Transforming science: cancer gene identification

Prognostic Value of Albumin/Globulin Ratio in Survival and Lymph Node Metastasis in Patients with Cancer: A Systematic Review and Meta-analysis

The impact of albumin to globulin ratio (AGR) on the prognosis of various human cancers has not been well established. Here, a systemic review and meta-analysis has been performed to comprehensively assess the relationships between AGR and lymph node metastasis (LNM) or overall survival (OS). Systematical search through six electronic databases has been carried out to identify reports involving the role of AGR on OS and LNM in human cancers. Hazard ratio (HR), odd ratio (OR) and their 95% confidence intervals (95% CI) were evaluated through meta-analysis according to standard steps. Of 403 studies retrieved, 14 eligible studies with 4136 patients were included in this study. The analysis based on random-effect model demonstrated that low AGR was significantly associated with poor OS in various cancers (HR=1.87, 95% CI 1.50-2.34; P < 0.001). Subsequent results showed a significant increase in the risk of LNM in the low AGR group when compared with high AGR group (HR=2.24; 95% CI=1.49-3.36; P<0.001). To conclusion, this study suggested that AGR was associated with OS and LNM in cancer patients and AGR may be a potential marker to assess prognosis of cancer patients. However, a large scale of samples and prospective studies are needed in the future to validate the role of AGR in practice.

The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach

With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

Atypical mRNA fusions in PML-RARA positive, RARA-PML negative acute promyelocytic leukemia

Reciprocal RARA-PML transcripts are not detected in approximately 25% of patients with PML-RARA positive acute promyelocytic leukemia (APL), but the reasons for this are poorly understood. We studied 21 PML-RARA positive/RARA-PML negative cases by bubble PCR and multiplex long template PCR to identify the genomic breakpoints. Additional RT-PCR analysis was performed based on the DNA findings. Three cases were found to have complex rearrangements involving a third locus: the first had a PML-CDC6-RARA forward DNA fusion and expressed a chimeric PML-CDC6-RARA mRNA in addition to a PML-RARA. The other two had HERC1-PML and NT_009714.17-PML genomic fusion sequences at their respective reciprocal breakpoints. Six patients were falsely classified as RARA-PML negative due to deletions on chromosome 15 and/or 17, or alternative splicing leading to atypical RARA-PML fusion transcripts, which were not identified by conventional RT-PCR assays. This study demonstrates that the frequency of RARA-PML expression has been underestimated and highlights remarkable complexity at chromosomal breakpoint regions in APL even in cases with an apparently simple balanced t(15;17)(q24;q12).

Novel candidate cancer genes identified by a large-scale cross-species comparative oncogenomics approach

Comparative genomic hybridization (CGH) can reveal important disease genes but the large regions identified could sometimes contain hundreds of genes. Here we combine high-resolution CGH analysis of 598 human cancer cell lines with insertion sites isolated from 1,005 mouse tumors induced with the murine leukemia virus (MuLV). This cross-species oncogenomic analysis revealed candidate tumor suppressor genes and oncogenes mutated in both human and mouse tumors, making them strong candidates for novel cancer genes. A significant number of these genes contained binding sites for the stem cell transcription factors Oct4 and Nanog. Notably, mice carrying tumors with insertions in or near stem cell module genes, which are thought to participate in cell self-renewal, died significantly faster than mice without these insertions. A comparison of the profile we identified to that induced with the Sleeping Beauty (SB) transposon system revealed significant differences in the profile of recurrently mutated genes. Collectively, this work provides a rich catalogue of new candidate cancer genes for functional analysis.

Digital candidate gene approach (DigiCGA) for identification of cancer genes

The candidate gene approach is one of the most commonly used methods for identifying genes underlying disease traits. Advances in genomics have greatly contributed to the development of this approach in the past decade. More recently, with the explosion of genomic resources accessible via the public Web, digital candidate gene approach (DigiCGA) has emerged as a new development in this field. DigiCGA, an approach still in its infancy, has already achieved some primary success in cancer gene discovery. However, a detailed discussion concerning the applications of DigiCGA in cancer gene identification has not been addressed. This chapter will focus on discussing DigiCGA in a generalized sense and its applications to the identification of cancer genes, including the cancer gene resources, application status, platform and tools, challenges, and prospects.

