Abstract
Our understanding of breast cancer heterogeneity at the protein level is limited despite proteins being the ultimate effectors of cellular functions. We investigated the heterogeneity of breast cancer (41 primary tumors and 15 breast cancer cell lines) at the protein and phosphoprotein levels to identify activated oncogenic pathways and developing targeted therapeutic strategies. Heterogeneity was observed not only across histological subtypes, but also within subtypes. Tumors of the Triple negative breast cancer (TNBC) subtype distributed across four different clusters where one cluster (cluster ii) showed high deregulation of many proteins and phosphoproteins. The majority of TNBC cell lines, particularly mesenchymal lines, resembled the cluster ii TNBC tumors. Indeed, TNBC cell lines were more sensitive than non-TNBC cell lines when treated with targeted inhibitors selected based on upregulated pathways in cluster ii. In line with the enrichment of the upregulated pathways with onco-clients of Hsp90, we found synergy in combining Hsp90 inhibitors with several kinase inhibitors, particularly Erk5 inhibitors. The combination of Erk5 and Hsp90 inhibitors was effective in vitro and in vivo against TNBC leading to upregulation of pro-apoptotic effectors. Our studies contribute to proteomic profiling and improve our understanding of TNBC heterogeneity to provide therapeutic opportunities for this disease.
Highlights
Gene expression profiling has contributed significantly to our understanding of breast cancer heterogeneity, biology and prognosis
We focused on triple negative breast cancer (TNBC); a subtype associated with poor prognosis, and found that a subgroup in Triple negative breast cancer (TNBC)
TNBC is heterogeneous at the proteomic level where one subgroup of TNBC showed a wide spectrum of activated oncogenic signaling pathways in comparison to other TNBC tumors as well as non-TNBC subtypes
Summary
Gene expression profiling has contributed significantly to our understanding of breast cancer heterogeneity, biology and prognosis. RPPA in microdissected breast tumors recognized the classification of breast cancer to subgroups according to protein and phosphoprotein level [4]. Hennessy et al [5] demonstrated that RPPA can classify breast tumors to the same subtypes deduced from transcriptome profiling. Due to the complex nature of this approach, limited studies use MS to investigate the heterogeneity of breast cancer [13, 14]. These two studies, using cell lines, again revealed that the proteome fingerprint classify breast cancer to subtypes similar to transcriptome classification
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