Construction of preferential cDNA microarray specialized for human colorectal carcinoma: molecular sketch of colorectal cancer

RNF43 Inactivation Enhances the B-RAF/MEK Signaling and Creates a Combinatory Therapeutic Target in Cancer Cells

RING finger 43 (RNF43), a RING-type E3 ubiquitin ligase, is a key regulator of WNT signaling and is mutated in 6-10% of pancreatic tumors. However, RNF43-mediated effects remain unclear, as only a few in vivo substrates of RNF43 are identified. Here, it is found that RNF43-mutated pancreatic cancer cells exhibit elevated B-RAF/MEK activity and are highly sensitive to MEK inhibitors. The depletion of RNF43 in normal pancreatic ductal cells also enhances MEK activation, suggesting that it is a physiologically regulated process. It is confirmed that RNF43 ubiquitinates B-RAF at K499 to promote proteasome-dependent degradation, resulting in reduced MEK activity and proliferative ability in cancer cells. In addition, phosphorylation of B-RAF at T491 suppresses B-RAF ubiquitination by decreasing the interaction between RNF43 and B-RAF. Mutations at K499 in B-RAF are identified in various cancer types. MEK and WNT inhibitors synergistically suppress the growth of RNF43-mutated pancreatic cancer cells in vitro and in vivo. Collectively, the research reveals a novel mechanism by which RNF43 inhibits B-RAF/MEK signaling to suppress tumor growth and provide a new strategy for the treatment of RNF43-inactivated pancreatic cancer.

Role of SPARC in the epithelial-mesenchymal transition induced by PTHrP in human colon cancer cells

Parathyroid hormone-related peptide (PTHrP) exerts its effects on cells derived from colorectal cancer (CRC) and tumor microenvironment and is involved in processes requiring the epithelial-mesenchymal transition (EMT). Here, we report that PTHrP modulates factors expression and morphological changes associated with EMT in HCT116 cells from CRC. PTHrP increased the protein expression of SPARC, a factor involved in EMT, in HCT116 cells but not in Caco-2 cells also from CRC but with less aggressiveness. PTHrP also increased SPARC expression and its subsequent release from endothelial HMEC-1 cells. The conditioned media of PTHrP-treated HMEC-1 cells induced early changes related to EMT in HCT116 cells. Moreover, SPARC treatment on HCT116 cells potentiated PTHrP modulation in E-cadherin expression and cell migration. In vivo PTHrP also increased SPARC expression and decreased E-cadherin expression. These results suggest a novel PTHrP action on CRC progression involving the microenvironment in the modulation of events associated with EMT.

hsa-miR-29c-3p regulates biological function of colorectal cancer by targeting SPARC

Colorectal cancer (CRC) is the most common type of behavioral cancers, miRNAs play a critical role in cancer development and progression. In the present study, we downloaded the original data from Gene Expression Omnibus (GEO) and conduct data analysis. has-mir-29c-3p mimic, inhibitor, negative control or si-SPARC (secreted protein acidic, rich in cysteine) were transfected into HCT116 cells, respectively. Quantitative real time PCR (qRT-PCR) was used to measure has-mir-29c-3p and SPARC mRNA expressions, western blot was used to detect ACAA1 (acetyl-CoA acyltransferase 1), ACOX1 (acyl-CoA oxidase 1), COL1A1(collagen, type I, alpha-1), COL1A2 (collagen, type I, alpha-2), COL4A1 (collagen, type IV, alpha-1), COL5A2 (collagen, type V, alpha-2), COL12A1 (collagen, type XII, alpha-1), CPT2 (carnitine palmitoyltransferase 2), ETHE1 (persulfide dioxygenase), HMGCS2 (3-hydroxy-3-methylglutaryl-CoA synthase 2), SPARC, SQRDL (sulfide quinone oxidoreductase), and TST (thiosulfate sulfurtransferase) protein expression. CCK-8 and wound healing assay were employed to verify cell proliferation and migration. The luciferase reporter assay data made sure the target correlation of has-mir-29c-3p and SPARC. Firstly, we found that the expression of has-mir-29c-3p was lower in CRC tissues than in their paired corresponding non-cancerous tissues and there was significant inversed correlation between has-mir-29c-3p and SPARC. Overexpression of has-mir-29c-3p reduced cell proliferation and migration. SPARC was identified as a direct target of has-mir-29c-3p, whose silencing reduced cell proliferation and migration. These data showed that has-mir-29c-3p regulates CRC cell functions through regulating SPARC expression. Taken together, has-mir-29c-3p may function as an oncogenic miRNA targeting SPARC, targeted modulation of has-mir-29c-3p expression may became a potential strategy for the treatment.

A hybrid imputation approach for microarray missing value estimation

BACKGROUND

Missing data is an inevitable phenomenon in gene expression microarray experiments due to instrument failure or human error. It has a negative impact on performance of downstream analysis. Technically, most existing approaches suffer from this prevalent problem. Imputation is one of the frequently used methods for processing missing data. Actually many developments have been achieved in the research on estimating missing values. The challenging task is how to improve imputation accuracy for data with a large missing rate.

METHODS

In this paper, induced by the thought of collaborative training, we propose a novel hybrid imputation method, called Recursive Mutual Imputation (RMI). Specifically, RMI exploits global correlation information and local structure in the data, captured by two popular methods, Bayesian Principal Component Analysis (BPCA) and Local Least Squares (LLS), respectively. Mutual strategy is implemented by sharing the estimated data sequences at each recursive process. Meanwhile, we consider the imputation sequence based on the number of missing entries in the target gene. Furthermore, a weight based integrated method is utilized in the final assembling step.

RESULTS

We evaluate RMI with three state-of-art algorithms (BPCA, LLS, Iterated Local Least Squares imputation (ItrLLS)) on four publicly available microarray datasets. Experimental results clearly demonstrate that RMI significantly outperforms comparative methods in terms of Normalized Root Mean Square Error (NRMSE), especially for datasets with large missing rates and less complete genes.

CONCLUSIONS

It is noted that our proposed hybrid imputation approach incorporates both global and local information of microarray genes, which achieves lower NRMSE values against to any single approach only. Besides, this study highlights the need for considering the imputing sequence of missing entries for imputation methods.

Predictive gene signatures: molecular markers distinguishing colon adenomatous polyp and carcinoma

Cancers exhibit abnormal molecular signatures associated with disease initiation and progression. Molecular signatures could improve cancer screening, detection, drug development and selection of appropriate drug therapies for individual patients. Typically only very small amounts of tissue are available from patients for analysis and biopsy samples exhibit broad heterogeneity that cannot be captured using a single marker. This report details application of an in-house custom designed GenomeLab System multiplex gene expression assay, the hCellMarkerPlex, to assess predictive gene signatures of normal, adenomatous polyp and carcinoma colon tissue using archived tissue bank material. The hCellMarkerPlex incorporates twenty-one gene markers: epithelial (EZR, KRT18, NOX1, SLC9A2), proliferation (PCNA, CCND1, MS4A12), differentiation (B4GANLT2, CDX1, CDX2), apoptotic (CASP3, NOX1, NTN1), fibroblast (FSP1, COL1A1), structural (ACTG2, CNN1, DES), gene transcription (HDAC1), stem cell (LGR5), endothelial (VWF) and mucin production (MUC2). Gene signatures distinguished normal, adenomatous polyp and carcinoma. Individual gene targets significantly contributing to molecular tissue types, classifier genes, were further characterised using real-time PCR, in-situ hybridisation and immunohistochemistry revealing aberrant epithelial expression of MS4A12, LGR5 CDX2, NOX1 and SLC9A2 prior to development of carcinoma. Identified gene signatures identify aberrant epithelial expression of genes prior to cancer development using in-house custom designed gene expression multiplex assays. This approach may be used to assist in objective classification of disease initiation, staging, progression and therapeutic responses using biopsy material.

