Expression and genomic profiling of colorectal cancer

Predicting Survival Among Colorectal Cancer Patients: Development and Validation of Polygenic Survival Score

Purpose

Colorectal cancer is the second leading cause of cancer-related death in the United States. A multi-omics approach has contributed in identifying various cancer-specific mutations, epigenetic alterations, and cells response to chemotherapy. This study aimed to determine the factors associated with colorectal cancer survival and develop and validate a polygenic survival scoring system (PSS) using a multi-omics approach.

Patients and Methods

Data were obtained from the Cancer Genome Atlas (TCGA). Colon Adenocarcinoma (TCGA-COAD) data were used to develop a survival prediction model and PSS, whereas rectal adenocarcinoma (TCGA-READ) data were used to validate the PSS. Cox proportional hazards regression analysis was conducted to examine the association between the demographic characteristics, clinical variables, and mRNA gene expression.

Results

Overall accuracy of PSS was also evaluated. The median overall survival for TCGA-COAD patients was 7 years and for TCGA-READ patients was 5 years. The multivariate Cox proportional hazards model identified age, cancer stage, and expression of nine genes as predictors of colon cancer survival. Based on the median PSS of 0.38, 48% of TCGA-COAD patients had high mortality risk. Patients in the low risk group had significantly higher 5-year survival rates than those in the high group (p <0.0001). The PSS demonstrated a high overall accuracy in predicting colorectal cancer survival.

Conclusion

This study integrated clinical and transcriptome data to identify survival predictors in patients with colorectal cancer. PSS is an accurate and valid measure for estimating colorectal cancer survival. Thus, it can serve as an important tool for future colorectal cancer research.

SNP array genomic analysis of matched pairs of brain and liver metastases in primary colorectal cancer

PURPOSE

Brain metastasis formation is a rare and late event in colorectal cancer (CRC) patients and associated with poor survival. In contrast to other metastatic sites, the knowledge on chromosomal aberrations in brain metastases is very limited.

METHODS

Therefore, we carried out single nucleotide polymorphism (SNP) array analyses on matched primary CRC and brain metastases of four patients as well as on liver metastases of three patients.

RESULTS

Brain metastases showed more chromosomal aberrations than primary tumors or liver metastases. Commonly occurring aberrations were gain of 8q11.1-q24.3 (primary CRC), gain of 13q12.13-q12.3 (liver metastases), and gain of 20q11.1-q13.33 (brain metastases). Furthermore, we found one copy-neutral loss of heterozygosity (cn-LOH) region on chromosome 3 in primary CRC, three cn-LOH regions in liver metastases and 23 cn-LOH regions in brain metastases, comprising 26 previously undescribed sites.

CONCLUSION

The more frequent occurrence of cn-LOHs and subsequently affected genes in brain metastases shed light on the pathophysiology of brain metastasis formation. Further pairwise genetic analyses between primary tumors and their metastases will help to define the role of affected genes in cn-LOH regions.

The multifaceted PDCD10/CCM3 gene

The programmed cell death 10 (PDCD10) gene was originally identified as an apoptosis-related gene, although it is now usually known as CCM3, as the third causative gene of cerebral cavernous malformation (CCM). CCM is a neurovascular disease that is characterized by vascular malformations and is associated with headaches, seizures, focal neurological deficits, and cerebral hemorrhage. The PDCD10/CCM3 protein has multiple subcellular localizations and interacts with several multi-protein complexes and signaling pathways. Thus PDCD10/CCM3 governs many cellular functions, which include cell-to-cell junctions and cytoskeleton organization, cell proliferation and apoptosis, and exocytosis and angiogenesis. Given its central role in the maintenance of homeostasis of the cell, dysregulation of PDCD10/CCM3 can result in a wide range of altered cell functions. This can lead to severe diseases, including CCM, cognitive disability, and several types of cancers. Here, we review the multifaceted roles of PDCD10/CCM3 in physiology and pathology, with a focus on its functions beyond CCM.

Genome-wide analysis of copy number alterations led to the characterisation of PDCD10 as oncogene in ovarian cancer

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We have identified 201 altered chromosomal bands and 3300 altered genes in human ovarian cancer samples.

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The gene encoding for PDCD10 was selected for further studies.

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PDCD10 was found to be over-expressed in primary cancer samples and in the corresponding metastatic lesions.

