Biomedical subjects
Martin J Page
Publications and source records attributed to Martin J Page.
Hyaluronidase gene profiling and role of hyal-1 overexpression in an orthotopic model of prostate cancer.
The mRNA levels of hyal-1, hyal-2, LUCA3 and PH20, the 4 hyaluronidases with demonstrated endoglucosaminidase activity, were extensively profiled in normal and tumor tissues and cell lines, using dot blot analysis and quantitative PCR. In normal tissues, hyal-1, hyal-2 and LUCA3 all showed unique patterns of mRNA expression, but were generally of widespread distribution, whereas PH20 mRNA was restricted to testes. In a small set of breast tumor samples, no elevations in hyal-1, hyal-2 or LUCA3 mRNA were seen. Hyaluronidase activity measured by a novel assay or zymography was also not elevated in sera from a number of breast cancer patients, compared to sera from normal volunteers. In ex vivo xenograft tumor cell lines, however, hyal-1 or hyal-2 mRNA levels were frequently elevated, whereas LUCA3 was only infrequently elevated and PH20 not at all. Two cell lines were engineered to overexpress hyal-1: a breast cancer line (CAL51) and a prostate cancer line (PC3M). Although the in vitro properties of the hyal-1 overexpressing cell lines were indistinguishable from the parental cells, the orthotopic growth of hyal-1 expressing PC3M cells in nu/nu mice resulted in significantly increased numbers of metastases, supportive of a role for hyal-1 in extravasation and metastatic tumor formation in this model of prostate cancer.
Cluster analysis of an extensive human breast cancer cell line protein expression map database.
In the current study, the protein expression maps (PEMs) of 26 breast cancer cell lines and three cell lines derived from normal breast or benign disease tissue were visualised by high resolution two-dimensional gel electrophoresis. Analysis of this data was performed with ChiClust and ChiMap, two analytical bioinformatics tools that are described here. These tools are designed to facilitate recognition of specific patterns shared by two or more (a series) PEMs. Both tools use PEMs that were matched by an image analysis program and locally written programs to create a match table that is saved in an object relational database. The ChiClust tool uses clustering and subclustering methods to extract statistically significant protein expression patterns from a large series of PEMs. The ChiMap tool calculates a differential value (either as percentage change or a fold change) and represents these graphically. All such differentials or just those identified using ChiClust can be submitted to ChiMap. These methods are not dependent on any particular commercial image analysis program, and the whole software package gives an integrated procedure for the comparison and analysis of a series of PEMs. The ChiClust tool was used here to order the breast cell lines into groups according to biological characteristics including morphology in vitro and tumour forming ability in vivo. ChiMap was then used to highlight eight major protein feature-changes detected between breast cancer cell lines that either do or do not proliferate in nude mice. Mass spectrometry was used to identify the proteins. The possible role of these proteins in cancer is discussed.