S_mmmmary Nitric oxide (NO) is generated by a family of isoenzymes (NO synthases)

Using zymography and computer assisted image analysis, we have measured the levels of type IV collagenases in biopsies from normal breast, and benign and malignant breast disease. The 92 kDa form was present in three of 11 cases of normal/benign disease, three of nine grade I tumours, four of 12 grade II tumours, but 11 of 11 grade III tumours. Mean levels were higher in grade III tumours (P < 0.0001). When the levels of 72 kDa collagenase and its active 62 kDa form were considered together, there was no difference between the benign and malignant cases (P = 0.55), but the amount of active enzyme, considered as a proportion of the 62 + 72 kDa forms, was significantly higher in malignant disease (P = 0.003). There was also a trend towards a higher proportion of active enzyme with increasing tumour grade (P < 0.0001). In situ hybridisation and immunohistochemistry studies showed that that mRNA and protein for the 92 kDa enzyme was primarily found in the tumour stroma. mRNA for the 72 kDa enzyme was also found in stromal areas. This study demonstrates a clear relationship between production of Type IV collagenases and malignant breast disease. Inhibitors of these enzymes may be of value in preventing metastatic disease. Images Figure 1 Figure 2

Purpose Mutations in the mitochondrial enzyme succinate dehydrogenase (SDH) subunit genes are associated with a wide spectrum of tumours including phaeochromocytoma and paraganglioma (PPGL) 1, 2, gastrointestinal stromal tumours (GIST) 3, renal cell carcinoma (RCC) 4 and pituitary adenomas5. SDH-related tumorigenesis is believed to be secondary to accumulation of the oncometabolite succinate. Our aim was to investigate the potential clinical applications of MRI spectroscopy (1H-MRS) in a range of suspected SDH-related tumours. Patients and methods Fifteen patients were recruited to this study. Respiratory-gated single-voxel 1H-MRS was performed at 3T to quantify the content of succinate at 2.4 ppm and choline at 3.22 ppm. Results A succinate peak was seen in six patients, all of whom had a germline SDHx mutation or loss of SDHB by immunohistochemistry. A succinate peak was also detected in two patients with a metastatic wild-type GIST (wtGIST) and no detectable germline SDHx mutation but a somatic epimutation in SDHC. Three patients without a tumour succinate peak retained SDHB expression, consistent with SDH functionality. In six cases with a borderline or absent peak, technical difficulties such as motion artefact rendered 1H-MRS difficult to interpret. Sequential imaging in a patient with a metastatic abdominal paraganglioma demonstrated loss of the succinate peak after four cycles of [177Lu]-DOTATATE, with a corresponding biochemical response in normetanephrine. Conclusions This study has demonstrated the translation into clinical practice of in vivo metabolomic analysis using 1H-MRS in patients with SDH-deficient tumours. Potential applications include non-invasive diagnosis and disease stratification, as well as monitoring of tumour response to targeted treatments.

KCNJ5 mutations are common in APA, particularly those arising from ZF. The long-recognized heterogeneity among APA may have a genetic basis.

The histopathologic classification of breast cancer stratifies tumors based on tumor grade, stage, and type. Despite an overall correlation with survival, this classification is poorly predictive and tumors with identical grade and stage can have markedly contrasting outcomes. Recently, breast carcinomas have been classified by their gene expression profiles on frozen material. The validation of such a classification on formalin-fixed paraffin-embedded tumor archives linked to clinical information in a high-throughput fashion would have a major impact on clinical practice. The authors tested the ability of tumor tissue microarrays (TMAs) to sub-classify breast cancers using a TMA containing 107 breast cancers. The pattern of expression of 13 different protein biomarkers was assessed by immunohistochemistry and the multidimensional data was analyzed using an unsupervised two-dimensional clustering algorithm. This revealed distinct tumor clusters which divided into two main groups correlating with tumor grade (P<0.001) and nodal status (P = 0.04). None of the protein biomarkers tested could individually identify these groups. The biological significance of this classification is supported by its similarity with one derived from gene expression microarray analysis. Thus, molecular profiling of breast cancer using a limited number of protein biomarkers in TMAs can sub-classify tumors into clinically and biologically relevant subgroups.