Showing papers in "Cellular Oncology in 2008"

Gene prioritization through genomic data fusion

Abstract: The identification of genes involved in health and disease remains a challenge. We describe a bioinformatics approach, together with a freely accessible, interactive and flexible software termed Endeavour, to prioritize candidate genes underlying biological processes or diseases, based on their similarity to known genes involved in these phenomena. Unlike previous approaches, ours generates distinct prioritizations for multiple heterogeneous data sources, which are then integrated, or fused, into a global ranking using order statistics. In addition, it offers the flexibility of including additional data sources. Validation of our approach revealed it was able to efficiently prioritize 627 genes in disease data sets and 76 genes in biological pathway sets, identify candidates of 16 mono- or polygenic diseases, and discover regulatory genes of myeloid differentiation. Furthermore, the approach identified a novel gene involved in craniofacial development from a 2-Mb chromosomal region, deleted in some patients with DiGeorge-like birth defects. The approach described here offers an alternative integrative method for gene discovery.

Hypermethylation of the FANCC and FANCL promoter regions in sporadic acute leukaemia

Abstract: Objective: Inactivation of the FA-BRCA pathway results in chromosomal instability. Fanconi anaemia (FA) patients have an inherited defect in this pathway and are strongly predisposed to the development of acute myeloid leukaemia (AML). Studies in sporadic cancers have shown promoter methylation of the FANCF gene in a significant proportion of various solid tumours. However, only a single leukaemic case with methylation of one of the FA-BRCA genes has been described to date, i.e. methylation of FANCF in cell line CHRF-288. We investigated the presence of aberrant methylation in 11 FA-BRCA genes in sporadic cases of leukaemia.

MLPAnalyzer: data analysis tool for reliable automated normalization of MLPA fragment data.

Abstract: Background: Multiplex Ligation dependent Probe Amplification (MLPA) is a rapid, simple, reliable and customized method for detection of copy number changes of individual genes at a high resolution and allows for high throughput analysis. This technique is typically applied for studying specific genes in large sample series. The large amount of data, dissimilarities in PCR efficiency among the different probe amplification products, and sample-to-sample variation pose a challenge to data analysis and interpretation. We therefore set out to develop an MLPA data analysis strategy and tool that is simple to use, while still taking into account the above-mentioned sources of variation. Materials and methods: MLPAnalyzer was developed in Visual Basic for Applications, and can accept a large number of file formats directly from capillary sequence systems. Sizes of all MLPA probe signals are determined and filtered, quality control steps are performed, and variation in peak intensity related to size is corrected for. DNA copy number ratios of test samples are computed, displayed in a table view and a set of comprehensive figures is generated. To validate this approach, MLPA reactions were performed using a dedicated MLPA mix on 6 different colorectal cancer cell lines. The generated data were normalized using our program and results were compared to previously performed array-CGH results using both statistical methods and visual examination. Results and discussion: Visual examination of bar graphs and direct ratios for both techniques showed very similar results, while the average Pearson moment correlation over all MLPA probes was found to be 0.42. Our results thus show that automated MLPA data processing following our suggested strategy may be of significant use, especially when handling large MLPA data sets, when samples are of different quality, or interpretation of MLPA electropherograms is too complex. It remains, however, important to recognize that automated MLPA data processing may only be successful when a dedicated experimental setup is also considered.

Alterations in AP-1 and AP-1 regulatory genes during HPV-induced carcinogenesis.

Abstract: Background: Previous studies demonstrated a functional involvement of the AP-1 transcription factor in HPV-induced cervical carcinogenesis. Here, we aimed to obtain further insight in expression alterations of AP-1 family members during HPV-mediated transformation and their relationship to potential regulatory (Notch1, Net) and target (CADM1) genes.

Differential proteomic analysis of nuclear matrix in muscle-invasive bladder cancer: potential to improve diagnosis and prognosis.

Abstract: Introduction: Although several molecular markers for bladder cancer have been identified, at present little information on prognostic biomarkers is available in the literature. Prognostication of this tumor is largely based on clinicopathological characteristics. Our aim was to identify nuclear matrix (NM) proteins that might serve to better characterize the phenotype of the invasive bladder cancer and to investigate their diagnostic and prognostic roles. Methods: NM proteins expressed in normal (n = 3) or non-tumoral (n = 9) tissue specimens and muscle-invasive bladder cancer (n = 21) specimens were analyzed by two dimensional (2D) gel electrophoresis. PDQuest image analysis software was used to generate a comparative NM proteome analysis. Selected spots were characterized by liquid chromatography coupled to tandem mass spectrometry and Western blot. Results: We detected over 800 protein spots in each 2D map and 43 spots were identified. 30 proteins were differentially expressed by bladder tumor cells; among these, 19 proteins were detected in bladder tumoral tissues but not in normal and non-tumoral tissues and seven proteins correlated with tumor stage. One protein (p54 nrb ) was strongly correlated with vascular invasions and appeared to be also significantly ( P< 0.0001) associated with a decreased probability of survival. Conclusion: Important alterations in NM proteins occur in muscle-invasive bladder cancer. The differentially expressed pro- teins include biomarkers potentially useful for disease diagnosis, progression and prognosis. Our findings beyond improving the understanding of the biology of bladder cancer, could help to stratify patients into different prognostic subgroups and to select those who might be better candidate to multimodal therapeutic approaches.