RNF43 is a tumour suppressor gene mutated in mucinous tumours of the ovary

Mucinous carcinomas represent a distinct morphological subtype which can arise from several organ sites, including the ovary, and their genetic characteristics are largely under-described. Exome sequencing of 12 primary mucinous ovarian tumours identified RNF43 as the most frequently somatically mutated novel gene, secondary to KRAS and mutated at a frequency equal to that of TP53 and BRAF. Further screening of RNF43 in a larger cohort of ovarian tumours identified additional mutations, with a total frequency of 2/22 (9%) in mucinous ovarian borderline tumours and 6/29 (21%) in mucinous ovarian carcinomas. Seven mutations were predicted to truncate the protein and one missense mutation was predicted to be deleterious by in silico analysis. Six tumours had allelic imbalance at the RNF43 locus, with loss of the wild-type allele. The mutation spectrum strongly suggests that RNF43 is an important tumour suppressor gene in mucinous ovarian tumours, similar to its reported role in mucinous pancreatic precancerous cysts.

An application of the 2-nitrobenzenesulfenyl method to proteomic profiling of human colorectal carcinoma: A novel approach for biomarker discovery

In the development of novel biomarkers, the proteomic approach is advantageous because using it the cancer-associated proteins can be directly identified. We previously developed a 2-nitrobenzenesulfenyl (NBS) method to improve quantitative proteome analysis. Here, we applied this method to proteomic profiling of colorectal carcinoma (CRC) to identify novel proteins with altered expression in CRC. Each pair of tumor and normal tissue specimens from 12 CRC patients was analyzed, and approximately 5000 NBS-labeled paired peaks were quantified. Peaks with altered signal intensities (>1.5-fold) and occurring frequently in the samples (>70%) were selected, and 128 proteins were identified by MS/MS analyses as differentially expressed proteins in CRC tissues. Many proteins were newly revealed to be CRC related; 30 were reported in earlier studies of CRC. Six proteins that were up-regulated in CRC (ZYX, RAN, RCN1, AHCY, LGALS1, and VIM) were further characterized and validated by Western blot and immunohistochemistry. All six were found to be CRC-localized, either in cancer cells or in stroma cells near the cancer cells. These results indicate that the proteins identified in this study are novel candidates for CRC markers, and that the NBS method is useful in proteome mining to discover novel biomarkers.

SPARC, FOXP3, CD8 and CD45 correlation with disease recurrence and long-term disease-free survival in colorectal cancer

Background

SPARC is a matricellular protein involved in tissue remodelling, cell migration and angiogenesis, while forkhead box P3 (FOXP3) protein functions as a transcription factor involved in immune cell regulation. Both SPARC and FOXP3 can play an anti-tumorigenic role in cancer progression. The aim was to determine if SPARC, FOXP3, CD8 and CD45RO expression levels are associated with colorectal cancer (CRC) stage, disease outcome and long-term cancer-specific survival (CSS) in stage II and III CRC.

Methods and Findings

SPARC expression was initially assessed in 120 paired normal and stage I-IV CRCs. Subsequently, approximately 1000 paired patient samples of stage II or III CRCs in tissue microarrays were stained for SPARC, FOXP3, CD8 or CD45RO. Proportional hazards modelling assessed correlations between these markers and clinicopathological data, including disease outcome and cancer specific survival (CSS). Both SPARC and FOXP3 expression were significantly greater in CRC than normal colon (p<0.0001). High SPARC expression correlated with good disease outcome (≥60 mths without disease recurrence, p = 0.0039) and better long-term CSS in stage II CRC (<0.0001). In stage III CRC, high SPARC expression correlated with better long-term CSS (p<0.0001) and less adjuvant chemotherapy use (p = 0.01). High FOXP3 correlated with a good disease outcome, better long-term CSS and less adjuvant chemotherapy use in stage II (p<0.0037, <0.0001 and p = 0.04 respectively), but not in stage III CRC. High CD8 and CD45RO expression correlated with better disease outcome in stage II CRC, and better CSS, but the differences were not as marked as for SPARC and FOXP3.

Conclusions

These data suggest that high SPARC and FOXP3 are associated with better disease outcome in stage II CRC and may be prognostic indicators of CSS. Further assessment of whether these markers predict patients at high risk of recurrence with stage II CRC and functional studies of these effects are underway

Custom design of a GeXP multiplexed assay used to assess expression profiles of inflammatory gene targets in normal colon, polyp, and tumor tissue

Colon cancers are characterized by aberrant gene expression signatures associated with disease initiation and progression. Identification of aberrant gene expression associated with colon carcinogenesis has increased significantly with application of gene array technologies. Downstream processing of these data has been hindered by the lack of robust multiplexed gene quantitative technologies facilitating study of the identified multiple gene targets. The GenomeLab Genetic Analysis System presents a novel technology platform for quantitative multiplexed gene expression analysis. This report describes the custom design of a GeXP multiplexed assay used to assess expression profiles of 14 inflammatory gene targets in normal, polyp, and tumor tissue. Characteristic normal, polyp, and tumor tissue gene expression profiles were obtained. Statistical analysis confirmed comparable relative quantitation of gene expression using the GeXP, macroarray, and single-plex real-time polymerase chain reaction assays. GeXP assays may be usefully applied in clinical and regulatory studies of multiple gene targets. This system permits custom-design options for relative quantification of multiple gene target expression, simultaneously in a single reaction, using nanogram quantities of total RNA template. The system provides an approach to advance the study of multiple targets identified from gene array analysis with potential for characterizing gene expression signatures in clinical diagnostics.

Reduced levels of hydroxylated, polyunsaturated ultra long-chain fatty acids in the serum of colorectal cancer patients: implications for early screening and detection

BACKGROUND

There are currently no accurate serum markers for detecting early risk of colorectal cancer (CRC). We therefore developed a non-targeted metabolomics technology to analyse the serum of pre-treatment CRC patients in order to discover putative metabolic markers associated with CRC. Using tandem-mass spectrometry (MS/MS) high throughput MS technology we evaluated the utility of selected markers and this technology for discriminating between CRC and healthy subjects.

METHODS

Biomarker discovery was performed using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). Comprehensive metabolic profiles of CRC patients and controls from three independent populations from different continents (USA and Japan; total n = 222) were obtained and the best inter-study biomarkers determined. The structural characterization of these and related markers was performed using liquid chromatography (LC) MS/MS and nuclear magnetic resonance technologies. Clinical utility evaluations were performed using a targeted high-throughput triple-quadrupole multiple reaction monitoring (TQ-MRM) method for three biomarkers in two further independent populations from the USA and Japan (total n = 220).

RESULTS

Comprehensive metabolomic analyses revealed significantly reduced levels of 28-36 carbon-containing hydroxylated polyunsaturated ultra long-chain fatty-acids in all three independent cohorts of CRC patient samples relative to controls. Structure elucidation studies on the C28 molecules revealed two families harbouring specifically two or three hydroxyl substitutions and varying degrees of unsaturation. The TQ-MRM method successfully validated the FTICR-MS results in two further independent studies. In total, biomarkers in five independent populations across two continental regions were evaluated (three populations by FTICR-MS and two by TQ-MRM). The resultant receiver-operator characteristic curve AUCs ranged from 0.85 to 0.98 (average = 0.91 +/- 0.04).

