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Copyright © 2008 Elsevier Inc. All rights reserved.
Biology Contribution
Gene Expression Changes in Cervical Squamous Cell Carcinoma After Initiation of Chemoradiation and Correlation With Clinical Outcome
Results: About 200 genes responded to ionizing radiation on the transcriptional level in primary human fibroblasts. The expression profile depended on individual genetic backgrounds. Thirty genes (28 up- and 2 down-regulated) responded to radiation in identical manner in all investigated cells. Twenty of these consensus radiation response genes were functionally categorized: most of them belong to the DNA damage response (GADD45A, BTG2, PCNA, IER5), regulation of cell cycle and cell proliferation (CDKN1A, PPM1D, SERTAD1, PLK2, PLK3, CYR61), programmed cell death (BBC3, TP53INP1) and signaling (SH2D2A, SLIC1, GDF15, THSD1) pathways. Four genes (SEL10, FDXR, CYP26B1, OR11A1) were annotated to other functional groups. Many of the consensus radiation response genes are regulated by, or regulate p53. Time- and dose-dependent expression profiles of selected consensus genes (CDKN1A, GADD45A, IER5, PLK3, CYR61) were investigated by quantitative RT-PCR. Transcriptional alterations depended on the applied dose, and on the time after irradiation.
Conclusions: The data presented here could help in the better understanding of early radiation responses and the development of biomarkers to identify radiation susceptible individuals.
![]() Gynecologic Oncology, Volume 108, Issue 3, March 2008, Pages 520-526 Petra Biewenga, Marrije R. Buist, Perry D. Moerland, Emiel Ver Loren van Themaat, Antoine H.C. van Kampen, Fiebo J.W. ten Kate, Frank Baas Abstract Objective.Pelvic lymph node metastases are the main prognostic factor for survival in early stage cervical cancer, yet accurate detection methods before surgery are lacking. In this study, we examined whether gene expression profiling can predict the presence of lymph node metastasis in early stage squamous cell cervical cancer before treatment. In addition, we examined gene expression in cervical cancer compared to normal cervical tissue.Methods.Tumour samples of 35 patients with early stage cervical cancer who underwent radical hysterectomy and pelvic lymph node dissection, 16 with and 19 without lymph node metastasis, were analysed. Also five normal cervical tissues samples were analysed. We investigated differential expression and prediction of patient status for lymph node positive versus lymph node negative tumours and for healthy versus cancer tissue. Classifiers were built by using a multiple validation strategy, enabling the assessment of both classifier accuracy and variability. Results.Five genes (BANF1, LARP7, SCAMP1, CUEDC1 and PEBP1) showed differential expression between tumour samples from patients with and without lymph node metastasis. Mean accuracy of class prediction is 64.5%with a 95%confidence interval (CI) of 40–90%. For healthy cervical tissue versus early stage cervical cancer, the mean accuracy of class prediction is 99.5%(95%CI of 90–100%). A subset of genes involved in cervical cancer was identified. Conclusion.No accurate class prediction for lymph node status in early stage cervical cancer was obtained. Replication studies are needed to determine the relevance of the differentially expressed genes according to lymph node status. Early stage cervical cancer can be perfectly differentiated from healthy cervical tissue by means of gene expression profiling. ![]() |
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Gene Expression Changes in Cervical Squamous Cell Carcinoma After Initiation of Chemoradiation and Correlation With Clinical Outcome