title: Grading breast cancer tissues using molecular portraits.
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.
authors: Department of Immunotechnology and CREATE HEALTH, Lund University, Medicon Village, SE-223 81 Lund, Sweden;
authors: Niclas
authors: N
authors: Olsson
authors: Petter
authors: P
authors: Carlsson
authors: Peter
authors: P
authors: James
authors: Karin
authors: K
authors: Hansson
authors: Sofia
authors: S
authors: Waldemarson
authors: Per
authors: P
authors: Malmström
authors: Mårten
authors: M
authors: Fernö
authors: Lisa
authors: L
authors: Ryden
authors: Christer
authors: C
authors: Wingren
authors: Carl A K
authors: CA
authors: Borrebaeck
mesh_terms: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000401:mortality / Q000473:pathology*; D002277:Carcinoma / Q000175:diagnosis / Q000235:genetics* / Q000401:mortality / Q000473:pathology*; D018450:Disease Progression; D018572:Disease-Free Survival; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008875:Middle Aged; D060787:Neoplasm Grading; D011379:Prognosis; D040901:Proteomics / Q000379:methods / Q000706:statistics & numerical data; D059467:Transcriptome; D059016:Tumor Microenvironment / Q000235:genetics
chemical_list: D014408:Biomarkers, Tumor
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