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High PDCD10 expression correlates with grade, nodal involvement or advanced FIGO stage.

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PDCD10 is involved in the control of cell growth and motility in vitro as well as tumorigenicity in vivo.

Copy Number Alterations (CNAs) represent the most common genetic alterations identified in ovarian cancer cells, being responsible for the extensive genomic instability observed in this cancer. Here we report the identification of CNAs in a cohort of Italian patients affected by ovarian cancer performed by SNP-based array.

Our analysis allowed the identification of 201 significantly altered chromosomal bands (70 copy number gains; 131 copy number losses). The 3300 genes subjected to CNA identified here were compared to those present in the TCGA dataset. The analysis allowed the identification of 11 genes with increased CN and mRNA expression (PDCD10, EBAG9, NUDCD1, ENY2, CSNK2A1, TBC1D20, ZCCHC3, STARD3, C19orf12, POP4, UQCRFS1). PDCD10 was selected for further studies because of the highest frequency of CNA.

PDCD10 was found, by immunostaining of three different Tissue Micro Arrays, to be over-expressed in the majority of ovarian primary cancer samples and in metastatic lesions. Moreover, significant correlations were found in specific subsets of patients, between increased PDCD10 expression and grade (p < 0.005), nodal involvement (p < 0.05) or advanced FIGO stage (p < 0.01).

Finally, manipulation of PDCD10 expression by shRNA in ovarian cancer cells (OVCAR-5 and OVCA429) demonstrated a positive role for PDCD10 in the control of cell growth and motility in vitro and tumorigenicity in vivo.

In conclusion, this study allowed the identification of novel genes subjected to copy number alterations in ovarian cancer. In particular, the results reported here point to a prominent role of PDCD10 as a bona fide oncogene.

Integrative Gene Expression Profiling Analysis to Investigate Potential Prognostic Biomarkers for Colorectal Cancer

BACKGROUND Despite noteworthy advancements in the multidisciplinary treatment of colorectal cancer (CRC) and deeper understanding in the molecular mechanisms of CRC, many of CRC patients with histologically identical tumors present different treatment response and prognosis. Thus, more evidence on novel predictive and prognostic biomarkers for CRC remains urgently needed. This study aims to identify potential prognostic biomarkers for CRC with integrative gene expression profiling analysis. MATERIAL AND METHODS Differential expression analysis of paired CRC and adjacent normal tissue samples in 6 microarray datasets was independently performed, and the 6 datasets were integrated by the robust rank aggregation method to detect consistent differentially expressed genes (DEGs). Aberrant expression patterns of these genes were further validated in RNA sequencing data. Then, gene set enrichment analysis (GSEA) was performed to investigate significantly dysregulated biological functions in CRC. Finally, univariate, LASSO and multivariate Cox regression models were built to identify key prognostic genes in CRC patients. RESULTS A total of 990 DEGs (495 downregulated and 495 upregulated genes) were acquired after integratedly analyzing the 6 microarray datasets, and 4131 DEGs (2050 downregulated and 2081 upregulated genes) were obtained from the RNA sequencing dataset. Subsequently, these DEGs were intersected and 885 consistent DEGs were finally identified, including 458 downregulated and 427 upregulated genes. Two risky prognostic genes (TIMP1 and LZTS3) and 5 protective prognostic genes (AXIN2, CXCL1, ITLN1, CPT2 and CLDN23) were identified, which were significantly associated with the prognosis of CRC. CONCLUSIONS The 7 genes that we identified would provide more evidence for further applying novel diagnostic and prognostic biomarkers in clinical practice to facilitate personalized treatment of CRC.

Diabetes-mediated promotion of colon mucosa carcinogenesis is associated with mitochondrial dysfunction

