A susceptibility gene set for early onset colorectal cancer that integrates diverse signaling pathways: implication for tumorigenesis

Genome-wide association study identified copy number variants associated with sporadic colorectal cancer risk

Background

Multiple single nucleotide polymorphisms (SNPs) have been associated with colorectal cancer (CRC) risk. The role of structural or copy number variants (CNV) in CRC, however, remained unclear. We investigated the role of CNVs in patients with sporadic CRC.

Methods

A genome-wide association study (GWAS) was performed on 1000 Singapore Chinese patients aged 50 years or more with no family history of CRC and 1000 ethnicity-matched, age-matched and gender-matched healthy controls using the Affymetrix SNP 6 platform. After 16 principal component corrections, univariate and multivariate segmentations followed by association testing were performed on 1830 samples that passed quality assurance tests.

Results

A rare CNV region (CNVR) at chromosome 14q11 (OR=1.92 (95% CI 1.59 to 2.32), p=2.7e-12) encompassing CHD8, and common CNVR at chromosomes 3q13.12 (OR=1.54 (95% CI 1.33 to 1.77), p=2.9e-9) and 12p12.3 (OR=1.69 (95% CI 1.41 to 2.01), p=2.8e-9) encompassing CD47 and RERG/ARHGDIB, respectively, were significantly associated with CRC risk. CNV loci were validated in an independent replication panel using an optimised copy number assay. Whole-genome expression data in matched tumours of a subset of cases demonstrated that copy number loss at CHD8 was significantly associated with dysregulation of several genes that perturb the Wnt, TP53 and inflammatory pathways.

Conclusions

A rare CNVR at 14q11 encompassing the chromatin modifier CHD8 was significantly associated with sporadic CRC risk. Copy number loss at CHD8 altered expressions of genes implicated in colorectal tumourigenesis.

Knockdown of tripartite motif-59 inhibits the malignant processes in human colorectal cancer cells

The aim of the present study was to clarify the clinical implication and functional role of tripartite motif-59 (TRIM59) in colorectal carcinoma (CRC) and explore the underlying mechanism of aberrant high expression of TRIM59 in cancer. We validated that TRIM59 was upregulated in CRC samples, and also demonstrated that its upregulation was associated with advanced tumor stage of CRC patients; and its high expression indicated shorter overall survival and faster recurrence. Knockdown of TRIM59 significantly inhibited cell proliferation, migration and invasion. Cell cycle analysis showed that TRIM59-depleted cells accumulated in S-phase. In addition, the cell cycle regulators CDC25C, cyclin B1 and cyclin D1 were decreased by TRIM59 siRNA mediated knockdown. Furthermore, the depletion of TRIM59 promoted apoptosis in cell culture as indicated by the cleavage of caspase-3 and PARP when TRIM59 was depleted. These results suggested that TRIM59 is upregulated in human colorectal tumors compared with non-tumor tissues. The level of TRIM59 is correlated with malignant features of CRC and may serve as potential therapeutic and preventive strategies for CRC.

Role of keratin 24 in human epidermal keratinocytes

Keratin 24 (K24) is a new kind of keratin genes, which encodes a novel keratin protein, K24 that bears high similarity to the type I keratins and displays a unique expression profile. However, the role of K24 is incompletely understood. In our study, we investigated the localization of K24 within the epidermis and possible functions. Keratin 24 was found to be modestly overexpressed in senescent keratinocytes and was mainly restricted to the upper stratum spinosum of epidermis. The protein was required for terminal differentiation upon CaCl2-induced differentiation. In vitro results showed that increased K24 in keratinocytes dramatically changed the differentiation of primary keratinocytes. It also inhibited cell survival by G1/S phase cell cycle arrest and induced senescence, autophagy and apoptosis of keratinocytes. In addition, K24 activated PKCδ signal pathway involving in cellular survival. In summary, K24 may be suggested as a potential differentiation marker and anti-proliferative factor in the epidermis.

Identification of Key Candidate Genes and Pathways in Colorectal Cancer by Integrated Bioinformatical Analysis

Colorectal cancer (CRC) is one of the most common malignant diseases worldwide, but the involved signaling pathways and driven-genes are largely unclear. This study integrated four cohorts profile datasets to elucidate the potential key candidate genes and pathways in CRC. Expression profiles GSE28000, GSE21815, GSE44076 and GSE75970, including 319 CRC and 103 normal mucosa, were integrated and deeply analyzed. Differentially expressed genes (DEGs) were sorted and candidate genes and pathways enrichment were analyzed. DEGs-associated protein–protein interaction network (PPI) was performed. Firstly, 292 shared DEGs (165 up-regulated and 127 down-regulated) were identified from the four GSE datasets. Secondly, the DEGs were clustered based on functions and signaling pathways with significant enrichment analysis. Thirdly, 180 nodes/DEGs were identified from DEGs PPI network complex. Lastly, the most significant 2 modules were filtered from PPI, 31 central node genes were identified and most of the corresponding genes are involved in cell cycle process, chemokines and G protein-coupled receptor signaling pathways. Taken above, using integrated bioinformatical analysis, we have identified DEGs candidate genes and pathways in CRC, which could improve our understanding of the cause and underlying molecular events, and these candidate genes and pathways could be therapeutic targets for CRC.

Chromosome 19q13 disruption alters expressions of CYP2A7, MIA and MIA-RAB4B lncRNA and contributes to FAP-like phenotype in APC mutation-negative familial colorectal cancer patients

Familial adenomatous polyposis (FAP) is an autosomal-dominantly inherited form of colorectal cancer (CRC) caused by mutation in the adenomatous polyposis coli (APC) gene. Our ability to exhaustively screen for APC mutations identify microsatellite-stable and APC-mutation negative familial CRC patients, enabling us to search for novel genes. We performed genome-wide scan on two affected siblings of one family and 88 ethnicity- and gender-matched healthy controls to identify deletions shared by the siblings. Combined loss of heterozygosity, copy number and allelic-specific copy number analysis uncovered 5 shared deletions. Long-range polymerase chain reaction (PCR) confirmed chromosome 19q13 deletion, which was subsequently found in one other family. The 32 kb deleted region harbors the CYP2A7 gene and was enriched with enhancer, repressor and insulator sites. The wildtype allele was lost in the polyps of the proband. Further, real-time RT-PCR assays showed that expressions of MIA and MIA-RAB4B located 35 kb upstream of the deletion, were up-regulated in the polyps compared to the matched mucosa of the proband. MIA-RAB4B, the read-through long non-coding RNA (lncRNA), RAB4B, PIM2 and TAOK1 share common binding site of a microRNA, miR-24, in their 3'UTRs. PIM2 and TAOK1, two target oncogenes of miR-24, were co-ordinately up-regulated with MIA-RAB4B in the polyps, suggesting that MIA-RAB4B could function as competitive endogenous RNA to titrate miR-24 away from its other targets. The data suggest that the 19.13 deletion disrupted chromatin boundary, leading to altered expression of several genes and lncRNA, could contribute to colorectal cancer via novel genetic and epigenetic mechanisms.