CONCLUSIONS

A novel comprehensive metabolomics technology was used to identify a systemic metabolic dysregulation comprising previously unknown hydroxylated polyunsaturated ultra-long chain fatty acid metabolites in CRC patients. These metabolites are easily measurable in serum and a decrease in their concentration appears to be highly sensitive and specific for the presence of CRC, regardless of ethnic or geographic background. The measurement of these metabolites may represent an additional tool for the early detection and screening of CRC.

Molecular prediction of early recurrence after resection of hepatocellular carcinoma

The prognosis of hepatocellular carcinoma (HCC) remains poor. Vascular invasion, tumour multiplicity and large tumour size are the conventional poor prognostic indicators related to early recurrence. However, it is difficult to predict prognosis of each HCC in the absence of these indicators. The purpose of this study is to predict early recurrence of HCC after radical resection based on whole human gene expression profiling. Microarray analyses were performed in 139 HCC primary tumours. A total of 88 cases lacking the conventional poor prognostic indicators were analysed to establish a molecular prediction system characteristic for early recurrence in 42 training cases with two polarised prognoses, and to test its predictive performance in 46 independent cases (group C). Subsequently, this system was applied to another 51 independent cases with some poor prognostic indicators (group D). The molecular prediction system accurately differentiated HCC cases into poor and good prognoses in both the independent group C (disease-free survival [DFS]: p=0.029, overall survival [OS]: p=0.0043) and independent group D (DFS: p=0.0011, OS, p=0.035). Multivariate Cox regression analysis indicated that the clinical value of molecular prediction system was an independent prognostic factor (p<0.0001, hazard ratio=3.29). Gene expression pattern related to early intrahepatic recurrence inherited in the primary HCC tumour can be useful for the prediction of prognosis.

Gene profiling of colonic serrated adenomas by using oligonucleotide microarray

PURPOSE

The serrated pathway has been proposed as an important concept explaining the colorectal carcinogenesis. However, the key molecules of the serrated pathway which contribute to the formation of serrated polyp are still poorly understood. To elucidate the molecular genetic basis of the serrated pathway, we performed an initial oligonucleotide microarray to analyze the gene expression pattern of patients with colonic serrated adenomas.

METHODS

Oligonucleotide microarrays containing 3,096 genes were used to compare individual gene profiles of serrated adenoma samples (n = 5) and normal mucosal samples obtained from colon in patients by colonoscopy. Three genes were further investigated by means of quantitative reverse transcription polymerase chain reaction (RT-PCR) for validation. The Significance Analysis of Microarray (SAM) package method was used to identify differentially expressed genes.

RESULTS

Compared with normal colonic mucosa tissue, 73 genes were upregulated at least twofold, and 51 genes were downregulated by at least 50% in serrated polyp samples (approximately 3.6% of genes evaluated) with a p-value of less than 0.05. Moreover, some of the gene expression patterns observed were similar to those of previously reported in colorectal cancer, suggesting reinforcement of tendency to malignancy. Three genes (TNFRSF10A, BENE, RARA) with strongly significant expression intensities in the oligonucleotide microarray results were validated by quantitative RT-PCR. TNFRSF10A had upregulated expression patterns while BENE, RARA had downregulated expression pattern.

CONCLUSION

Although our report presents only preliminary results, we think they provide important data regarding serrated adenomas not only to better define the precise mechanism of genetic changes involved as the main member in serrated pathway of colorectal carcinogenesis but also to yield practical information for identifying optimized diagnostic modalities.

Missing value imputation for microarray gene expression data using histone acetylation information

BACKGROUND

It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages.

RESULTS

The paper explores the feasibility of doing missing value imputation with the help of gene regulatory mechanism. An imputation framework called histone acetylation information aided imputation method (HAIimpute method) is presented. It incorporates the histone acetylation information into the conventional KNN(k-nearest neighbor) and LLS(local least square) imputation algorithms for final prediction of the missing values. The experimental results indicated that the use of acetylation information can provide significant improvements in microarray imputation accuracy. The HAIimpute methods consistently improve the widely used methods such as KNN and LLS in terms of normalized root mean squared error (NRMSE). Meanwhile, the genes imputed by HAIimpute methods are more correlated with the original complete genes in terms of Pearson correlation coefficients. Furthermore, the proposed methods also outperform GOimpute, which is one of the existing related methods that use the functional similarity as the external information.

CONCLUSION

We demonstrated that the using of histone acetylation information could greatly improve the performance of the imputation especially at high missing percentages. This idea can be generalized to various imputation methods to facilitate the performance. Moreover, with more knowledge accumulated on gene regulatory mechanism in addition to histone acetylation, the performance of our approach can be further improved and verified.

Involvement of ribonucleotide reductase M1 subunit overexpression in gemcitabine resistance of human pancreatic cancer

Pancreatic cancer is the most lethal of all solid tumors partially because of its chemoresistance. Although gemcitabine is widely used as a first selected agent for the treatment of this disease despite low response rate, molecular mechanisms of gemcitabine resistance in pancreatic cancer still remain obscure. The aim of this study is to elucidate the mechanisms of gemcitabine resistance. The 81-fold gemcitabine resistant variant MiaPaCa2-RG was selected from pancreatic cancer cell line MiaPaCa2. By microarray analysis between MiaPaCa2 and MiaPaCa2-RG, 43 genes (0.04%) were altered expression of more than 2-fold. The most upregulated gene in MiaPaCa2-RG was ribonucleotide reductase M1 subunit (RRM1) with 4.5-fold up-regulation. Transfection with RRM1-specific RNAi suppressed more than 90% of RRM1 mRNA and protein expression. After RRM1-specific RNAi transfection, gemcitabine chemoresistance of MiaPaCa2-RG was reduced to the same level of MiaPaCa2. The 18 recurrent pancreatic cancer patients treated by gemcitabine were divided into 2 groups by RRM1 levels. There was a significant association between gemcitabine response and RRM1 expression (p = 0.018). Patients with high RRM1 levels had poor survival after gemcitabine treatment than those with low RRM1 levels (p = 0.016). RRM1 should be a key molecule in gemcitabine resistance in human pancreatic cancer through both in vitro and clinical models. RRM1 may have the potential as predictor and modulator of gemcitabine treatment.

cDNA array analysis for prediction of hepatic metastasis of colorectal carcinoma

PURPOSE

Distant metastasis is a significant prognostic factor of colon carcinoma. Adjuvant chemotherapy has been shown to decrease its recurrence. However, there are no definitive methods for the diagnosis of hepatic recurrence after potentially curative surgery. The aim of this study was to evaluate the accuracy of mRNA expression profiling using samples obtained from primary tumors to predict hepatic recurrence.

METHODS

Patients with stage III colorectal carcinoma without any recurrence for at least 5 years (group A: n = 9) and patients with stage IV carcinoma with hepatic metastasis (group B: n = 10) were included in this study. Tissue samples were collected from the primary tumor and adjacent normal colonic mucosa at the time of surgery in each patient. Total RNA was extracted and the mRNA expression profile was examined using a cDNA macroarray.

RESULTS

A hierarchical clustering analysis revealed a dendrogram in which the patients were divided into two clusters. One cluster consisted of seven patients in group A and two in group B. The other consisted of two patients in group A and eight in group B. Therefore, the positive and negative predictive value of hierarchical clustering analysis for hepatic metastasis was 80.0% and 78.8%, respectively. Fifteen genes were revealed to be upregulated and 12 were downregulated in group B. The upregulated genes included CCNA2, TP53, and MDM2, while the downregulated genes included CDH1, GADD45A, and BCL2L2.

