european journal of cancer 48, suppl. 5 (2012) S25–S288
tion. Yeast cells were grown in yeast extract-peptone-dextrose broth (1:2:2;%). 12 ml of DNA was used in each sample. Bleomycin: Samples with 12 ml of DNA were exposed to different Bleomycin doses (0, 0.015, 0.045, 0.15, 0.45, 0.5 UI/ml) for different times (24, 48, 72 hours). Electrophoresis: After treatments, DNA samples were electrophoresed in a 1% agarose gel (in 0.5 X Tris-Borate EDTA) at 80 V, 90 min. The gel was stained with ethidium bromide 10 mg/ml. Image analysis of gels: After electrophoresis, photography of the gel was taken and the images in jpg ﬁles were analyzed with the ImageJ 1.34s software. A DNA proﬁle (intensity of signal versus migration distance) was obtained for each electrophoresis lane. The area under the curve, that is indicative of the content of DNA, was obtained automatically with this software in each proﬁle. Results: Bleomycin induced DNA degradation that was increased with the increment of time of exposure and with the dose. The images of the gels analyzed showed that the DNA damage was about 20% of degradation at high bleomycin doses (0.45 UI/ml) and 24 hours of exposure. Longer exposure period (72 hours) induced a 30% of DNA degradation at a dose of 0.15 UI/ml, and a 50% of degradation at 0.45 UI/ml. Results showed a dose-response relationship that can be used to estimate the effective dose of bleomycin analyzing the DNA degradation obtained. Conclusion: Belomycin is a genotoxic agent that can induce DNA degradation time and dose dependent. The optimization of dose-response curves, like in this study, permits the estimation of the effective dose of exposure to a better evaluation of the antineoplastic activity based on the study of DNA degradation; which could be used for dosimetric purposes. 1183 DNA Methylation in Lung Cancer Primary Tumor as a Biomarker for Cancer M. Zohri1 , M. Shadmehr2 , M. Rahmani-Khalili3 , Z. Farsad3 , N. Doozandeh4 , R. Sheikhnejad3 . 1 Toﬁgh Daru, Molecular and Cancer Biology, Tehran, Iran, 2 Shahid Beheshti University of Medical Sciences, Tracheal Diseases Research Center, Tehran, Iran, 3 Toﬁgh Daru, Molecular Biology, Tehran, Iran, 4 Shahid Beheshti University of Medical Sciences Tehran, Pathology, Tehran, Iran Lung cancer is the leading cause of cancer deaths in the world among both men and women because most of them are normally diagnosed in late stages. Detection of lung cancer at earlier stages could potentially increase survival rates by 10-to 50-folds. Lung cancer screening often reveals more benign conditions that require invasive testing and expose people to unnecessary risks. Therefore safer diagnostic tests are required to detect cancer early. DNA methylation is a highly characterized epigenetic modiﬁcation of the human genome that is implicated in cancer. Aberrant hypermethylation of the CpG Island linked to some tumor suppressor genes is acquired during tumorigenesis. Some of these genes are considered promising DNA methylation biomarkers for early cancer diagnostics. PCR-based methods that use sodium bisulﬁte-treated DNA as a template is generally accepted as the most analytically sensitive and speciﬁc techniques for analyzing DNA methylation at single loci. In this study, we evaluate the promoter methylation status of eleven tumor suppressor genes (CDH1, APC, FHIT, DAPK, SFRP1, GSTP1, p16, RARb-2, DLC1, SHP, and SOCs) in surgically removed primary lung tumors of 28 Iranian patients. The frozen tissue specimens, 10 mg each were crushed and lysed in a buffer containing proteinase k and RNase A. DNA was extracted using QIAmp Mini Kit and bisulﬁte treatment was performed using EpiTect® Bisulﬁte Kit (QIAGEN). The Methylation-speciﬁc Real-time PCR was performed which is based on the continuous monitoring of a progressive ﬂuorogenic PCR by an optical system. Aberrant methylation was detected in, SHP, 28 (100%); APC, 22 (73.3%); CDH1, 17 (56%); DAPK 13 (46.4%); SFRP, 8 (28.5%); DLC1, 6 (21%); P16, 6 (21%); RAR-b2 6 (21%); GSTP1, 1 (3.5%); SOCs, 1 (3.5%); FHIT 0 (0%). High frequency of methylation at some of the above tumor suppressor genes suggests that the detection of these changes may help determining cancer susceptibility and early diagnosis. Additional studies are aimed to detect these changes in Circulating Tumor DNA and develop a panel of biomarkers for lung cancer early detection.
