SMAD4 - Molecular gladiator of the TGF-β signaling is trampled upon by mutational insufficiency in colorectal carcinoma of Kashmiri population: an analysis with relation to KRAS proto-oncogene

<p>Abstract</p> <p>Background</p> <p>The development and progression of colorectal cancer has been extensively studied and the genes responsible have been well characterized. However the correlation between the <it>SMAD4 </it>gene mutations with <it>KRAS </it>mutant status has not been explored by many studies so far. Here, in this study we aimed to investigate the role of <it>SMAD4 </it>gene aberrations in the pathogenesis of CRC in Kashmir valley and to correlate it with various clinicopathological variables and <it>KRAS </it>mutant genotype.</p> <p>Methods</p> <p>We examined the paired tumor and normal tissue specimens of 86 CRC patients for the occurrence of aberrations in MCR region of <it>SMAD4 </it>and exon 1 of <it>KRAS </it>by PCR-SSCP and/or PCR-Direct sequencing.</p> <p>Results</p> <p>The overall mutation rate of mutation cluster region (MCR) region of <it>SMAD4 </it>gene among 86 patients was 18.6% (16 of 86). 68.75% (11/16) of the <it>SMAD4 </it>gene mutants were found to have mutations in <it>KRAS </it>gene as well. The association between the <it>KRAS </it>mutant genotype with <it>SMAD4 </it>mutants was found to be significant (P =< 0.05). Further more, we found a significant association of tumor location, tumor grade, node status, occupational exposure to pesticides and bleeding PR/Constipation with the mutation status of the <it>SMAD4 </it>gene (P =< 0.05).</p> <p>Conclusion</p> <p>Our study suggests that <it>SMAD4 </it>gene aberrations are the common event in CRC development but play a differential role in the progression of CRC in higher tumor grade (C+D) and its association with the <it>KRAS </it>mutant status suggest that these two molecules together are responsible for the progression of the tumor to higher/advanced stage.</p

In silico analysis and verification of S100 gene expression in gastric cancer

<p>Abstract</p> <p>Background</p> <p>The S100 protein family comprises 22 members whose protein sequences encompass at least one EF-hand Ca²⁺binding motif. They were involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. However, the expression status of S100 family members in gastric cancer was not known yet.</p> <p>Methods</p> <p>Combined with analysis of series analysis of gene expression, virtual Northern blot and microarray data, the expression levels of S100 family members in normal and malignant stomach tissues were systematically investigated. The expression of S100A3 was further evaluated by quantitative RT-PCR.</p> <p>Results</p> <p>At least 5 S100 genes were found to be upregulated in gastric cance by in silico analysis. Among them, four genes, including S100A2, S100A4, S100A7 and S100A10, were reported to overexpressed in gastric cancer previously. The expression of S100A3 in eighty patients of gastric cancer was further examined. The results showed that the mean expression levels of S100A3 in gastric cancer tissues were 2.5 times as high as in adjacent non-tumorous tissues. S100A3 expression was correlated with tumor differentiation and TNM (Tumor-Node-Metastasis) stage of gastric cancer, which was relatively highly expressed in poorly differentiated and advanced gastric cancer tissues (<it>P </it>< 0.05).</p> <p>Conclusion</p> <p>To our knowledge this is the first report of systematic evaluation of S100 gene expressions in gastric cancers by multiple in silico analysis. The results indicated that overexpression of S100 gene family members were characteristics of gastric cancers and S100A3 might play important roles in differentiation and progression of gastric cancer.</p

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms

<p>Abstract</p> <p>Background</p> <p>The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries.</p> <p>Results</p> <p>We discovered that the CGAP approach often includes libraries from dependent or irrelevant tissues (one third of libraries were incorrect on average, with some tissue searches no correct libraries being selected at all). We also discovered that the CGAP approach reported genes from outside the selected libraries and may omit genes found within the libraries. Other errors include the incorrect estimation of the significance values and inaccurate settings for the library size cut-off values. We advocated a revised approach to finding libraries associated with tissues. In doing so, libraries from dependent or irrelevant tissues do not get included in the final library pool. We also revised the method for determining the presence or absence of a gene by searching the UniGene relational database, revised calculation of statistical significance and sorted the library cut-off filter.</p> <p>Conclusion</p> <p>Our results justify re-evaluation of all previously reported results where NCBI CGAP expression data and tools were used.</p

TGF-beta receptor 2 downregulation in tumour-associated stroma worsens prognosis and high-grade tumours show more tumour-associated macrophages and lower TGF-beta1 expression in colon carcinoma: a retrospective study

