Classification of Dukes' B and C colorectal cancers using expression arrays

Neuroendocrine neoplasms: current and potential diagnostic, predictive and prognostic markers

Some biomarkers for functioning and non-functioning neuroendocrine neoplasms (NENs) are currently available. Despite their application in clinical practice, results should be interpreted cautiously. Considering the variable sensitivity and specificity of these parameters, there is an unmet need for novel biomarkers to improve diagnosis and predict patient outcome. Nowadays, several new biomarkers are being evaluated and may become future tools for the management of NENs. These biomarkers include (1) peptides and growth factors; (2) DNA and RNA markers based on genomics analysis, for example, the so-called NET test, which has been developed for analyzing gene transcripts in circulating blood; (3) circulating tumor/endothelial/progenitor cells or cell-free tumor DNA, which represent minimally invasive methods that would provide additional information for monitoring treatment response and (4) improved imaging techniques with novel radiolabeled somatostatin analogs or peptides. Below we summarize some future directions in the development of novel diagnostic and predictive/prognostic biomarkers in NENs. This review is focused on circulating and selected tissue markers.

Transcription factor ZNF25 is associated with osteoblast differentiation of human skeletal stem cells

Background

The differentiation of human bone marrow derived skeletal stem cells (known as human bone marrow stromal or mesenchymal stem cells, hMSCs) into osteoblasts involves the activation of a small number of well-described transcription factors. To identify additional osteoblastic transcription factors, we studied gene expression of hMSCs during ex vivo osteoblast differentiation.

Results

Clustering of gene expression, and literature investigation, revealed three transcription factors of interest – ZNF25, ZNF608 and ZBTB38. siRNA knockdown of ZNF25 resulted in significant suppression of alkaline phosphatase (ALP) activity. This effect was not present for ZNF608 and ZBTB38. To identify possible target genes of ZNF25, we analyzed gene expression following ZNF25 siRNA knockdown. This revealed a 23-fold upregulation of matrix metallopeptidase 1 and an 18-fold upregulation of leucine-rich repeat containing G protein-coupled receptor 5 and RAN-binding protein 3-like. We also observed enrichment in extracellular matrix organization, skeletal system development and regulation of ossification in the entire upregulated set of genes. Consistent with its function as a transcription factor during osteoblast differentiation of hMSC, we showed that the ZNF25 protein exhibits nuclear localization and is expressed in osteoblastic and osteocytic cells in vivo. ZNF25 is conserved in tetrapod vertebrates and contains a KRAB (Krueppel-associated box) transcriptional repressor domain.

Conclusions

This study shows that the uncharacterized transcription factor, ZNF25, is associated with differentiation of hMSC to osteoblasts.

Development of novel diagnostic and prognostic molecular markers for sporadic colon cancer

Gene expression studies are informative about changes in colon cancer, increase understanding of the biology of tumorigenesis and aid in developing diagnostic and prognostic markers. In this review, expression techniques used to examine the multistage process of colon cancer are discussed. Many genes have been found to differ in expression between normal and tumorigenic states, as early as the seemingly normal colonic crypts. The clinical usefulness of markers varies with stage, ethnicity and anatomic location of colon cancer. Thus, combinations of markers can be used to develop an approach to molecularly screen and follow the progression of this prevalent cancer.

Role of MUC20 overexpression as a predictor of recurrence and poor outcome in colorectal cancer

Background

Colorectal cancer (CRC) remains one of the most common cancers worldwide. We observed that MUC20 was significantly up-regulated in CRC patients with poor prognosis based on the microarray analysis. However, little is known about the role of MUC20 in CRC.

Methods

Microarray experiments were performed on the Affymetrix U133 plus 2.0 GeneChip Array. The protein and mRNA levels of MUC20 were examined by immunohistochemistry (IHC) and Real-Time quantitative PCR (RT-qPCR) in CRC tissues and adjacent noncancerous tissues (ANCT). ShRNA and overexpression plasmids were used to regulate MUC20 expression in CRC cell lines in vitro; wound healing, Transwell migration assays, and Western blotting were used to detect migration and invasion changes.

Results

MUC20 was one of the up-regulated genes in CRC patients with poor prognosis by microarray. Using IHC and RT-qPCR, we showed that MUC20 expression was significantly higher in CRC tissues than in ANCT (P < 0.05). We further showed that MUC20 overexpression was correlated with recurrence and poor outcome (P < 0.05). The Kaplan-Meier survival curves indicated that disease-free survival (DFS) and overall survival (OS) were significantly worse in CRC patients with MUC20 overexpression. The Cox multivariate analysis revealed that MUC20 overexpression and TNM stage were independent prognostic factors. Elevated expression of MUC20 in cells promoted migration and invasion, whereas ShRNA-mediated knockdown inhibited these processes. In addition, Western blotting demonstrated that MUC20-induced invasion was associated with MMP-2, MMP-3, and E-cadherin.

Conclusions

Cumulatively, MUC20 may serve as an important predictor of recurrence and poor outcome for CRC patients. MUC20 overexpression could enhance migration and invasion abilities of CRC cells. Translation of its roles into clinical practice will need further investigation and additional test validation.

The identification of gut neuroendocrine tumor disease by multiple synchronous transcript analysis in blood

Gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs) are increasing in both incidence and prevalence. A delay in correct diagnosis is common for these lesions. This reflects the absence of specific blood biomarkers to detect NENs. Measurement of the neuroendocrine secretory peptide Chromogranin A (CgA) is used, but is a single value, is non-specific and assay data are highly variable. To facilitate tumor detection, we developed a multi-transcript molecular signature for PCR-based blood analysis. NEN transcripts were identified by computational analysis of 3 microarray datasets: NEN tissue (n = 15), NEN peripheral blood (n = 7), and adenocarcinoma (n = 363 tumors). The candidate gene signature was examined in 130 blood samples (NENs: n = 63) and validated in two independent sets (Set 1 [n = 115, NENs: n = 72]; Set 2 [n = 120, NENs: n = 58]). Comparison with CgA (ELISA) was undertaken in 176 samples (NENs: n = 81). 51 significantly elevated transcript markers were identified. Gene-based classifiers detected NENs in independent sets with high sensitivity (85–98%), specificity (93–97%), PPV (95–96%) and NPV (87–98%). The AUC for the NEN gene-based classifiers was 0.95–0.98 compared to 0.64 for CgA (Z-statistic 6.97–11.42, p<0.0001). Overall, the gene-based classifier was significantly (χ² = 12.3, p<0.0005) more accurate than CgA. In a sub-analysis, pancreatic NENs and gastrointestinal NENs could be identified with similar efficacy (79–88% sensitivity, 94% specificity), as could metastases (85%). In patients with low CgA, 91% exhibited elevated transcript markers. A panel of 51 marker genes differentiates NENs from controls with a high PPV and NPV (>90%), identifies pancreatic and gastrointestinal NENs with similar efficacy, and confirms GEP-NENs when CgA levels are low. The panel is significantly more accurate than the CgA assay. This reflects its utility to identify multiple diverse biological components of NENs. Application of this sensitive and specific PCR-based blood test to NENs will allow accurate detection of disease, and potentially define disease progress enabling monitoring of treatment efficacy.

