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Tumorigenesis involves a complex interplay between genetically modified cancer cells and their adjacent normal tissue, the stroma. We used an established breast cancer mouse model to investigate this inter-relationship. Conditional activation of Rho-associated protein kinase (ROCK) in a model of mammary tumorigenesis enhances tumor growth and progression by educating the stroma and enhancing the production and remodeling of the extracellular matrix. We used peptide matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to quantify the proteomic changes occurring within tumors and their stroma in their regular spatial context. Peptides were ranked according to their ability to discriminate between the two groups, using a receiver operating characteristic tool. Peptides were identified by liquid chromatography tandem mass spectrometry, and protein expression was validated by quantitative immunofluorescence using an independent set of tumor samples. We have identified and validated four key proteins upregulated in ROCK-activated mammary tumors relative to those expressing kinase-dead ROCK, namely, collagen I, α-SMA, Rab14, and tubulin-β4. Rab14 and tubulin-β4 are expressed within tumor cells, whereas collagen I is localized within the stroma. α-SMA is predominantly localized within the stroma but is also expressed at higher levels in the epithelia of ROCK-activated tumors. High expression of COL1A , the gene encoding the pro-α 1 chain of collagen, correlates with cancer progression in two human breast cancer genomic data sets, and high expression of COL1A and ACTA2 (the gene encoding α-SMA) are associated with a low survival probability ( COLIA , p = 0.00013; ACTA2 , p = 0.0076) in estrogen receptor-negative breast cancer patients. To investigate whether ROCK-activated tumor cells cause stromal cancer-associated fibroblasts (CAFs) to upregulate expression of collagen I and α-SMA, we treated CAFs with medium conditioned by primary mammary tumor cells in which ROCK had been activated. This led to abundant production of both proteins in CAFs, clearly highlighting the inter-relationship between tumor cells and CAFs and identifying CAFs as the potential source of high levels of collagen 1 and α-SMA and associated enhancement of tissue stiffness. Our research emphasizes the capacity of MALDI-MSI to quantitatively assess tumor-stroma inter-relationships and to identify potential prognostic factors for cancer progression in human patients, using sophisticated mouse cancer models.

Cytoskeletal proteins are essential building blocks of cells. More than 100 cytoskeletal and cytoskeleton-associated proteins are known and for some, their function and regulation are understood in great detail. Apart from cell shape and support, they facilitate many processes such as intracellular signaling and transport, and cancer related processes such as proliferation, migration, and invasion. During the last decade, comparative proteomic studies have identified cytoskeletal proteins as in vitro markers for tumor progression and metastasis. Here, these results are summarized and a number of unrelated studies are highlighted, identifying the same cytoskeletal proteins as potential biomarkers. These findings might indicate that the abundance of these potential markers of tumor progression is associated with the biological outcome and are independent of the cancer origin. This correlates well with recently published results from the Cancer Genome Atlas, indicating that cancers show remarkable similarities in their analyzed molecular information, independent of their organ of origin. It is postulated that the quantification of cytoskeletal proteins in healthy tissues, tumors, in adjacent tissues, and in stroma, is a great source of molecular information, which might not only be used to classify tumors, but more importantly to predict patients' outcome or even best treatment choices., (© 2019 The Authors. Proteomics published by Wiley-VCH Verlag GmbH & Co. KGaA.)

This review discusses the current status of proteomics technology in endometrial cancer diagnosis, treatment and prognosis. The first part of this review focuses on recently identified biomarkers for endometrial cancer, their importance in clinical use as well as the proteomic methods used in their discovery. The second part highlights some of the emerging mass spectrometry based proteomic technologies that promise to contribute to a better understanding of endometrial cancer by comparing the abundance of hundreds or thousands of proteins simultaneously., (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The timely detection of gastric cancer will contribute significantly towards effective treatment and is aided by the availability and reliability of appropriate biomarkers. A combination of several biomarkers can improve the sensitivity and specificity of cancer detection and this work reports results from a panel of 4 proteins. By combining a validated preclinical mouse model with a proteomic approach we have recently discovered novel biomarkers for the detection of gastric cancer. Here, we investigate the specificity of four of those biomarkers (afamin, clusterin, VDBP and haptoglobin) for the detection of gastric cancer using two independent methods of validation: ELISA, and a non antibody based method: Multiple Reaction Monitoring with High Resolution Mass Spectrometry (MRM-HR). All four biomarkers reliably differentiated GC from benign patient serum, and also in a small cohort of 11 early stage cases. We also present a novel isoform specific biomarker alpha-1-antitrypsin (A1AT) that was identified using a mouse model for gastric cancer. This isoform is distinct in charge and mobility in a pH gradient and was validated using human samples by isoelectric focussing and Western-blot (IEF-WB). This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge., (Copyright © 2014 Elsevier B.V. All rights reserved.)