Type 2 diabetes mellitus (T2DM) has been associated with an increased risk of cancer, including colon cancer (CC). However, we recently reported no influence of T2DM on CC prognosis, suggesting that any effect might be at the early stages of tumor development. We hypothesized that T2DM may create an environment in the healthy tissue, which acts as a carcinogenesis driver in agreement with the field of cancerization concept. Here, we focused on early carcinogenesis by analyzing paired tumor and normal colonic mucosa samples from the same patients. The proteome of CC and paired mucosa was quantitatively analyzed in 28 individuals (12 diabetics and 16 nondiabetics) by mass spectrometry with isobaric labeling. Out of 3076 identified proteins, 425 were differentially expressed at the tumor in diabetics compared with nondiabetics. In the adjacent mucosa, 143 proteins were differentially expressed in diabetics and nondiabetics. An enrichment analysis of this signature pointed to mitochondria, ribosome, and translation. Only six proteins were upregulated by diabetes both in tumor and mucosa, of which five were mitochondrial proteins. Differential expression in diabetic versus nondiabetic mucosa was confirmed for MRPL53, MRPL18, and TIMM8B. Higher levels of MRPL18, TIMM8B, and EIF1A were also found in normal colon epithelial cells exposed to high‐glucose conditions. We conclude that T2DM is associated with specific molecular changes in the normal mucosa of CC patients, consistent with field of cancerization in a diabetic environment. The mitochondrial protein signature identifies a potential therapeutic target that could underlie the higher risk of CC in diabetics.

Positive expression of basic transcription factor 3 predicts poor survival of colorectal cancer patients: possible mechanisms involved

Basic transcription factor 3 (BTF3) is associated with the development of several cancers. The aim of our study was to elucidate the role of BTF3 in colorectal cancer (CRC) tissues. CRC tissues or their paired adjacent noncancerous (ANCT) tissues were obtained from 90 patients who underwent operations in our hospital from November 2011 to December 2016, and then we implemented a gene microarray assay for detecting significant changes in gene expression and confirmed expression in tissues using immunohistochemistry and real-time PCR. We transfected or injected the silencing BTF3 (BTF3-siRNA) plasmid into cells and nude mice, and measured the tumorigenicity of CRC cells with flow cytometry and studied the expression level of BTF3 downstream genes (MAD2L2, MCM3 and PLK1) in CRC cells. BTF3 expression level was not only significantly higher in CRC tissue than in ANCT tissue (2.61 ± 0.07 vs 1.90 ± 0.03, P < 0.001) but BTF3-siRNA decreased tumor formation in a nude mice model. Furthermore, based on the data of gene microarray analysis, MAD2L2, MCM3 and PLK1 were detected as the downstream target genes of BTF3 and their expressions were positive related with BTF3 expression. Also, through transfecting BTF3-siRNA into HCT116 cells, we found that BTF3-siRNA could decrease cell viability and induced cell apoptosis and blocking the cell cycle. In conclusion, BTF3 is positively related to CRC and BTF3-siRNA attenuated the tumorigenicity of colorectal cancer cells via MAD2L2, MCM3 and PLK1 activity reduction.

TRIM59 promotes breast cancer motility by suppressing p62-selective autophagic degradation of PDCD10

Cancer cells adopt various modes of migration during metastasis. How the ubiquitination machinery contributes to cancer cell motility remains underexplored. Here, we report that tripartite motif (TRIM) 59 is frequently up-regulated in metastatic breast cancer, which is correlated with advanced clinical stages and reduced survival among breast cancer patients. TRIM59 knockdown (KD) promoted apoptosis and inhibited tumor growth, while TRIM59 overexpression led to the opposite effects. Importantly, we uncovered TRIM59 as a key regulator of cell contractility and adhesion to control the plasticity of metastatic tumor cells. At the molecular level, we identified programmed cell death protein 10 (PDCD10) as a target of TRIM59. TRIM59 stabilized PDCD10 by suppressing RING finger and transmembrane domain-containing protein 1 (RNFT1)-induced lysine 63 (K63) ubiquitination and subsequent phosphotyrosine-independent ligand for the Lck SH2 domain of 62 kDa (p62)-selective autophagic degradation. TRIM59 promoted PDCD10-mediated suppression of Ras homolog family member A (RhoA)-Rho-associated coiled-coil kinase (ROCK) 1 signaling to control the transition between amoeboid and mesenchymal invasiveness. PDCD10 overexpression or administration of a ROCK inhibitor reversed TRIM59 loss-induced contractile phenotypes, thereby accelerating cell migration, invasion, and tumor formation. These findings establish the rationale for targeting deregulated TRIM59/PDCD10 to treat breast cancer.

