Martin Koch1, Michael Wiese. 1. Pharmaceutical Institute, University Bonn, An der Immenburg 4, 53121 Bonn, Germany.
Abstract
PURPOSE: To assign functional properties to gene expression profiles of cervical cancer stages and identify clinically relevant biomarker genes. EXPERIMENTAL DESIGN: Microarray samples of 24 normal and 102 cervical cancer biopsies from four publicly available studies were pooled and evaluated. High-quality microarrays were normalized using the CONOR package from the Bioconductor project. Gene expression profiling was performed using variance-component analysis for accessing most reliable probes, which were subsequently processed by gene set enrichment analysis. RESULTS: Of 22.277 probes that were subject to variance-component analysis, eleven probes had low heterogeneity, that is, a W/T ratio between 0.18 and 0.38. Seven of these probes are induced in all cervical cancer stages: they are GINS1, PAK2, DTL, AURKA, PRKDC, NEK2 and CEP55. The other four probes are induced in normal cervix: P11, EMP1, UPK1A and HSPC159. We performed GSEA of 9.873 probes exhibiting less variability, that is, having a W/T ratio of <0.75. Repeatedly, significant gene expression signatures were found that are related to treatment using angiocidin and darapladib. Additionally, expression signatures from immunological disease signatures were found, for example graft versus host disease and acute kidney rejection. Another finding comprises a gene expression signature in stage IB2 that refers to MT1-MMP-dependent migration and invasion. This gene signature is accompanied by gene expression signatures which refer to ECM receptor-mediated interactions. CONCLUSION: Analysis of cervical cancer patient gene expression data reveals a novel perspective on HPV-mediated transcription processes. This novel point of view contains a better understanding and even might provide improvements to cancer therapy.
PURPOSE: To assign functional properties to gene expression profiles of cervical cancer stages and identify clinically relevant biomarker genes. EXPERIMENTAL DESIGN: Microarray samples of 24 normal and 102 cervical cancer biopsies from four publicly available studies were pooled and evaluated. High-quality microarrays were normalized using the CONOR package from the Bioconductor project. Gene expression profiling was performed using variance-component analysis for accessing most reliable probes, which were subsequently processed by gene set enrichment analysis. RESULTS: Of 22.277 probes that were subject to variance-component analysis, eleven probes had low heterogeneity, that is, a W/T ratio between 0.18 and 0.38. Seven of these probes are induced in all cervical cancer stages: they are GINS1, PAK2, DTL, AURKA, PRKDC, NEK2 and CEP55. The other four probes are induced in normal cervix: P11, EMP1, UPK1A and HSPC159. We performed GSEA of 9.873 probes exhibiting less variability, that is, having a W/T ratio of <0.75. Repeatedly, significant gene expression signatures were found that are related to treatment using angiocidin and darapladib. Additionally, expression signatures from immunological disease signatures were found, for example graft versus host disease and acute kidney rejection. Another finding comprises a gene expression signature in stage IB2 that refers to MT1-MMP-dependent migration and invasion. This gene signature is accompanied by gene expression signatures which refer to ECM receptor-mediated interactions. CONCLUSION: Analysis of cervical cancerpatient gene expression data reveals a novel perspective on HPV-mediated transcription processes. This novel point of view contains a better understanding and even might provide improvements to cancer therapy.
Authors: Robert L Wilensky; Yi Shi; Emile R Mohler; Damir Hamamdzic; Mark E Burgert; Jun Li; Anthony Postle; Robert S Fenning; James G Bollinger; Bryan E Hoffman; Daniel J Pelchovitz; Jisheng Yang; Rosanna C Mirabile; Christine L Webb; LeFeng Zhang; Ping Zhang; Michael H Gelb; Max C Walker; Andrew Zalewski; Colin H Macphee Journal: Nat Med Date: 2008-09-21 Impact factor: 53.440
Authors: Christophe Rosty; Michal Sheffer; Dafna Tsafrir; Nicolas Stransky; Ilan Tsafrir; Martine Peter; Patricia de Crémoux; Anne de La Rochefordière; Rémy Salmon; Thierry Dorval; Jean Paul Thiery; Jérôme Couturier; François Radvanyi; Eytan Domany; Xavier Sastre-Garau Journal: Oncogene Date: 2005-10-27 Impact factor: 9.867
Authors: Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov Journal: Proc Natl Acad Sci U S A Date: 2005-09-30 Impact factor: 11.205
Authors: Maartje G Noordhuis; Rudolf S N Fehrmann; G Bea A Wisman; Esther R Nijhuis; Jelmer J van Zanden; Perry D Moerland; Emiel Ver Loren van Themaat; Haukeline H Volders; Mirjam Kok; Klaske A ten Hoor; Harry Hollema; Elisabeth G E de Vries; Geertruida H de Bock; Ate G J van der Zee; Ed Schuuring Journal: Clin Cancer Res Date: 2011-03-08 Impact factor: 12.531
Authors: Dohun Pyeon; Michael A Newton; Paul F Lambert; Johan A den Boon; Srikumar Sengupta; Carmen J Marsit; Craig D Woodworth; Joseph P Connor; Thomas H Haugen; Elaine M Smith; Karl T Kelsey; Lubomir P Turek; Paul Ahlquist Journal: Cancer Res Date: 2007-05-15 Impact factor: 12.701
Authors: Robbert J C Slebos; Yajun Yi; Kim Ely; Jesse Carter; Amy Evjen; Xueqiong Zhang; Yu Shyr; Barbara M Murphy; Anthony J Cmelak; Brian B Burkey; James L Netterville; Shawn Levy; Wendell G Yarbrough; Christine H Chung Journal: Clin Cancer Res Date: 2006-02-01 Impact factor: 12.531
Authors: Peter A van Dam; Christian Rolfo; Rossana Ruiz; Patrick Pauwels; Christophe Van Berckelaer; Xuan Bich Trinh; Jose Ferri Gandia; Johannes P Bogers; Steven Van Laere Journal: ESMO Open Date: 2018-06-28