, C. S., Wong, K. K., Samimi, G., Thompson, M. S., Liu, J., Zaid, T. M., Ghosh, S., Birrer, M. J., … Mok, S. C. (2013). TGF-β modulates ovarian cancer invasion by upregulating CAF-derived versican in the tumor microenvironment. Cancer research, 73(16), 5016-28.6. Qin, H., Chan, M. W., Liyanarachchi, S., Balch, C., Potter, D., Souriraj, I. J., Cheng, A. S., Agosto-Perez, F. J., Nikonova, E. V., Yan, P. S., Lin, H. J., Nephew, K. P., Saltz, J. H., Showe, L. C., Huang, T. H., … Davuluri, R. V. (2009). An integrative ChIP-chip and gene expression profiling to model SMAD regulatory modules. BMC systems biology, 3, 73. doi:10.1186/1752-0509-3-737. Bowen, N. J., Walker, L. D., Matyunina, L. V., Logani, S., Totten, K. A., Benigno, B. B., & McDonald, J. F. (2009). Gene expression profiling supports the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as ovarian cancer initiating cells. BMC medical genomics, 2, 71. doi:10.1186/1755-8794-2-718. Du, L., Yamamoto, S., Burnette, B. L., Huang, D., Gao, K., Jamshidi, N., & Kuo, M. D. (2016). Transcriptome profiling reveals novel gene expression signatures and regulating transcription factors of TGFβ-induced epithelial-to-mesenchymal transition. Cancer medicine, 5(8), 1962-72.9. CA125 and transvaginal ultrasound monitoring in high-risk women cannot prevent the diagnosis of advanced ovarian cancer Olivier, R.I. et al.Gynecologic Oncology , Volume 100 , Issue 1 , 20 - 26Analysis of Potential Protein Biomarkers in Epithelial Ovarian Cancer Using the Gene Expression Omnibus Database

Analysis of Potential Protein Biomarkers in Epithelial Ovarian Cancer Using the Gene Expression Omnibus Database

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Analysis of Potential Protein Biomarkers in Epithelial Ovarian Cancer Using the Gene Expression Omnibus Database

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