Subtypes of primary colorectal tumors correlate with response to targeted treatment in colorectal cell lines

Background

Colorectal cancer (CRC) is a heterogeneous and biologically poorly understood disease. To tailor CRC treatment, it is essential to first model this heterogeneity by defining subtypes of patients with homogeneous biological and clinical characteristics and second match these subtypes to cell lines for which extensive pharmacological data is available, thus linking targeted therapies to patients most likely to respond to treatment.

Methods

We applied a new unsupervised, iterative approach to stratify CRC tumor samples into subtypes based on genome-wide mRNA expression data. By applying this stratification to several CRC cell line panels and integrating pharmacological response data, we generated hypotheses regarding the targeted treatment of different subtypes.

Results

In agreement with earlier studies, the two dominant CRC subtypes are highly correlated with a gene expression signature of epithelial-mesenchymal-transition (EMT). Notably, further dividing these two subtypes using iNMF (iterative Non-negative Matrix Factorization) revealed five subtypes that exhibit activation of specific signaling pathways, and show significant differences in clinical and molecular characteristics. Importantly, we were able to validate the stratification on independent, published datasets comprising over 1600 samples. Application of this stratification to four CRC cell line panels comprising 74 different cell lines, showed that the tumor subtypes are well represented in available CRC cell line panels. Pharmacological response data for targeted inhibitors of SRC, WNT, GSK3b, aurora kinase, PI3 kinase, and mTOR, showed significant differences in sensitivity across cell lines assigned to different subtypes. Importantly, some of these differences in sensitivity were in concordance with high expression of the targets or activation of the corresponding pathways in primary tumor samples of the same subtype.

Conclusions

The stratification presented here is robust, captures important features of CRC, and offers valuable insight into functional differences between CRC subtypes. By matching the identified subtypes to cell line panels that have been pharmacologically characterized, it opens up new possibilities for the development and application of targeted therapies for defined CRC patient sub-populations.

MicroRNAs: relevant tools for a colorectal surgeon?

Colorectal cancer is the third most common malignancy and cause of cancer-related deaths worldwide. Approximately half of the patients diagnosed with colorectal cancer ultimately die of the condition. Death from colorectal cancer can be prevented by early detection, but unfortunately presentation is often late, with a worse prognosis. Screening by fecal occult blood testing reduces disease-specific mortality, but there is a need for sensitive and specific noninvasive biomarkers to facilitate detecting the disease, staging it, and predicting the best therapeutic options. MicroRNAs (miRNAs) are short noncoding RNA sequences that have a crucial role in the regulation of gene expression. They have significant regulatory functions in basic cellular processes, such as cell differentiation, proliferation, and apoptosis. Evidence suggests that miRNAs may function as both tumor suppressors and oncogenes. The main mechanism for changes in the function of miRNAs in cancer cells is due to aberrant gene expression. Accurate discrimination of miRNA profiles between tumor and normal mucosa in colorectal cancer allows definition of specific expression patterns of miRNAs, giving good potential as diagnostic and therapeutic targets. MiRNAs expressed in colorectal cancers are also abundantly present and stable in stool and plasma samples. Their extraction from these three sources is feasible and reproducible. The ease and reliability of determining miRNA profiles in plasma or stool makes them potential molecular markers for colorectal cancer screening. This review summarizes the role miRNAs have in colorectal cancer, highlighting particularly the potential diagnostic, prognostic, and therapeutic implications in the future treatment of the disease.

Exploring gene expression signatures for predicting disease free survival after resection of colorectal cancer liver metastases

BACKGROUND AND OBJECTIVES

This study was designed to identify and validate gene signatures that can predict disease free survival (DFS) in patients undergoing a radical resection for their colorectal liver metastases (CRLM).

METHODS

Tumor gene expression profiles were collected from 119 patients undergoing surgery for their CRLM in the Paul Brousse Hospital (France) and the University Medical Center Utrecht (The Netherlands). Patients were divided into high and low risk groups. A randomly selected training set was used to find predictive gene signatures. The ability of these gene signatures to predict DFS was tested in an independent validation set comprising the remaining patients. Furthermore, 5 known clinical risk scores were tested in our complete patient cohort.

RESULT

No gene signature was found that significantly predicted DFS in the validation set. In contrast, three out of five clinical risk scores were able to predict DFS in our patient cohort.

CONCLUSIONS

No gene signature was found that could predict DFS in patients undergoing CRLM resection. Three out of five clinical risk scores were able to predict DFS in our patient cohort. These results emphasize the need for validating risk scores in independent patient groups and suggest improved designs for future studies.

Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior

Background

Colon cancer patients with the same stage show diverse clinical behavior due to tumor heterogeneity. We aimed to discover distinct classes of tumors based on microarray expression patterns, to analyze whether the molecular classification correlated with the histopathological stages or other clinical parameters and to study differences in the survival.

Methods

Hierarchical clustering was performed for class discovery in 88 colon tumors (stages I to IV). Pathways analysis and correlations between clinical parameters and our classification were analyzed. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the main subtype was generated using the 3-Nearest-Neighbor method. Coincidences with other prognostic predictors were assesed.

Results

Hierarchical clustering identified four robust tumor subtypes with biologically and clinically distinct behavior. Stromal components (p < 0.001), nuclear β-catenin (p = 0.021), mucinous histology (p = 0.001), microsatellite-instability (p = 0.039) and BRAF mutations (p < 0.001) were associated to this classification but it was independent of Dukes stages (p = 0.646). Molecular subtypes were established from stage I. High-stroma-subtype showed increased levels of genes and altered pathways distinctive of tumour-associated-stroma and components of the extracellular matrix in contrast to Low-stroma-subtype. Mucinous-subtype was reflected by the increased expression of trefoil factors and mucins as well as by a higher proportion of MSI and BRAF mutations. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the Low-stroma-subtype distinguished low risk patients from high risk patients in the external cohort (Dukes B and C:HR = 8.56(2.53-29.01); Dukes B,C and D:HR = 1.87(1.07-3.25)). Eight different reported survival gene signatures segregated our tumors into two groups the Low-stroma-subtype and the other tumor subtypes.

Conclusions

We have identified novel molecular subtypes in colon cancer with distinct biological and clinical behavior that are established from the initiation of the tumor. Tumor microenvironment is important for the classification and for the malignant power of the tumor. Differential gene sets and biological pathways characterize each tumor subtype reflecting underlying mechanisms of carcinogenesis that may be used for the selection of targeted therapeutic procedures. This classification may contribute to an improvement in the management of the patients with CRC and to a more comprehensive prognosis.

Dysplasia-carcinoma transition specific transcripts in colonic biopsy samples

BACKGROUND

The early molecular detection of the dysplasia-carcinoma transition may enhance the strength of diagnosis in the case of colonic biopsies. Our aims were to identify characteristic transcript sets in order to develop diagnostic mRNA expression patterns for objective classification of benign and malignant colorectal diseases and to test the classificatory power of these markers on an independent sample set.