Molecular fluorescence-guided surgery of peritoneal carcinomatosis of colorectal origin: A narrative review

Patients with peritoneal carcinomatosis (PC) from colorectal origin may undergo cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) as a curative approach. One major prognostic factor that affects survival is completeness of cytoreduction. Molecular Fluorescence Guided Surgery (MFGS) is a novel intraoperative imaging technique that may improve tumor identification in the future, potentially preventing over- and under-treatment in these patients. This narrative review outlines a chronological overview of MFGS development in patients with PC of colorectal origin.

ACGH detects distinct genomic alterations of primary intrahepatic cholangiocarcinomas and matched lymph node metastases and identifies a poor prognosis subclass

Lymph node metastases (LNM) are an important prognostic factor for patients with intrahepatic cholangiocarcinoma, but underlying genetic alterations are poorly understood. Whole genome array comparative genomic hybridization (aCGH) was performed in 37 tumors and 14 matched LNM. Genomic analyses of tumors confirmed known and identified new (gains in 19q) copy number alterations (CNA). Tumors with LNM (N1) had more alterations and exclusive gains (3p, 4q, 5p, 13q) and losses (17p and 20p). LNM shared most alterations with their matched tumors (86%), but 79% acquired new isolated gains [12q14 (36%); 1p13, 2p23, 7p22, 7q11, 11q12, 13q13 and 14q12 (>20%)]. Unsupervised clustering revealed a poor prognosis subclass with increased alterations significantly associated to tumor differentiation and survival. TP53 and KRAS mutations occurred in 19% of tumors and 6% of metastases. Pathway analyses revealed association to cancer-associated pathways. Advanced tumor stage, microvascular/perineural invasion, and microscopic positive resection margin (R1) were significantly correlated to metastases, while N1-status, R1-resection, and poor tumor differentiation were significantly correlated to survival. ACGH identified clear differences between N0 (no LNM) and N1 tumors, while N1 tumors and matched LNM displayed high clonality with exclusive gains in the metastases. A novel subclass with increased CNAs and poor tumor differentiation was significantly correlated to survival.

Influence of Schistosoma japonicum programmed cell death protein 10 on the growth and development of schistosomula

Background

Schistosomiasis caused by Schistosoma japonicum is among the most serious endemic zoonoses in China. To study interactions between schistosomula, the pre-adult juvenile stage, and hosts, it is important to study the functions of key genes involved in schistosomula growth and development. Programmed cell death protein 10 (pcdp10) is an important apoptosis-related gene with various biological functions. This study described the molecular characterization of S. japonicum PCDP10 (SjPCDP10) and evaluated its functions in schistosomula.

Methods

Real-time quantitative polymerase chain reaction (qPCR) and western blot were used to detect Sjpcdp10 mRNA and protein levels, respectively, at different developmental stages. Immunolocalization was performed to determine SjPCDP10 expression in the parasite. RNA interference (RNAi) experiments were used to assess gene functions associated with SjPCDP10 in schistosomula growth and development.

Results

Real-time qPCR revealed that Sjpcdp10 was expressed during all investigated developmental stages and upregulated during schistosomula growth and development. Histochemical localization showed that SjPCDP10 was mainly distributed in the teguments of schistosomula in all investigated stages and part of the parenchymal area of 14-, 18-, and 21-day-old schistosomula. Following Sjpcdp10 knockdown by RNAi, the lengths, widths, areas, and volumes of schistosomula were significantly lower than those in the control group. Scanning electron microscopy showed that the body surfaces of schistosomula subjected to RNAi were seriously damaged, with few tegumental spines and sensory papillae. Transmission electron microscopy indicated that the teguments of Sjpcdp10-knockdown schistosomula were incomplete, the number of layers was reduced, and the thickness decreased significantly as compared with those in the control group. Furthermore, terminal deoxynucleotidyl transferase dUTP nick-end labelling results showed that the rate of apoptosis in Sjpcdp10-knockdown schistosomula was significantly higher than that in the control group.

Conclusions

Sjpcdp10-knockdown influenced the growth and development of schistosomula. Therefore, our results indicated that SjPCDP10 contributes to the regulation of cell apoptosis and is essential for schistosomula growth and development.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2636-8) contains supplementary material, which is available to authorized users.

