Deriving evolutionary tree models of the oncogenesis of endometrial adenocarcinoma

Abstract

Endometrial adenocarcinoma (EAC) is the fourth leading cause of cancer death in women worldwide, but not much is known about the underlying genetic factors involved in the development of this complex disease. In the present work, we used 3 different algorithms to derive tree models of EAC oncogenesis from data on the frequencies of genomic alterations in rat chromosome 10 (RNO10). The tumor material was derived from progenies of crosses between the EAC susceptible BDII inbred rat strain and two non susceptible inbred rat strains. Data from allelic imbalance scans of RNO10 with microsatellite markers on solid tumor material and corresponding tissue cultures were used. For the analysis, RNO10 was divided into 24 segments containing a total of 59 informative microsatellite markers. The derived tree models show that genomic alterations have occurred in 11 of the 24 segments. In addition, the models provide information about the likely order of the alterations as well as their relationship with each other. Interestingly, there was a high degree of consistency among the different tree models and with the results of previous studies, which supports the reliability of the tree models. Our results may be extended into a general approach for tree modeling of whole genome alterations during oncogenesis. ' 2006 Wiley-Liss, Inc.Key words: oncogenesis; microsatellite markers; endometrial adenocarcinoma; tree model; allelic imbalance Carcinogenesis is a multi-step process, which develops through the accumulation of multiple genetic mutations. 1,2 In a normal cell, the first mutation usually results in limited expansion of a clone. One of the descendants of the clone acquires a second mutation, resulting in further loss of growth control, and each successive mutation provides a further growth advantage. Once a set of critical genetic alterations develops, the cancer cell proliferates in an uncontrolled manner and the progeny starts to accumulate seemingly random alterations. 3 Eventually, the developing tumor will become malignant, invade the surrounding normal tissue and metastasize to other tissues and organs. 4,5 The total number of mutations that are present in a tumor cell population is estimated to be as many as 10,000. 6 However, the pivotal mutations that make transformation of a single normal cell into a malignant derivative can be as few as 3-7. 5 Obviously, it would be very difficult to identify these primary causative mutations among a total of 10,000, the majority of which are random events resulting from genomic instability. Mathematical models provide a promising approach to resolve this puzzle.Early work on models of oncogenesis used simple path models. One example is the work of Vogelstein et al. 7 where the progression of colorectal cancer by a chain of 4 genetic events was described. Once the first of these events occurs, the probability of the second event increases, and when the second event occurs, the probability of the third increases, and so on. Unfortunately, attempts to find similar path models for o...

Analysis of an independent tumor suppressor locus telomeric to Tp53 suggested Inpp5k and Myo1c as novel tumor suppressor gene candidates in this region

“…Cytogenetic and molecular analysis of ECs developed in a rat model for this malignancy revealed frequent allelic losses/deletions in the proximal to middle part of rat chromosome 10 (RNO10) [ 11 – 13 ]. Through deriving onco-tree models based on allelic imbalance (AI) data, we determined the likely order of allelic loss events along RNO10 as well as their relationship to each other [ 14 ]. In the analysis one of the small regions of recurrent allelic loss located at RNO10q24-q25 was placed closest to the root of the onco-tree models, suggesting this region to harbor early and important genetic alterations.…”

Accurate Reconstruction of the Temporal Order of Mutations in Neoplastic Progression

“…As before, the interpretation is that a given mutation increases the chances of obtaining the following mutation. A number of studies have constructed oncogenetic trees from cross-sectional data, including for renal cell carcinoma (12), endometrial adenocarcinoma (13), gastrointestinal stromal tumors (14), oral cancer (15), and colon cancer (16). …”

An FYVE-Domain-Containing Protein, PsFP1, Is Involved in Vegetative Growth, Oxidative Stress Response and Virulence of Phytophthora sojae

“…Although no homozygous transformants were obtained, heterozygous transformants can also be to study the function of PsFP1 , because the PsFP1 gene is hardly expressed in heterozygous transformants. Previous studies have shown that allelic expression imbalance exists widely in eukaryotes [ 38 , 39 , 40 ]. Thus, the significant decrease in PsFP1 expression in heterozygous transformants may be due to the deletion of the preponderant allele of PsFP1 .…”