Databases and tools for constructing signal transduction networks in cancer

Traditionally, biologists have devoted their careers to studying individual biological entities of their own interest, partly due to lack of available data regarding that entity. Large, high-throughput data, too complex for conventional processing methods (i.e., “big data”), has accumulated in cancer biology, which is freely available in public data repositories. Such challenges urge biologists to inspect their biological entities of interest using novel approaches, firstly including repository data retrieval. Essentially, these revolutionary changes demand new interpretations of huge datasets at a systems-level, by so called “systems biology”. One of the representative applications of systems biology is to generate a biological network from high-throughput big data, providing a global map of molecular events associated with specific phenotype changes. In this review, we introduce the repositories of cancer big data and cutting-edge systems biology tools for network generation, and improved identification of therapeutic targets.

A novel pathway analysis approach based on the unexplained disregulation of genes

A crucial step in the understanding of any phenotype is the correct identification of the signaling pathways that are significantly impacted in that phenotype. However, most current pathway analysis methods produce both false positives as well as false negatives in certain circumstances. We hypothesized that such incorrect results are due to the fact that the existing methods fail to distinguish between the primary dis-regulation of a given gene itself and the effects of signaling coming from upstream. Furthermore, a modern whole-genome experiment performed with a next-generation technology spends a great deal of effort to measure the entire set of 30,000-100,000 transcripts in the genome. This is followed by the selection of a few hundreds differentially expressed genes, step that literally discards more than 99% of the collected data. We also hypothesized that such a drastic filtering could discard many genes that play crucial roles in the phenotype. We propose a novel topology-based pathway analysis method that identifies significantly impacted pathways using the entire set of measurements, thus allowing the full use of the data provided by NGS techniques. The results obtained on 24 real data sets involving 12 different human diseases, as well as on 8 yeast knock-out data sets show that the proposed method yields significant improvements with respect to the state-of-the-art methods: SPIA, GSEA and GSA.

AVAILABILITY

Primary dis-regulation analysis is implemented in R and included in ROntoTools Bioconductor package (versions ≥ 2.0.0). https://www.bioconductor.org/packages/release/bioc/html/ROntoTools.html.

A novel statistical approach for identification of the master regulator transcription factor

BACKGROUND

Transcription factors are known to play key roles in carcinogenesis and therefore, are gaining popularity as potential therapeutic targets in drug development. A 'master regulator' transcription factor often appears to control most of the regulatory activities of the other transcription factors and the associated genes. This 'master regulator' transcription factor is at the top of the hierarchy of the transcriptomic regulation. Therefore, it is important to identify and target the master regulator transcription factor for proper understanding of the associated disease process and identifying the best therapeutic option.

METHODS

We present a novel two-step computational approach for identification of master regulator transcription factor in a genome. At the first step of our method we test whether there exists any master regulator transcription factor in the system. We evaluate the concordance of two ranked lists of transcription factors using a statistical measure. In case the concordance measure is statistically significant, we conclude that there is a master regulator. At the second step, our method identifies the master regulator transcription factor, if there exists one.

RESULTS

In the simulation scenario, our method performs reasonably well in validating the existence of a master regulator when the number of subjects in each treatment group is reasonably large. In application to two real datasets, our method ensures the existence of master regulators and identifies biologically meaningful master regulators. An R code for implementing our method in a sample test data can be found in http://www.somnathdatta.org/software .

CONCLUSION

We have developed a screening method of identifying the 'master regulator' transcription factor just using only the gene expression data. Understanding the regulatory structure and finding the master regulator help narrowing the search space for identifying biomarkers for complex diseases such as cancer. In addition to identifying the master regulator our method provides an overview of the regulatory structure of the transcription factors which control the global gene expression profiles and consequently the cell functioning.

N-terminal truncated carboxypeptidase E expression is associated with poor prognosis of lung adenocarcinoma

Lung cancer is a malignant tumor with high morbidity and mortality rates. To date, no suitable molecular diagnostic tool to predict disease recurrence and metastasis has been identified. The current study aimed to evaluate the potential of N-terminal truncated carboxypeptidase E (CPEΔN) to predict the recurrence and metastasis of lung adenocarcinoma. Western blotting revealed the co-expression of CPE and CPEΔN in the surgically collected pathological and pericarcinoma tissues tissues of 62.1% (59/95) lung adenocarcinoma patients. The full length CPE protein was predominantly expressed in pericarcinoma tissues and CPEΔN expression was identified in the pericarcinoma normal tissues of only 5.26% (5/95) patients. The 3-year postoperative recurrence and metastasis rates were significantly higher in patients with positive CPEΔN expression than in patients with negative CPEΔN expression (P=0.009). Furthermore, the overall survival rate of patients with predominant nuclear CPE expression was lower than that of patients with predominant cytoplasmic CPE expression (46.3 vs. 64.7%); however, no statistically significant difference was identified (P=0.125). Thus, the results of the current study indicated that CPEΔN may present a novel molecular biomarker for predicting recurrence and metastasis of lung adenocarcinoma, which may aid with stratifying patients by risk and thus, may facilitate individualized therapy.

CYR61 and TAZ Upregulation and Focal Epithelial to Mesenchymal Transition May Be Early Predictors of Barrett's Esophagus Malignant Progression

Barrett's esophagus is the major risk factor for esophageal adenocarcinoma. It has a low but non-neglectable risk, high surveillance costs and no reliable risk stratification markers. We sought to identify early biomarkers, predictive of Barrett's malignant progression, using a meta-analysis approach on gene expression data. This in silico strategy was followed by experimental validation in a cohort of patients with extended follow up from the Instituto Português de Oncologia de Lisboa de Francisco Gentil EPE (Portugal). Bioinformatics and systems biology approaches singled out two candidate predictive markers for Barrett's progression, CYR61 and TAZ. Although previously implicated in other malignancies and in epithelial-to-mesenchymal transition phenotypes, our experimental validation shows for the first time that CYR61 and TAZ have the potential to be predictive biomarkers for cancer progression. Experimental validation by reverse transcriptase quantitative PCR and immunohistochemistry confirmed the up-regulation of both genes in Barrett's samples associated with high-grade dysplasia/adenocarcinoma. In our cohort CYR61 and TAZ up-regulation ranged from one to ten years prior to progression to adenocarcinoma in Barrett's esophagus index samples. Finally, we found that CYR61 and TAZ over-expression is correlated with early focal signs of epithelial to mesenchymal transition. Our results highlight both CYR61 and TAZ genes as potential predictive biomarkers for stratification of the risk for development of adenocarcinoma and suggest a potential mechanistic route for Barrett's esophagus neoplastic progression.

