I don't think that you can. A ROC curve assumes that you have a binary classifier (the "ground truth" or "gold standard") and a predictor for each subject. If you don't have the binary classifier then you cannot form the ROC curve at all.
You should look at your study and see if you can use a modified classifier. For instance, I was doing an ROC analysis once for a test in the medical field. On some subjects we had pathology as our classifier, but on others we used clinical follow-up. I.e. if the suspected disease had not progressed at the 12 mo follow-up then we called it "negative" even though, in principle, they could have had very very slowly progressing disease.