METHODOLOGY/PRINCIPAL FINDINGS

Colorectal cancer (CRC) and adenoma specific transcript sets were identified using HGU133plus2 microarrays and 53 biopsies (22 CRC, 20 adenoma and 11 normal). Ninety-four independent biopsies (27 CRC, 29 adenoma and 38 normal) were analyzed on microarrays for testing the classificatory power of the discriminatory genes. Array real-time PCR validation was done on 68 independent samples (24 CRC, 24 adenoma and 20 normal). A set of 11 transcripts (including CXCL1, CHI3L1 and GREM1) was determined which could correctly discriminate between high-grade dysplastic adenoma and CRC samples by 100% sensitivity and 88.9% specificity. The discriminatory power of the marker set was proved to be high on independent samples in both microarray and RT-PCR analyses. 95.6% of original and 94.1% of cross-validated samples was correctly classified in discriminant analysis.

CONCLUSIONS/SIGNIFICANCE

The identified transcripts could correctly characterize the dysplasia-carcinoma transition in biopsy samples, also on a large independent sample set. These markers can establish the basis of gene expression based diagnostic classification of colorectal cancer. Diagnostic RT-PCR cards can become part of the automated routine procedure.

MicroRNA signature analysis in colorectal cancer: identification of expression profiles in stage II tumors associated with aggressive disease

PURPOSE

Colorectal cancer (CRC) is a clinically diverse disease whose molecular etiology remains poorly understood. The purpose of this study was to identify miRNA expression patterns predictive of CRC tumor status and to investigate associations between microRNA (miRNA) expression and clinicopathological parameters.

METHODS

Expression profiling of 380 miRNAs was performed on 20 paired stage II tumor and normal tissues. Artificial neural network (ANN) analysis was applied to identify miRNAs predictive of tumor status. The validation of specific miRNAs was performed on 102 tissue specimens of varying stages.

RESULTS

Thirty-three miRNAs were identified as differentially expressed in tumor versus normal tissues. ANN analysis identified three miRNAs (miR-139-5p, miR-31, and miR-17-92 cluster) predictive of tumor status in stage II disease. Elevated expression of miR-31 (p = 0.004) and miR-139-5p (p < 0.001) and reduced expression of miR-143 (p = 0.016) were associated with aggressive mucinous phenotype. Increased expression of miR-10b was also associated with mucinous tumors (p = 0.004). Furthermore, progressively increasing levels of miR-10b expression were observed from T1 to T4 lesions and from stage I to IV disease.

CONCLUSION

Association of specific miRNAs with clinicopathological features indicates their biological relevance and highlights the power of ANN to reliably predict clinically relevant miRNA biomarkers, which it is hoped will better stratify patients to guide adjuvant therapy.

RNA expression of the molecular signature genes for metastasis in colorectal cancer

Colorectal cancer is an endemic disease in the western world. Search for molecular signatures present in primary tumors that predict tumor metastasis potential has been proposed and in particular, a 17-gene molecular signature is associated with poor survival in breast cancer, prostate cancer, meduloblastoma and lymphoma in a recent study. Using quantitative real-time PCR assay (qPCR), our study observed tumor-normal differential RNA expression in 15 of these 17 genes in a cohort of 52 stage III colorectal cancer patients (all p<0.05), which signified the importance of these 17 signature genes in colorectal cancer. Although no significant correlation was found between tumor RNA levels of these 17 genes and some of clinical features (age, gender, and location, all p>0.05), two distinct groups among these genes were observed with Spearman correlation scores>0.6 (p<0.01), suggesting co-expression/interaction within these genes. Of the 37 patients for whom complete follow-up data was available, 12 patients had recurrence and 25 had no recurrence. There was no significant difference in tumor RNA levels between recurrence and non-recurrence groups for the 17 genes (all p>0.05), but the recurrence group had more patients with mucinous tumors (9/12 vs. 7/25, p<0.05) and more lymph node involvement (median 7.2 vs. 2.5, p<0.05) compared to the non-recurrence group. Moreover, survival analysis revealed a significant difference in patient overall survival time between low and high tumor RNA levels for 1 of the 17 genes (PTTG1, p=0.024). Our qPCR validation study confirms the importance of most 17-gene molecular signature genes with differential RNA expression and suggests the relevance of PTTG1 for survival in colorectal cancers.

Identification of predictive markers of response to the MEK1/2 inhibitor selumetinib (AZD6244) in K-ras-mutated colorectal cancer

Mutant K-ras activity leads to the activation of the RAS/RAF/MEK/ERK pathway in approximately 44% of colorectal cancer (CRC) tumors. Accordingly, several inhibitors of the MEK pathway are under clinical evaluation in several malignancies including CRC. The aim of this study was to develop and characterize predictive biomarkers of response to the MEK1/2 inhibitor AZD6244 in CRC in order to maximize the clinical utility of this agent. Twenty-seven human CRC cell lines were exposed to AZD6244 and classified according to the IC(50) value as sensitive (≤ 0.1 μmol/L) or resistant (>1 μmol/L). All cell lines were subjected to immunoblotting for effector proteins, K-ras/BRAF mutation status, and baseline gene array analysis. Further testing was done in cell line xenografts and K-ras mutant CRC human explants models to develop a predictive genomic classifier for AZD6244. The most sensitive and resistant cell lines were subjected to differential gene array and pathway analyses. Members of the Wnt signaling pathway were highly overexpressed in cell lines resistant to AZD6244 and seem to be functionally involved in mediating resistance by shRNA knockdown studies. Baseline gene array data from CRC cell lines and xenografts were used to develop a k-top scoring pair (k-TSP) classifier, which predicted with 71% accuracy which of a test set of patient-derived K-ras mutant CRC explants would respond to AZD6244, providing the basis for a patient-selective clinical trial. These results also indicate that resistance to AZD6244 may be mediated, in part, by the upregulation of the Wnt pathway, suggesting potential rational combination partners for AZD6244 in CRC.

Identification of cancer-associated proteins by proteomics and downregulation of β-tropomyosin expression in colorectal adenoma and cancer

Elucidating the molecular mechanism underlying the development of adenoma, the major precursor lesion of colorectal cancer (CRC), would provide a basis for early detection, prevention as well as treatment of CRC. Using the highly sensitive 2-D DIGE method coupled with MS, we identified 24 differentially expressed proteins in adenoma tissues compared with matched normal colonic mucosa and CRC tissues. Fifteen proteins were downregulated and three proteins were upregulated in adenoma tissues when compared with individual-matched normal colonic mucosa. Five proteins were downregulated, while one protein was upregulated in adenoma tissues when compared with matched CRC tissues. A protein, β-tropomyosin (TM-β), recently suggested to be a biomarker of esophageal squamous carcinoma, was downregulated in both adenoma and CRC tissues. Additionally, the reduction in the level of TM-β in adenoma and CRC tissues was further validated by Western blotting (p<0.05) and RT-PCR (p<0.001). Our findings suggest that downregulation of TM-β is involved in the early development of CRC and that differentially expressed proteins might serve as potential biomarkers for detection of CRC.