<p>Abstract</p> <p>Background</p> <p>Histological phenotype and clinical behaviour of malignant tumours are not only dependent on alterations in the epithelial cell compartment, but are affected by their interaction with inflammatory cells and tumour-associated stroma. Studies in animal models have shown influence of tumour-associated macrophages (TAM) on histological grade of differentiation in colon carcinoma. Disruption of transforming growth factor beta (TGF-beta) signalling in tumour cells is related to more aggressive clinical behaviour. Expression data of components of this pathway in tumour-associated stroma is limited.</p> <p>Methods</p> <p>Tissue micro arrays of 310 colon carcinomas from curatively resected patients in UICC stage II and III were established. In a first step we quantified amount of CD68 positive TAMs and expression of components of TGF-beta signalling (TGF-beta1, TGF-beta receptors type 1 and 2, Smad 3 and 4) in tumour and associated stroma. Further we analyzed correlation to histological and clinical parameters (histological grade of differentiation (low-grade (i.e. grade 1 and 2) vs. high-grade (i.e. grade 3 and 4)), lymph node metastasis, distant metastasis, 5 year cancer related survival) using Chi-square or Fisher's exact test, when appropriate, to compare frequencies, Kaplan-Meier method to calculate 5-year rates of distant metastases and cancer-related survival and log rank test to compare the rates of distant metastases and survival. To identify independent prognostic factors Cox regression analysis including lymph node status and grading was performed.</p> <p>Results</p> <p>High-grade tumours and those with lymph node metastases showed higher rates of TAMs and lower expression of TGF-beta1. Loss of nuclear Smad4 expression in tumor was associated with presence of lymph node metastasis, but no influence on prognosis could be demonstrated. Decrease of both TGF-beta receptors in tumour-associated stroma was associated with increased lymph node metastasis and shorter survival. Stromal TGF-beta receptor 2 expression was an independent prognostic factor for cancer related survival.</p> <p>Conclusion</p> <p>Histological phenotype and clinical behaviour of colon cancer is not only influenced by mutational incidents in tumour cells but also affected by interaction of tumour tissue with inflammatory cells like macrophages and associated stroma and TGF-beta signalling is one important part of this crosstalk. Further studies are needed to elucidate the exact mechanisms.</p

Generation of a non-small cell lung cancer transcriptome microarray

<p>Abstract</p> <p>Background</p> <p>Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality worldwide. At present no reliable biomarkers are available to guide the management of this condition. Microarray technology may allow appropriate biomarkers to be identified but present platforms are lacking disease focus and are thus likely to miss potentially vital information contained in patient tissue samples.</p> <p>Methods</p> <p>A combination of large-scale in-house sequencing, gene expression profiling and public sequence and gene expression data mining were used to characterise the transcriptome of NSCLC and the data used to generate a disease-focused microarray – the Lung Cancer DSA research tool.</p> <p>Results</p> <p>Built on the Affymetrix GeneChip platform, the Lung Cancer DSA research tool allows for interrogation of ~60,000 transcripts relevant to Lung Cancer, tens of thousands of which are unavailable on leading commercial microarrays.</p> <p>Conclusion</p> <p>We have developed the first high-density disease specific transcriptome microarray. We present the array design process and the results of experiments carried out to demonstrate the array's utility. This approach serves as a template for the development of other disease transcriptome microarrays, including non-neoplastic diseases.</p

Identification of germline alterations of the mad homology 2 domain of SMAD3 and SMAD4 from the Ontario site of the breast cancer family registry (CFR)

Abstract Introduction A common feature of neoplastic cells is that mutations in SMADs can contribute to the loss of sensitivity to the anti-tumor effects of transforming growth factor-β (TGF-β). However, germline mutation analysis of SMAD3 and SMAD4, the principle substrates of the TGF-β signaling pathway, has not yet been conducted in breast cancer. Thus, it is currently unknown whether germline SMAD3 and SMAD4 mutations are involved in breast cancer predisposition. Methods We performed mutation analysis of the highly conserved mad-homology 2 (MH2) domains for both genes in genomic DNA from 408 non-BRCA1/BRCA2 breast cancer cases and 710 population controls recruited by the Ontario site of the breast cancer family registry (CFR) using denaturing high-performance liquid chromatography (DHPLC) and direct DNA sequencing. The results were interpreted in several ways. First, we adapted nucleotide diversity analysis to quantitatively assess whether the frequency of alterations differ between the two genes. Next, in silico tools were used to predict variants' effect on domain function and mRNA splicing. Finally, 37 cases or controls harboring alterations were tested for aberrant splicing using reverse-transcription polymerase chain reaction (PCR) and real-time PCR statistical comparison of germline expressions by non-parametric Mann-Whitney test of independent samples. Results We identified 27 variants including 2 novel SMAD4 coding variants c.1350G > A (p.Gln450Gln), and c.1701A > G (p.Ile525Val). There were no inactivating mutations even though c.1350G > A was predicted to affect exonic splicing enhancers. However, several additional findings were of note: 1) nucleotide diversity estimate for SMAD3 but not SMAD4 indicated that coding variants of the MH2 domain were more infrequent than expected; 2) in breast cancer cases SMAD3 was significantly over-expressed relative to controls (P A was associated with elevated germline expression (> 5-fold); 3) separate analysis using tissue expression data showed statistically significant over-expression of SMAD3 and SMAD4 in breast carcinomas. Conclusions This study shows that inactivating germline alterations in SMAD3 and SMAD4 are rare, suggesting a limited role in driving tumorigenesis. Nevertheless, aberrant germline expressions of SMAD3 and SMAD4 may be more common in breast cancer than previously suspected and offer novel insight into their roles in predisposition and/or progression of breast cancer