David Cordero

Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.

Introduction The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. Methods A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. Results Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. Conclusions The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.

Gene Expression Differences between Colon and Rectum Tumors

Purpose: Colorectal cancer studies typically include both colon and rectum tumors as a common entity, though this assumption is controversial and only minor differences have been reported at the molecular and epidemiologic level. We conducted a molecular study based on gene expression data of tumors from colon and rectum to assess the degree of similarity between these cancer sites at transcriptomic level. Experimental Design: A pooled analysis of 460 colon tumors and 100 rectum tumors from four data sets belonging to three independent studies was conducted. Microsatellite instable tumors were excluded as these are known to have a different expression profile and have a preferential proximal colon location. Expression differences were assessed with linear models, and significant genes were identified using adjustment for multiple comparisons. Results: Minor differences at a gene expression level were found between tumors arising in the proximal colon, distal colon, or rectum. Only several HOX genes were found to be associated with tumor location. More differences were found between proximal and distal colon than between distal colon and rectum. Conclusions: Microsatellite stable colorectal cancers do not show major transcriptomic differences for tumors arising in the colon or rectum. The small but consistent differences observed are largely driven by the HOX genes. These results may have important implications in the design and interpretation of studies in colorectal cancer. Clin Cancer Res; 17(23); 7303–12. ©2011 AACR.

Aberrant gene expression in mucosa adjacent to tumor reveals a molecular crosstalk in colon cancer

BackgroundA colorectal tumor is not an isolated entity growing in a restricted location of the body. The patient’s gut environment constitutes the framework where the tumor evolves and this relationship promotes and includes a complex and tight correlation of the tumor with inflammation, blood vessels formation, nutrition, and gut microbiome composition. The tumor influence in the environment could both promote an anti-tumor or a pro-tumor response.MethodsA set of 98 paired adjacent mucosa and tumor tissues from colorectal cancer (CRC) patients and 50 colon mucosa from healthy donors (246 samples in total) were included in this work. RNA extracted from each sample was hybridized in Affymetrix chips Human Genome U219. Functional relationships between genes were inferred by means of systems biology using both transcriptional regulation networks (ARACNe algorithm) and protein-protein interaction networks (BIANA software).ResultsHere we report a transcriptomic analysis revealing a number of genes activated in adjacent mucosa from CRC patients, not activated in mucosa from healthy donors. A functional analysis of these genes suggested that this active reaction of the adjacent mucosa was related to the presence of the tumor. Transcriptional and protein-interaction networks were used to further elucidate this response of normal gut in front of the tumor, revealing a crosstalk between proteins secreted by the tumor and receptors activated in the adjacent colon tissue; and vice versa. Remarkably, Slit family of proteins activated ROBO receptors in tumor whereas tumor-secreted proteins transduced a cellular signal finally activating AP-1 in adjacent tissue.ConclusionsThe systems-level approach provides new insights into the micro-ecology of colorectal tumorogenesis. Disrupting this intricate molecular network of cell-cell communication and pro-inflammatory microenvironment could be a therapeutic target in CRC patients.

Tools for protein-protein interaction network analysis in cancer research

As cancer is a complex disease, the representation of a malignant cell as a protein-protein interaction network (PPIN) and its subsequent analysis can provide insight into the behaviour of cancer cells and lead to the discovery of new biomarkers. The aim of this review is to help life-science researchers without previous computer programming skills to extract meaningful biological information from such networks, taking advantage of easyto-use, public bioinformatics tools. It is structured in four parts: the first section describes the pipeline of consecutive steps from network construction to biological hypothesis generation. The second part provides a repository of public, user-friendly tools for network construction, visualisation and analysis. Two different and complementary approaches of network analysis are presented: the topological approach studies the network as a whole by means of structural graph theory, whereas the global approach divides the PPIN into sub-graphs, or modules. In section three, some concepts and tools regarding heterogeneous molecular data integration through a PPIN are described. Finally, the fourth part is an example of how to extract meaningful biological information from a colorectal cancer PPIN using some of the described tools.

Oncogenic KRAS is not necessary for Wnt signalling activation in APC-associated FAP adenomas.