1184 An Eleven-gene Signature of Lung Biopsy Specimens for Cancer Diagnostic F. Khani1 , S.K. Bidoki1 , F. Rahbarizadeh2 , H. Jabari3 , A. Kiani4 , M. Hamedani5 , M. Sajadi5 , R. Sheikhnejad5 . 1 Payame Noor University, Molecular Biology, Tehran, Iran, 2 Tarbiat Modares University, School of Medicine, Tehran, Iran, 3 Shahid Beheshti University of Medical Sciences, Bronchoscopy Center Masih Daneshvari Hospital, Tehran, Iran, 4 Shahid Beheshti University of Medical Sciences, Pathology Department Masih Daneshvari Hospital, Tehran, Iran, 5 Toﬁgh Daru, Molecular Biology, Tehran, Iran Background: Lung cancer is the leading cause of cancer deaths in the world because most of them are diagnosed in late stages. Therefore reliable tools for the early detection of cancer and the identiﬁcation of speciﬁc molecular targets would help to develop personalized medicine. All cancers are considered genetic diseases caused by alterations in cancer-associated genes. The identiﬁcation of altered genes is critical for understanding the pathogenesis of cancer. In this study, we use an eleven gene signature test to examine lung biopsy specimens for diagnostic, prognostic and therapeutic purposes. Methods: Bronchoscopy was performed to collect 102 fresh specimens from 51 patients (two per case). Fifty one specimens were used for histological examination and 51 to determine gene expression signature. In addition, 32 frozen lung tumors and their adjacent normal tissues were examined along with biopsy specimens. Total RNA was isolated from each specimen and puriﬁed using RNeasy mini kit (Qiagen, Hilden, Germany) to generate cDNA using qRT-PCR analysis. Results: The results indicate that the expressions of 3 oncogenes bcl-2, k-ras and h-ras were signiﬁcantly high (p < 0.05) in surgically removed tumors as well as biopsy specimens compare to adjacent normal tissues. The differential expressions of these 3 genes were strikingly higher in cigarette using patients than nonsmokers. Conclusion: The gene expression proﬁling techniques using real-time qRTPCR is, efﬁcient, consistent and reliable to examine small biopsy specimens. Considering the overall results of this study, it can be concluded that, lung tissue abnormalities other than cancer could also cause the elevation of some oncogene expression. This study further veriﬁes that smoking can deﬁnitely cause oncogenic mutation, activation and/or ampliﬁcation; which is now a globally proven fact. Overall, our data show the feasibility of a relatively simple diagnostic test for lung biopsy specimens. 1185 Dietary Patterns and Postmenopausal Breast Cancer Survival − a Prospective Patient Cohort Study A. Vrieling1 , K. Buck1 , P. Seibold1 , J. Heinz2 , N. Obi2 , D. Flesch-Janys2 , J. Chang-Claude1 . 1 Deutsches Krebsforschungszentrum, Division of Cancer Epidemiology, Heidelberg, Germany, 2 University Cancer Center Hamburg and University Medical Center Hamburg-Eppendorf, Department of Cancer Epidemiology/Clinical Cancer Registry, Hamburg, Germany Introduction: Research on the association between dietary patterns and breast cancer survival is very limited. Materials and Methods: We assessed the association of pre-diagnostic dietary patterns with survival and recurrence in a prospective cohort study in Germany. Postmenopausal breast cancer patients were diagnosed between 2001 and 2005, and vital status, causes of death, and recurrences were veriﬁed through the end of 2009. Food frequency questionnaire data referring to the year before diagnosis were available for 2,522 patients, and principal component factor analysis was used to identify dietary patterns. Hazard ratios (HR) and 95% conﬁdence intervals (CI) were calculated with Cox proportional hazards models, stratiﬁed by age at diagnosis and study center and adjusted for relevant prognostic factors. Results: Two major dietary patterns were identiﬁed: ‘healthy’ [high intakes of vegetables, garlic/onions, oil and vinegar dressing, mayonnaise (primarily from salad dressings), and red meat] and ‘unhealthy’ [high intakes of red meat, processed meat, and deep-frying fat and low intake of fruits]. Increasing consumption of an ‘unhealthy’ dietary pattern was associated with a signiﬁcantly increased risk of overall mortality (highest versus lowest quartile: HR = 1.48, 95% CI: 1.05, 2.07) and non-breast cancer mortality (HR = 3.80, 95% CI: 1.83, 7.86). No associations with breast cancer-speciﬁc mortality (HR = 1.09, 95% CI: 0.73, 1.61) and breast cancer recurrence (HR = 1.18, 95% CI: 0.81, 1.71) were found. The ‘healthy’ dietary pattern was not associated with any of the outcomes. Conclusion: In conclusion, increasing intake of an ‘unhealthy’ dietary pattern may increase the risk of overall and non-breast cancer mortality.