Exosomes in colorectal carcinoma formation: ALIX under the magnifying glass

Exosomes are small membrane vesicles that have important roles in transporting a great variety of bioactive molecules between epithelial compartment and their microenvironment during tumor formation including colorectal adenoma-carcinoma sequence. We tested the mRNA expression of the top 25 exosome-related markers based on ExoCharta database in healthy (n=49), adenoma (n=49) and colorectal carcinoma (n=49) patients using Affymetrix HGU133 Plus2.0 microarrays. Most related genes showed significantly elevated expression including PGK1, PKM, ANXA5, ENO1, HSP90AB1 and MSN during adenoma-carcinoma sequence. Surprisingly, the expression of ALIX (ALG 2-interacting protein X), involved in multivesicular body (MVB) and exosome formation, was significantly reduced in normal vs adenoma (P=5.02 × 10(-13)) and in normal vs colorectal carcinoma comparisons (P=1.51 × 10(-10)). ALIX also showed significant reduction (P<0.05) at the in situ protein level in the epithelial compartment of adenoma (n=35) and colorectal carcinoma (n=37) patients compared with 27 healthy individuals. Furthermore, significantly reduced ALIX protein levels were accompanied by their gradual transition from diffuse cytoplasmic expression to granular signals, which fell into the 0.6-2 μm diameter size range of MVBs. These ALIX-positive particles were seen in the tumor nests, including tumor-stroma border, which suggest their exosome function. MVB-like structures were also detected in tumor microenvironment including α-smooth muscle actin-positive stromal cells, budding off cancer cells in the tumor front as well as in cancer cells entrapped within lymphoid vessels. In conclusion, we determined the top aberrantly expressed exosome-associated markers and revealed the transition of diffuse ALIX protein signals into a MVB-like pattern during adenoma-carcinoma sequence. These tumor-associated particles seen both in the carcinoma and the surrounding microenvironment can potentially mediate epithelial-stromal interactions involved in the regulation of tumor growth, metastatic invasion and therapy response.

Krüppel-Like Factor 12 Promotes Colorectal Cancer Growth through Early Growth Response Protein 1

Krüppel-like factor 12 (KLF12) is a transcription factor that plays a role in normal kidney development and repression of decidualization. KLF12 is frequently elevated in esophageal adenocarcinoma and has been reported to promote gastric cancer progression. Here, we examined the role of KLF12 in colorectal cancer (CRC). Indeed, KLF12 promotes tumor growth by directly activating early growth response protein 1 (EGR1). The levels of KLF12 and EGR1 correlate synergistically with a poor prognosis. These results indicate that KLF12 likely plays an important role in CRC and could serve as a potential prognostic marker and therapeutic target.

SPATIAL: A System-level PAThway Impact AnaLysis approach

The goal of pathway analysis is to identify the pathways that are significantly impacted when a biological system is perturbed, e.g. by a disease or drug. Current methods treat pathways as independent entities. However, many signals are constantly sent from one pathway to another, essentially linking all pathways into a global, system-wide complex. In this work, we propose a set of three pathway analysis methods based on the impact analysis, that performs a system-level analysis by considering all signals between pathways, as well as their overlaps. Briefly, the global system is modeled in two ways: (i) considering the inter-pathway interaction exchange for each individual pathways, and (ii) combining all individual pathways to form a global, system-wide graph. The third analysis method is a hybrid of these two models. The new methods were compared with DAVID, GSEA, GSA, PathNet, Crosstalk and SPIA on 23 GEO data sets involving 19 tissues investigated in 12 conditions. The results show that both the ranking and the P-values of the target pathways are substantially improved when the analysis considers the system-wide dependencies and interactions between pathways.

Gene-set activity toolbox (GAT): A platform for microarray-based cancer diagnosis using an integrative gene-set analysis approach

Cancer is a complex disease that cannot be diagnosed reliably using only single gene expression analysis. Using gene-set analysis on high throughput gene expression profiling controlled by various environmental factors is a commonly adopted technique used by the cancer research community. This work develops a comprehensive gene expression analysis tool (gene-set activity toolbox: (GAT)) that is implemented with data retriever, traditional data pre-processing, several gene-set analysis methods, network visualization and data mining tools. The gene-set analysis methods are used to identify subsets of phenotype-relevant genes that will be used to build a classification model. To evaluate GAT performance, we performed a cross-dataset validation study on three common cancers namely colorectal, breast and lung cancers. The results show that GAT can be used to build a reasonable disease diagnostic model and the predicted markers have biological relevance. GAT can be accessed from http://gat.sit.kmutt.ac.th where GAT's java library for gene-set analysis, simple classification and a database with three cancer benchmark datasets can be downloaded.

Kinase-Dependent and -Independent Roles for PTK6 in Colon Cancer

Disruption of the gene encoding Protein Tyrosine Kinase 6 (Ptk6) delayed differentiation and increased growth in the mouse intestine. However, Ptk6-null mice were also resistant to azoxymethane-induced colon tumorigenesis. To further explore functions of PTK6 in colon cancer, expression of epithelial and mesenchymal markers, as well as proliferation, migration, and xenograft tumor growth, was examined in human colon tumor cell lines with knockdown or overexpression of PTK6. PTK6 protein, transcript, and activation were also examined in a human colon tumor tissue array, using immunohistochemistry and qRT-PCR. Knockdown of PTK6 led to the epithelial-mesenchymal transition (EMT) in SW480 and HCT116 cells, whereas overexpression of PTK6 in SW620 cells restored an epithelial phenotype in a kinase-independent manner. PTK6 knockdown also increased xenograft tumor growth of SW480 cells, suggesting tumor suppressor functions. In clinical specimens, PTK6 expression was highest in normal differentiated epithelial cells and reduced in tumors. In contrast, overexpression of constitutively active PTK6 promoted STAT3 and ERK5 activation in colon cancer cells, and endogenous PTK6 promoted cell survival and oncogenic signaling in response to DNA-damaging treatments. These data indicate that PTK6 has complex, context-specific functions in colon cancer; PTK6 promotes the epithelial phenotype to antagonize the EMT in a kinase-independent manner, whereas activation of PTK6 promotes oncogenic signaling.

IMPLICATIONS

Understanding context-specific functions of PTK6 is important, because although it promotes cell survival and oncogenic signaling after DNA damage, expression of PTK6 in established tumors may maintain the epithelial phenotype, preventing tumor progression. Mol Cancer Res; 14(6); 563-73. ©2016 AACR.

Acetylcarnitine Is a Candidate Diagnostic and Prognostic Biomarker of Hepatocellular Carcinoma

The identification of serum biomarkers to improve the diagnosis and prognosis of hepatocellular carcinoma has been elusive to date. In this study, we took a mass spectroscopic approach to characterize metabolic features of the liver in hepatocellular carcinoma patients to discover more sensitive and specific biomarkers for diagnosis and progression. Global metabolic profiling of 50 pairs of matched liver tissue samples from hepatocellular carcinoma patients was performed. A series of 62 metabolites were found to be altered significantly in liver tumors; however, levels of acetylcarnitine correlated most strongly with tumor grade and could discriminate between hepatocellular carcinoma tumors and matched normal tissues. Post hoc analysis to evaluate serum diagnosis and progression potential further confirmed the diagnostic capability of serum acetylcarnitine. Finally, an external validation in an independent batch of 58 serum samples (18 hepatocellular carcinoma patients, 20 liver cirrhosis patients, and 20 healthy individuals) verified that serum acetylcarnitine was a meaningful biomarker reflecting hepatocellular carcinoma diagnosis and progression. These findings present a strong new candidate biomarker for hepatocellular carcinoma with potentially significant diagnostic and prognostic capabilities. Cancer Res; 76(10); 2912-20. ©2016 AACR.