Comparability of microarray data between amplified and non amplified RNA in colorectal carcinoma

Microarray analysis reaches increasing popularity during the investigation of prognostic gene clusters in oncology. The standardisation of technical procedures will be essential to compare various datasets produced by different research groups. In several projects the amount of available tissue is limited. In such cases the preamplification of RNA might be necessary prior to microarray hybridisation. To evaluate the comparability of microarray results generated either by amplified or non amplified RNA we isolated RNA from colorectal cancer samples (stage UICC IV) following tumour tissue enrichment by macroscopic manual dissection (CMD). One part of the RNA was directly labelled and hybridised to GeneChips (HG-U133A, Affymetrix), the other part of the RNA was amplified according to the “Eberwine” protocol and was then hybridised to the microarrays. During unsupervised hierarchical clustering the samples were divided in groups regarding the RNA pre-treatment and 5.726 differentially expressed genes were identified. Using independent microarray data of 31 amplified vs. 24 non amplified RNA samples from colon carcinomas (stage UICC III) in a set of 50 predictive genes we validated the amplification bias. In conclusion microarray data resulting from different pre-processing regarding RNA pre-amplification can not be compared within one analysis.

Genetic prognostic and predictive markers in colorectal cancer

Despite many studies of the likely survival outcome of individual patients with colorectal cancer, our knowledge of this subject remains poor. Until recently, we had virtually no understanding of individual responses to therapy, but the discovery of the KRAS mutation as a marker of probable failure of epidermal growth factor receptor (EGFR)-targeted therapy is a first step in the tailoring of treatment to the individual. With the application of molecular analyses, as well as the ability to perform high-throughput screens, there has been an explosive increase in the number of markers thought to be associated with prognosis and treatment outcome in this disease. In this Review, we attempt to summarize the sometimes confusing findings, and critically assess those markers already in the public domain.

An expression module of WIPF1-coexpressed genes identifies patients with favorable prognosis in three tumor types

Wiskott–Aldrich syndrome (WAS) predisposes patients to leukemia and lymphoma. WAS is caused by mutations in the protein WASP which impair its interaction with the WIPF1 protein. Here, we aim to identify a module of WIPF1-coexpressed genes and to assess its use as a prognostic signature for colorectal cancer, glioma, and breast cancer patients. Two public colorectal cancer microarray data sets were used for discovery and validation of the WIPF1 co-expression module. Based on expression of the WIPF1 signature, we classified more than 400 additional tumors with microarray data from our own experiments or from publicly available data sets according to their WIPF1 signature expression. This allowed us to separate patient populations for colorectal cancers, breast cancers, and gliomas for which clinical characteristics like survival times and times to relapse were analyzed. Groups of colorectal cancer, breast cancer, and glioma patients with low expression of the WIPF1 co-expression module generally had a favorable prognosis. In addition, the majority of WIPF1 signature genes are individually correlated with disease outcome in different studies. Literature gene network analysis revealed that among WIPF1 co-expressed genes known direct transcriptional targets of c-myc, ESR1 and p53 are enriched. The mean expression profile of WIPF1 signature genes is correlated with the profile of a proliferation signature. The WIPF1 signature is the first microarray-based prognostic expression signature primarily developed for colorectal cancer that is instrumental in other tumor types: low expression of the WIPF1 module is associated with better prognosis.

Diagnostic mRNA expression patterns of inflamed, benign, and malignant colorectal biopsy specimen and their correlation with peripheral blood results

PURPOSE

Gene expression profile (GEP)-based classification of colonic diseases is a new method for diagnostic purposes. Our aim was to develop diagnostic mRNA expression patterns that may establish the basis of a new molecular biological diagnostic method.

EXPERIMENTAL DESIGN

Total RNA was extracted, amplified, and biotinylated from frozen colonic biopsies of patients with colorectal cancer (n=22), adenoma (n=20), hyperplastic polyp (n=11), inflammatory bowel disease (n=21), and healthy normal controls (n=11), as well as peripheral blood samples of 19 colorectal cancer and 11 healthy patients. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays. To identify the differentially expressed features, the significance analysis of microarrays and, for classification, the prediction analysis of microarrays were used. Expression patterns were validated by real-time PCR. Tissue microarray immunohistochemistries were done on tissue samples of 121 patients.

RESULTS

Adenoma samples could be distinguished from hyperplastic polyps by the expression levels of nine genes including ATP-binding cassette family A, member 8, insulin-like growth factor 1 and glucagon (sensitivity, 100%; specificity, 90.91%). Between low-grade and high-grade dysplastic adenomas, 65 classifier probesets such as aquaporin 1, CXCL10, and APOD (90.91/100) were identified; between colorectal cancer and adenoma, 61 classifier probesets including axin 2, von Willebrand factor, tensin 1, and gremlin 1 (90.91/100) were identified. Early- and advanced-stage colorectal carcinomas could be distinguished using 34 discriminatory transcripts (100/66.67).

CONCLUSIONS

Whole genomic microarray analysis using routine biopsy samples is suitable for the identification of discriminative signatures for differential diagnostic purposes. Our results may be the basis for new GEP-based diagnostic methods.

Orthotopic implantation mouse model and cDNA microarray analysis indicates several genes potentially involved in lymph node metastasis of colorectal cancer

In colorectal cancer (CRC) patients, metastasis to the regional lymph node (LN) is an important first step in the dissemination of cancers. To identify the genes possibly involved in LN metastasis of CRC, we analyzed LN metastases in an orthotopic implantation mouse model with 22 CRC cell lines using Matrigel, an extracellular matrix protein derived from mice sarcoma, and combined the data with gene expression profiles of cDNA microarray of those cell lines. With this implantation analysis, the incidence of LN metastasis was 60% in 228 orthotopically implanted mice and varied from 100% to 0% among the cell lines. KM12c and Clone A showed LN metastasis in all orthotopically implanted mice, but DLD-1, HCT-8, and SW948 did not show LN metastases at all. In contrast, the incidence of liver and lung metastasis in 22 CRC cell lines was 13% and 1%, respectively. Combining those data with cDNA microarray in vitro, we isolated 636 genes that were differentially expressed depending on the incidence of LN metastasis. Among those genes, the expression level of ring finger protein 125 (RNF125), previously known as an E3 ubiquitin ligase in T cell activation, was significantly different between primary tumors in Stage III CRC patients with LN metastasis and Stage II patients without LN metastasis. In conclusion, the orthotopic implantation mice model with Matrigel was useful, and we isolated candidate genes such as RNF125 that possibly play an important role in LN metastasis of CRC cells.

Molecular profiling and risk stratification of adenocarcinoma of the colon

Staging systems are used to predict the clinical and biologic behavior of tumors. This manuscript examines several molecular markers that hope to improve staging for colon cancer. It is unclear if a molecular marker, genetic signature, or a combination of histologic, genetic, and molecular parameters will provide the best prognostic information. What is clear is that more accurate staging tools are needed so patients receive the best therapy.

