The histologic appearances of ductal invasion were studied in 139 cases of prostatic adenocarcinoma diagnosed in the Department of Pathology, Howard University Hospital, during the period January 1980 through October 1983. Intraductal spread was found in almost half (48%) of the prostatic glands examined. Ductal spread was associated with the local extent (P < 0.001) rather than with the grade of the tumor (P c 0.01). Three distinct patterns of ductal penetration were recognized. The duct wall was completely destroyed in microinvasion. In foci of ductal permeation the integrity of the basement membrane was generally preserved, and the duct wall was infiltrated mainly by solitary tumor cells. When the tumor spread was by extension in continuity within the duct wall, the neoplastic cells appeared to grow between the preexisting epithelial layers. It was concluded that prostatic carcinoma cells have the ability to penetrate the wall of benign ducts and progressively replace the normal epithelial elements. In this process the general framework of the affected duct appears to be preserved.
Cancer is a complex disease that involves the accumulation of both genetic and epigenetic alterations of numerous genes. Data in the Genetic Alterations in Cancer database for gene mutations and allelic loss [loss of heterozygosity (LOH)] in human tumors (e.g. lung, oral, esophagus, stomach and colon/rectum) were reviewed. Results for the genes and pathways implicated in tumor development at these sites are presented. Mutation incidence, spectra and codon specificity are described for lung, larynx and oral tumors. LOH occurred more frequently than gene mutations in tumors from all sites examined. The cell cycle gene, TP53 (all sites), and cell signaling gene, APC (colorectal and gastric cancers), were the only genes with similar incidences of LOH and mutation. Alterations of one or more cell cycle and cell signaling genes were reported for tumors from each site. Site-specific activation was apparent in the cell signaling mitogen-activated protein kinase oncogenes (KRAS in lung, HRAS in oral cancers and BRAF in esophageal and colorectal cancers). Analysis of genetic changes in lung tumors showed that the incidence of mutations in the TP53 and KRAS genes and the incidence of LOH in the FHIT gene were significantly greater in smokers versus non-smokers (P < 0.01). In lung and oral cancers, the TP53 GC --> TA transversion frequency increased with tobacco smoke exposure (P < 0.05). Furthermore, the TP53 mutational hot spots for lung and laryngeal cancers from smokers included codons 157, 245 and 273, whereas for oral tumors included codons 280 and 281.
Abstract. Studies designed to understand species distributions and community assemblages typically use separate analytical approaches (e.g., logistic regression and ordination) to model the distribution of individual species and to relate community composition to environmental variation. Multilevel models (MLMs) offer a promising strategy for integrating species and community-level analyses. Here, we demonstrate how MLMs can be used to analyze differences in species composition of communities across environmental gradients. We first use simulated data to show that MLMs can outperform three standard methods that researchers use to identify environmental drivers of the species composition of communities, redundancy analysis (RDA), canonical correspondence analysis (CCA), and nonmetric multidimensional scaling (NMDS). In particular, MLMs can separate the effects of collinearity among environmental drivers and factor out the effect of changes in overall species abundances or occurrences that do not involve changes in composition. We then apply MLMs to presence/absence data for 14 species of understory herbs and topographic, biotic, and edaphic variables measured in 54 forested plots in the Southern Appalachian Mountains. In addition to providing information about community composition, MLMs simultaneously identify the responses of individual species to the environmental variables. Thus, MLMs not only have potentially superior statistical properties in analyses of community composition compared to standard methods, but they simultaneously provide detailed information about species-specific responses underlying the changes in community composition.
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