Network-based methods for identifying critical pathways of complex diseases: a survey

We review seven major network-based pathway analysis methods and enumerate their benefits and limitations from an algorithmic perspective to provide a reference for the next generation of pathway analysis methods.

CPE overexpression is correlated with pelvic lymph node metastasis and poor prognosis in patients with early-stage cervical cancer

PURPOSE

Elevated carboxypeptidase E (CPE) levels play crucial roles in tumorigenesis and metastasis. This study investigated the expression and clinicopathological significance of CPE in early-stage cervical cancer.

METHODS

Elevated carboxypeptidase E expression was analyzed using quantitative polymerase chain reaction and western blotting in normal cervical tissue, cervical cancer cell lines, and in cervical cancer tissues and adjacent noncancerous tissues (ANTs) from the same patient. Immunohistochemistry (IHC) was used to examine CPE expression in tissue samples from 112 patients with early-stage cervical cancer (FIGO stages Ia2-IIa2), 60 patients with cervical intraepithelial neoplasia, and 19 patients with normal cervical tissues (NCTs). Associations between CPE expression and prognostic and diagnostic factors were evaluated statistically.

RESULTS

CPE expression was significantly higher in cervical cancer cell lines and tissues than in normal tissues and ANTs. Semi-quantitative analysis of IHC indicated that CPE gradually increased from CIN I to cervical cancer, but was absent in NCTs. CPE expression was seen in 40.2 % (45/112) of the cervical cancer samples. CPE expression was significantly associated with FIGO stage (P = 0.003), tumor size (P = 0.012), stromal invasion (P < 0.001), lymphovascular space invasion (P = 0.016), parametrial infiltration (P = 0.027), vaginal involvement (P = 0.007), postoperative adjuvant therapy (P = 0.024), recurrence (P < 0.001), survival (P < 0.001), and pelvic lymph node metastasis (PLNM) (P < 0.001), and it was significantly higher in tissues from patients with PLNM than without PLNM. Logistic regression analysis identified high-level CPE expression as an independent risk factor for PLNM (P = 0.001). Patients with higher CPE expression had shorter overall survival duration than patients with lower CPE expression. Univariate and multivariate Cox-regression analyses suggested that high-level CPE expression is an independent prognostic factor for overall survival in early-stage cervical cancer.

CONCLUSIONS

High-level CPE expression was associated with a poor prognosis in early-stage cervical cancer. CPE may serve as a biomarker for predicting PLNM and survival in these patients.

Prostaglandins induce early growth response 1 transcription factor mediated microsomal prostaglandin E2 synthase up-regulation for colorectal cancer progression

Cyclooxygenase2 (COX2) has been associated with cell growth, invasiveness, tumor progression and metastasis of colorectal carcinomas. However, the downstream prostaglandin (PG)-PG receptor pathway involved in these effects is poorly characterized.We studied the PG-pathway in gene expression databases and we found that PTGS2 (prostaglandin G/H synthase and cyclooxygenase) and PTGES (prostaglandin E synthase) are co-expressed in human colorectal tumors. Moreover, we detected that COX2 and microsomal Prostaglandin E2 synthase 1 (mPGES1) proteins are both up-regulated in colorectal human tumor biopsies.Using colon carcinoma cell cultures we found that COX2 overexpression significantly increased mPGES1 mRNA and protein. This up-regulation was due to an increase in early growth response 1 (EGR1) levels and its transcriptional activity. EGR1 was induced by COX2-generated PGF2α. A PGF2α receptor antagonist, or EGR1 silencing, inhibited the mPGES1 induction by COX2 overexpression. Moreover, using immunodeficient mice, we also demonstrated that both COX2- and mPGES1-overexpressing carcinoma cells were more efficient forming tumors.Our results describe for the first time the molecular pathway correlating PTGS2 and PTGES in colon cancer progression. We demonstrated that in this pathway mPGES1 is induced by COX2 overexpression, via autocrine PGs release, likely PGF2α, through an EGR1-dependent mechanism. This signaling provides a molecular explanation to PTGS2 and PTGES association and contribute to colon cancer advance, pointing out novel potential therapeutic targets in this oncological context.

Comparative study on gene set and pathway topology-based enrichment methods

Background

Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis.

Methods

We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods.

Results

In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower.

Conclusions

We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both types of methods for enrichment analysis require further improvements in order to deal with the problem of pathway overlaps.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0751-5) contains supplementary material, which is available to authorized users.

An Integrative Approach for Mapping Differentially Expressed Genes and Network Components Using Novel Parameters to Elucidate Key Regulatory Genes in Colorectal Cancer

For examining the intricate biological processes concerned with colorectal cancer (CRC), a systems biology approach integrating several biological components and other influencing factors is essential to understand. We performed a comprehensive system level analysis for CRC which assisted in unravelling crucial network components and many regulatory elements through a coordinated view. Using this integrative approach, the perceptive of complexity hidden in a biological phenomenon is extensively simplified. The microarray analyses facilitated differential expression of 631 significant genes employed in the progression of disease and supplied interesting associated up and down regulated genes like jun, fos and mapk1. The transcriptional regulation of these genes was deliberated widely by examining transcription factors such as hnf4, nr2f1, znf219 and dr1 which directly influence the expression. Further, interactions of these genes/proteins were evaluated and crucial network motifs were detected to associate with the pathophysiology of CRC. The available standard statistical parameters such as z-score, p-value and significance profile were explored for the identification of key signatures from CRC pathway whereas a few novel parameters representing over-represented structures were also designed in the study. The applied approach revealed 5 key genes i.e. kras, araf, pik3r5, ralgds and akt3 via our novel designed parameters illustrating high statistical significance. These novel parameters can assist in scrutinizing candidate markers for diseases having known biological pathways. Further, investigating and targeting these proposed genes for experimental validations, instead being spellbound by the complicated pathway will certainly endow valuable insight in a well-timed systematic understanding of CRC.

Long Non-Coding RNAs: The Key Players in Glioma Pathogenesis

Long non-coding RNAs (LncRNAs) represent a novel class of RNAs with no functional protein-coding ability, yet it has become increasingly clear that interactions between lncRNAs with other molecules are responsible for important gene regulatory functions in various contexts. Given their relatively high expressions in the brain, lncRNAs are now thought to play important roles in normal brain development as well as diverse disease processes including gliomagenesis. Intriguingly, certain lncRNAs are closely associated with the initiation, differentiation, progression, recurrence and stem-like characteristics in glioma, and may therefore be exploited for the purposes of sub-classification, diagnosis and prognosis. LncRNAs may also serve as potential therapeutic targets as well as a novel biomarkers in the treatment of glioma. In this article, the functional aspects of lncRNAs, particularly within the central nervous system (CNS), will be briefly discussed, followed by highlights of the important roles of lncRNAs in mediating critical steps during glioma development. In addition, the key lncRNA players and their possible mechanistic pathways associated with gliomagenesis will be addressed.

