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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.