Nathan Ellis, PhD: Current Research
In Ellis’ early years, he studied X chromosome inactivation with Stanley Gartler at the University of Washington and sex determination with Peter Goodfellow at the Imperial Cancer Research Fund. His work on the molecular structure of pseudoautosomal region was key to identification of the sex-determining gene SRY (1-3). He obtained his first independent investigator position at the New York Blood Center, where he worked closely with James L. German III. At the Blood Center, he cloned and characterized the XG blood group gene (4,5). XG deserved special interest because it is co-regulated, with the upstream gene MIC2, by a cis-acting, polymorphic regulatory element, referred to as XGR (6).
Where he truly made his mark was in the characterization of the molecular basis of the rare, autosomal recessive entity Bloom’s syndrome. Here, he made clever use of Bloom’s syndrome’s unique genetics. In Bloom’s syndrome, about one third of patients exhibit somatic mosaicism, that is, the presence of functionally normal and mutant cells in the same patient. This unusual observation was unexplained. Ellis and German showed that there are at least two molecular mechanisms (somatic intragenic recombination and back mutation) that explain somatic mosaicism in Bloom’s syndrome (7,8). Both mechanisms have the effect of correcting the mutated BLM gene to generate a normal BLM gene. Somatic reversion has been described in many different autosomal recessive disorders; its importance as a corrective or ameliorating influence in Bloom’s syndrome has not been demonstrated. Increased somatic mutation is a central developmental feature of Bloom’s syndrome, as somatic mutations are fundamental to driving carcinogenesis in general and in particular in Bloom’s syndrome, where cancer is often a fatal consequence of the hyper-mutability inherent in the syndrome.
Somatic intragenic recombination also provided an elegant method for cloning BLM. Having identified, through the study of somatic mosaicism, recombination events within the BLM gene, the cloning of BLM followed quickly (9). Mutations were soon identified in BLM that cause Bloom’s syndrome. Subsequently, the group showed that they could correct the cellular defect in Bloom’s syndrome by re-introducing BLM into Bloom’s syndrome cells (10,11). These results identified BLM as a critical factor in the maintenance of genome integrity, and it made connections between the RecQ helicase family—a family of DNA helicases conserved from bacteria to mammals of which BLM is a member—and human disease. Other human RecQ genes that are mutated in rare syndromes include WRN, which is mutated in Werner syndrome, and RECQL4, which is mutated in a subset of persons with Rothmund-Thomson syndrome.
Ellis and German conducted a detailed mutational analysis of BLM in all available Bloom’s syndrome patients, identifying cryptic relatedness as a strong genetic force in human populations: persons who do not know themselves to be related in fact carry the same DNA change identical by descent from a recent common ancestor (12,13). Although the mutational analysis in Bloom’s syndrome and other rare human genetic disorders has demonstrated the widespread character of cryptic relatedness in human populations, we do not fully appreciate its impact on human evolution.
In 1997, Ellis moved to Memorial Sloan-Kettering Cancer Center, where he was able to expand his research program to study cancer susceptibility more broadly. The BLM mutation blmAsh is a unique Bloom’s syndrome-causing mutation specific to Ashkenazi Jews; consequently, a straightforward PCR assay could be used to test whether BLM+/- heterozygotes are at increased risk of cancer. This was an important question because disease gene heterozygotes are much more frequent than disease gene homozygotes, and increased risk in heterozygotes might help explain some of the cancer susceptibility in the general population. By comparing Ashkenazi Jewish cases and controls, Ellis and collaborators found that BLM+/- heterozygotes have approximately two times the risk of developing colorectal cancer (CRC) compared to BLM+/+ (14). In recent years, investigators have been returning to the idea that genetically-determined cancer susceptibility in the general population might be caused by rare mutations that have moderate effects, just as BLM+/- does.
Besides blmAsh, Ellis and collaborators have studied, in multiple cancer types, multiple cancer-causing mutations that are specific to the Ashkenazi Jewish population, including MSH2 A636P, the three common BRCA1/BRCA2 mutations, and CHEK2 S428F (15-19). These disease-causing mutations are in linkage disequilibrium (LD) with surrounding genetic markers. LD is defined as the excess co-occurrence of two alleles over that which is expected at random. Ellis hypothesized that the LD surrounding Jewish founder mutations might facilitate the identification of disease genes using an association-based strategy. The association strategy have increase the power to identify novel disease genes in the Jewish population, because the number of different mutations in disease genes is small (often a single mutation as is the case for blmAsh) and the genetic distance over which LD spreads is large (from 1 to 10 million base pairs). As a proof of principle, his group found that they could “re-discover” BLM, MSH2, and BRCA2 using this strategy (20-21), and the strategy subsequently formed the basis of a genome-wide association study to identify breast cancer genes in Ashkenazi Jews (22).
