The rigorous testing of hypotheses on suitable sample cohorts is a major limitation in translational research. This is particularly the case for the validation of protein biomarkers where the lack of accurate, reproducible and sensitive assays for most proteins has precluded the systematic assessment of hundreds of potential marker proteins described in the literature. Here, we describe a high throughput method for the development and refinement of selected reaction monitoring (SRM) assays for human proteins. The method was applied to generate such assays for more than 1000 cancer-associated proteins, which are functionally related to candidate cancer driver mutations. We used the assays to determine the detectability of the target proteins in two clinically relevant samples, plasma and urine. 182 proteins were detected in depleted plasma, spanning five orders of magnitude in abundance and reaching below a concentration of 10 ng/mL. The narrower concentration range of proteins in urine allowed the detection of 408 proteins. Moreover, we demonstrate that these SRM assays allow the reproducible quantification of 34 biomarker candidates across 84 patient plasma samples. Through public access to the entire assay library, which will also be expandable in the future, researchers will be able to target their cancer-associated proteins of interest in any sample type using the detectability information in plasma and urine as a guide. The generated reference map of SRM assays for cancer-associated proteins is a valuable resource for accelerating and planning biomarker verification studies.

A large proportion of women with lymph node negative breast cancer do not benefit from chemotherapy. Proliferation markers have been shown to recognize patients at high risk for recurrence. The Ki67 protein has recently been included in the St Gallen guidelines. The authors investigated the prognostic importance of cyclin B1 in node negative breast cancer and included a study of reproducibility. In a population-based case-control study, 190 women who died from breast cancer were defined as cases and 190 women alive at the time for the corresponding case's death were defined as controls. Inclusion criteria were tumor size

Introduction Some patients with breast cancer develop local recurrence after breast-conservation surgery despite postoperative radiotherapy, whereas others remain free of local recurrence even in the absence of radiotherapy. As clinical parameters are insufficient for identifying these two groups of patients, we investigated whether gene expression profiling would add further information.

A large proportion of breast cancer patients are treated with adjuvant chemotherapy after the primary operation, but some will recur in spite of this treatment. In order to achieve an improved and more individualized therapy, our knowledge in mechanisms for drug resistance needs to be increased. We have investigated to what extent cDNA microarray measurements could distinguish the likelihood of recurrences after adjuvant CMF (cyclophosphamide, methotrexate and 5-fluorouracil) treatment of premenopausal, lymph node positive breast cancer patients, and have also compared with the corresponding performance using conventional clinical variables.We tried several gene selection strategies, and built classifiers using the resulting gene lists.