Transcriptional Regulation of SDHa flavoprotein by nuclear respiratory factor-1 prevents pseudo-hypoxia in aerobic cardiac cells

Nuclear respiratory factor-1 (NRF-1) is integral to the transcriptional regulation of mitochondrial biogenesis, but its control over various respiratory genes overlaps other regulatory elements including those involved in O(2) sensing. Aerobic metabolism generally suppresses hypoxia-sensitive genes, e.g. via hypoxia-inducible factor-1 (HIF-1), but mutations in Complex II-succinate dehydrogenase (SDH), a tumor suppressor, stabilize HIF-1, producing pseudo-hypoxia. In aerobic cardiomyocytes, which rely on oxidative phosphorylation, we tested the hypothesis that NRF-1 regulates Complex II expression and opposes hypoxia-inducible factor-1. NRF-1 gene silencing blocked aerobic succinate oxidation, increasing nuclear HIF-1alpha protein prior to the loss of Complex I function. We postulated that NRF-1 suppression either specifically decreases the expression of one or more SDH subunits and increases succinate availability to regulate HIF-1 prolyl hydroxylases, or stimulates mitochondrial reactive oxygen production, which interferes with HIF-1alpha degradation. Using promoter analysis, gene silencing, and chromatin immunoprecipitation, NRF-1 was found to bind to the gene promoters of two of four nuclear-encoded Complex II subunits: SDHa and SDHd, but the enzyme activity was dynamically regulated through the catalytic SDHa flavoprotein. Complex II was inactivated by SDHa silencing, which led to aerobic HIF-1alpha stabilization, nuclear translocation, and enhanced expression of glucose transporters and heme oxygenase-1. This was unrelated to mitochondrial ROS production, reversible by high alpha-ketoglutarate concentrations, and coherent with regulation of HIF-1 by succinate reported in tumor cells. These findings disclose a novel role for NRF-1 in the transcriptional control of Complex II and prevention of pseudo-hypoxic gene expression in aerobic cardiac cells.

[Functional mRNA expression analysis and classification of colonic biopsy samples using overall cDNA microarray technique]

BACKGROUND

Overall mRNA expression analysis of colon biopsies can contribute to the understanding of molecular background of the local alterations and gene ontology-based functional classification of colonic biopsies into inflammatory and neoplastic diseases.

METHODS

Total RNA was extracted from frozen biopsies and amplified by T7-method. Expression profile was evaluated by Atlas Glass 1K microarrays. After microarray quality control, applicable data were available from 10 adenomas, 6 colorectal adenocarcinoma (CRC), and inflammatory bowel diseases (IBDs: 3-3 CD and UC). Multivariate statistical and cell functional analyses were performed. Real-time RT-PCR and immunohistochemistry were used for validation.

RESULTS

Discriminant analysis of selected genes could correctly reclassify all 22 samples using 4 parameters (heat shock transcription factor-1, bystin-like, calgranulin-A, TRAIL receptor 3). IBD samples were characterized by overregulated chemokine (C-X-C motif) ligand 13, replication protein A1, E74-like factor 2 and downregulated TNF receptor-associated factor 6, BCL2-interacting killer genes. In adenomas upregulation of TNF receptor-associated factor 6, replication protein A1, E74-like factor 2 and underexpression of BCL2-associated X protein, calgranulin-A genes were found. CRC cases had significantly increased epidermal growth factor receptor, topoisomerase-1, v-jun, TNF receptor-associated factor 6 and TRAIL receptor 3, and decreased RAD51 and RAD52 DNA repair gene, protein phosphatase-2A and BCL2-interacting killer mRNA levels. Epidermal growth factor receptor RT-PCR and immunohistochemistry, topoisomerase-1 RT-PCR confirmed the chip results.

CONCLUSIONS

Different histological alterations can be objectively classified by functional, multivariate analysis using cDNA microarrays. Disease-specific gene expression patterns can assist to avoid the intermediate and nondescript cases in diagnostics, which do not belong to any of the conventional diagnostic groups.

In vivo biomarkers for targeting colorectal neoplasms

Colorectal carcinoma continues to be a leading cause of cancer morbidity and mortality despite widespread adoption of screening methods. Targeted detection and therapy using recent advances in our knowledge of in vivo cancer biomarkers promise to significantly improve methods for early detection, risk stratification, and therapeutic intervention. The behavior of molecular targets in transformed tissues is being comprehensively assessed using new techniques of gene expression profiling and high throughput analyses. The identification of promising targets is stimulating the development of novel molecular probes, including significant progress in the field of activatable and peptide probes. These probes are being evaluated in small animal models of colorectal neoplasia and recently in the clinic. Furthermore, innovations in optical imaging instrumentation are resulting in the scaling down of size for endoscope compatibility. Advances in target identification, probe development, and novel instruments are progressing rapidly, and the integration of these technologies has a promising future in molecular medicine.

[Identification of colorectal cancer, adenoma, and inflammatory bowel disease specific gene expression patterns using whole genomic oligonucleotide microarray system]

BACKGROUND

Discrimination and classification of colorectal diseases (adenoma, colorectal cancer, inflammatory bowel disease) using biopsy samples and expression microarrays, has not been solved yet, nevertheless, it can contribute to the understanding of the colonic diseases.

METHODS

Total ribonucleic acid was extracted, amplified and biotinylated from frozen colonic biopsies of 15 patients with colorectal cancer, 15 with adenoma, 14 with inflammatory bowel disease and 8 normal controls. Genome-wide gene expression profile was evaluated by Human Genome U133 Plus 2.0 microarrays. Two independent methods were used for data normalization and "Prediction Analysis of Microarrays" was performed for feature selection. Leave one-out stepwise discriminant analysis was performed. The expression results were verified by real-time polymerase chain reaction.

RESULTS

Top validated genes included CD44 antigen, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; collagen IValpha1, lipocalin-2, calumenin, aquaporin-8 genes in colorectal cancer; and lipocalin-2, ubiquitin D and interferon induced transmembrane protein 2 genes in inflammatory bowel disease. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes. The expression of 94% of the 52 genes measured by Taqman real-time polymerase chain reaction correlated with the results obtained using Affymetrix microarrays at a significance of p < 0.05.

CONCLUSIONS

We successfully performed whole genomic microarray analysis to identify discriminative signatures using routine biopsy samples. The results set up data warehouse which can be further mined.

A proteomics analysis of cell signaling alterations in colorectal cancer

To gain further insight into alterations in cellular pathways, tumor profiling, and marker discovery in colorectal cancer (CRC) we used a new antibody microarray specific for cell signaling. Soluble protein extracts were prepared from paired tumor/normal biopsies of 11 patients diagnosed with colorectal carcinoma at different stages; four liver carcinomas were used as a reference. Antibody microarray analysis identified 46 proteins that were differentially expressed between normal colorectal epithelium and adenocarcinoma. These proteins gave a specific signature for CRC, different from other tumors, as well as a panel of novel markers and potential targets for CRC. Twenty-four proteins were validated by using a specific colorectal cancer tissue microarray and immunoblotting analysis. Together with some previously well known deregulated proteins in CRC (beta-catenin, c-MYC, or p63), we found new potential markers preferentially expressed in CRC tumors: cytokeratin 13, calcineurin, CHK1, clathrin light chain, MAPK3, phospho-PTK2/focal adhesion kinase (Ser-910), and MDM2. CHK1 antibodies were particularly effective in discriminating between tumoral and normal mucosa in CRC. Moreover a global picture of alterations in signaling pathways in CRC was observed, including a significant up-regulation of different components of the epidermal growth factor receptor and Wnt/beta-catenin pathways and the down-regulation of p14(ARF). The experimental approach described here should be applicable to other pathologies and neoplastic processes.