Network Comparison of Inflammation in Colorectal Cancer and Alzheimer's Disease

Recently, a large clinical study revealed an inverse correlation of individual risk of cancer versus Alzheimer's disease (AD). However, no explanation exists for this anticorrelation at the molecular level; however, inflammation is crucial to the pathogenesis of both diseases, necessitating a need to understand differing signaling usage during inflammatory responses distinct to both diseases. Using a subpathway analysis approach, we identified numerous well-known and previously unknown pathways enriched in datasets from both diseases. Here, we present the quantitative importance of the inflammatory response in the two disease pathologies and summarize signal transduction pathways common to both diseases that are affected by inflammation.

Subpathway Analysis based on Signaling-Pathway Impact Analysis of Signaling Pathway

Pathway analysis is a common approach to gain insight from biological experiments. Signaling-pathway impact analysis (SPIA) is one such method and combines both the classical enrichment analysis and the actual perturbation on a given pathway. Because this method focuses on a single pathway, its resolution generally is not very high because the differentially expressed genes may be enriched in a local region of the pathway. In the present work, to identify cancer-related pathways, we incorporated a recent subpathway analysis method into the SPIA method to form the “sub-SPIA method.” The original subpathway analysis uses the k-clique structure to define a subpathway. However, it is not sufficiently flexible to capture subpathways with complex structure and usually results in many overlapping subpathways. We therefore propose using the minimal-spanning-tree structure to find a subpathway. We apply this approach to colorectal cancer and lung cancer datasets, and our results show that sub-SPIA can identify many significant pathways associated with each specific cancer that other methods miss. Based on the entire pathway network in the Kyoto Encyclopedia of Genes and Genomes, we find that the pathways identified by sub-SPIA not only have the largest average degree, but also are more closely connected than those identified by other methods. This result suggests that the abnormality signal propagating through them might be responsible for the specific cancer or disease.

[Screening of Highly Expressed CPEΔN Lung Cancer H1299 Cells]

背景与目的

N端截短的羧肽酶E（N-terminal truncated carboxypeptidase E, CPEΔN）是一个新的肿瘤转移相关蛋白。本研究旨在筛选高表达CPEΔN的H1299肺癌细胞株，为完成小鼠活体成像实验创造条件。

方法

构建CPEΔN的慢病毒表达载体。分别用CPEΔN慢病毒表达载体或对照慢病毒空载体转染H1299细胞，2 μg/mL的嘌呤霉素加压筛选。Western blot分析CPEΔN蛋白的表达，荧光素酶报告基因实验分析荧光素酶对底物的分解作用。

结果

当感染倍数（multiple of infection, MOI）是20时，慢病毒对H1299细胞的转染效率可以达到80%。CPEΔN高表达H1299细胞株（H1299-CPEΔN）和对照慢病毒载体表达H1299细胞株（H1299-control）中CPEΔN蛋白的表达量为4:1。H1299-CPEΔN和H1299-control均能够有效分解荧光素酶底物，可以满足活体成像实验的需求。

结论

筛选出高表达CPEΔN的H1299肺癌细胞株，为活体成像实验的开展创造了条件，也为进一步解释CPEΔN促进肿瘤转移的分子机制奠定了基础。

Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics

This study aimed to explore the underlying molecular mechanisms of colorectal cancer (CRC) using bioinformatics analysis. Using GSE4107 datasets downloaded from the Gene Expression Omnibus, the differentially expressed genes (DEGs) were screened by comparing the RNA expression from the colonic mucosa between 12 CRC patients and ten healthy controls using a paired t-test. The Gene Ontology (GO) functional and pathway enrichment analyses of DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) software followed by the construction of a protein–protein interaction (PPI) network. In addition, hub gene identification and GO functional and pathway enrichment analyses of the modules were performed. A total of 612 up- and 639 downregulated genes were identified. The upregulated DEGs were mainly involved in the regulation of cell growth, migration, and the MAPK signaling pathway. The downregulated DEGs were significantly associated with oxidative phosphorylation, Alzheimer’s disease, and Parkinson’s disease. Moreover, FOS, FN1, PPP1CC, and CYP2B6 were selected as hub genes in the PPI networks. Two modules (up-A and up-B) in the upregulated PPI network and three modules (d-A, d-B, and d-C) in the downregulated PPI were identified with the threshold of Molecular Complex Detection (MCODE) Molecular Complex Detection (MCODE) score ≥4 and nodes ≥6. The genes in module up-A were significantly enriched in neuroactive ligand–receptor interactions and the calcium signaling pathway. The genes in module d-A were enriched in four pathways, including oxidative phosphorylation and Parkinson’s disease. DEGs, such as FOS, FN1, PPP1CC, and CYP2B6, may be used as potential targets for CRC diagnosis and treatment.

USP11-dependent selective cIAP2 deubiquitylation and stabilization determine sensitivity to Smac mimetics

Given their crucial role in apoptosis suppression, inhibitor of apoptosis proteins (IAPs) have recently become attractive targets for cancer therapy. Here, we report that cellular IAP2 (cIAP2) is specifically stabilized in several cancer cell lines, leading to resistance to Smac mimetics, such as BV6 and birinapant. In particular, our results showed that cIAP2 depletion, but not cIAP1 depletion, sensitized cancer cells to Smac mimetic-induced apoptosis. Ubiquitin-specific protease 11 (USP11) is a deubiquitylase that directly stabilizes cIAP2. USP11 overexpression is frequently found in colorectal cancer and melanoma and is correlated with poor survival. In our study, cancer cell lines expressing high levels of USP11 exhibited strong resistance to Smac mimetic-induced cIAP2 degradation. Furthermore, USP11 downregulation sensitized these cells to apoptosis induced by TRAIL and BV6 and suppressed tumor growth in a xenograft model. Finally, the TNFα/JNK pathway induced USP11 expression and maintained cIAP2 stability, suggesting an alternative TNFα-dependent cell survival pathway. Collectively, our data suggest that USP11-stabilized cIAP2 may serve as a barrier against IAP-targeted clinical approaches.

Low expression of chloride channel accessory 1 predicts a poor prognosis in colorectal cancer

BACKGROUND

Chloride channel accessory 1 (CLCA1) is a CLCA protein that plays a functional role in regulating the differentiation and proliferation of colorectal cancer (CRC) cells. Here we investigated the relationship between the level of CLCA1 and the prognosis of CRC.

METHODS

First, the level of CLCA1 was detected quantitatively in normal and cancerous colonic epithelial tissues with immunohistochemistry. Next, the correlations between CLCA1 expression, pathological tumor features, and the overall survival rate of patients was analyzed. Finally, 3 publicly available data sets from the Gene Expression Omnibus were examined: normal CRC versus early CRC (GSE4107), primary CRC versus metastatic lesions (GSE28702), and low chromosomal instability versus high chromosomal instability (GSE30540).

RESULTS

The expression of CLCA1 was decreased markedly in tumor specimens. CLCA1 expression was correlated significantly with the histological grade (P < .01) and lymph node metastasis (P < .01). A significantly poorer overall survival rate was found in patients with low levels of CLCA1 expression versus those with high expression levels (P < .05). The results confirmed that the low expression of CLCA1 in CRC was highly associated with tumorigenesis, metastasis, and high chromosomal instability. In addition, the loss of CLCA1 disrupted the differentiation of human colon adenocarcinoma cells (Caco-2) in vitro.