Recent studies have suggested that APC loss alone may be insufficient to promote aberrant Wnt/β‐catenin signalling. Our aim was to comprehensively characterize Wnt signalling components in a set of APC‐associated familial adenomatous polyposis (FAP) tumours. Sixty adenomas from six FAP patients with known pathogenic APC mutations were included. Somatic APC and KRAS mutations, β‐catenin immunostaining, and qRT‐PCR of APC, MYC, AXIN2 and SFRP1 were analysed. Array‐comparative genomic hybridization (aCGH) was also assessed in 26 FAP adenomas and 24 paired adenoma–carcinoma samples. A somatic APC alteration was present in 15 adenomas (LOH in 11 and four point mutations). KRAS mutations were detected in 10% of the cases. APC mRNA was overexpressed in adenomas. MYC and AXIN2 were also overexpressed, with significant intra‐case heterogeneity. Increased cytoplasmic and/or nuclear β‐catenin staining was seen in 94% and 80% of the adenomas. β‐Catenin nuclear staining was strongly associated with MYC levels (p value 0.03) but not with KRAS mutations. Copy number aberrations were rare. However, the recurrent chromosome changes observed more frequently contained Wnt pathway genes (p value 0.012). Based on β‐catenin staining and Wnt pathway target genes alterations the Wnt pathway appears to be constitutively activated in all APC‐FAP tumours, with alterations occurring both upstream and downstream of APC. Wnt aberrations are present at both the DNA and the RNA level. Somatic profiling of APC‐FAP tumours provides new insights into the role of APC in tumourigenesis. Copyright

Identification of candidate susceptibility genes for colorectal cancer through eQTL analysis

In this study, we aim to identify the genes responsible for colorectal cancer risk behind the loci identified in genome-wide association studies (GWAS). These genes may be candidate targets for developing new strategies for prevention or therapy. We analyzed the association of genotypes for 26 GWAS single nucleotide polymorphisms (SNPs) with the expression of genes within a 2 Mb region (cis-eQTLs). Affymetrix Human Genome U219 expression arrays were used to assess gene expression in two series of samples, one of healthy colonic mucosa (n = 47) and other of normal mucosa adjacent to colon cancer (n = 97, total 144). Paired tumor tissues (n = 97) were also analyzed but did not provide additional findings. Partial Pearson correlation (r), adjusted for sample type, was used for the analysis. We have found Bonferroni-significant cis-eQTLs in three loci: rs3802842 in 11q23.1 associated to C11orf53, COLCA1 (C11orf92) and COLCA2 (C11orf93; r = 0.60); rs7136702 in 12q13.12 associated to DIP2B (r = 0.63) and rs5934683 in Xp22.3 associated to SHROOM2 and GPR143 (r = 0.47). For loci in chromosomes 11 and 12, we have found other SNPs in linkage disequilibrium that are more strongly associated with the expression of the identified genes and are better functional candidates: rs7130173 for 11q23.1 (r = 0.66) and rs61927768 for 12q13.12 (r = 0.86). These SNPs are located in DNA regions that may harbor enhancers or transcription factor binding sites. The analysis of trans-eQTLs has identified additional genes in these loci that may have common regulatory mechanisms as shown by the analysis of protein-protein interaction networks.

Discovery and Validation of New Potential Biomarkers for Early Detection of Colon Cancer

Background Accurate detection of characteristic proteins secreted by colon cancer tumor cells in biological fluids could serve as a biomarker for the disease. The aim of the present study was to identify and validate new serum biomarkers and demonstrate their potential usefulness for early diagnosis of colon cancer. Methods The study was organized in three sequential phases: 1) biomarker discovery, 2) technical and biological validation, and 3) proof of concept to test the potential clinical use of selected biomarkers. A prioritized subset of the differentially-expressed genes between tissue types (50 colon mucosa from cancer-free individuals and 100 normal-tumor pairs from colon cancer patients) was validated and further tested in a series of serum samples from 80 colon cancer cases, 23 patients with adenoma and 77 cancer-free controls. Results In the discovery phase, 505 unique candidate biomarkers were identified, with highly significant results and high capacity to discriminate between the different tissue types. After a subsequent prioritization, all tested genes (N = 23) were successfully validated in tissue, and one of them, COL10A1, showed relevant differences in serum protein levels between controls, patients with adenoma (p = 0.0083) and colon cancer cases (p = 3.2e-6). Conclusion We present a sequential process for the identification and further validation of biomarkers for early detection of colon cancer that identifies COL10A1 protein levels in serum as a potential diagnostic candidate to detect both adenoma lesions and tumor. Impact The use of a cheap serum test for colon cancer screening should improve its participation rates and contribute to decrease the burden of this disease.