The surgeon's role in cancer prevention. The model in colorectal carcinoma

Cancer Prevention is an emerging field, capturing the old traditional concept of anticipating the development of a major disease and preventing its full impact by early detection, treatment, or aborting the tumorigenic process by a "molecular vaccine" and alleviating the full impact of the disease. Surgeons are important clinician scientists who can carry this discipline forward and develop its full potential in the clinics and in the community. Advances in molecular biology, genetics, and other technologies have permitted seminal understanding of the carcinogenic pathways and identification of targets and intermediate end points in neoplasia. In this review, we will see that we have the means of preventing significant numbers of colorectal carcinomas (CRC).

Proteome analysis and tissue microarray for profiling protein markers associated with lymph node metastasis in colorectal cancer

BACKGROUND

Understanding the proteins associated with lymph node metastasis (LNM) in colorectal cancer (CRC) will benefit us in the prediction of CRC prognosis and provide us new potential targets in the intervention of CRC. The aim of this study is to investigate the LNM-associated proteins and to evaluate the clinicopathological characteristics of these target proteins' expression in CRC.

METHODS

Fresh tumor and paired normal mucosa from five cases for each group of non-LNM CRC and LNM CRC were analyzed by two-dimensional electrophoresis coupled with MALDI-TOF-MS, followed by Western blotting confirmation. In 40 paraffin-embedded CRC samples, each for non-LNM CRC and LNM CRC, four differentially expressed proteins identified by proteomics analysis were detected by tissue microarray with immunohistochemistry staining to access the clinicopathological characteristics of these proteins in LNM of CRC.

RESULTS

Twenty-five proteins were found to be differentially expressed between normal mucosa and CRC tissue. Increased expression levels of heat shock protein-27 (HSP-27), glutathione S-transferase (GST), and Annexin II, but a decreased expression level of liver-fatty acid binding protein (L-FABP), existed in LNM CRC as compared with non-LNM CRC (p<0.01 or p<0.05, respectively).

CONCLUSION

The techniques of proteomic analysis combined with tissue microarray provide us a dramatic tool for screening of LNM-associated proteins in cancer research. The increased expression of HSP-27, GST, and Annexin II, but decreased expression of L-FABP, suggests a significantly elevated incidence of LNM in CRC.

Gene expression profiling reveals a massive, aneuploidy-dependent transcriptional deregulation and distinct differences between lymph node-negative and lymph node-positive colon carcinomas

To characterize patterns of global transcriptional deregulation in primary colon carcinomas, we did gene expression profiling of 73 tumors [Unio Internationale Contra Cancrum stage II (n = 33) and stage III (n = 40)] using oligonucleotide microarrays. For 30 of the tumors, expression profiles were compared with those from matched normal mucosa samples. We identified a set of 1,950 genes with highly significant deregulation between tumors and mucosa samples (P < 1e-7). A significant proportion of these genes mapped to chromosome 20 (P = 0.01). Seventeen genes had a >5-fold average expression difference between normal colon mucosa and carcinomas, including up-regulation of MYC and of HMGA1, a putative oncogene. Furthermore, we identified 68 genes that were significantly differentially expressed between lymph node-negative and lymph node-positive tumors (P < 0.001), the functional annotation of which revealed a preponderance of genes that play a role in cellular immune response and surveillance. The microarray-derived gene expression levels of 20 deregulated genes were validated using quantitative real-time reverse transcription-PCR in >40 tumor and normal mucosa samples with good concordance between the techniques. Finally, we established a relationship between specific genomic imbalances, which were mapped for 32 of the analyzed colon tumors by comparative genomic hybridization, and alterations of global transcriptional activity. Previously, we had conducted a similar analysis of primary rectal carcinomas. The systematic comparison of colon and rectal carcinomas revealed a significant overlap of genomic imbalances and transcriptional deregulation, including activation of the Wnt/beta-catenin signaling cascade, suggesting similar pathogenic pathways.

Down-regulation of pro-apoptotic genes is an early event in the progression of malignant melanoma

INTRODUCTION

Down-regulation of apoptosis genes has been implicated in the development and progression of malignant melanoma. We used cDNA microarray to evaluate pro-apoptotic gene expression comparing normal skin to melanoma (thin and thick), nodal disease and distant metastases.

METHODS

Twenty-eight specimens including skin (n = 1), thin melanoma (n = 6), thick melanoma (n = 7), nodal disease (n = 6), and distant metastases (n = 8), were harvested at the time of resection from 16 individuals. RNA was isolated and microarray analysis utilizing the Affymetrix GeneChip (54,000 genetic elements, U133A+B... levels) was performed. Mean level of expression was calculated for each gene within a sample group. Expression profiles were then compared between tissue groups. Student's t-test was used to determine variance in expression between groups.

RESULTS

We reviewed the expression of 54,000 genetic elements, of which 2,015 were found to have significantly altered expression. This represents 1,602 genes. Twenty-two pro-apoptotic genes were found to be down-regulated when compared to normal skin. Overall reduction was evaluated comparing normal skin to metastases with a range of 3.31-64.04-fold-decrease. When comparing the tissue types sequentially, the greatest fold-decrease in gene expression occurred when comparing skin to all melanomas (thin and thick) (p = 0.011). Subset analysis comparing normal skin to thin melanoma or thick melanoma, revealed the greatest component of overall reduction at the transition from thin to thick lesions (p = 0.003).

CONCLUSION

Sequential down-regulation of pro-apoptotic genes is associated with the progression of malignant melanoma. The greatest fold-decrease occurs in the transformation from thin to thick lesions.

Differentially expressed genes between early and advanced hepatocellular carcinoma (HCC) as a potential tool for selecting liver transplant recipients

Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world. Liver transplantation (LT) represents a curative treatment for "small" HCC. Preoperative staging is critical in selecting optimal candidates for LT to optimize the use of this scarce resource. From December 1997 to February 2004, 148 patients diagnosed with cirrhosis and HCC were evaluated at our center. After staging, the patients were listed for LT according to United Network for Organ Sharing (UNOS) criteria. When pretransplant liver MRIs were compared with the findings of the explanted livers, 8 of 35 patients (22.8%) were understaged. Three of the 8 patients (37.5%) had recurrence post-LT. A retrospective gene expression profiling study was done using microarray technology for tumor samples in the pretransplant hepatitis C virus (HCV)-HCC understaged patients and in a contemporaneous group of HCV-HCC patients that were accurately staged. Two sample t tests comparing the early versus advanced HCV-HCCs with respect to gene expression showed an important set of genes differentially expressed among the samples. Hierarchical clustering analysis of the gene expression profiling classified 93.8% of the total tumor samples and 85.7% of the understaged samples in concordance with the explanted pathological staging. We found a distinctive pattern of gene expression between early and advanced HCV-HCCs. These results suggest that gene expression profiling could improve the pre-LT HCC staging to more closely mimic the explant pathology. Whether gene expression profiling of HCC will be refined to the point of predicting potential metastatic biologic behavior to predict post-LT recurrence will require longitudinal prospective study of this gene array technology.

mRNA expression, functional profiling and multivariate classification of colon biopsy specimen by cDNA overall glass microarray

AIM

To understand the local pathophysiological alterations and gene ontology-based functional classification of colonic biopsies into inflammatory and neoplastic diseases.