A plasma lipidomics strategy reveals perturbed lipid metabolic pathways and potential lipid biomarkers of human colorectal cancer

To explore underlying molecular mechanisms and identify novel lipid biomarkers promising for colorectal cancer (CRC) diagnosis, a continuous-flow two dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry (2D LC-QToF/MS) method was employed to comprehensively measure lipid species in human plasma of CRC patients and healthy controls. With a total of 427 annotated lipid species, we identified 64 lipid species with corrected p value less than 0.05 and fold change more than 1.5. These significantly altered lipid species were mainly involved in glycerolipids and glycerophospholipids metabolism and sphingolipids metabolism. After the diagnosis ability evaluation based on the receiver operating characteristic (ROC) curve, phosphatidylglycerol (34:0), sphingomyelin (42:2), ceramide (44:5), lysophosphatidylcholine (18:3), lysophosphatidylcholine (18:2), phosphatidylethanolamine (O-36:3), phosphatidylethanolamine (O-38:3) and sphingomyelin (38:8) were finally proposed as the potential biomarkers with the area under the curve (AUC) more than 0.900. These results suggest that this 2D LC-QToF/MS-based lipidomics profiling has great potential as a noninvasive diagnostic method in detecting CRC and hopefully provide new clues to understand its underlying mechanism.

In Search for Optimal Targets for Intraoperative Fluorescence Imaging of Peritoneal Metastasis From Colorectal Cancer

Peritoneal metastasis (PM) occurs in about 10% of patients with colorectal cancer (CRC). Fluorescence imaging can enhance contrast between cancerous and benign tissue, enabling the surgeon to clearly visualize PM during cytoreductive surgery. This study assessed the suitability of different biomarkers as potential targets for tumor-targeted imaging of PM of CRC. Tissue samples from primary tumor and PM from patients with CRC were obtained from the pathology archives and immunohistochemical stainings were performed. Overexpression of the epithelial cell adhesion molecule (EpCAM) and carcinoembryonic antigen (CEA) was seen in 100% of PM samples and the expression was strong in >70% of samples. Tyrosine-kinase Met (C-Met) and folate receptor α overexpression was seen in 20% of PM samples. For successful application of tumor-targeted intraoperative fluorescence imaging of PM, biomarkers need to be identified. We demonstrated that both EpCAM and CEA are suitable targets for fluorescence imaging of PM in patients with CRC.

Risk analysis of colorectal cancer incidence by gene expression analysis

Background

Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction.

Objective

Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples.

Methods

We collected microarray data from the GEO database to establish colorectal cancer microarray gene expression datasets for a combined analysis. Using the Prediction Analysis for Microarrays (PAM) method and the GSEA MSigDB resource, we analyzed the 14,698 genes that were identified through an examination of their expression values between normal and tumor tissues.

Results

Ten genes (ABCG2, AQP8, SPIB, CA7, CLDN8, SCNN1B, SLC30A10, CD177, PADI2, and TGFBI) were found to be good indicators of the candidate genes that correlate with CRC. From these selected genes, an average of six significant genes were obtained using the PAM method, with an accuracy rate of 95%. The results demonstrate the potential of utilizing a model with the PAM method for data mining. After a detailed review of the published reports, the results confirmed that the screened candidate genes are good indicators for cancer risk analysis using the PAM method.

Conclusions

Six genes were selected with 95% accuracy to effectively classify normal and colorectal cancer tissues. We hope that these results will provide the basis for new research projects in clinical practice that aim to rapidly assess colorectal cancer risk using microarray gene expression analysis.

Dissecting characteristics and dynamics of differentially expressed proteins during multistage carcinogenesis of human colorectal cancer

AIM: To discover novel biomarkers for early diagnosis, prognosis or treatment of human colorectal cancer.

METHODS: iTRAQ 2D LC-MS/MS analysis was used to identify differentially expressed proteins (DEPs) in the human colonic epithelial carcinogenic process using laser capture microdissection-purified colonic epithelial cells from normal colon, adenoma, carcinoma in situ and invasive carcinoma tissues.

RESULTS: A total of 326 DEPs were identified, and four DEPs (DMBT1, S100A9, Galectin-10, and S100A8) with progressive alteration in the carcinogenic process were further validated by immunohistochemistry. The DEPs were involved in multiple biological processes including cell cycle, cell adhesion, translation, mRNA processing, and protein synthesis. Some of the DEPs involved in cellular process such as “translation” and “mRNA splicing” were progressively up-regulated, while some DEPs involved in other processes such as “metabolism” and “cell response to stress” was progressively down-regulated. Other proteins with up- or down-regulation at certain stages of carcinogenesis may play various roles at different stages of the colorectal carcinogenic process.

