Abstract
Tumor progression and prognosis in breast cancer patients are difficult to assess using current clinical and laboratory parameters, where a pathological grading is indicative of tumor aggressiveness. This grading is based on assessments of nuclear grade, tubule formation, and mitotic rate. We report here the first protein signatures associated with histological grades of breast cancer, determined using a novel affinity proteomics approach. We profiled 52 breast cancer tissue samples by combining nine antibodies and label-free LC-MS/MS, which generated detailed quantified proteomic maps representing 1,388 proteins. The results showed that we could define in-depth molecular portraits of histologically graded breast cancer tumors. Consequently, a 49-plex candidate tissue protein signature was defined that discriminated between histological grades 1, 2, and 3 of breast cancer tumors with high accuracy. Highly biologically relevant proteins were identified, and the differentially expressed proteins indicated further support for the current hypothesis regarding remodeling of the tumor microenvironment during tumor progression. The protein signature was corroborated using meta-analysis of transcriptional profiling data from an independent patient cohort. In addition, the potential for using the markers to estimate the likelihood of long-term metastasis-free survival was also indicated. Taken together, these molecular portraits could pave the way for improved classification and prognostication of breast cancer.
Highlights
Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among women, accounting for 23% of the total cancer cases and 14% of cancer-related
We set out to design an improved grading analysis based on protein expression portraits reflecting each grade, and to identify trends in expression patterns associated with disease aggressiveness
Information on pathways regulated in association with tumor grade has the potential to provide insight into the mechanisms underlying tumor progression, as well as an improved understanding of the features of histological grade that influence prognosis
Summary
Clinical Samples—This study was approved by the regional ethics review board at Lund University, Sweden. Fifty-two breast cancer patients (stages I and II) were recruited from the Department of Oncology (Skane University Hospital, Lund, Sweden). Full clinical records were accessible for 50 of the reevaluated tissue samples, including tumor size, steroid receptor status, and lymph node involvement (Table I and supplemental Table S1). The samples were subdivided via careful pathologic evaluation at the Department of Pathology (Skane University Hospital) based on Nottingham histological grades 1 (n ϭ 9), 2 (n ϭ 17), and 3 (n ϭ 24). Forty-six of the specimens had a defined HER2 status, and all HER2-positive tumors (10%) were grade 3 tumors (Table I and supplemental Table S1). 41 of the tumors had a defined Ki67 status, and 17 of the samples were defined as Ki67positive (supplemental Table S1). Tissue pieces (about 50 mg/ sample) were homogenized in Teflon containers, pre-cooled in liquid
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