• About
  • Policies
  • What is open access
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Science
      • Department of Molecular Biology and Genetics
      • View Item
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Science
      • Department of Molecular Biology and Genetics
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      A combined ULBP2 and SEMA5A expression signature as a prognostic and predictive biomarker for colon cancer

      Thumbnail
      View / Download
      988.3 Kb
      Author(s)
      Demirkol, S.
      Gomceli, I.
      Isbilen, M.
      Dayanc, B. E.
      Tez, M.
      Bostanci, E. B.
      Turhan, N.
      Akoglu, M.
      Ozyerli, E.
      Durdu, S.
      Konu, O.
      Nissan, A.
      Gonen, M.
      Gure, A. O.
      Date
      2017
      Source Title
      Journal of Cancer
      Print ISSN
      1837-9664
      Publisher
      Ivyspring International Publisher
      Volume
      8
      Issue
      7
      Pages
      1113 - 1122
      Language
      English
      Type
      Article
      Item Usage Stats
      238
      views
      155
      downloads
      Abstract
      Background: Prognostic biomarkers for cancer have the power to change the course of disease if they add value beyond known prognostic factors, if they can help shape treatment protocols, and if they are reliable. The aim of this study was to identify such biomarkers for colon cancer and to understand the molecular mechanisms leading to prognostic stratifications based on these biomarkers. Methods and Findings: We used an in house R based script (SSAT) for the in silico discovery of stage-independent prognostic biomarkers using two cohorts, GSE17536 and GSE17537, that include 177 and 55 colon cancer patients, respectively. This identified 2 genes, ULBP2 and SEMA5A, which when used jointly, could distinguish patients with distinct prognosis. We validated our findings using a third cohort of 48 patients ex vivo. We find that in all cohorts, a combined ULBP2/SEMA5A classification (SU-GIB) can stratify distinct prognostic sub-groups with hazard ratios that range from 2.4 to 4.5 (p=0.01) when overall- or cancer-specific survival is used as an end-measure, independent of confounding prognostic parameters. In addition, our preliminary analyses suggest SU-GIB is comparable to Oncotype DX colon(®) in predicting recurrence in two different cohorts (HR: 1.5-2; p=0.02). SU-GIB has potential as a companion diagnostic for several drugs including the PI3K/mTOR inhibitor BEZ235, which are suitable for the treatment of patients within the bad prognosis group. We show that tumors from patients with worse prognosis have low EGFR autophosphorylation rates, but high caspase 7 activity, and show upregulation of pro-inflammatory cytokines that relate to a relatively mesenchymal phenotype. Conclusions: We describe two novel genes that can be used to prognosticate colon cancer and suggest approaches by which such tumors can be treated. We also describe molecular characteristics of tumors stratified by the SU-GIB signature.
      Keywords
      Biomarker
      Colon cancer
      Prognosis
      Biological marker
      Caspase 7
      Dactolisib
      Epidermal growth factor receptor
      Protein derivative
      Protein sema5a
      Protein ULBP2
      Unclassified drug
      Adult
      Aged
      Autophosphorylation
      Cancer prognosis
      Cancer recurrence
      Cancer specific survival
      Colon cancer
      Enzyme activity
      Female
      Human
      Human tissue
      Major clinical study
      Male
      Microsatellite instability
      Overall survival
      Protein expression
      Upregulation
      Permalink
      http://hdl.handle.net/11693/36992
      Published Version (Please cite this version)
      https://.doi.org/10.7150/jca.17872
      Collections
      • Department of Molecular Biology and Genetics 542
      Show full item record

      Related items

      Showing items related by title, author, creator and subject.

      • Thumbnail

        TRIB2 confers resistance to anti-cancer therapy by activating the serine/threonine protein kinase AKT 

        Hill, R.; Madureira, P. A.; Ferreira, B.; Baptista, I.; Machado, S.; Colaço, L.; Dos Santos, M.; Liu, N.; Dopazo, A.; Ugurel, S.; Adrienn, A.; Kiss-Toth, E.; Isbilen, M.; Gure, A. O.; Link, W. (Nature Publishing Group, 2017)
        Intrinsic and acquired resistance to chemotherapy is the fundamental reason for treatment failure for many cancer patients. The identification of molecular mechanisms involved in drug resistance or sensitization is imperative. ...
      • Thumbnail

        The miR-644a/CTBP1/p53 axis suppresses drug resistance by simultaneous inhibition of cell survival and epithelialmesenchymal transition in breast cancer 

        Raza, U.; Saatci, O.; Uhlmann, S.; Ansari, S. A.; Eyüpoglu, E.; Yurdusev, E.; Mutlu, M.; Ersan, P. G.; Altundağ, M. K.; Zhang, J. D.; Dogan, H. T.; Güler, G.; Şahin, Ö. (Impact Journals LLC, 2016)
        Tumor cells develop drug resistance which leads to recurrence and distant metastasis. MicroRNAs are key regulators of tumor pathogenesis; however, little is known whether they can sensitize cells and block metastasis ...
      • Thumbnail

        Adjuvant autologous melanoma vaccine for macroscopic stage III disease: survival, biomarkers, and improved response to CTLA-4 blockade 

        Lotem, M.; Merims, S.; Frank, S.; Hamburger, T.; Nissan, A.; Kadouri, L.; Cohen, J.; Straussman, R.; Eisenberg, G.; Frankenburg, S.; Carmon, E.; Alaiyan, B.; Shneibaum, S.; Ayyildiz, Z. O.; Isbilen, M.; Senses, K. M.; Ron, I.; Steinberg, H.; Smith, Y.; Shiloni, E.; Gure, A. O.; Peretz, T. (Hindawi Limited, 2016)
        Background. There is not yet an agreed adjuvant treatment for melanoma patients with American Joint Committee on Cancer stages III B and C. We report administration of an autologous melanoma vaccine to prevent disease ...

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsCoursesThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsCourses

      My Account

      Login

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 2976
      © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy