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    Is chromosomal radiosensitivity a predictive tool for cancer risks?
    (Parlar Scientific Publications, 2021) Kolusayın Ozar, Melek Özlem; Orta, Tuncay; Dizdar, Yavuz; Kaytan Sağlam, Esra; Sağlam, Sezer; Turna, Akif; Okutan, Murat; Demirci, Sibel; Ozar, Engin; Daştan, Kadir; Yükseloğlu, Emel Hülya
    There is an extensive landscape of genomic disruptions caused by environmental carcinogens. A major environmental mutagen that can trigger direct changes in the DNA is radiation. In certain places, ionizing radiation such as X-rays can break DNA sequences leading to chromosome rearrangements. Prediction of cancer risk is an important phenomenon in the early diagnosis of cancer. Early diagnosis will lead to the most economical treatment protocols, thus decreasing the mortality and morbidity rates. Chromosome aberrations and radiosensitivity have been shown to be biological indicators of cancer predisposition. Four different types of cancers [breast, lung, prostate and colon] were examined in this study to see the indicator role of chromosome radio sensitivity in predicting cancer. We measured chromosome aberrations before and after giving 2 Gy radiation in peripheral blood lymphocyte samples of four cancer groups each consisted of 30 newly diagnosed patients and their matched healthy individuals summed up to total of 180 individual donors. Acentric, dicentric and ring chromosome aberrations were scored before and after irradiation for each donor. Absolute chromosome frequencies were calculated by subtracting spontaneous frequencies from 2 Gy irradiated values. Dicentrics as being primer indicator of radiation and total chromosome aberrations were evaluated for each group to predict effectiveness of chromosomal radiosensitivity. Our results show that the chromosomal radiosensitivity might predict cancer risk for prostate and lung cancer patient groups, but not for breast and colon cancer; however, whole total aberrations without any idea of cancer type; chromosomal radiosensitivity might enlighten the possibility of predicting cancer risk.