CONCLUSIONS

mRNA expression profiling by a cDNA array analysis of specimens obtained from primary tumors was found to be useful for distinguishing patients with and without hepatic metastasis. This method is expected to contribute to the identification of patients at high risk for hepatic recurrence, while also helping in the administration of intensive adjuvant chemotherapy for such high risk patients.

Iterated local least squares microarray missing value imputation

Microarray gene expression data often contains multiple missing values due to various reasons. However, most of gene expression data analysis algorithms require complete expression data. Therefore, accurate estimation of the missing values is critical to further data analysis. In this paper, an Iterated Local Least Squares Imputation (ILLSimpute) method is proposed for estimating missing values. Two unique features of ILLSimpute method are: ILLSimpute method does not fix a common number of coherent genes for target genes for estimation purpose, but defines coherent genes as those within a distance threshold to the target genes. Secondly, in ILLSimpute method, estimated values in one iteration are used for missing value estimation in the next iteration and the method terminates after certain iterations or the imputed values converge. Experimental results on six real microarray datasets showed that ILLSimpute method performed at least as well as, and most of the time much better than, five most recent imputation methods.

Stage-specific alterations of the genome, transcriptome, and proteome during colorectal carcinogenesis

To identify sequential alterations of the genome, transcriptome, and proteome during colorectal cancer progression, we have analyzed tissue samples from 36 patients, including the complete mucosa-adenoma-carcinoma sequence from 8 patients. Comparative genomic hybridization (CGH) revealed patterns of stage specific, recurrent genomic imbalances. Gene expression analysis on 9K cDNA arrays identified 58 genes differentially expressed between normal mucosa and adenoma, 116 genes between adenoma and carcinoma, and 158 genes between primary carcinoma and liver metastasis (P < 0.001). Parallel analysis of our samples by CGH and expression profiling revealed a direct correlation of chromosomal copy number changes with chromosome-specific average gene expression levels. Protein expression was analyzed by two-dimensional gel electrophoresis and subsequent mass spectrometry. Although there was no direct match of differentially expressed proteins and genes, the majority of them belonged to identical pathways or networks. In conclusion, increasing genomic instability and a recurrent pattern of chromosomal imbalances as well as specific gene and protein expression changes correlate with distinct stages of colorectal cancer progression. Chromosomal aneuploidies directly affect average resident gene expression levels, thereby contributing to a massive deregulation of the cellular transcriptome. The identification of novel genes and proteins might deliver molecular targets for diagnostic and therapeutic interventions.

Identification of the differential expressive tumor associated genes in rectal cancers by cDNA microarray

AIM: To identify tumor associated genes of rectal cancer and to probe the application possibility of gene expression profiles for the classification of tumors.

METHODS: Rectal cancer tissues and their paired normal mucosa were obtained from patients undergoing surgical resection of rectal cancer. Total RNA was extracted using Trizol reagents. First strand cDNA synthesis was indirectly labeled with aminoallyl-dUTP and coupled with Cy3 or Cy5 dye NHS mono-functional ester. After normalization to total spots, the genes which background subtracted intensity did not exceed 2 SD above the mean blank were excluded. The data were then sorted to obtain genes differentially expressed by ≥ 2 fold up or down in at least 5 of the 21 patients.

RESULTS: In the 21 rectal cancer patients, 23 genes were up-regulated in at least 5 samples and 15 genes were down-regulated in at least 5 patients. Hierachical cluster analysis classified the patients into two groups according to the clinicopathological stage, with one group being all above stage II and one group all below stage II.

CONCLUSION: The up-regulated genes and down-regulated genes may be molecular markers of rectal cancer. The expression profiles can be used for classification of rectal cancer.

Identification of molecular targets for immunotherapy of patients with head and neck squamous cell carcinoma

To identify molecular targets for immunotherapy of head and neck squamous cell carcinoma (HNSCC) patients, we analyzed gene expression profile in matched tumor (HN) and normal fibroblast (FB) cell lines established from a HNSCC patient using microarray technique followed by real-time RT-PCR. Screening against a series of established normal and malignant cell lines followed by screening against a panel of normal human tissues led to the identification of 7 genes (AREG, CDH3, KLK10, NmU, SLPI, ANAX3 and MAL2), which were over-expressed at least 10-fold in tumors over any of the normal tissues. We determined the expression of mRNA encoding these genes against a panel of 15 HNSCC primary tumor samples. Relative expression of these genes was at least 20-fold. Expression of AREG, CDH3, KLK10, NmU and SLPI at the protein level was determined by immunohistochemistry in seven supraglottic laryngeal cancer specimens. All five proteins were expressed in these tumor samples with high intensity. We conclude that these molecules are potential targets for immunotherapy of HNSCC patients.

Expression and genomic profiling of colorectal cancer

Colorectal cancer still represents a paradigm for the elucidation of the cellular, genetic and molecular mechanisms that underly solid tumor initiation, progression to malignancy, and metastasis to distal organ sites. The relative ease with which pathological specimens can be obtained by either surgery or endoscopy from different stages of tumor progression has facilitated the application of omics technologies to allow the genome-wide analysis both at the RNA (gene expression) and DNA (aneuploidy) levels. Here, we have reviewed the multiplicity of studies appeared to date in the scientific literature on the expression and genomic analysis of colorectal cancer, and attempted an integration of the profiling data generated and made available in the public domain. This approach is likely to pinpoint specific chromosomal loci and the corresponding genes which (i) play rate-limiting roles in colorectal cancer, (ii) represent putative diagnostic and prognostic markers for the accurate prediction of clinical outcome and response to treatment, and (iii) encompass potential therapeutic targets. Moreover, cross-species data mining and integration of the human colorectal cancer profiles with those obtained from mouse models of intestinal tumorigenesis will even more contribute to the elucidation of highly conserved pathways and cellular functions underlying malignancy in the GI tract. Notwithstanding the above promises, tumor heterogeneity, limited cohort sizes, and methodological differences among experimental and bioinformatic approaches still poses main obstacles towards the optimal utilization and integration of omics profiles.

Comparative transcriptome maps: a new approach to the diagnosis of colorectal carcinoma patients using cDNA microarrays

The progression of colorectal cancer involves accumulation of various genetic and epigenetic events that dramatically change gene expression. The aim of this study was to investigate a possible new approach to the diagnosis of colorectal carcinoma patients, based on their gene expression profiles. Human 19K cDNA microarrays were used to analyze the gene expression profiles of 18 colorectal carcinoma patients. Transcriptome maps (TMs) were analyzed to detect chromosomal regions that could serve as potential diagnostic markers for colon cancer. A comparison of TMs showed chromosome regions with conserved changes of gene expression typical of colorectal cancer in general, and also patient-specific variable regions. We identified 195 genes with significantly altered expression in colon cancer. Functional analysis of the regulated genes distinguished three main categories: biological processes, cellular components, and molecular functions. We found that different patients had chromosome regions characterized by very similar changes of gene expression, probably linked to the most fundamental events in carcinogenesis. On the other hand, variable chromosome regions can be patient-specific. The variable regions may provide further information on the individual pathogenesis and prognosis of the patient. Comparison of TMs is proposed as a tool to facilitate diagnosis and treatment planning for individual patients.

