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Abstract Background Although impacts upon gastric cancer incidence of race, age, sex, and Lauren type have been individually explored, neither their importance when evaluated together nor the presence or absence of interactions among them have not been fully described. Methods This study, derived from SEER (Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute) data, analyzed the incidences of gastric cancer between the years 1992–2001. There were 7882 patients who had developed gastric cancer. The total denominator population was 145,155, 669 persons (68,395,787 for 1992–1996, 78,759,882 for 1997–2001). Patients with multiple tumors were evaluated as per the default of the SEER*Stat program. 160 age-, five year period (1992–1996 vs 1997–2001)-, sex-, race (Asian vs non-Asian)-, Lauren type- specific incidences were derived to form the stratified sample evaluated by linear regression. (160 groups = 2 five year periods × 2 race groups × 2 sexes × 2 Lauren types × 10 age groups.) Linear regression was used to analyze the importance of each of these explanatory variables and to see if there were interactions among the explanatory variables. Results Race, sex, age group, and Lauren type were found to be important explanatory variables, as were interactions between Lauren type and each of the other important explanatory variables. In the final model, the contribution of each explanatory variable was highly statistically significant (t > 5, d.f. 151, P < 0.00001). The regression equation for Lauren type 1 had different coefficients for the explanatory variables Race, Sex, and Age, than did the regression equation for Lauren type 2. Conclusion The change of the incidence of stomach cancer with respect to age for Lauren type 1 stomach cancer differs from that for Lauren type 2 stomach cancers. The relationships between age and Lauren type do not differ across gender or race. The results support the notion that Lauren type 1 and Lauren type 2 gastric cancers have different etiologies and different patterns of progression from pre-cancer to cancer. The results should be validated by evaluation of other databases.

Abstract Background Human sperm protein 17 (Sp17) is a highly conserved protein that was originally isolated from a rabbit epididymal sperm membrane and testis membrane pellet. It has recently been included in the cancer/testis (CT) antigen family, and shown to be expressed in multiple myeloma and ovarian cancer. We investigated its immunolocalisation in specimens of nervous system (NS) malignancies, in order to establish its usefulness as a target for tumour-vaccine strategies. Methods The expression of Sp17 was assessed by means of a standardised immunohistochemical procedure [(mAb/antigen) MF1/Sp17] in formalin-fixed and paraffin embedded surgical specimens of NS malignancies, including 28 neuroectodermal primary tumours (6 astrocytomas, 16 glioblastoma multiforme, 5 oligodendrogliomas, and 1 ependymoma), 25 meningeal tumours, and five peripheral nerve sheath tumours (4 schwannomas, and 1 neurofibroma),. Results A number of neuroectodermal (21%) and meningeal tumours (4%) were found heterogeneously immunopositive for Sp17. None of the peripheral nerve sheath tumours was immunopositive for Sp17. The expression pattern was heterogeneous in all of the positive samples, and did not correlate with the degree of malignancy. Conclusion The frequency of expression and non-uniform cell distribution of Sp17 suggest that it cannot be used as a unique immunotherapeutic target in NS cancer. However, our results do show the immunolocalisation of Sp17 in a proportion of NS tumour cells, but not in their non-pathological counterparts. The emerging complex function of Sp17 makes further studies necessary to clarify the link between it and immunopositive cells.

Abstract Background Modeling the complex development and growth of tumor angiogenesis using mathematics and biological data is a burgeoning area of cancer research. Architectural complexity is the main feature of every anatomical system, including organs, tissues, cells and sub-cellular entities. The vascular system is a complex network whose geometrical characteristics cannot be properly defined using the principles of Euclidean geometry, which is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature. However, fractal geometry is a more powerful means of quantifying the spatial complexity of real objects. Methods This paper introduces the surface fractal dimension (Ds) as a numerical index of the two-dimensional (2-D) geometrical complexity of tumor vascular networks, and their behavior during computer-simulated changes in vessel density and distribution. Results We show that Ds significantly depends on the number of vessels and their pattern of distribution. This demonstrates that the quantitative evaluation of the 2-D geometrical complexity of tumor vascular systems can be useful not only to measure its complex architecture, but also to model its development and growth. Conclusions Studying the fractal properties of neovascularity induces reflections upon the real significance of the complex form of branched anatomical structures, in an attempt to define more appropriate methods of describing them quantitatively. This knowledge can be used to predict the aggressiveness of malignant tumors and design compounds that can halt the process of angiogenesis and influence tumor growth.