Whole-body sleeping beauty mutagenesis can cause penetrant leukemia/lymphoma and rare high-grade glioma without associated embryonic lethality

The Sleeping Beauty (SB) transposon system has been used as a somatic mutagen to identify candidate cancer genes. In previous studies, efficient leukemia/lymphoma formation on an otherwise wild-type genetic background occurred in mice undergoing whole-body mobilization of transposons, but was accompanied by high levels of embryonic lethality. To explore the utility of SB for large-scale cancer gene discovery projects, we have generated mice that carry combinations of different transposon and transposase transgenes. We have identified a transposon/transposase combination that promotes highly penetrant leukemia/lymphoma formation on an otherwise wild-type genetic background, yet does not cause embryonic lethality. Infiltrating gliomas also occurred at lower penetrance in these mice. SB-induced or accelerated tumors do not harbor large numbers of chromosomal amplifications or deletions, indicating that transposon mobilization likely promotes tumor formation by insertional mutagenesis of cancer genes, and not by promoting wide-scale genomic instability. Cloning of transposon insertions from lymphomas/leukemias identified common insertion sites at known and candidate novel cancer genes. These data indicate that a high mutagenesis rate can be achieved using SB without high levels of embryonic lethality or genomic instability. Furthermore, the SB system could be used to identify new genes involved in lymphomagenesis/leukemogenesis.

Identifying candidate genes involved in brain tumor formation

Malignant primary brain tumors, gliomas, often overexpress both platelet-derived growth factor (PDGF) ligands and receptors providing an autocrine and/or paracrine boost to tumor growth. Glioblastoma multiforme (GBM) is the most frequent glioma. Its aggressive and infiltrative growth renders it extremely difficult to treat. Median survival after diagnosis is currently only 12-14 months. The present review describes the use of retroviral tagging to identify candidate cancer-causing genes that cooperate with PDGF in brain tumor formation. Newborn mice injected intracerebrally with a Moloney murine leukemia retrovirus carrying the sis/PDGF-B oncogene and a replication competent helper virus developed brain tumors with many characteristics of human gliomas. Analysis of proviral integrations in the brain tumors identified almost 70 common insertion sites (CISs). These CISs were named brain tumor loci and harbored known but also putative novel cancer-causing genes. Microarray analysis identified differentially expressed genes in the mouse brain tumors compared to normal brain. Known tumor genes and markers of immature cells were upregulated in the tumors. Tumors developed 13-42 weeks after injection and short latency tumors were further distinguished as fast growing and GBM-like. Long latency tumors resembled slow-growing oligodendrogliomas and contained significantly less integrations as compared to short latency tumors. Several candidate genes tagged in this retroviral screen have known functions in neoplastic transformation and oncogenesis. Some candidates with a previously unknown function in tumorigenesis were found and their putative role in brain tumor formation will be discussed in this review. The results show that proviral tagging may be a useful tool in the search for candidate glioma genes.

Therapeutic potential of RNA interference against cellular targets of HIV infection

RNA interference is not only very promising in identifying new targets for drug development, siRNA/shRNA themselves may be directly used as therapeutic agents. In inhibiting viral infections by RNA interference, both viral targets and cellular proteins have been evaluated. Most of the early studies in this field had chosen viral targets for RNA interference. However, recent efforts are mainly focusing on cellular proteins for RNA silencing due to the realization that a variety of viral responses substantially minimize siRNA effects. With the application of siRNA approaching, many new cellular targets relevant to HIV infection have been identified. The value of siRNA/shRNA in the treatment of AIDS is largely dependent on better understanding of the biology of HIV replication. Efforts in the identification of cellular processes with the employment of siRNA/shRNA have shed some new lights on our understanding of how HIV infection occurs. Furthermore, the relative specific effects and simplicity of design makes siRNA/shRNA themselves to be favorable drug leads.