A novel function of differentiation revealed by cDNA microarray profiling of p75NTR-regulated gene expression

The expression of the p75 neurotrophin receptor (p75NTR) is diminished in epithelial cells during progression of prostate cancer in vivo and in vitro. Previous studies have demonstrated a role for p75NTR as a tumor suppressor in prostate growth. To better understand the molecular mechanism of p75(NTR) on tumor suppression, we utilized a complementary deoxyribonucleic acid microarray composed of approximately 6,000 human cancer-related genes to determine the gene expression pattern altered by re-introduction of p75NTR into PC-3 prostate tumor cells. Comparison of the transcripts in the neo and p75NTR-transfected cells revealed 52 differentially expressed genes, of which 21 were up-regulated and 31 were down-regulated in the presence of p75NTR. Based on the known biological functions of the p75NTR-regulated genes, we observed that p75NTR modulated the expression of genes that are critically involved in the regulation of differentiation as well as cell adhesion, signal transduction, apoptosis, tumor cell invasion, and metastasis. Several differentially expressed genes identified by microarray were selected for confirmation using quantitative real-time polymerase chain reaction. Immunoblot analysis further confirmed increased cellular retinoic acid-binding protein I (CRABPI) and IGFBP5 protein levels and decreased level of PLAUR protein with increasing p75NTR protein expression. As CRABPI was elevated far more than any other genes, we observed that the retinoids, all-trans retinoic acid and 9-cis retinoic acid, that bind CRABPI, promoted nitroblue tetrazolium-associated functional cell differentiation in p75NTR PC-3 cells, but not in neo control PC-3 cells. Subsequent examination of the retinoic acid receptors (RARs) expression levels demonstrated an absence of RAR-beta in the neo control cells and re-expression in the p75NTR expressing cells, consistent with previous findings where RAR-beta is believed to play a critical role as a tumor suppressor gene that is lost during de-differentiation of prostate epithelial cells. Whereas the RAR-alpha and -gamma protein levels remained unchanged, retinoid X receptor (RXR)-alpha and -beta also exhibited increasing protein levels with re-expression of the p75NTR protein. Moreover, the ability of p75NTR siRNA to knockdown levels of RAR-beta, RXR-alpha, and RXR-beta supports the specificity of the functional involvement of p75NTR in differentiation. Hence, re-expression of the p75NTR appears to partially reverse de-differentiation of prostate cancer cells by up-regulating the expression of CRABPI for localized sequestration of retinoids that are available to newly up-regulated RAR-beta, RXR-alpha, and RXR-beta.

Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding scheme

Background

Gene expression profiling has become a useful biological resource in recent years, and it plays an important role in a broad range of areas in biology. The raw gene expression data, usually in the form of large matrix, may contain missing values. The downstream analysis methods that postulate complete matrix input are thus not applicable. Several methods have been developed to solve this problem, such as K nearest neighbor impute method, Bayesian principal components analysis impute method, etc. In this paper, we introduce a novel imputing approach based on the Support Vector Regression (SVR) method. The proposed approach utilizes an orthogonal coding input scheme, which makes use of multi-missing values in one row of a certain gene expression profile and imputes the missing value into a much higher dimensional space, to obtain better performance.

Results

A comparative study of our method with the previously developed methods has been presented for the estimation of the missing values on six gene expression data sets. Among the three different input-vector coding schemes we tried, the orthogonal input coding scheme obtains the best estimation results with the minimum Normalized Root Mean Squared Error (NRMSE). The results also demonstrate that the SVR method has powerful estimation ability on different kinds of data sets with relatively small NRMSE.

Conclusion

The SVR impute method shows better performance than, or at least comparable with, the previously developed methods in present research. The outstanding estimation ability of this impute method is partly due to the use of the most missing value information by incorporating orthogonal input coding scheme. In addition, the solid theoretical foundation of SVR method also helps in estimation of performance together with orthogonal input coding scheme. The promising estimation ability demonstrated in the results section suggests that the proposed approach provides a proper solution to the missing value estimation problem. The source code of the SVR method is available from for non-commercial use.

Web-based data warehouse on gene expression in human colorectal cancer

Based on biomedical literature databases, we tried a first step for constructing a gene expression "data warehouse" specific to human colorectal cancer (CRC). Results of genome-wide transcriptomic research were available from 12 studies, using various technologies, namely, SAGE, cDNA and oligonucleotide arrays, and adaptor-tagged amplification. Three studies analyzed CRC cell lines and nine studies of human samples. The total number of patients was 144. Out of 982 up- or down-regulated genes, 863 (88%) were found to be differentially expressed in a single study, 88 in two studies, 22 in three studies, 7 in four studies, and only 2 genes in six studies. Eight large-scale proteomics studies were published in CRC, using 2-D-, SDS- or free-flow electrophoresis, involving only 11 patients. Out of 408 differentially expressed proteins, 339 (83%) were found to be differentially expressed only in a single study, 16 in three studies, 10 in four studies, 3 in five, and 1 in eight studies. Confirmation at proteome level of results obtained with large-scale transcriptomics studies was possible in 25%. This proportion was higher (67%) for reproducing proteome results using transcriptomics technologies. Obviously, reproducibility and overlapping between published gene expression results at proteome and transcriptome level are low in human CRC. Thus, the development of standardized processes for collecting samples, storing, retrieving, and querying gene expression data obtained with different technologies is of central importance in translational research.

Ring finger protein 43 as a new target for cancer immunotherapy

We have performed genome-wide exploration by using cDNA microarray profiling, and successfully identified a new tumor-associated antigen (TAA) that can induce potent cytotoxic T lymphocytes (CTLs) specific to tumor cells. In our preceding study, we identified multiple new genes by using gene expression profiling with a genome-wide cDNA microarray containing 23,040 genes. Among them, we selected RNF43 (ring finger protein 43) as a promising candidate for a TAA expressed by colon cancer cells. In this study, we examined whether the RNF43 protein contains antigenic epitope peptides restricted to HLA-A*0201 or HLA-A*2402. The CTL clones were successfully induced with stimulation by using the peptides binding to HLA-A*0201 (ALWPWLLMA and ALWPWLLMAT) and HLA-A*2402 (NSQPVWLCL), and these CTL clones showed the cytotoxic activity specific to not only the peptide-pulsed targets but also the tumor cells expressing RNF43 and respective HLAs. Lytic activities mediated by two HLA-A2-restricted epitopes were marginal, whereas tumor lysis mediated by the HLA-A24 epitope was clearly better. These findings might be caused by the poor natural presentation of RNF43-11(IX) and RNF43-11(X) by tumors or poor T-cell receptor avidity for these specific epitopes. These results strongly suggest that RNF43 is a new TAA of colon cancer. Furthermore, these results also suggest that our strategy might be a promising one to efficiently discover clinically useful TAAs.

Gene expression profile induced by BCNU in human glioma cell lines with differential MGMT expression

Chemotherapy with the alkylating agent BCNU (1,3-bis (2-chloroethyl)-1-nitrosourea) is the most commonly used chemotherapeutic agent for gliomas. However, the usefulness of this agent is limited because tumor cell resistance to BCNU is frequently found in clinical brain tumor therapy. The O6-methylguanine-DNA methyltransferase protein (MGMT) reverses alkylation at the O6 position of guanine and we have reported the role of MGMT in the response of brain tumors to alkylating agents. However, the different mechanisms underlying the patterns related to MGMT remain unclear. To better understand the molecular mechanism by which BCNU exerts its effect in glioma cell lines according MGMT expression, we used microarray technology to interrogate 3800 known genes and determine the gene expression profiles altered by BCNU treatment. Our results showed that treatment with BCNU alters the expression of a diverse group of genes in a time-dependent manner. A subset of gene changes was found common in both glioma cell lines and other subset is specific of each cell line. After 24 h of BCNU treatment, up-regulation of transcription factors involved in the nucleation of both RNA polymerase II and III transcription initiation complexes was reported. Interestingly, BCNU promoted the expression of actin-dependent regulators of chromatin. Similar effects were found with higher BCNU doses in MGMT+ cell line showing a similar mechanism that in MGMT-deficient cell with standard doses. Our data suggest that human glioma cell lines treated with BCNU, independently of MGMT expression, show changes in the expression of cell cycle and survival-related genes interfering the transcription mechanisms and the chromatin regulation.