In recent years, Ellis has been using comparative genetics to investigate cancer susceptibility genes in CRC. Although genome-wide association studies have localized many, many new susceptibility alleles, we still do not know their true identity. Comparing the risk signals in African Americans and whites, he has learned that only 30-40% of the risk alleles that are detectable in whites can be detected in African Americans (23-24).The result have no only led to better localization of those risk alleles that are shared between continental populations but also revealed new genetic mechanisms at play in CRC susceptibility.
Identification of the true, functionally relevant DNA changes that cause increased cancer risk remains a significant challenge to our field. Solving this problem will require success in genetic analysis of the risk genes using DNA sequencing, bioinformatics, and additional association analyses and genetic model systems (cell culture and animal models) in which to test functional consequences of the variation. The Ellis laboratory is in a unique position to combine the genetic and functional analyses and to identify and characterize functionally important cancer-causing genetic variation.
1. Ellis et al. Nature 337:81 (1989) http://www.ncbi.nlm.nih.gov/pubmed/2594087
2. Ellis et al. Nature 344:663 (1990) http://www.ncbi.nlm.nih.gov/pubmed/2325773
3. Ellis et al. Cell 63: 977 (1990) http://www.ncbi.nlm.nih.gov/pubmed/2124175
4. Ellis et al. Nat Genet 6:394 (1994) http://www.ncbi.nlm.nih.gov/pubmed/8054981
5. Ellis et al. Nat Genet 8:285 (1994) http://www.ncbi.nlm.nih.gov/pubmed/7533029
6. Tippett and Ellis, Transfusion Med Rev 12:233 (1998) http://www.ncbi.nlm.nih.gov/pubmed/9798268
7. Ellis et al. Am J Hum Genet 57:1019 (1995) http://www.ncbi.nlm.nih.gov/pubmed/7485150
8. Ellis et al. Hum Genet 108: 167 (2001) http://www.ncbi.nlm.nih.gov/pubmed/11281456
9. Ellis et al. Cell 83: 655 (1995) http://www.ncbi.nlm.nih.gov/pubmed/7585968
10. Neff et al. Mol Biol Cell 10:665 (1999) http://www.ncbi.nlm.nih.gov/pubmed/10069810
11. Ellis et al. Am J Hum Genet65:1368 (1999) http://www.ncbi.nlm.nih.gov/pubmed/10521302
12. Ellis et al. Am J Hum Genet63: 1685 (1998) http://www.ncbi.nlm.nih.gov/pubmed/9837821
13. German et al. Hum Mutation 28:743 (2007) http://www.ncbi.nlm.nih.gov/pubmed/17407155
14. Gruber et al. Science 297:2013 (2002) http://www.ncbi.nlm.nih.gov/pubmed/12242432
15. Foulkes et al. Am J Hum Genet71: 1395 (2002) http://www.ncbi.nlm.nih.gov/pubmed/12454801
16. Offit et al. BMC Med Genet 4:1 (2003) http://www.ncbi.nlm.nih.gov/pubmed/12529183
17. Kirchoff et al. JNCI 96:68 (2004) http://www.ncbi.nlm.nih.gov/pubmed/14709740
18. Kirchoff et al. Clin Cancer Res 10:2918 (2004) http://www.ncbi.nlm.nih.gov/pubmed/15131025
19. Shaag et al. Hum Mol Genet 14:555 (2005) http://www.ncbi.nlm.nih.gov/pubmed/15649950
20. Mitra et al. Can Res 64: 8116 (2004) http://www.ncbi.nlm.nih.gov/pubmed/15520224
21. Ellis et al. Genet Epidem 30:48 (2006) http://www.ncbi.nlm.nih.gov/pubmed/16206141
22. Gold et al. Proc Natl Acad Sci 105:4340 (2008) http://www.ncbi.nlm.nih.gov/pubmed/18326623
23. Kupfer et al. Gasteroenterology 139:1677 (2010) http://www.ncbi.nlm.nih.gov/pubmed/20659471
24. Kupfer et al. Carcinogenesis April 21 (2014) http://www.ncbi.nlm.nih.gov/pubmed/24753543