Title: Immune Cells as Predictors for Early Diagnosis and Chemotherapy Toxicity in Ovarian Cancer.
Dietmar PILS (Austria) Medical University of Vienna, Department of Obstetrics and Gynaecology, Vienna
Michele PEIRETTI (Italy) European Institute of Oncology, Division of Gynecologic Oncology Unit of Preventive Gynecology, Milan
Jalid SEHOULI (Germany) Charité - Universitätsmedizin Berlin, Gynecological Department, Berlin
One of the most deadly malignant diseases in women is epithelial ovarian cancer, mainly due to late and unspecific symptoms resulting in late diagnosis. Biomarkers for early detection of this malignancy, especially in women with unspecific symptoms, women with suspicious adnexal masses, and women at high-risk (e.g. BRCA1 and BRCA2 mutation carriers) would help to increase survival and reduce costs in health care systems. During this project a combined multimarker panel, comprised of 13 gene expression values combined with a six cancer protein panel will be validated in cancer patients, high-risk women, and controls. The gene expression values will be derived from a specific immune cell fraction and the protein abundances from blood plasma. A predictive model obtained from training cohorts showed a cross validated sensitivity of 97.8% at a set specificity of 99.6%. In addition, a seven gene signature for prediction of chemotherapy toxicity which leads–in rare cases–to fatal side effects, will be statistically validated and assessed for clinical utility. Three partners, i) the Medical University of Vienna, Austria, serving as coordinator, ii) the Charité Medical University Berlin, Germany, and iii) the European Institute of Oncology in Milan, Italy, will provide approx. 3,100 samples from 1,600 women, evenly distributed over all three centres. Aim of this project is the positive validation of both signatures, the first for usage in early diagnosis of ovarian cancer and the second for prediction of chemotherapy toxicity, promising a more personalized approach for chemotherapy.
During this project two blood based gene expression signatures were validated, one (13 blood gene expressions) for the improvement of a known blood protein based test to earlier detect ovarian cancer and another (seven blood gene expressions) to prognosticate cases of early death (i.e. death within two years after diagnosis), thought to be associated with problems with chemotherapy. More than 1,000 blood samples of patients with (early) ovarian cancer, breast cancer, with benign gynecologic diseases, and diseases with systemic inflammation, and of healthy women were collected and 599 thereof analysed. Unfortunately, the 13 gene expressions, measured from blood, thought to improve a blood protein based test for ovarian cancer, failed to improve this test. The gene expressions were indeed significantly associated with (early cases of) ovarian cancer, but also with breast cancer and diseases with systemic inflammation, but this association was less stable in the validation cohort, compared to the protein alone test. Therefore, the 13 gene expressions could not improve the test characteristics (specificity and sensitivity) of the protein alone test, which is on its own also not suitable as early detection test for ovarian cancer. The test would yield too much false positives (i.e. healthy individuals, but tested as positive) and also too much false negatives (i.e. ovarian cancer patients not tested positive).
Interestingly, the seven blood based gene expressions, measured from a specific fraction of white blood cells (i.e. immune cells), indicative for rare cases of early death events from ovarian cancer (death within two years after diagnosis) in the training cohort, was also significantly associated to rare early death events in the validation cohort. Therefore, the validation was positive. Our hypothesis that these events and the signature are associated to problems with chemotherapy seems to be wrong, as the signature was not associated to non-lethal side-effects of the chemotherapy (indicated by deferred or changed scheme of chemotherapy cycles). We assume that the signature indicates the global health status of patients, already compromised by the malignant disease or other diseases. Single genes of this signature lets suggest that the signature indicates the activation status of the innate immune system. Unfortunately, the test characteristics (specificity and sensitivity) of this signature are not good enough to use the test for clinical prognostication. The results are more of scientific interest than of clinical relevance.
(Project funded under JTC 2011)