Common denominator genes that distinguish colorectal carcinoma from normal mucosa

PURPOSE

Microarray technology has been used by a growing number of investigators and several studies have been published that list hundreds of genes differentially expressed by colorectal carcinoma (CRC) and normal mucosa (MC). On the basis of our own and other investigators' microarray data, our goal was to identify a common denominator gene cluster distinguishing CRC from MC.

METHODS

Thirty GeneChips (HG-U133A, Affymetrix) were hybridized, 20 with RNA of CRC stages I-IV (UICC) and 10 with MC. Expression signals showing at least a 4-fold difference between CRC and MC (p<0.01) were identified as differentially expressed. In addition, in our integrative data analysis approach only those genes whose expression was altered simultaneously in at least 2 of 5 recently published studies were subjected to an unsupervised hierarchical cluster analysis.

RESULTS

We detected 168 up- and 283 down-regulated genes in CRC relative to MC. Twenty-three genes were filtered from the five articles reviewed. An unsupervised hierarchical cluster analysis of these 23 genes confirmed the high specificity of these genes to differentiate between CRC and MC in our microarray data.

CONCLUSIONS

Colorectal cancer and mucosa could be clearly separated by 23 genes selected for being differentially expressed more than once in a recent literature review. These genes represent a common denominator gene cluster that can be used to distinguish colorectal MC from CRC.

Gene expression profiling of colorectal adenomas and early invasive carcinomas by cDNA array analysis

It is generally accepted that most colorectal carcinomas arise in pre-existing adenomas. Morphologically, colorectal adenomas can be divided into two groups, protruded type and flat type. The aim of this study was to clarify relevant alterations of gene expression associated with the early stage of colorectal carcinogenesis. Using cDNA array, we analysed the expression profiles of 550 cancer-related genes in 36 colorectal adenomas (18 flat-type and 18 protruded-type adenomas) and 14 early invasive carcinomas. Among the 550 genes, we chose 32 genes the average expression levels of which were at least three-fold up- or downregulated in tumour tissues compared with levels in matched normal tissues. A total of 13 and 19 genes were identified as up- and downregulated genes in tumour tissues, respectively. Among the upregulated genes, the average expression levels of E1AF, bone morphogenic protein (BMP)-4, insulin-like growth factor (IGF)-2, inducible nitric oxide synthase (iNOS), tissue inhibitors of metalloproteinase (TIMP)-1, Smad4, and nm23 in tumour tissues were over five times higher than those in matched normal tissues. Colorectal adenomas and early invasive carcinomas were divided into two major clusters by clustering analysis. Moreover, flat- and protruded-type adenomas were divided into two major clusters by clustering analysis. The expression profiles obtained by the cDNA array clearly indicate that colorectal adenomas and early invasive carcinomas have specific expression profiles. Likewise, the gene expression profiles of flat- and protruded-type adenomas are different. These results indicate that molecular classification of early colorectal tumours by a cDNA array is feasible.

Gene expression profiling for molecular staging and prognosis prediction in colorectal cancer

A key issue for patients undergoing surgery for colorectal cancer is the accurate prediction of treatment outcome. Currently, classification of a tumor by histopathologic stage is the most accurate prognostic factor for the risk assessment of treatment failure. However, despite improved histologic techniques and the application of novel immunohistochemical and molecular techniques, it is still not possible to delineate the underlying biochemical and genetic events that predict clinical outcome for individual cancer patients. One reason for this lack of progress is that the factors which determine the metastatic potential of a primary tumor are still unknown. This reality, coupled to dramatic technological developments in the field of expression profiling, has started a paradigm shift in the staging of colorectal cancers. It has raised expectations that genetic and/or transcriptome profiling of the primary tumor will result in the identification of prognostic determinants relevant to the individual patient. In turn, this may allow a clinically relevant definition of patient subgroups based on individual molecular parameters for rational decision making regarding choice of therapy.

Missing value estimation for DNA microarray gene expression data: local least squares imputation

MOTIVATION

Gene expression data often contain missing expression values. Effective missing value estimation methods are needed since many algorithms for gene expression data analysis require a complete matrix of gene array values. In this paper, imputation methods based on the least squares formulation are proposed to estimate missing values in the gene expression data, which exploit local similarity structures in the data as well as least squares optimization process.

RESULTS

The proposed local least squares imputation method (LLSimpute) represents a target gene that has missing values as a linear combination of similar genes. The similar genes are chosen by k-nearest neighbors or k coherent genes that have large absolute values of Pearson correlation coefficients. Non-parametric missing values estimation method of LLSimpute are designed by introducing an automatic k-value estimator. In our experiments, the proposed LLSimpute method shows competitive results when compared with other imputation methods for missing value estimation on various datasets and percentages of missing values in the data.

AVAILABILITY

The software is available at http://www.cs.umn.edu/~hskim/tools.html

CONTACT

hpark@cs.umn.edu

Microarray gene expression profiling and analysis in renal cell carcinoma

Background

Renal cell carcinoma (RCC) is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays.

Methods

Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC.

Results

Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR). Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved.

Conclusions

This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most notably, genes involved in cell adhesion were dominantly up-regulated whereas genes involved in transport were dominantly down-regulated. This study reveals significant gene expression alterations in key biological pathways and provides potential insights into understanding the molecular mechanism of renal cell carcinogenesis.

Gene expression profiling reveals novel targets of estramustine phosphate in prostate cancer cells

Estramustine phosphate (EMP) is a compound widely used for the treatment of hormone-refractory prostate cancer. In order to better understand the precise molecular mechanism(s) by which EMP exerts its effects on hormone-resistant PC3 prostate cancer cells, we have utilized microarray to interrogate 22,215 known genes to determine the gene expression profiles altered by EMP treatment. The purpose of this investigation was to identify gene expression profile first and then in future studies determine the specific role of these genes in EMP-induced apoptosis in prostate cancer cells. We found a total of 726 genes which showed >2 fold change after EMP treatment. Clustering analysis showed 12 different types of expression alteration. These genes were also subjected to cluster analysis according to their biological functions. We found that EMP regulated the expression of genes, which are critically involved in the regulation of cell growth, cell cycle, apoptosis, iron homeostasis, cytoskeleton and cell signaling transduction. Real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR) analysis was used to confirm the results of microarray, and the results of real-time quantitative RT-PCR were consistent with the microarray data. From these results, we conclude that EMP caused changes in the expression of a large number of genes that are related to the control of cell survival and physiological behaviors. The gene expression profiles may provide comprehensive molecular mechanism(s) by which EMP exerts its pleiotropic effects on prostate cancer cells. EMP-induced regulation of these genes may be further exploited for devising therapeutic strategies for prostate cancer.