CONCLUSIONS

These findings suggest that CLCA1 levels may be a potential predictor of prognosis in primary human CRC. Low expression of CLCA1 predicts disease recurrence and lower survival, and this has implications for the selection of patients most likely to need and benefit from adjuvant chemotherapy. Cancer 2015;121:1570–1580. © 2015 American Cancer Society.

Proteins in the ERK pathway are affected by arsenic-treated cells

This study revealed that arsenic regulates SLC25A12, PSME3, vinculin, QR and STIP1 expressions through activation of the ERK-signaling pathway.

Understanding disease mechanisms with models of signaling pathway activities

BACKGROUND

Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is one of the main challenges in the analysis of genomic data and is on the basis of the future implementation of precision medicine.

RESULTS

Here we propose a simple probabilistic model in which signaling pathways are separated into elementary sub-pathways or signal transmission circuits (which ultimately trigger cell functions) and then transforms gene expression measurements into probabilities of activation of such signal transmission circuits. Using this model, differential activation of such circuits between biological conditions can be estimated. Thus, circuit activation statuses can be interpreted as biomarkers that discriminate among the compared conditions. This type of mechanism-based biomarkers accounts for cell functional activities and can easily be associated to disease or drug action mechanisms. The accuracy of the proposed model is demonstrated with simulations and real datasets.

CONCLUSIONS

The proposed model provides detailed information that enables the interpretation disease mechanisms as a consequence of the complex combinations of altered gene expression values. Moreover, it offers a framework for suggesting possible ways of therapeutic intervention in a pathologically perturbed system.

A role for the mitochondrial pyruvate carrier as a repressor of the Warburg effect and colon cancer cell growth

Cancer cells are typically subject to profound metabolic alterations, including the Warburg effect wherein cancer cells oxidize a decreased fraction of the pyruvate generated from glycolysis. We show herein that the mitochondrial pyruvate carrier (MPC), composed of the products of the MPC1 and MPC2 genes, modulates fractional pyruvate oxidation. MPC1 is deleted or underexpressed in multiple cancers and correlates with poor prognosis. Cancer cells re-expressing MPC1 and MPC2 display increased mitochondrial pyruvate oxidation, with no changes in cell growth in adherent culture. MPC re-expression exerted profound effects in anchorage-independent growth conditions, however, including impaired colony formation in soft agar, spheroid formation, and xenograft growth. We also observed a decrease in markers of stemness and traced the growth effects of MPC expression to the stem cell compartment. We propose that reduced MPC activity is an important aspect of cancer metabolism, perhaps through altering the maintenance and fate of stem cells.

Sporadic early-onset colorectal cancer is a specific sub-type of cancer: a morphological, molecular and genetics study

Sporadic early onset colorectal carcinoma (EOCRC) which has by definition no identified hereditary predisposition is a growing problem that remains poorly understood. Molecular analysis could improve identification of distinct sub-types of colorectal cancers (CRC) with therapeutic implications and thus can help establish that sporadic EOCRC is a distinct entity. From 954 patients resected for CRC at our institution, 98 patients were selected. Patients aged 45–60 years were excluded to help define “young” and “old” groups. Thirty-nine cases of sporadic EOCRC (patients≤45 years with microsatellite stable tumors) were compared to both microsatellite stable tumors from older patients (36 cases, patients>60 years) and to groups of patients with microsatellite instability. Each group was tested for TP53, KRAS, BRAF, PIK3CA mutations and the presence of a methylator phenotype. Gene expression profiles were also used for pathway analysis. Compared to microsatellite stable CRC from old patients, sporadic EOCRC were characterized by distal location, frequent synchronous metastases and infrequent synchronous adenomas but did not have specific morphological characteristics. A familial history of CRC was more common in sporadic EOCRC patients despite a lack of identified hereditary conditions (p = 0.013). Genetic studies also showed the absence of BRAF mutations (p = 0.022) and the methylator phenotype (p = 0.005) in sporadic EOCRC compared to older patients. Gene expression analysis implicated key pathways such as Wnt/beta catenin, MAP Kinase, growth factor signaling (EGFR, HGF, PDGF) and the TNFR1 pathway in sporadic EOCRC. Wnt/beta catenin signaling activation was confirmed by aberrant nuclear beta catenin immunostaining (p = 0.01). This study strongly suggests that sporadic EOCRC is a distinct clinico-molecular entity presenting as a distal and aggressive disease associated with chromosome instability. Furthermore, several signaling pathways including the TNFR1 pathway have been identified as potential biomarkers for both the diagnosis and treatment of this disease.

Inferring the perturbed microRNA regulatory networks from gene expression data using a network propagation based method

BACKGROUND

MicroRNAs (miRNAs) are a class of endogenous small regulatory RNAs. Identifications of the dys-regulated or perturbed miRNAs and their key target genes are important for understanding the regulatory networks associated with the studied cellular processes. Several computational methods have been developed to infer the perturbed miRNA regulatory networks by integrating genome-wide gene expression data and sequence-based miRNA-target predictions. However, most of them only use the expression information of the miRNA direct targets, rarely considering the secondary effects of miRNA perturbation on the global gene regulatory networks.

RESULTS

We proposed a network propagation based method to infer the perturbed miRNAs and their key target genes by integrating gene expressions and global gene regulatory network information. The method used random walk with restart in gene regulatory networks to model the network effects of the miRNA perturbation. Then, it evaluated the significance of the correlation between the network effects of the miRNA perturbation and the gene differential expression levels with a forward searching strategy. Results show that our method outperformed several compared methods in rediscovering the experimentally perturbed miRNAs in cancer cell lines. Then, we applied it on a gene expression dataset of colorectal cancer clinical patient samples and inferred the perturbed miRNA regulatory networks of colorectal cancer, including several known oncogenic or tumor-suppressive miRNAs, such as miR-17, miR-26 and miR-145.

CONCLUSIONS

Our network propagation based method takes advantage of the network effect of the miRNA perturbation on its target genes. It is a useful approach to infer the perturbed miRNAs and their key target genes associated with the studied biological processes using gene expression data.

A signature predicting poor prognosis in gastric and ovarian cancer represents a coordinated macrophage and stromal response

PURPOSE

Gene-expression profiling has revolutionized the way we think about cancer and confers the ability to observe the synchronous expression of thousands of genes. The use of putative genome-level expression profiles has allowed biologists to observe the complex interactions of genes that constitute recognized biologic pathways. We used gastric and ovarian datasets to identify gene-expression signatures and determine any functional significance.

EXPERIMENTAL DESIGN

Microarray data of 94-tumor and 45-benign samples derived from patients with gastric cancer were interrogated using Hierarchical Ordered Partitioning and Collapsing Hybrid analysis identifying clusters of coexpressed genes. Clusters were further characterized with respect to biologic significance, gene ontology, and ability to discriminate between normal and tumor tissue. Tumor tissues were separated into epithelial and stromal compartments and immunohistochemical analysis performed to further elucidate specific cell lineages expressing genes contained in the signature.

