Cancer gene discovery in mouse and man

The elucidation of the human and mouse genome sequence and developments in high-throughput genome analysis, and in computational tools, have made it possible to profile entire cancer genomes. In parallel with these advances mouse models of cancer have evolved into a powerful tool for cancer gene discovery. Here we discuss the approaches that may be used for cancer gene identification in both human and mouse and discuss how a cross-species ‘oncogenomics’ approach to cancer gene discovery represents a powerful strategy for finding genes that drive tumourigenesis.     

Second-generation sequencing for gene discovery in the Brassicaceae

The Brassicaceae contains the most diverse collection of agriculturally important crop species of all plant families. Yet, this is one of the few families that do not form functional symbiotic associations with mycorrhizal fungi in the soil for improved nutrient acquisition. The genes involved in this symbiosis were more recently recruited by legumes for symbiotic association with nitrogen-fixing rhizobia bacteria. This study applied second-generation sequencing (SGS) and analysis tools to discover that two such genes, NSP1 (Nodulation Signalling Pathway 1) and NSP2, remain conserved in diverse members of the Brassicaceae despite the absence of these symbioses. We demonstrate the utility of SGS data for the discovery of putative gene homologs and their analysis in complex polyploid crop genomes with little prior sequence information. Furthermore, we show how this data can be applied to enhance downstream reverse genetics analyses. We hypothesize that Brassica NSP genes may function in the root in other plant-microbe interaction pathways that were recruited for mycorrhizal and rhizobial symbioses during evolution.     

Breast cancer gene discovery

Many important advances have been made in the past decade in understanding breast cancer at the molecular level, and two important high-penetrance breast cancer genes--BRCA1 and BRCA2--have been identified. However, germline mutations in these two genes are responsible for only a minority (approximately 5%) of all breast carcinomas, and the genes responsible for the majority of breast cancer cases remain to be identified. There is evidence that there are additional high-to-moderate-penetrance breast cancer susceptibility genes but, given the high degree of molecular heterogeneity in breast carcinomas, it is likely that each of these genes is responsible for only a subset of cases. There are also many candidate low-penetrance breast cancer genes and many more are likely to be identified. In addition to germline, and somatic, sequence alterations, epigenetic changes in many genes are likely to play an important role in the pathobiology of breast cancer. Recently developed genomic technologies and the completion of the human genome sequence provide us with powerful tools to identify novel candidate breast cancer genes that could play an important role in breast tumourigenesis.     

High throughput sequencing approaches to mutation discovery in the mouse

Phenotype-driven approaches in mice are powerful strategies for the discovery of genes and gene functions and for unravelling complex biological mechanisms. Traditional methods for mutation discovery are reliable and robust, but they can also be laborious and time consuming. Recently, high-throughput sequencing (HTS) technologies have revolutionised the process of forward genetics in mice by paving the way to rapid mutation discovery. However, successful application of HTS for mutation discovery relies heavily on the sequencing approach employed and strategies for data analysis. Here we review current HTS applications and resources for mutation discovery and provide an overview of the practical considerations for HTS implementation and data analysis.     

Cancer chemotherapy-induced lymphocytosis: a revolutionary discovery in the medical oncology

The recent advances in the investigation of tumor immunobiology have suggested that cancer chemotherapy, in addition to its well known cytotoxic activity, may play modulatory effects on the endogenous production of cytokines involved in the control of both tumor angiogenesis and antitumor immunity. Cancer chemotherapy constantly acts with inhibitory effects on anti-bacterial, anti-viral and anti- mycotic immune responses, whereas its action on anticancer immunity, which is mainly mediated by lymphocytes, has still to be better investigated and defined. The present study was carried out to evaluate the influence of chemotherapy on lymphocyte count and its relation to the clinical response in cancer patients suffering from the most commonly frequent tumor histotypes, including lung, colorectal, breast and prostate carcinomas. The study included 144 consecutive metastatic solid tumor patients. Lung cancer patients were treated with cisplatin plus gemcitabine, colorectal cancer patients received oxaliplatin plus 5-fluorouracil, while those affected by breast cancer or prostate carcinoma were treated with taxotere alone. An objective tumor regression was achieved in 66 out of 144 (46 percent) patients, whereas the remaining 78 patients had only a stable disease (SD)or a progressive disease. Independently of tumor histotype and chemotherapeutic regimen, a lymphocytosis occurred in patients who achieved an objective tumor regression in response to chemotherapy, and lymphocyte mean count observed at the end of the chemotherapeutic treatment was significantly higher with respect to the values seen before the onset of treatment. On the contrary, lymphocyte mean number decreased on chemotherapy in patients with SD or PD, even though the decline was statistically significant with respect to the pretreatment values in the only patients who had a PD in response to chemotherapy. This study would suggest that chemotherapy itself may paradoxically act, at least in part, as a cancer immunotherapy by inducing lymphocytosis, as well as previously demonstrated for the only immunotherapy with IL-2, probably by modulating the cytokine network and correcting the altered endogenous production of cytokines, responsible for cancer-related immunodeficiency.     