Tissue preparation for gene expression profiling of colorectal carinoma: three alternatives to laser microdissection with preamplification

Colorectal-carcinoma specimens are heterogeneous and include areas of nonmalignant mucosal and connective tissue. For those study designs in which laser microdissection and RNA preamplification are impracticable, the optimal yield of genuine cancer RNA is a key factor in gene-expression analysis. In this study we compared alternative methods of tissue purification. Three contiguous 0.5-cm(3) samples taken from an advanced primary adenocarcinoma of the sigmoid colon were processed immediately after surgery with the use of the following methods: (1) cryotomy after manual dissection (CMD), (2) microscopically assisted manual dissection (MAMD), and (3) tumor-cell isolation with the use of Ber-EP4 antibodies and Dynabeads (Dynal Biotech GmbH, Hamburg, Germany; technique abbreviated as DB). We generated gene-expression profiles with the use of GeneChip technology (Affymetrix, Santa Clara, Calif) and recorded preparation times, costs, and RNA quantity and quality. CMD took 60 minutes, MAMD 180 minutes, and DB 90 minutes to isolate 22, 8, and 23 microg of RNA, respectively. Expenses for materials amounted to 41, 23, and 91 US dollars for CMD, MAMD, and DB, respectively. The 3'/5' ratio, as determined with the GeneChips, for GAPDH/beta-actin was 1.01:1.03 for CMD, 1.13:1.28 for MAMD, 1.43:1.68 for DB, K-ras, APC, smad 2, transforming growth factor-beta, and p53 were marked as present in all cases, with the exception of APC, which was graded as marginal on DB. The correlation values of gene-expression profiles were 91% (CMD/DB), 93% (CMD/MAMD), and 97% (DB/MAMD). All 3 methods provided enough RNA, of sufficient quality, for gene-expression microarray analysis in colorectal carcinoma. Cross-methodologic analyses of array data should not be performed uncritically.

Differential expression of DOC-1 in microsatellite-unstable human colorectal cancer

The precise genetic mechanism of malignant transformation in DNA mismatch repair deficient, microsatellite-unstable colorectal cancer (CRC) has yet to be elucidated. We employed cDNA microarray to identify patterns of gene expression among CRC cell lines and to compare directly lines with and without microsatellite instability. This study was undertaken to test the hypothesis that microsatellite-unstable CRC cell lines demonstrate specific patterns of gene expression that differ significantly from those observed among microsatellite-stable CRC. Multiple differential expression patterns were identified. Genes demonstrating differential expression included deleted-in-oral-cancer-1 (DOC-1), a highly conserved growth suppressor. DOC-1 expression correlated with microsatellite status, with significantly decreased expression in microsatellite-unstable cell lines and constitutive expression in microsatellite-stable cell lines. We also observed alterations in the biologic behavior of p12(DOC-1)-deficient cell lines, with increased S phase and decreased apoptosis compared to microsatellite-stable (DOC-1+) cell lines. Transfection of p12(DOC-1) into SW48, which lacks p12(DOC-1) expression, resulted in cell cycle and apoptosis profiles similar to other p12(DOC-1)+ cell lines. These results support the hypothesis that microsatellite-unstable CRC is characterized by novel patterns of gene expression different from those associated with microsatellite-stable CRC, and demonstrate that p12(DOC-1) has tumor suppressor potential in colon epithelial cells.

Replicating parvoviruses that target colon cancer cells

The wnt signaling pathway is constitutively activated in colon tumors by mutations in the adenomatous polyposis coli and beta-catenin genes. We have modified the minute virus of mice (MVM) P4 promoter to make it responsive to wnt signaling by inserting binding sites for the heterodimeric beta-catenin/Tcf transcription factor. In luciferase assays we can see up to 20-fold selectivity of Tcf mutant P4 promoters for cells with activated wnt signaling. Hybrid MVM/H-1 viruses containing Tcf mutant promoters were tested for NS1 expression, viral DNA replication, virus replication, and cytopathic effect on colon, lung, kidney, and cervical cancer cell lines. Activation of the wnt pathway by expression of Delta N-beta-catenin increased NS1 expression and viral burst size in 293T and H1299 lung cancer cells, showing that the Tcf mutant P4 promoter can respond to wnt signals in the context of the virus. Compared to the parental virus, the burst size of the Tcf mutant viruses was reduced at least 1,000-fold in H1299, 293T, NB324K, and HeLa cells, which have inactive wnt signaling pathways. The burst size and cytopathic effect of the Tcf viruses was near wild-type levels in SW480 and Isreco1 colon cancer cell lines, which have high Tcf activity. The high specificity of these viruses should permit the development of H-1 virus-based vectors which combine high safety and greater efficacy in cancer therapy.

Difference of gene expression profiles between esophageal carcinoma and its pericancerous epithelium by gene chip

AIM: To study the difference of gene expression between esophageal carcinoma and its pericancerous epithelium and to screen novel associated genes in the early stage of esophageal carcinogenesis by cDNA microarray.

METHODS: Total RNA was extracted with the original single step way from esophageal carcinoma, its pericancerous epithelial tissue and normal esophageal epithelium far from the tumor. The cDNA retro-transcribed from equal quantity of mRNA was labeled with Cy5 and Cy3 fluorescence functioning as probes. The mixed probes were hybridized with two pieces of BioDoor 4096 double dot human whole gene chip. Fluorescence signals were scanned by ScanArray 3000 laser scanner and farther analyzed by ImaGene 3.0 software with the digital computer.

RESULTS: (1) A total of 135 genes were screened out, in which 85 and 50 genes whose the gene expression levels (fluorescence intensity) in esophageal carcinoma were more than 2 times and less than 0.5 times respectively compared with the normal esophageal epithelium. (2) There were also total 31 genes, among then 27 and 4 whose expressions in pericancerous tissue were 2-fold up-regulated and 0.5-fold down-regulated respectively compared with normal esophageal epithelium. (3) There were 13 genes appeared simultaneously in both pericancerous epithelium and esophageal carcinoma, while another 18 genes existed in pericancerous epithelium only.

CONCLUSION: With the parallel comparison among these three gene profiles, it was shown that (1). A total of 135 genes, Whose expression difference manifested as fluorescence intensity were more than 2 times between esophageal carcinoma and normal esophageal epithelium, were probably related to the occurrence and development of the esophageal carcinoma. (2). The 31 genes showing expression difference more than 2 times between pericancerous and normal esophageal epithelium might be relate to the promotion of esophageal pericancerosis and its progress. The present study illustrated that by using the gene chip to detect the difference of gene expression profiles might be of benefit to the gene diagnosis, treatment and prevention of esophageal carcinoma.

Identification of expressed genes linked to malignancy of human colorectal carcinoma by parametric clustering of quantitative expression data

BACKGROUND

Individual human carcinomas have distinct biological and clinical properties: gene-expression profiling is expected to unveil the underlying molecular features. Particular interest has been focused on potential diagnostic and therapeutic applications. Solid tumors, such as colorectal carcinoma, present additional obstacles for experimental and data analysis.

RESULTS

We analyzed the expression levels of 1,536 genes in 100 colorectal cancer and 11 normal tissues using adaptor-tagged competitive PCR, a high-throughput reverse transcription-PCR technique. A parametric clustering method using the Gaussian mixture model and the Bayes inference revealed three groups of expressed genes. Two contained large numbers of genes. One of these groups correlated well with both the differences between tumor and normal tissues and the presence or absence of distant metastasis, whereas the other correlated only with the tumor/normal difference. The third group comprised a small number of genes. Approximately half showed an identical expression pattern, and cancer tissues were classified into two groups by their expression levels. The high-expression group had strong correlation with distant metastasis, and a poorer survival rate than the low-expression group, indicating possible clinical applications of these genes. In addition to c-yes, a homolog of a viral oncogene, prognostic indicators included genes specific to glial cells, which gives a new link between malignancy and ectopic gene expression.

