Research update and the end of the first year from Dr. Matthew Breen looking at prediction of prognosis and outcome for various forms of lymphoma.
This study involves the evaluation of a cohort of canine lymphoma specimens for the presence of tumor-associated abnormalities associated with four key cancer-associated genes. The presence of these abnormalities, alone and in combination, has been shown to be predictive of the response to standard treatment modalities in human lymphoma patients, and provides powerful opportunities to predict prognosis in newly diagnosed patients. We hypothesize that the same may apply in dogs.
Thus far we have screened the full cohort of canine lymphoma cases for abnormalities involving the first of these genes, and have scored approximately 75% of the cases for abnormalities involving the second of these genes. The reagents required for analysis of the remaining genes have been developed and validated on well-characterized control specimens, and will be used to screen the lymphoma cohort in the second year of this study.
On completion of these analyses the data for each gene in each case will be used to assess the frequency and distribution of abnormalities across the dog lymphoma cohort. This information will be used to identify whether there are recurrent patterns evident when comparing the data for each gene within and between cases that would suggest they are not random events. We will also integrate these data with the clinical outcome data for those cases for which this information is available. This will allow us to determine whether the pattern of abnormalities in these four genes can be used to assist with determining prognosis in prospective canine lymphoma cases. During the course of the study we are continuing to accumulate additional clinical data for a proportion of cases for which treatment outcome information was not available at the time the study was initiated. The availability of this additional information will enable us to maximize the statistical power of our study.