CONCLUSION: These findings give insights into our understanding of the mechanisms of colorectal carcinogenesis and provide clues for further investigation of carcinogenesis and identification of biomarkers.

Overexpression of the S100A2 protein as a prognostic marker for patients with stage II and III colorectal cancer

We aimed to identify a novel prognostic biomarker related to recurrence in stage II and III colorectal cancer (CRC) patients. Stage II and III CRC tissue mRNA expression was profiled using an Affymetrix Gene Chip, and copy number profiles of 125 patients were generated using an Affymetrix 250K Sty array. Genes showing both upregulated expression and copy number gains in cases involving recurrence were extracted as candidate biomarkers. The protein expression of the candidate gene was assessed using immunohistochemical staining of tissue from 161 patients. The relationship between protein expression and clinicopathological features was also examined. We identified 9 candidate genes related to recurrence of stage II and III CRC, whose mRNA expression was significantly higher in CRC than in normal tissue. Of these proteins, the S100 calcium-binding protein A2 (S100A2) has been observed in several human cancers. S100A2 protein overexpression in CRC cells was associated with significantly worse overall survival and relapse-free survival, indicating that S100A2 is an independent risk factor for stage II and III CRC recurrence. S100A2 overexpression in cancer cells could be a biomarker of poor prognosis in stage II and III CRC recurrence and a target for treatment of this disease.

Essential role of miR-200c in regulating self-renewal of breast cancer stem cells and their counterparts of mammary epithelium

Background

Breast cancer stem cells (BCSCs) have been reported as the origin of breast cancer and the radical cause of drug resistance, relapse and metastasis in breast cancer. BCSCs could be derived from mutated mammary epithelial stem cells (MaSCs). Therefore, comparing the molecular differences between BCSCs and MaSCs may clarify the mechanism underlying breast carcinogenesis and the targets for gene therapy. Specifically, the distinct miRNome data of BCSCs and MaSCs need to be analyzed to find out the key miRNAs and reveal their roles in regulating the stemness of BCSCs.

Methods

MUC1⁻ESA⁺ cells were isolated from normal mammary epithelial cell line MCF-10A by fluorescence-activated cell sorting (FACS) and tested for stemness by clonogenic assay and multi-potential differentiation experiments. The miRNA profiles of MaSCs, BCSCs and breast cancer MCF-7 cells were compared to obtain the candidate miRNAs that may regulate breast tumorigenesis. An miRNA consecutively upregulated from MaSCs to BCSCs to MCF-7 cells, miR-200c, was chosen to determine its role in regulating the stemness of BCSCs and MaSCs in vitro and in vivo. Based on bioinformatics, the targets of miR-200c were validated by dual-luciferase report system, western blot and rescue experiments.

Results

In a 2-D clonogenic assay, MUC1⁻ESA⁺ cells gave rise to multiple morphological colonies, including luminal colonies, myoepithelial colonies and mixed colonies. The clonogenic potential of MUC1⁻ESA⁺ (61.5 ± 3.87 %) was significantly higher than that of non-stem MCF-10A cells (53.5 ± 3.42 %) (P < 0.05). In a 3-D matrigel culture, MUC1⁻ESA⁺ cells grew into mammospheres with duct-like structures. A total of 12 miRNAs of interest were identified, 8 of which were upregulated and 4 downregulated in BCSCs compared with MaSCs. In gain- and lost-of-function assays, miR-200c was sufficient to inhibit the self-renewal of BCSCs and MaSCs in vitro and the growth of BCSCs in vivo. Furthermore, miR-200c negatively regulated programmed cell death 10 (PDCD10) in BCSCs and MaSCs. PDCD10 could rescue the tumorigenesis inhibited by miR-200c in BCSCs.

Discussion

Accumulating evidence shows that there is a milignant transformation from MaSCs into BCSCs. The underlying mechanism remains unclear. In present study, miRNA profiles between MaSCs and BCSCs were obtained. Then miRNA-200c, downregulated in both MaSCs and BCSCs, were verified as anti-oncogene, and played essential role in regulating self-renewal of both kinds of stem-like cells. These findings reveal a novel insights of breast tumorigenesis.

Conclusions

PDCD10 is a target gene of miR-200c and also a possible mechanism by which miR-200c plays a role in regulating the stemness of BCSCs and MaSCs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1655-5) contains supplementary material, which is available to authorized users.

