Improved Early Diagnosis in Female Pelvic Cancer With OC Detect

The goal of this observational study is to learn if so called Volatile Organic Compounds (VOCs) in blood can be used for early diagnosis of ovarian cancer. The main question it aims to answer is: Can OC Detect, a new in vitro diagnostic instrument, distinguish between VOC patterns in blood plasma from women with ovarian cancer (especially in early stage) and VOC patterns in helthy women? Participants are previosuly diagnosed patients with ovarian cancer, who agreed to store their blood samples in biobanks for future medical research purposes. Healthy female blood donors serve as benign control blood samples.

Pelvic Endometrial and Ovarian cancer (ovarian-/tubal-/peritoneal cancer) is the sixth and seventh most frequent type of cancer and ovarian cancer the fourth leading cause of cancer related death among Swedish women. Endometrial cancer gives mostly early symptoms but two thirds of patients with ovarian cancer are diagnosed with advanced stage of the disease, and this is reflected in poor outcome. Early diagnosis is challenging especially in ovarian cancer. Plasma protein biomarker panels with improved diagnostic performance and predicting survival in patients with ovarian tumors have been performed by several research groups. The sensitivity is good, but specificity is today not good enough for screening purposes. Several blood-based protein biomarker candidates for endometrial cancer detection have been reported but the protein biomarkers have so far only clinical relevance in advanced or recurrent endometrial cancers. However, there is a need for improved more specific broader biomarker panels for discrimination between localized or metastatic disease and preoperative risk stratification especially in endometrial cancer patients. Such improved biomarker panels would be able to predict metastatic disease and guide adjuvant chemotherapy treatment. Endogenous volatile organic compounds (VOCs) are products of metabolic activity in the body and changes to these VOCs can be characteristic of specific disease processes such as cancer development. Analyses in plasma of VOCs such as triethylamine, pyridine, toluene, etc. with Field-Effect-Transistor (FET) -based gas sensors have shown to be able to measure VOCs very accurately in low concentrations (Bastuck thesis, 2009). The metabolism in cancer cells vastly differs from that of healthy cells. Elevated glycolysis leads to increases in lactate and fumarate metabolites resulting in altered VOC abundances in exhaled breath. Experimental data indicate that the detection of VOCs released by various cancer cells may be useful in early diagnoses of cancer. In patients with ovarian cancer, analyzes of specific VOC: s in blood has shown promising results to discriminate patient with ovarian cancer from healthy women (Horvath). The investigators have very recently in 37 patients out 38 with ovarian cancer found VOC indicating cancer which indicates a preliminary sensitivity of 97 %. In the total material of 68 analyzed samples, 3 false positive results were found which indicates a specificity of 90 %. In a population with 1 % malignancy the positive predictive value would be almost 10 % and negative predictive value 99.9 %. In the current study, samples from more ovarian cancer patients will be included, and also samples from patients with other cancer types (totally 245 patients, of which 50 ovarian cancers). The aim will be to see if good sensitivity and specificity can be achived with larger patient population (same or better values than in the previous study). Special focus will be put on early stages of ovarian cancer, as well as borderline tumours. The investigators aim also to see how distinct is VOC pattern for ovarian cancer compared to the VOC patterns for the other cancer forms. Finally, the study will give preliminary answer if VOC patterns for the other types of cancer (i.e., breast, colorectal, bladder, endometrie, cervix, ...) is specific so it could be used in the future for development of dedicated diagnostic tools for those diseases.