METHODS

Total RNA was extracted from frozen biopsies and amplified by T7-method. Expression profile was evaluated by Atlas Glass 1K microarrays. After microarray quality control, applicable data were available from 10 adenomas, 6 colorectal adenocarcinomas (CRCs), and 6 inflammatory bowel diseases (IBDs). Multivariate statistical and cell functional analyses were performed. Real-time RT-PCR and immunohistochemistry were used for validation.

RESULTS

Discriminant analysis of selected genes, could correctly reclassify all 22 samples using 4 parameters (heat shock transcription factor-1, bystin-like, calgranulin-A, TRAIL receptor 3). IBD samples were characterized by overregulated chemokine (C-X-C motif) ligand 13, replication protein A1, E74-like factor 2 and downregulated TNF receptor-associated factor 6, BCL2-interacting killer genes. In adenomas upregulation of TNF receptor-associated factor 6, replication protein A1, E74-like factor 2 and underexpression of BCL2-associated X protein, calgranulin-A genes were found. CRC cases had significantly increased epidermal growth factor receptor, topoisomerase-1, v-jun, TNF receptor-associated factor 6 and TRAIL receptor 3, and decreased RAD51 and RAD52 DNA repair gene, protein phosphatase-2A and BCL2-interacting killer mRNA levels. Epidermal growth factor receptor RT-PCR and immunohistochemistry, topoisomerase-1 RT-PCR confirmed the chip results.

CONCLUSION

Different histological alterations can be reclassified by functional, multivariate analysis using cDNA microarrays. Further studies with expanded sample number are needed for subclassification of pathological alterations.

Genomics and the Impact of New Technologies on the Management of Colorectal Cancer

High-throughput genomic technologies have the potential to have a major impact on preclinical and clinical drug development and the selection and stratification of patients in clinical trials. These technologies, which are at varying stages of commercialization, include array-based comparative genomic hybridization, single-nucleotide polymorphism arrays, and (the most mature example) expression-based arrays. One of the rate-limiting steps in the routine clinical application of expression array-based technology is the need for suitable clinical samples. One of the major challenges moving forward, therefore, relates to the ability to use formalin-fixed, paraffin-embedded--derived tissue in expression profiling-based approaches.

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.

Microarrays in gastrointestinal cancer: is personalized prediction of response to chemotherapy at hand?

PURPOSE OF REVIEW

Molecular profiling has proven to be an invaluable tool in cancer research. Although only in its infancy, microarray technology and gene arrays have led to substantial advances in tumor identification, staging and prediction of response. This review outlines some of the more recent advances in the use of microarrays as a novel means to advance the standard of care for patients with gastrointestinal cancers.

RECENT FINDINGS

Recent investigations have shown that gene expression profiles can be used to identify, stage, and guide therapeutic intervention in many gastrointestinal cancers. In cases of unknown primary disease, genetic fingerprints can be used to define the origin of the tumor in the majority of cases. Similarly, gene expression has been shown to allow for more accurate staging of patients with a variety of tumor types. Perhaps most exciting is early data that support the potential for microarray to guide therapeutic intervention by providing specific gene fingerprints which correlate with sensitivity to specific chemotherapy, biologic therapy, or other cancer treatments.

SUMMARY

Gene microarrays have become a powerful resource in cancer investigations. Individualized cancer care based on specific gene profiles is on the horizon for patients with gastrointestinal cancers.

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.

Transcriptional census of 36 microdissected colorectal cancers yields a gene signature to distinguish UICC II and III

UICC stage II and III colorectal cancers (CRC) differ fundamentally in prognosis and therapeutic concepts. To analyze differential gene expression between both stages and to establish a relationship between molecular background and clinical presentation, tumor material from 36 unselected consecutive patients presenting with sporadic CRC, 18 UICC stage II and 18 UICC stage III, were laser microdissected to separate epithelial tumor cells. Gene expression levels were measured using U133A Affymetrix gene arrays. Twelve CRC associated signal transduction pathways as well as all 22,000 probe sets were screened for differential gene expression. We identified a signature consisting of 45 probe sets that allowed discrimination between UICC stage II and stage III with a rate of correct classification of about 80%. The most distinctive elements in this signature were the gene GSTP-binding elongation factor (GSPT2) and the transcription factor HOXA9. Differential expression of these genes was confirmed by quantitative real-time polymerase chain reaction (p(HOXA9) = 0.04, p(GSTP2) = 0.02). Despite the reliability of the presented data, there was no substantial differential expression of genes in cancer-related pathways. However, the comparison with recently published data corroborates the 45 gene signature showing structural agreement in the direction of fold changes of gene expression levels for our set of genes chosen to discriminate between both stages.

Gene expression profiling of nonneoplastic mucosa may predict clinical outcome of colon cancer patients

PURPOSE

This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in Stage II and III colon cancer patients.

METHODS

Tumor and nonneoplastic mucosa mRNA samples from 12 colon cancer patients were profiled using the Affymetrix HGU133A GeneChip. Six of 12 patients experienced a metachronous metastasis, whereas the 6 others remained disease-free for more than five years. Three datasets were constituted, including, respectively, the gene expression measures in tumor samples (T), in adjacent nonneoplastic mucosa samples (A), and the log-ratio of the gene expression measures (L). The step-down procedure of Westfall and Young and the k-nearest neighbor class prediction method were applied on T, A, and L. Leave-one-out cross-validation was used to estimate the generalization error of predictors based on different numbers of genes and neighbors.

RESULTS

The most frequent results were one false prediction with the A-based predictors (95 percent) and two false predictions with the T- and L: -based predictors (65 and 60 percent, respectively). A-based predictors were more stable (i.e., less sensitive to changes of parameters, such as numbers of genes and neighbors) than T- and L: -based predictors. Informative genes in A-based predictors included genes involved in the oxidative and phosphorylative mitochondrial metabolism and genes involved in cell-signaling pathways and their receptors.

CONCLUSIONS

This study suggests that one can build a prognosis predictor for Stage II and III colon cancer patients, based on microarray gene expression measures, and suggests the potential usefulness of nonneoplastic mucosa for this purpose.

The results of the expression array studies correlate and enhance the known genetic basis of gastric and colorectal cancer

Gastric and colorectal cancers belong to the most frequent cancer types in the world today. This fact emphasizes the importance of identification of useful diagnostic and prognostic markers, in the earliest stage of the disease. The examination of gene expression profile in gastric and colorectal cancer may develop the bases of early diagnosis and of individual therapeutic strategies. In the microarray examinations done so far for these types of cancers, the expression of hundreds and thousands of genes were studied, however, both the sample collection and the results showed wide variations. The diversity of expression array methods and data analysis makes the comparison of microarray results difficult. Beside the exposition of the practical aspects of the chip technology, our aims are the systematization of data that are currently available in the international scientific literature and the description of the results in a comprehensive way. Microarray results show that the gene expression pattern, detected in gastric and colon cancers, highly depends on the histological type and heterogeneity of the sample, array type, and softwares, used for data analysis. Recent experiments point out not just the changes of the alterations of tumor suppression, apoptosis, cell-cycle regulation, and signal transduction, but tumor cell metabolism and cell-microenvironment interactions also. Results show connection to and make more complete the already known molecular background of gastric and colorectal cancers. Based on the accumulation of recent and further data, such kind of multifunctional diagnostic microarrays that can be suited for completing the conventional histological diagnostics and subtypization will certainly become available in the near future.

