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To identify molecular alterations implicated in the initiating steps of breast tumorogenesis, we compared the gene expression profiles of normal and ductal carcinoma in situ (DCIS) mammary epithelial cells by using serial analysis of gene expression (SAGE). Through the pair-wise comparison of normal and DCIS SAGE libraries, we identified several differentially expressed genes. Here, we report the characterization of one of these genes, HIN-1 (high in normal-1). HIN-1 expression is significantly down regulated in 94% of human breast carcinomas and in 95% of preinvasive lesions, such as ductal and lobular carcinoma in situ. This decrease in HIN-1 expression is accompanied by hypermethylation of its promoter in the majority of breast cancer cell lines (>90%) and primary tumors (74%). HIN-1 is a putative cytokine with no significant homology to known proteins. Reintroduction of HIN-1 into breast cancer cells inhibits cell growth. These results indicate that HIN-1 is a candidate tumor suppressor gene that is inactivated at high frequency in the earliest stages of breast tumorogenesis.

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho‐signaling in drug‐treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy. SYNOPSIS SigPath is a targeted, quantitative mass spectrometry assay that measures 284 phosphosites spanning 200 phosphoproteins with high throughput and quantitative precision across a broad swath of signaling biology of known interest. The value of the assay is demonstrated by application to drug‐treated cancer cell lines, breast cancer preclinical models and human medulloblastoma tumors. Large numbers of differentially regulated phosphosites newly associated with disease models and human tumors are identified. The results highlight the potential use of SigPath to nominate mechanistic hypotheses regarding oncogenesis, response and resistance to therapy. Graphical Abstract SigPath is a targeted, quantitative mass spectrometry assay that measures 284 phosphosites spanning 200 phosphoproteins with high throughput and quantitative precision across a broad swath of signaling biology of known interest.

Abstract Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug-treatment in cells and tissues but are presently lacking. Here we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response and resistance to therapy. Competing Interest Statement The authors have declared no competing interest. Footnotes * Lead Contact: HK hasmik{at}broadinstitute.org