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GENE EXPRESSION PROFILES PREDICT SENSITIVITY OF PROSTATE CANCER TO RADIOTHERAPY Inventors: Prof. Avi Orr-Urtreger, Anat Bar-Shira4 , 4 Genetic Institute, Tel Aviv Sourasky Medical Center, Tel-Aviv University, Tel-Aviv, Israel Prof. Zelig Eshhar Dr. Lilach Agemy1, Itai Kela1, , Eytan Domany, Department of Immunology and Physics of Complex Systems, Weizmann Institute of Science Rehovot Background: Prostatic adenocarcinoma is the most common malignancy in males in the western world. Radiation therapy is one of the principle treatments for localized disease. Modern conformal radiotherapy delivers high doses to the prostate, nevertheless a significant proportion (10-40%) of tumors recur after radiotherapy. The lack of a predictive test to determine the sensitivity of the individual tumor to radiotherapy results in administration of excessive irradiation to some patients, and inadequate or ineffective treatment to others. Using gene-array analysis of human prostate cancer xenografts that differ in their response to irradiation in SCID mice, we identified a number of genes whose expression level distinguishes between radiation resistant and sensitive phenotypes. Selected genes from this list may serve at diagnosis, to predict not only which patient will benefit from irradiation and who should resort to other treatments, but also to offer a measure to adapt radiation dose to tumor radio sensitivity. Results: Gene clusters that differentiate resistant and sensitive phenotypes were identified using statistical and clustering methods. Two gene clusters showed higher and two others - lower expression levels in radioresistant xenografts. Expression levels of 113 genes differed at least 3-fold between sensitive and resistant xenografts. The data predicted the radiosensitivity of cultured PC cell lines (whose response to irradiation was unknown and tested later). The combined data have served to create a shorter list of genes with predictive potential. Interestingly, irradiation did not induce changes in gene expression of PC xenografts that survived it and recur. Conclusions: The expression levels of the indicated genes (or part thereof) may predict at the time of biopsy the expected response of an individual PC to radiotherapy. The data strongly support a model of radiosensitivity, of PC drawn from a single homogeneous population, rather that from a given tumor being comprised of a mixture of radioresistant and radiosensitive cell subpopulations.