A comparative Analysis by SAGE of Gene Expression Profiles of Esophageal Adenocarcinoma and Esophageal Squamous Cell Carcinoma

Abstract: Esophageal adenocarcinoma (EA) and esophageal squamous cell carcinoma (ESCC) are the two main types of esophageal cancer. Despite extensive research the exact molecular basis of these cancers is unclear. Therefore we evaluated the transcriptome of EA in comparison to non-dysplastic Barrett’s esophagus (BE), the metaplastic epithelium that predisposes for EA, and compared the transcriptome of ESCC to normal esophageal squamous epithelium. For obtaining the transcriptomes tissue biopsies were used and serial analysis of gene expression (SAGE) was applied. Validation of results by RT-PCR and immunoblotting was performed using tissues of an additional 23 EA and ESCC patients. Over 58,000 tags were sequenced. Between EA and BE 1013, and between ESCC and normal squamous epithelium 1235 tags were significantly differentially expressed (p < 0.05). The most up-regulated genes in EA compared to BE were SRY-box 4 and Lipocalin2, whereas the most down-regulated genes in EA were Trefoil factors and Annexin A10. The most up-regulated genes in ESCC compared to normal squamous epithelium were BMP4, E-Cadherin and TFF3. The results could suggest that the BE expression profile is closer related to normal squamous esophagus then to EA. In addition, several uniquely expressed genes are identified.

Patterns of Genome Dynamics and Cancer Evolution

Abstract: The importance of the chromosome versus the gene as a causative agent in cancer formation has sparked a heated debate. This issue is directly related to two different schools of thought, namely the gene-centric or genome-centric paradigms of cancer research [1–3]. For decades we have essentially ignored the evolutionary nature of complex cancer systems due to the influence of reductionist viewpoints and experimental approaches. Cancer research has focused on identifying and characterizing the step-wise accumulation of gene mutations and the consequent effects on the corresponding pathways, as the cancer evolutionary process has been thought by many as a linear and predictable process. Despite the fact that chromosome aberrations are nearly universally detected in cancer cases, the gene-centric viewpoint has led to the conclusion that chromosome aberrations are a consequence of gene mutations and therefore must be late events. Furthermore, chromosomal research has focused on the identification of recurrent types of clonal chromosome aberrations (CCAs). Specific patterns of these clonal events have been utilized both in clinical diagnosis and treatment. However, due to hyper-focus on identifying recurrent changes, the true karyotypic heterogeneity of cancer has been under appreciated, with non-recurrent change being considered “genetic noise”, which has been largely ignored [4]. Recently, the existence of an overwhelming amount of non-clonal chromosome aberrations (NCCAs), the major form of genome variation and the key index for system instability, has been identified in patients and cancer progression models [5,6]. The study of chromosomes in cancer has also been considered a low resolution approach compared with molecular methods such as DNA sequencing and thus was said to not offer causative insight. How-

IL-1 beta-31T > C promoter polymorphism is associated with gastric stump cancer but not with early-onset and conventional gastric cancers

Abstract: It has been reported that interleukin-1beta (IL-1B) genes play a crucial role in the genetic predisposition to gastric cancer although there is no information about their role in different subtypes of gastric cancer. We performed single nucleotide polymorphism analysis of IL-1B in 241 gastric cancers including early onset gastric cancers (EOGC), conventional gastric cancers, and gastric stump cancers (GSCs) as well as 100 control patients, using real-time polymerase chain reaction and sequence analysis. The C allele was present in 60% of EOGCs, 59% of conventional gastric cancers, and 90% of GSCs, compared to 62% in the control group. Interestingly, there was no difference between early onset and conventional gastric cancer with respect to the IL-1B −31T>C polymorphism distribution. A statistically significant difference in the presence of the C allele compared to the control group was found in patients with gastric stump cancer (p = 0.008) with the T allele conferring protection against gastric stump cancer. In summary, we have shown that the IL-1B −31C allele promoter polymorphism is significantly associated with gastric stump cancer compared to the control group. Although several molecular differences have been identified between conventional gastric cancer and early onset gastric cancer, the IL-1B −31 allele distribution is similar between these two groups.

Evaluation of DNA-ploidy heterogeneity in gastric cancers.

Abstract: Prognostic value of DNA-ploidy in gastric cancers is still a matter of controversy. A possible explanation for the discrepant results reported in the literature could be sampling error in tumours with multiple stemlines differing in DNA-ploidy [2,4]. In order to determine whether or not such heterogeneity exists and play a role in biology of gastric cancers we have analysed two different types of gastric carcinoma; the early gastric carcinoma (EGC) and the advanced gastric carcinoma (AGC). We have performed DNA-ploidy analysis on multiple samples providing from a group of 17 EGC of which 8 were pure intramucosal and 9 were infiltrating into the sub-mucosa. Then we have analysed 16 AGC, according to the same procedure. We found an aneuploid DNA-stemline in 8 EGC (47%) more often in tumours invading into the submucosa (5/9) than in pure mucosal tumours (3/8). Multiple DNA-stemlines were found more frequently in submucosal infiltrating tumours (4/5) [3]. From the 16 AGC cases, 15 revealed DNA-aneuploid with heterogeneity in 4 cases (26%). In conclusion we have reported that 53% of EGC were diploid compared to only 6% of AGC. Heterogeneity was found in 13% intramucosal EGC, 44% in submucosal EGC and 26% of AGC [1]. These results are consistent with the hypothesis of stepwise ploidy progression: from diploid in most