CONCLUSIONS

The malignancy of human colorectal carcinoma is correlated with a unique expression pattern of a specific group of genes, allowing the classification of tumor tissues into two clinically distinct groups.

Direct comparison of microarray gene expression profiles between non-amplification and a modified cDNA amplification procedure applicable for needle biopsy tissues

Global gene expression profiling by cDNA microarray analysis has been used to discover the biomarkers for early diagnosis of various cancers, subclassing cancer type, and prediction of patient's treatment outcome. The information provided by gene expression profiling may contribute to the design of molecular mechanism-based strategies for cancer prevention and/or treatment. However, the standard procedure for cDNA microarray analysis requires 5mug of good quality total RNA as starting material for each target preparation reaction. Thus, there is a limit for needle biopsy samples, laser capture microdissected tissues, or flow-sorted cells to successfully utilize the microarray technology. In order to profile the gene expression of needle biopsy tissue, we have modified the standard protocol by carrying out cDNA amplification after cDNA synthesis. We compared percentage present calls, absent calls, reproducibility, and concordance in needle biopsy samples processed by standard microarray protocol (cDNA non-amplification method) and our modified protocol (cDNA amplification method). The results showed that cDNA amplification method provided high reproducibility, representation, and concordance with the standard cDNA non-amplification method. We have successfully analyzed the gene expression profiles of needle biopsy tissues using the modified method without significantly changing the expression profiles. These results suggest that the global gene expression profiles of small biopsy samples can be achieved by our modified method to facilitate the analysis of gene expression profiles for clinical application.

Gene expression profiles of genistein-treated PC3 prostate cancer cells

Our previous studies have shown that genistein inhibits the growth of PC3 prostate cancer cells and induces apoptosis by inhibiting nuclear factor kappaB (NF-kappaB) and Akt signaling pathways. To better understand the precise molecular mechanism(s) by which genistein exerts its effects on PC3 cells, we utilized cDNA microarray to interrogate 12,558 known genes to determine the gene expression profiles altered by genistein treatment. We found a total of 832 genes that showed a greater than twofold change after genistein treatment from two independent experiments with a high degree of concordance. Among these genes, 774 genes were down-regulated and 58 genes were up-regulated with genistein treatment. Cluster analysis showed nine different types of expression alternations. These genes were also subjected to cluster analysis according to their biological functions. We found that genistein regulated the expression of genes that are critically involved in the regulation of cell growth, cell cycle, apoptosis, cell signaling transduction, angiogenesis, tumor cell invasion and metastasis. Reverse transcription-polymerase chain reaction (RT-PCR) analysis was used to confirm the results of cDNA microarray, and the results of RT-PCR were consistent with the microarray data. We conclude that genistein affected the expression of a large number of genes that are related to the control of cell survival and physiologic behaviors. The gene expression profiles provide comprehensive molecular mechanism(s) by which genistein exerts its pleiotropic effects on cancer cells. Genistein-induced regulation of these genes may be further exploited for devising chemopreventive and/or therapeutic strategies for prostate cancer.

Analysis of gene expression in human colorectal cancer tissues by cDNA array

BACKGROUND

The development and progression of cancer are accompanied by complex changes in patterns of gene expression. The purpose of this study was to clarify the relevance of macroarray analysis of human colorectal cancer tissues.

METHODS

Hybridization of cDNA macroarray filters on which 550 genes had been spotted was performed with biotin-labeled cDNA targets that were prepared from mRNA extracted from 20 pairs of colorectal cancer and corresponding noncancerous tissues. Expression of differentially expressed genes was further studied by semiquantitative RT-PCR.

RESULTS

Fourteen (2.5%) of the 550 genes were differentially expressed and up- or downregulated in cancer tissues by at least threefold compared with matched noncancerous tissues in 10 or more of the 20 patients. The genes that were upregulated in cancer tissues were associated with transcription, cell cycle, growth factor receptor, cell adhesion, extracellular matrix-degrading enzymes, and angiogenesis, and the downregulated genes were those involved in apoptosis and immune recognition. Semiquantitative RT-PCR analysis of these differentially expressed genes gave results consistent with those by cDNA array analysis.

CONCLUSIONS

Although the macroarray used in this study contained only a small number of genes, our results support the feasibility and usefulness of this approach to study variation in gene expression patterns in human colorectal cancer tissues. The results also suggest the possibility of a diagnostic application of cDNA macroarrays in daily clinical settings.

The colorectal adenoma-carcinoma sequence

BACKGROUND

It is widely accepted that the adenoma-carcinoma sequence represents the process by which most, if not all, colorectal cancers arise. The evidence supporting this hypothesis has increased rapidly in recent years and the purpose of this article is to review this evidence critically and highlight its clinical significance.

METHODS

Medline searches were used to identify recent key articles relating to the adenoma-carcinoma sequence. Further pertinent articles were obtained by manual scanning of the reference lists of identified papers.

RESULTS

The evidence supporting the adenoma-carcinoma sequence can be classified as epidemiological, clinicopathological and genetic. The most recent and largest body of data relates to molecular genetic events and their cellular effects; however, many other approaches, such as cytogenetics, molecular cytogenetics and cytometry, have also yielded valuable information.

CONCLUSION

Recent work continues to support the adenoma-carcinoma sequence, but there is a paucity of data on the interrelationship between different genetic mutations and on the relationship between molecular and other types of genetic abnormalities. The clinical utility of the observations described has yet to be fully realized and global genetic analysis of colorectal tumours may prove to be central in rational adenoma management.

The value of microarray techniques for quantitative gene profiling in molecular diagnostics

There has been an explosion of interest in microarray technologies that allow the quantification of whole-genome RNA expression data. The apparent correlation of expression profiles with clinically relevant parameters such as disease outcome has raised expectations with respect to the clinical usefulness of the data generated. Yet the accuracy and biological relevance of these data remain contentious, even in basic research applications. Therefore, numerous issues related to format, quality, validation and interpretation remain to be resolved before microarray profiling can become a diagnostic tool of clinical relevance for routine work.

Molecular pathology of tumor metastasis. II. Molecular staging and differential diagnosis

Molecular Pathology of Tumor Metastasis With the development of non-invasive methods, diagnosis of metastasis from various solid malignancies has become a routine task for diagnostic pathology. However, the differential diagnosis between primary and metastatic cancers and the precise identification of various metastatic cancer types requires the coordinated use of various morphological (light- and electron microscopic-), immunological and molecular techniques. The detection of the lymphatic spread of the primary tumor may now based on the sentinel lymph node technology while the identification of the hematogenous progression may be based on the analysis of the peripheral blood and the bone marrow. More and more frequently these techniques employ highly sensitive immunological and molecular techniques. Accordingly, clinical staging is now confronted with the results of molecular staging, where the only techniques which are able to detect cancer cells are immunocytochemistry or nucleic acid-based methodology. Although several clinical studies have provided evidences for the impact of the immunocytochemistry-based identification of micrometastases on the survival of patients with various type of cancers, none of these methods have become part of standard diagnostic protocols. Although more sensitive molecular techniques are being introduced to identify micrometastasis, their clinical significance is yet unknown. Multicentric clinical trials are now warranted to establish the clinical impact of molecular staging in various cancer types. Without the integration of these methods into the prognostic/predictive pathological protocols it is difficult to envision significant improvement in the results of cancer therapy.