Role of germ line p53 mutations in aneuploidy and immortalization of dermal fibroblasts from Li-Fraumeni cancer patients

Pedigree analysis of certain families with a high incidence of tumors suggests a genetic predisposition to cancer. Li and Fraumeni described a familial cancer syndrome that is characterized by multiple primary tumors, early age of onset, and marked variation in tumor type. Williams and Strong (1) demonstrated that at least 7% of childhood soft tissue sarcoma patients had family histories that is readily explained by a highly penetrant autosomal dominant gene. To characterize the mechanism for genetic predisposition to many tumor types in these families, we have studied genetic alterations in fibroblasts, a target tissue from patients with the Li-Fraumeni Syndrome (LFS).^ We have observed spontaneous changes in initially normal dermal fibroblasts from LFS patients as they are cultured in vitro. The cells acquire an altered morphology, chromosomal anomalies, and anchorage-independent growth. This aberrant behavior of fibroblasts from LFS patients had never been observed in fibroblasts from normal donors. In addition to these phenotypic alterations, patient fibroblasts spontaneously immortalize by 50 population doublings (pd) in culture; unlike controls that remain normal and senesce by 30-35 (2). At 50 pd, immortal fibroblasts from two patients were found to be susceptible to tumorigenic transformation by an activated T24 H-ras oncogene (3). Approximately 80% of the oncogene expressing transfectants were capable of forming tumors in nude mice within 2-3 weeks. p53 has been previously associated with immortalization of cells in culture and cooperation with ras in transfection assays. Therefore, patients' fibroblast and lymphocyte derived DNA was tested for point mutations in p53. It was shown that LFS patients inherited certain point mutations in one of the two p53 alleles (4). Further studies on the above LFS immortal fibroblasts have demonstrated loss of the remaining p53 allele concomitant with escape from senescence. While the loss of the second allele correlates with immortalization it is not sufficient to transformation by an activated H-ras or N-ras oncogene. These immortal fibroblasts are resistant to tumorigenic transformation by v-abl, v-src, c-neu or v-mos oncogene; implying that additional steps are required in the tumorigenic progression of LFS patients' fibroblasts.^ References. (1) Williams et al., J. Natl. Cancer Inst. 79:1213, 1987. (2) Bischoff et al., Cancer Res. 50:7979, 1990. (3) Bischoff et al., Oncogene 6:183, 1991. (4) Malkin et al., Science 250:1233, 1990. ^

A full pedigree based method for the statistical assessment of genetic anticipation

Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^