Mutation discovery in the mouse using genetically guided array capture and resequencing

Forward genetics (phenotype-driven approaches) remain the primary source for allelic variants in the mouse. Unfortunately, the gap between observable phenotype and causative genotype limits the widespread use of spontaneous and induced mouse mutants. As alternatives to traditional positional cloning and mutation detection approaches, sequence capture and next-generation sequencing technologies can be used to rapidly sequence subsets of the genome. Application of these technologies to mutation detection efforts in the mouse has the potential to significantly reduce the time and resources required for mutation identification by abrogating the need for high-resolution genetic mapping, long-range PCR, and sequencing of individual PCR amplimers. As proof of principle, we used array-based sequence capture and pyrosequencing to sequence an allelic series from the classically defined Kit locus (~200 kb) from each of five noncomplementing Kit mutants (one known allele and four unknown alleles) and have successfully identified and validated a nonsynonymous coding mutation for each allele. These data represent the first documentation and validation that these new technologies can be used to efficiently discover causative mutations. Importantly, these data also provide a specific methodological foundation for the development of large-scale mutation detection efforts in the laboratory mouse. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. M. D’Ascenzo and C. Meacham contributed equally to this work.     

Genomewide discovery and classification of candidate ovarian fertility genes in the mouse

Female infertility syndromes are among the most prevalent chronic health disorders in women, but their genetic basis remains unknown because of uncertainty regarding the number and identity of ovarian factors controlling the assembly, preservation, and maturation of ovarian follicles. To systematically discover ovarian fertility genes en masse, we employed a mouse model (Foxo3) in which follicles are assembled normally but then undergo synchronous activation. We developed a microarray-based approach for the systematic discovery of tissue-specific genes and, by applying it to Foxo3 ovaries and other samples, defined a surprisingly large set of ovarian factors (n = 348, approximately 1% of the mouse genome). This set included the vast majority of known ovarian factors, 44% of which when mutated produce female sterility phenotypes, but most were novel. Comparative profiling of other tissues, including microdissected oocytes and somatic cells, revealed distinct gene classes and provided new insights into oogenesis and ovarian function, demonstrating the utility of our approach for tissue-specific gene discovery. This study will thus facilitate comprehensive analyses of follicle development, ovarian function, and female infertility.     

Subtraction-coupled custom microarray analysis for gene discovery and gene expression studies in the CNS

The revolution in our knowledge about the genomes of organisms gives rise to the question, what do we do with this information? The development of techniques allowing high throughput analysis of RNA and protein expression, such as cDNA microarrays, provide for genome-wide analysis of gene expression. These analyses will help bridge the gap between systems and molecular neuroscience. This review discusses the advantages of using a subtractive hybridization technique, such as a representational difference analysis, to generate a custom cDNA microarray enriched for genes relevant to investigating complex, heterogeneous tissues such as those involved in the chemical senses. Real and hypothetical examples of these experiments are discussed. Benefits of this approach over traditional microarray techniques include having a more relevant clone set, the potential for gene discovery and the creation of a new tool to investigate similar systems. Potential pitfalls may include PCR artifacts and the need for sequencing. However, these disadvantages can be overcome so that the coupling of subtraction techniques to microarray screening can be a fruitful approach to a variety of experimental systems.     

Genome-wide approaches for cancer gene discovery

One of the central aims of cancer research is to identify and characterize cancer-causing alterations in cancer genomes. In recent years, unprecedented advances in genome-wide sequencing, functional genomics technologies for RNA interference screens and methods for evaluating three-dimensional chromatin organization in vivo have resulted in important discoveries regarding human cancer. The cancer-causing genes identified from these new genome-wide technologies have also provided opportunities for effective and personalized cancer therapy. In this review, we describe some of the most recent technologies for cancer gene discovery. We also provide specific examples in which these technologies have proven remarkably successful in uncovering important cancer-causing alterations.     

Admixture mapping as a tool in gene discovery

Admixture mapping is a rapidly developing method to map susceptibility alleles in complex genetic disease associated with continental ancestry. Theoretically, when admixture between continental populations has occurred relatively recently, the chromosomal segments derived from the parental populations can be deduced from the differences in genotype allele frequencies. Progress in computational algorithms, in identification of ancestry informative single nucleotide polymorphisms, and in recent studies applying these tools suggests that this approach will complement other strategies for identifying the variation that underlies many complex diseases.