Exome sequencing reveals AMER1 as a frequently mutated gene in colorectal cancer

Purpose: Somatic mutations occur at early stages of adenoma and accumulate throughout colorectal cancer progression. The aim of this study was to characterize the mutational landscape of stage II tumors and to search for novel recurrent mutations likely implicated in colorectal cancer tumorigenesis. Experimental Design: The exomic DNA of 42 stage II, microsatellite-stable colon tumors and their paired mucosae were sequenced. Other molecular data available in the discovery dataset [gene expression, methylation, and copy number variations (CNV)] were used to further characterize these tumors. Additional datasets comprising 553 colorectal cancer samples were used to validate the discovered mutations. Results: As a result, 4,886 somatic single-nucleotide variants (SNV) were found. Almost all SNVs were private changes, with few mutations shared by more than one tumor, thus revealing tumor-specific mutational landscapes. Nevertheless, these diverse mutations converged into common cellular pathways, such as cell cycle or apoptosis. Among this mutational heterogeneity, variants resulting in early stop codons in the AMER1 (also known as FAM123B or WTX) gene emerged as recurrent mutations in colorectal cancer. Losses of AMER1 by other mechanisms apart from mutations such as methylation and copy number aberrations were also found. Tumors lacking this tumor suppressor gene exhibited a mesenchymal phenotype characterized by inhibition of the canonical Wnt pathway. Conclusions: In silico and experimental validation in independent datasets confirmed the existence of functional mutations in AMER1 in approximately 10% of analyzed colorectal cancer tumors. Moreover, these tumors exhibited a characteristic phenotype. Clin Cancer Res; 21(20); 4709–18. ©2015 AACR.

Polymorphisms in Alcohol Metabolism Genes ADH1B and ALDH2, Alcohol Consumption and Colorectal Cancer

Background Colorectal cancer (CRC) is a leading cause of cancer death worldwide. Epidemiological risk factors for CRC included alcohol intake, which is mainly metabolized to acetaldehyde by alcohol dehydrogenase and further oxidized to acetate by aldehyde dehydrogenase; consequently, the role of genes in the alcohol metabolism pathways is of particular interest. The aim of this study is to analyze the association between SNPs in ADH1B and ALDH2 genes and CRC risk, and also the main effect of alcohol consumption on CRC risk in the study population. Methodology/Principal Findings SNPs from ADH1B and ALDH2 genes, included in alcohol metabolism pathway, were genotyped in 1694 CRC cases and 1851 matched controls from the Molecular Epidemiology of Colorectal Cancer study. Information on clinicopathological characteristics, lifestyle and dietary habits were also obtained. Logistic regression and association analysis were conducted. A positive association between alcohol consumption and CRC risk was observed in male participants from the Molecular Epidemiology of Colorectal Cancer study (MECC) study (OR = 1.47; 95%CI = 1.18-1.81). Moreover, the SNPs rs1229984 in ADH1B gene was found to be associated with CRC risk: under the recessive model, the OR was 1.75 for A/A genotype (95%CI = 1.21-2.52; p-value = 0.0025). A path analysis based on structural equation modeling showed a direct effect of ADH1B gene polymorphisms on colorectal carcinogenesis and also an indirect effect mediated through alcohol consumption. Conclusions/Significance Genetic polymorphisms in the alcohol metabolism pathways have a potential role in colorectal carcinogenesis, probably due to the differences in the ethanol metabolism and acetaldehyde oxidation of these enzyme variants.

Large differences in global transcriptional regulatory programs of normal and tumor colon cells

BackgroundDysregulation of transcriptional programs leads to cell malfunctioning and can have an impact in cancer development. Our study aims to characterize global differences between transcriptional regulatory programs of normal and tumor cells of the colon.MethodsAffymetrix Human Genome U219 expression arrays were used to assess gene expression in 100 samples of colon tumor and their paired adjacent normal mucosa. Transcriptional networks were reconstructed using ARACNe algorithm using 1,000 bootstrap replicates consolidated into a consensus network. Networks were compared regarding topology parameters and identified well-connected clusters. Functional enrichment was performed with SIGORA method. ENCODE ChIP-Seq data curated in the hmChIP database was used for in silico validation of the most prominent transcription factors.ResultsThe normal network contained 1,177 transcription factors, 5,466 target genes and 61,226 transcriptional interactions. A large loss of transcriptional interactions in the tumor network was observed (11,585; 81% reduction), which also contained fewer transcription factors (621; 47% reduction) and target genes (2,190; 60% reduction) than the normal network. Gene silencing was not a main determinant of this loss of regulatory activity, since the average gene expression was essentially conserved. Also, 91 transcription factors increased their connectivity in the tumor network. These genes revealed a tumor-specific emergent transcriptional regulatory program with significant functional enrichment related to colorectal cancer pathway. In addition, the analysis of clusters again identified subnetworks in the tumors enriched for cancer related pathways (immune response, Wnt signaling, DNA replication, cell adherence, apoptosis, DNA repair, among others). Also multiple metabolism pathways show differential clustering between the tumor and normal network.ConclusionsThese findings will allow a better understanding of the transcriptional regulatory programs altered in colon cancer and could be an invaluable methodology to identify potential hubs with a relevant role in the field of cancer diagnosis, prognosis and therapy.