Expression of ADAMTS1 in endothelial cells is induced by shear stress and suppressed in sprouting capillaries

ADAMTS1 inhibits capillary sprouting, and since capillary sprouts do not experience the shear stress caused by blood flow, this study undertook to clarify the relationship between shear stress and ADAMTS1. It was found that endothelial cells exposed to shear stress displayed a strong upregulation of ADAMTS1, dependent upon both the magnitude and duration of their exposure. Investigation of the underlying pathways demonstrated involvement of phospholipase C, phosphoinositide 3-kinase, and nitric oxide. Forkhead box protein O1 was identified as a likely inhibitor of the system, as its knockdown was followed by a slight increase in ADAMTS1 expression. In silico prediction displayed a transcriptional binding site for Forkhead box protein O1 in the promotor region of the ADAMTS1 gene, as well as sites for nuclear factor 1, SP1, and AP-1. The anti-angiogenic effects of ADAMTS1 were attributed to its cleavage of thrombospondin 1 into a 70-kDa fragment, and a significant enhancement of this fragment was indeed demonstrated by immunoblotting shear stress-treated cells. Accordingly, scratch wound closure displayed a slowdown in conditioned medium from shear stress-treated endothelial cells, an effect that could be completely blocked by a knockdown of thrombospondin 1 and partially blocked by a knockdown of ADAMTS1. Non-perfused capillary sprouts in rat mesenteries stained negative for ADAMTS1, while vessels in the microcirculation that had already experienced blood flow yielded the opposite results. The shear stress-dependent expression of ADAMTS1 in vitro was therefore also demonstrated in vivo and thereby confirmed as a mechanism connecting blood flow with the regulation of angiogenesis.

High HSP27 and HSP70 expression levels are independent adverse prognostic factors in primary resected colon cancer

The expression of Heat Shock Proteins (HSPs) is increased in various cancers and has been shown to correlate with biological tumor behaviour. This study aimed to investigate the impact of HSP70, HSP60 and HSP27 expression in colon cancer.

Tissue-based proteomics reveals FXYD3, S100A11 and GSTM3 as novel markers for regional lymph node metastasis in colon cancer

Regional lymph node metastasis negatively affects prognosis in colon cancer patients. The molecular processes leading to regional lymph node metastasis are only partially understood and proteomic markers for metastasis are still scarce. Therefore, a tissue-based proteomic approach was undertaken for identifying proteins associated with regional lymph node metastasis. Two complementary tissue-based proteomic methods have been employed. MALDI imaging was used for identifying small proteins (≤25 kDa) in situ and label-free quantitative proteomics was used for identifying larger proteins. A tissue cohort comprising primary colon tumours without metastasis (UICC II, pN0, n = 21) and with lymph node metastasis (UICC III, pN2, n = 33) was analysed. Subsequent validation of identified proteins was done by immunohistochemical staining on an independent tissue cohort consisting of primary colon tumour specimens (n = 168). MALDI imaging yielded ten discriminating m/z species, and label-free quantitative proteomics 28 proteins. Two MALDI imaging-derived candidate proteins (FXYD3 and S100A11) and one from the label-free quantitative proteomics (GSTM3) were validated on the independent tissue cohort. All three markers correlated significantly with regional lymph node metastasis: FXYD3 (p = 0.0110), S100A11 (p = 0.0071), and GSTM3 (p = 0.0173). FXYD3 and S100A11 were more highly expressed in UICC II patient tumour tissues. GSTM3 was more highly expressed in UICC III patient tumour tissues. By our tissue-based proteomic approach, we could identify a large panel of proteins which are associated with regional lymph node metastasis and which have not been described so far. Here we show that novel markers for regional lymph metastasis can be identified by MALDI imaging or label-free quantitative proteomics and subsequently validated on an independent tissue cohort. Copyright © 2012 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging

In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.

Development and application of a real-time TaqMan((R)) qPCR assay for detection and quantification of 'Candidatus Mycoplasma haemolamae' in South American camelids

Two alpacas from a herd in southwest Switzerland died for unknown reasons. Necropsy revealed chronic weight loss and pale mucous membranes. Infection with hemotropic mycoplasmas was suspected and subsequently confirmed by molecular methods. In order to investigate the epidemiological situation in this herd, a real-time TaqMan((R)) qPCR assay for the specific detection and quantification of hemoplasma infection in South American camelids was developed. This assay was based on the 16S rRNA gene and amplified 'Candidatus Mycoplasma haemolamae' DNA, but not DNA from other hemoplasmas or non-hemotropic mycoplasma species. The lower detection limit was one copy/PCR, and the amplification efficiency was 97.4%. In 11 out of 24 clinically healthy herd mates of the two infected alpacas, 'Candidatus M. haemolamae' infection was confirmed. No correlation was found between bacterial load and clinical signs or anemia. The assay described herein enables to detect and quantify 'Candidatus M. haemolamae' and may be used in future studies to investigate the prevalence, pathogenesis and treatment follow-up of hemoplasma infections in South American camelids.