RESULTS

We identified a "stromal-response" expression signature, highly enriched for inflammatory, extracellular matrix, cytokine, and growth factor proteins. The majority of genes in the signature are expressed in the tumor-associated stroma but were absent in associated premalignant conditions. In gastric cancer, this module almost perfectly differentiates tumor from nonmalignant gastric tissue and hence can be regarded as a highly tumor-specific gene-expression signature.

CONCLUSIONS

We show that these genes are consistently coexpressed across a range of independent gastric datasets as well as other cancer types suggesting a conserved functional role in cancer. In addition, we show that this signature can be a surrogate marker for M2 macrophage activity and has significant prognostic implications in gastric and ovarian high-grade serous cancer.

Could dysregulation of UPS be a common underlying mechanism for cancer and neurodegeneration? Lessons from UCHL1

Ubiquitin proteasome system (UPS) determines the timing and extent of protein turnover in cells, and it is one of the most strictly controlled cellular mechanisms. Lack of proper control over UPS is attributed to both cancer and to neurodegenerative diseases, yet in different context and direction. Cancerous cells have altered cellular metabolisms, uncontrolled cellular division, and increased proteasome activity. The specialized function prevent neurons from undergoing cellular division but allow them to extend an axon over long distances, establish connections, and to form stable neuronal circuitries. Neurons heavily depend on the proper function of the proteasome and the UPS for their proper function. Reduction of UPS function in vulnerable neurons results in protein aggregation, increased ER stress, and cell death. Identification of compounds that selectively block proteasome function in distinct set of malignancies added momentum to drug discovery efforts, and deubiquitinases (DUBs) gained much attention. This review will focus on ubiquitin carboxy-terminal hydrolase L1 (UCHL1), a DUB that is attributed to both cancer and neurodegeneration. The potential of developing effective treatment strategies for two major health problems by controlling the function of UPS opens up new avenues for innovative approaches and therapeutic interventions.

Analysis of key genes and pathways associated with colorectal cancer with microarray technology

OBJECTIVE

Microarray data were analyzed to explore key genes and their functions in progression of colorectal cancer (CRC).

METHODS

Two microarray data sets were downloaded from Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified using corresponding packages of R. Functional enrichment analysis was performed with DAVID tools to uncover their biological functions.

RESULTS

631 and 590 DEGs were obtained from the two data sets, respectively. A total of 32 common DEGs were then screened out with the rank product method. The significantly enriched GO terms included inflammatory response, response to wounding and response to drugs. Two interleukin-related domains were revealed in the domain analysis. KEGG pathway enrichment analysis showed that the PPAR signaling pathway and the renin-angiotensin system were enriched in the DEGs.

CONCLUSIONS

Our study to systemically characterize gene expression changes in CRC with microarray technology revealed changes in a range of key genes, pathways and function modules. Their utility in diagnosis and treatment now require exploration.

Inferring drug-disease associations from integration of chemical, genomic and phenotype data using network propagation

BACKGROUND

During the last few years, the knowledge of drug, disease phenotype and protein has been rapidly accumulated and more and more scientists have been drawn the attention to inferring drug-disease associations by computational method. Development of an integrated approach for systematic discovering drug-disease associations by those informational data is an important issue.

METHODS

We combine three different networks of drug, genomic and disease phenotype and assign the weights to the edges from available experimental data and knowledge. Given a specific disease, we use our network propagation approach to infer the drug-disease associations.

RESULTS

We apply prostate cancer and colorectal cancer as our test data. We use the manually curated drug-disease associations from comparative toxicogenomics database to be our benchmark. The ranked results show that our proposed method obtains higher specificity and sensitivity and clearly outperforms previous methods. Our result also show that our method with off-targets information gets higher performance than that with only primary drug targets in both test data.

CONCLUSIONS

We clearly demonstrate the feasibility and benefits of using network-based analyses of chemical, genomic and phenotype data to reveal drug-disease associations. The potential associations inferred by our method provide new perspectives for toxicogenomics and drug reposition evaluation.

Network cluster analysis of protein-protein interaction network identified biomarker for early onset colorectal cancer

Colorectal cancer (CRC) is a major cause of morbidity and mortality throughout the world. However, the genetic alterations and molecular mechanism of the early onset CRCs are not fully investigated. The present study aimed to characterize early onset CRC by analyzing its gene expression compared with normal controls and to identify network-based biomarkers of early onset CRC. The gene expression profiles of early onset CRC were downloaded from Gene Expression Omnibus and the differentially expressed genes (DEGs) in CRC patients were identified. Then, a protein-protein interaction (PPI) network was constructed and the clusters in PPI were analyzed by ClusterONE. Furthermore, the gene ontology functional analysis and pathway enrichment analysis were conducted to the modules in PPI network. A systems biology approach integrating microarray data and PPI was further applied to construct a PPI network in CRC. Total 631 DEGs were identified from the early onset CRC compared to healthy controls. These genes were found to be involved in several biological processes, including cell communication, cell proliferation, cell shape and apoptosis. Five functional modules which may play important roles in the initiation of early onset CRC were identified from the PPI network. Functional annotation revealed that these five modules were involved in the pathways of signal transduction, carcinogenesis and metastasis. The hub nodes of these five modules, CDC42, TEX11, QKI, CAV1 and FN1, may serve as the biomarkers of early onset CRC and have the potential to be targets for therapeutic intervention. However, further investigations are still needed to confirm our findings.

¹H NMR-based metabolic profiling of human rectal cancer tissue

Background

Rectal cancer is one of the most prevalent tumor types. Understanding the metabolic profile of rectal cancer is important for developing therapeutic approaches and molecular diagnosis.

Methods

Here, we report a metabonomics profiling of tissue samples on a large cohort of human rectal cancer subjects (n = 127) and normal controls (n = 43) using ¹H nuclear magnetic resonance (¹H NMR) based metabonomics assay, which is a highly sensitive and non-destructive method for the biomarker identification in biological systems. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA) were applied to analyze the ¹H-NMR profiling data to identify the distinguishing metabolites of rectal cancer.

Results

Excellent separation was obtained and distinguishing metabolites were observed among the different stages of rectal cancer tissues (stage I = 35; stage II = 37; stage III = 37 and stage IV = 18) and normal controls. A total of 38 differential metabolites were identified, 16 of which were closely correlated with the stage of rectal cancer. The up-regulation of 10 metabolites, including lactate, threonine, acetate, glutathione, uracil, succinate, serine, formate, lysine and tyrosine, were detected in the cancer tissues. On the other hand, 6 metabolites, including myo-inositol, taurine, phosphocreatine, creatine, betaine and dimethylglycine were decreased in cancer tissues. These modified metabolites revealed disturbance of energy, amino acids, ketone body and choline metabolism, which may be correlated with the progression of human rectal cancer.

Conclusion

Our findings firstly identify the distinguishing metabolites in different stages of rectal cancer tissues, indicating possibility of the attribution of metabolites disturbance to the progression of rectal cancer. The altered metabolites may be as potential biomarkers, which would provide a promising molecular diagnostic approach for clinical diagnosis of human rectal cancer. The role and underlying mechanism of metabolites in rectal cancer progression are worth being further investigated.