Colon cancer prognosis prediction by gene expression profiling

This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in stage II and III colon cancer patients. Tumour (T) and non-neoplastic mucosa (NM) mRNA samples from 18 patients (nine with a recurrence, nine with no recurrence) were profiled using the Affymetrix HGU133A GeneChip. The k-nearest neighbour method was used for prognosis prediction using T and NM gene expression measures. Six-fold cross-validation was applied to select the number of neighbours and the number of informative genes to include in the predictors. Based on this information, one T-based and one NM-based predictor were proposed and their accuracies were estimated by double cross-validation. In six-fold cross-validation, the lowest numbers of informative genes giving the lowest numbers of false predictions (two out of 18) were 30 and 70 with the T and NM gene expression measures, respectively. A 30-gene T-based predictor and a 70-gene NM-based predictor were then built, with estimated accuracies of 78 and 83%, respectively. This study suggests that one can build an accurate prognosis predictor for stage II and III colon cancer patients, based on gene expression measures, and one can use either tumour or non-neoplastic mucosa for this purpose.

Proteomic expression analysis of colorectal cancer by two-dimensional differential gel electrophoresis

The identification of specific protein markers for colorectal cancer would provide the basis for early diagnosis and detection, as well as clues for understanding the molecular mechanisms governing cancer progression. In this report, we describe the proteomic analysis of the samples of colorectal cancer corresponding to seven patients. We have used the highly sensitive two-dimensional differential gel electrophoresis (2-D DIGE) coupled with mass spectrometry (MS) for the identification of proteins differentially expressed in tumoral and neighboring normal mucosa. We have detected differences in abundance of 52 proteins with statistical variance of the tumor versus normal spot volume ratio within the 95th confidence level (Student's t-test; p < 0.05). Forty-one out of 52 analyzed proteins were unambiguously identified by matrix-assisted laser desorption/ionization-time of flight MS coupled with database interrogation as being differentially expressed in colorectal cancer. An ontology analysis of these proteins revealed that they were mainly involved in regulation of transcription (synovial sarcoma X5 protein, metastasis-associated protein 1), cellular reorganization and cytoskeleton (cytokeratins, vimentin, beta actin), cell communication and signal transduction (annexins IV and V, relaxin, APC), and protein synthesis and folding (heat shock protein 60, calreticulin, cathepsin D, RSP4) among others. Preliminary studies demonstrated that the differentially expressed proteins found by 2-D DIGE could be confirmed and validated by immunoblotting and immunohistochemistry analyses in those few cases where antibodies were available. We believe that the incorporation of more samples and new datasets will permit the definition of a collection of proteins with a potential interest as biomarkers for colorectal cancer.

Microarray versus conventional prediction of lymph node metastasis in colorectal carcinoma

BACKGROUND

The authors investigated whether microarray-based gene expression analysis of primary tumor biopsy material could be used to predict lymph node status in patients with colorectal carcinoma (CRC). Lymphatic metastasis strongly determines treatment algorithms in CRC. Currently, postoperative histology results are needed to determine lymph node status. Reliable preoperative information would be useful to advance treatment strategies.

METHODS

In specimens from 66 patients with CRC from the Erlangen Registry of Colorectal Cancer, 41 shock-frozen samples of International Union Against Cancer (UICC) Stage I-II CRC and 25 samples of UICC Stage III CRC were microdissected manually, RNA was isolated, and gene chips (HG-U133A; Affymetrix) were hybridized. Prediction rates for lymphatic metastasis were calculated using conventional clinicopathologic parameters, gene expression data, and a combination of both. Prediction error, specificity, and sensitivity were analyzed using six different statistical classifiers.

RESULTS

Analysis of conventional parameters produced a positive prediction rate that ranged between 53% and 61%, sensitivity of 42%, and specificity of 72%. Microarray prediction rates were between 62% and 67% for lymphatic metastasis. Specificity was between 76% and 83%, and sensitivity was between 38% and 48%, depending on the statistical procedure. The conventional estimates were improved by 9-12% when array data were added.

CONCLUSIONS

Current data show that the prediction of lymphatic metastasis can be improved by gene expression profiling of the primary tumor biopsy, alone or in combination with conventional parameters. Gene expression profiling may become valuable increasingly in planning treatment for patients with CRC.

Gene expression profiles of different clinical stages of colorectal carcinoma: toward a molecular genetic understanding of tumor progression

BACKGROUND AND AIMS

Colorectal cancer is one of the leading causes of cancer deaths in the Western world. A better understanding of the development and progression of colorectal carcinoma is needed to define novel targets and strategies for treatment.

PATIENTS/METHODS

Gene expression profiles were determined for primary tumors of 10 locally restricted (T3N0M0), 8 lymphatically metastasized (T3N+M0), 7 systemically metastasized (T3N+M1) colorectal carcinomas, and 6 specimens of normal colorectal tissue by histology-guided oligonucleotide microarray analysis.

RESULTS

A total of 1,995 genes were differently regulated in primary tumors of colorectal carcinoma compared with normal colorectal tissue. Besides common features of dedifferentiation and different expression of genes involved in cell division, cell adhesion, angiogenesis, signal transduction and metabolism we observed a deregulation of genes with an as yet unclear function. We identified 126 genes that were subsequently up- and 204 genes down-regulated during tumor progression. Furthermore, we found a cluster of five genes exclusively up-regulated in primary tumors of systemically metastasized colorectal carcinomas. A comparison of locally restricted (T3N0M0) and systemically metastasized (T3N+M1) primary tumors showed 50 deregulated genes with a massive down-regulation of immune-modulatory genes in primary tumors of systemically metastasized carcinomas. Primary tumors of lymphatically (T3N+M0) and systemically metastasized (T3N+M1) carcinomas differed in the expression of 19 genes.

CONCLUSION

These results provide an additional step toward the identification of crucial genes for the progression of colorectal cancer and the identification of novel treatment targets or strategies.

Metastatic transcriptional pattern revealed by gene expression profiling in primary colorectal carcinoma

Metastatic spread to the liver is the major contributor to mortality in patients with colorectal carcinoma (CRC). In order to seek for gene expression patterns associated with metastatic potential in primary CRC, we compared the transcriptional profiles of 10 radically resected primary CRCs from patients who did not develop distant metastases within a 5-year follow-up period with those of 10 primary/metastatic tumor pairs from patients with synchronous liver metastases. To focus selectively on neoplastic cells, the study was conducted on laser-microdissected bioptic tissues. Arrays of 7,864 human cDNAs were utilized. While a striking transcriptional similarity was observed between the primary tumors and their distant metastases, the nonmetastasizing primary tumors were clearly distinct from the primary/metastatic tumor pairs. Of 37 gene expression differences found between the 2 groups of primary tumors, 29 also distinguished nonmetastasizing tumors from metastases. The gene encoding for mannosyl (alpha-1,3-)-glycoprotein beta-1,4-N-acetyl-glucosaminyl-transferase (GnT-IV) became significantly upregulated in primary/metastatic tumor pairs (p < 0.001). GnT-IV upregulation was confirmed by RT-PCR. These data support the existence of a specific transcriptional signature distinguishing primary colon adenocarcinomas with different metastatic potential, the further pursuit of which may lead to relevant clinical and therapeutic applications.