Characterization and subchromosomal location of a novel tumor suppressor gene on human chromosome 7

Alterations in oncogenes and tumor suppressor genes (TSGs) are considered to be critical steps in oncogenesis. Consistent deletions and loss of heterozygosity (LOH) of polymorphic markers in a determinate chromosomal fragment are known to be indicative of a closely mapping TSG. Deletion of the long arm of chromosome 7 (hchr 7) is a frequent trait in many kinds of human primary tumors. LOH was studied with an extensive set of markers on chromosome 7q in several types of human neoplasias (primary breast, prostate, colon, ovarian and head and neck carcinomas) to determine the location of a putative TSG. The extent of LOH varied depending the type of tumor studied but all the LOH curves we obtained had a peak at (C-A)$\sb{\rm n}$ microsatellite repeat D7S522 at 7q31.1 and showed a Gaussian distribution. The high incidence of LOH in all tumor types studied suggests that a TSG relevant to the development of epithelial cancers is present on the 7q31.1. To investigate whether the putative TSG is conserved in the syntenic mouse locus, we studied LOH of 30 markers along mouse chromosome 6 (mchr 6) in chemically induced squamous cell carcinomas (SCCs). Tumors were obtained from SENCAR and C57BL/6 x DBA/2 F1 females by a two-stage carcinogenesis protocol. The high incidence of LOH in the tumor types studied suggests that a TSG relevant to the development of epithelial cancers is present on mchr 6 A1. Since this segment is syntenic with the hchr 7q31, these data indicate that the putative TSG is conserved in both species. Functional evidence for the existence of a TSG in hchr 7 was obtained by microcell fusion transfer of a single hchr 7 into a murine SCC-derived cell line. Five out of seven hybrids had two to three-fold longer latency periods for in vivo tumorigenicity assays than parental cells. One of the unrepressed hybrids had a deletion in the introduced chromosome 7 involving q31.1-q31.3, confirming the LOH data. ^

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^