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer

The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined subgroup. We performed a prior free analysis of CRC heterogeneity on 1113 CRC gene expression profiles and confronted our findings to established molecular determinants and clinical, histopathological and survival data. Unsupervised clustering based on gene modules allowed us to distinguish at least five different gene expression CRC subtypes, which we call surface crypt-like, lower crypt-like, CIMP-H-like, mesenchymal and mixed. A gene set enrichment analysis combined with literature search of gene module members identified distinct biological motifs in different subtypes. The subtypes, which were not derived based on outcome, nonetheless showed differences in prognosis. Known gene copy number variations and mutations in key cancer-associated genes differed between subtypes, but the subtypes provided molecular information beyond that contained in these variables. Morphological features significantly differed between subtypes. The objective existence of the subtypes and their clinical and molecular characteristics were validated in an independent set of 720 CRC expression profiles. Our subtypes provide a novel perspective on the heterogeneity of CRC. The proposed subtypes should be further explored retrospectively on existing clinical trial datasets and, when sufficiently robust, be prospectively assessed for clinical relevance in terms of prognosis and treatment response predictive capacity. Original microarray data were uploaded to the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under Accession Nos E-MTAB-990 and E-MTAB-1026.

Polyisoprenylated methylated protein methyl esterase is both sensitive to curcumin and overexpressed in colorectal cancer: implications for chemoprevention and treatment

Inhibition of PMPMEase, a key enzyme in the polyisoprenylation pathway, induces cancer cell death. In this study, purified PMPMEase was inhibited by the chemopreventive agent, curcumin, with a K(i) of 0.3 μM (IC50 = 12.4 μM). Preincubation of PMPMEase with 1 mM curcumin followed by gel-filtration chromatography resulted in recovery of the enzyme activity, indicative of reversible inhibition. Kinetics analysis with N-para-nitrobenzoyl-S-trans,trans-farnesylcysteine methyl ester substrate yielded K M values of 23.6 ± 2.7 and 85.3 ± 15.3 μM in the absence or presence of 20 μM curcumin, respectively. Treatment of colorectal cancer (Caco2) cells with curcumin resulted in concentration-dependent cell death with an EC50 of 22.0 μg/mL. PMPMEase activity in the curcumin-treated cell lysate followed a similar concentration-dependent profile with IC50 of 22.6 μg/mL. In colorectal cancer tissue microarray studies, PMPMEase immunoreactivity was significantly higher in 88.6% of cases compared to normal colon tissues (P < 0.0001). The mean scores ± SEM were 91.7 ± 11.4 (normal), 75.0 ± 14.4 (normal adjacent), 294.8 ± 7.8 (adenocarcinoma), and 310.0 ± 22.6 (mucinous adenocarcinoma), respectively. PMPMEase overexpression in colorectal cancer and cancer cell death stemming from its inhibition is an indication of its possible role in cancer progression and a target for chemopreventive agents.

Inferring the functional effect of gene expression changes in signaling pathways

Signaling pathways constitute a valuable source of information that allows interpreting the way in which alterations in gene activities affect to particular cell functionalities. There are web tools available that allow viewing and editing pathways, as well as representing experimental data on them. However, few methods aimed to identify the signaling circuits, within a pathway, associated to the biological problem studied exist and none of them provide a convenient graphical web interface. We present PATHiWAYS, a web-based signaling pathway visualization system that infers changes in signaling that affect cell functionality from the measurements of gene expression values in typical expression microarray case–control experiments. A simple probabilistic model of the pathway is used to estimate the probabilities for signal transmission from any receptor to any final effector molecule (taking into account the pathway topology) using for this the individual probabilities of gene product presence/absence inferred from gene expression values. Significant changes in these probabilities allow linking different cell functionalities triggered by the pathway to the biological problem studied. PATHiWAYS is available at: http://pathiways.babelomics.org/.

The transition from proliferation to differentiation in colorectal cancer is regulated by the calcium activated chloride channel A1

Breaking the balance between proliferation and differentiation in animal cells can lead to cancer, but the mechanisms maintaining this balance remain largely undefined. The calcium activated chloride channel A1 (CLCA1) is a member of the calcium sensitive chloride conductance family of proteins and is expressed mainly in the colon, small intestine and appendix. We show that CLCA1 plays a functional role in differentiation and proliferation of Caco-2 cells and of intestinal tissue. Caco-2 cells spontaneously differentiate either in confluent culture or when treated with butyrate, a molecule present naturally in the diet. Here, we compared CLCA1 expressional levels between patients with and without colorectal cancer (CRC) and determined the functional role of CLCA1 in differentiation and proliferation of Caco-2 cells. We showed that: 1) CLCA1 and CLCA4 expression were down-regulated significantly in CRC patients; 2) CLCA1 expression was up-regulated in Caco-2 cells induced to differentiate by confluent culture or by treatment with sodium butyrate (NaBT); 3) Knockdown of CLCA1 with siRNA significantly inhibited cell differentiation and promoted cell proliferation in Caco-2 confluent cultures, and 4) In Caco-2 3D culture, suppression of CLCA1 significantly increased cell proliferation and compromised NaBT-induced inhibition of proliferation. In conclusion, CLCA1 may contribute to promoting spontaneous differentiation and reducing proliferation of Caco-2 cells and may be a target of NaBT-induced inhibition of proliferation and therefore a potential diagnostic marker for CRC prognosis.

Inverted expression profiles of sex-biased genes in response to toxicant perturbations and diseases

The influence of sex factor is widely recognized in various diseases, but its molecular basis, particularly how sex-biased genes, those with sexually dimorphic expression, behave in response to toxico-pathological changes is poorly understood. In this study, zebrafish toxicogenomic data and transcriptomic data from human pathological studies were analysed for the responses of male- and female-biased genes. Our analyses revealed obvious inverted expression profiles of sex-biased genes, where affected males tended to up-regulate genes of female-biased expression and down-regulate genes of male-biased expression, and vice versa in affected females, in a broad range of toxico-pathological conditions. Intriguingly, the extent of these inverted profiles correlated well to the susceptibility or severity of a given toxico-pathological state, suggesting that inverted expression profiles of sex-biased genes observed in this study can be used as important indicators to assess biological disorders.

Molecular signature of cancer at gene level or pathway level? Case studies of colorectal cancer and prostate cancer microarray data

With recent advances in microarray technology, there has been a flourish in genome-scale identification of molecular signatures for cancer. However, the differentially expressed genes obtained by different laboratories are highly divergent. The present discrepancy at gene level indicates a need for a novel strategy to obtain more robust signatures for cancer. In this paper we hypothesize that (1) the expression signatures of different cancer microarray datasets are more similar at pathway level than at gene level; (2) the comparability of the cancer molecular mechanisms of different individuals is related to their genetic similarities. In support of the hypotheses, we summarized theoretical and experimental evidences, and conducted case studies on colorectal and prostate cancer microarray datasets. Based on the above assumption, we propose that reliable cancer signatures should be investigated in the context of biological pathways, within a cohort of genetically homogeneous population. It is hoped that the hypotheses can guide future research in cancer mechanism and signature discovery.