1. Molecular Biomarkers in Radiotherapy of Cervical Cancer A collaboration project between Department of Gynecologic Oncology and Department of Radiation Biology Project group The Radiation Therapy Team at Dept. of Gynecologic Oncology /Gunnar B. Kristensen, Dr. Med The Clinical Radiation Biology Group at Dept. of Radiation Biology /Heidi Lyng, Dr. Philos

2. Radiation field Lymph nodes External irradiation: Tumour region (50 Gy) and the rest of pelvis (45 Gy) Endocavitary brachytherapy: Cervix (21 Gy) Narrow therapeutic window  high frequency of side effects to pelvic organs Radiotherapy of cervical carcinomas External radiation, field_1 front Need for improved treatment – more individualized therapy based on biological information

3. Aims Molecular methods based on microarrays will be combined with MR and eventually PET techniques to find biomarkers that can be utilized for biologically optimized therapy  Identify predictive biomarkers for the therapeutic outcome, including patient survival, locoregional tumor control and normal tissue side effects.  Identify key radiation regulated pathways in tumors and possible targets for molecular intervention.  Explore how the molecular findings can be combined with functional (MR and PET) and molecular imaging in treatment planning and response monitoring. Microarrays MR imagingMR-spectroscopy

4. Study protocol on cervical cancer, stage 2b-4a Tumor biopsies DCE-MRI Blood sample DCE-MRI Pathology MR/CT findings Radiation field Follow-up MedInsight Clinical data base Tumor biopsies Radiation therapy, curative intent Research projects T2-MRI CT dose plan Image storage Blood and tissue storage >300 patients included

5. Research projects Studies in cell lines Molecular screeningSignaling Tumor biopsies Functional imaging DCE-MRI Normal tissue side effects CT dose plan, blood samples

6. Molecular screening - gene profile associated with clinical outcome - basis for further molecular studies Collaboration with statisticians Frigessi, Glad, Holden: UiO, NR Van de Wiel, Vrije Universiteit, Amsterdam Frigessi et al, Nucleic Acids Res, 2005 Scheel et al, Bioinformatics, 2005 Ferkingstad et al., Genome Biology, 2008 Nygaard et al., BMC Genomics, 2008 ”New” genes Marker for clinical outcome? Terapeutic target? P = 0.02 Gene profile 1 Gene profile 2 Classification of patients with different outcome based on gene profile Genuttrykk (mRNA) Analysis of tumor biopsies PhD student Malin Lando

7. Frequency (%) aCGH ratio (log 2 ) Chromosomal location 1pter-Xqter A C024/01 DNA index: 1.00 Tumor cell fraction: 55% B 1 3 5 7 9 11 13 15 17 19 21 X 2 4 6 8 10 12 14 16 18 20 22 1&21&2 1 2 3 2&32&3 1&21&2 2&32&3 1&21&2 Molecular screening: intratumor heterogeneity in gene copy number Pronounced heterogeneity in copy number within cervix tumors → resistent subpopulations may emerge at later stages of the disease Genome wide screening of copy number in cervix tumor -1pcen-31 +1q -6q24-25 -12q -17p -19p 22% 34% 44% Evolution -1pcen-31 +1q -6q24-25 -12q -17p -19p -13qcen-34 -1p31-ter -2q21-ter -4p +6p -8p C -1pcen-31 +1q -6q24-25 -12q -17p -19p Lyng et al., Genome Biology 2008 Subpopulations of tumor cells with different genetic characteristics

8. Characterization of signaling pathways of importance for outcome → mechanisms of activation Screening  signaling MSN P = 0.004 Progression free survival Score N Events 0-6 87 37 9 72 15 Time (months) Lyng et al., BMC Genomics, 2006 Low MSN expression → poor outcome Low MSN expression High MSN expression Analysis of tumor biopsies PhD student Cathinka Halle Collaboration with Division of Pathology Ruth Holm

9. Metabolic screening by use of MR-spectroscopy - relationship to molecular data, imaging (MR) and clinical data Collaboration with the MR center in Trondheim Ingrid Gribbestad (ppm) 0.00.40.81.21.62.02.42.83.23.64.04.4 Cre GPC PC Cho Cre  -Glc Lac TSP FA – CH 3 FA – (CH 2 ) n FA –CH 2 – CH 3 FA – CH 2 – CH 2 – CO- Ac Glycerol backbone Tau FA – CH = CH – CH 2 – CH 2 Gly Tumor biopsy from cervix cancer Metabolic profile Lyng et al., BMC Cancer 2007 -50 0 50 100 150 200 -20020406080100120140160180200 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Measured apoptotic cell density (cells/mm 2 ) r = 0.95 p < 0.001 Predicted apoptotic cell density (cells/mm 2 ) B Metabolites involved in treatment induced apoptosis