Folic acid supplements and colorectal cancer risk: meta-analysis of randomized controlled trials

Numerous studies have investigated the effects of folic acid supplementation on colorectal cancer risk, but conflicting results were reported. We herein performed a meta-analysis based on relevant studies to reach a more definitive conclusion. The PubMed and Embase databases were searched for quality randomized controlled trials (RCTs) published before October 2014. Eight articles met the inclusion criteria and were subsequently analyzed. The results suggested that folic acid treatment was not associated with colorectal cancer risk in the total population (relative risk [RR] = 1.00, 95% confidence interval [CI] = 0.82–1.22, P = 0.974). Moreover, no statistical effect was identified in further subgroup analyses stratified by ethnicity, gender, body mass index (BMI) and potential confounding factors. No significant heterogeneity or publication bias was observed. In conclusion, our meta-analysis demonstrated that folic acid supplementation had no effect on colorectal cancer risk. However, this finding must be validated by further large studies.

Imputation of Truncated p-Values For Meta-Analysis Methods and Its Genomic Application

Microarray analysis to monitor expression activities in thousands of genes simultaneously has become routine in biomedical research during the past decade. a tremendous amount of expression profiles are generated and stored in the public domain and information integration by meta-analysis to detect differentially expressed (DE) genes has become popular to obtain increased statistical power and validated findings. Methods that aggregate transformed p-value evidence have been widely used in genomic settings, among which Fisher's and Stouffer's methods are the most popular ones. In practice, raw data and p-values of DE evidence are often not available in genomic studies that are to be combined. Instead, only the detected DE gene lists under a certain p-value threshold (e.g., DE genes with p-value < 0.001) are reported in journal publications. The truncated p-value information makes the aforementioned meta-analysis methods inapplicable and researchers are forced to apply a less efficient vote counting method or naïvely drop the studies with incomplete information. The purpose of this paper is to develop effective meta-analysis methods for such situations with partially censored p-values. We developed and compared three imputation methods-mean imputation, single random imputation and multiple imputation-for a general class of evidence aggregation methods of which Fisher's and Stouffer's methods are special examples. The null distribution of each method was analytically derived and subsequent inference and genomic analysis frameworks were established. Simulations were performed to investigate the type Ierror, power and the control of false discovery rate (FDR) for (correlated) gene expression data. The proposed methods were applied to several genomic applications in colorectal cancer, pain and liquid association analysis of major depressive disorder (MDD). The results showed that imputation methods outperformed existing naïve approaches. Mean imputation and multiple imputation methods performed the best and are recommended for future applications.

Gene expression profile of peripheral blood in colorectal cancer

AIM: Optimal molecular markers for detecting colorectal cancer (CRC) in a blood-based assay were evaluated.

METHODS: A matched (by variables of age and sex) case-control design (111 CRC and 227 non-cancer samples) was applied. Total RNAs isolated from the 338 blood samples were reverse-transcribed, and the relative transcript levels of candidate genes were analyzed. The training set was made of 162 random samples of the total 338 samples. A logistic regression analysis was performed, and odds ratios for each gene were determined between CRC and non-cancer. The samples (n = 176) in the testing set were used to validate the logistic model, and an inferred performance (generality) was verified. By pooling 12 public microarray datasets(GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105), which included 519 cases of adenocarcinoma and 88 controls of normal mucosa, we were able to verify the selected genes from logistic models and estimate their external generality.

RESULTS: The logistic regression analysis resulted in the selection of five significant genes (P < 0.05; MDM2, DUSP6, CPEB4, MMD, and EIF2S3), with odds ratios of 2.978, 6.029, 3.776, 0.538 and 0.138, respectively. The five-gene model performed stably for the discrimination of CRC cases from controls in the training set, with accuracies ranging from 73.9% to 87.0%, a sensitivity of 95% and a specificity of 95%. In addition, a good performance in the test set was obtained using the discrimination model, providing 83.5% accuracy, 66.0% sensitivity, 92.0% specificity, a positive predictive value of 89.2% and a negative predictive value of 73.0%. Multivariate logistic regressions analyzed 12 pooled public microarray data sets as an external validation. Models that provided similar expected and observed event rates in subgroups were termed well calibrated. A model in which MDM2, DUSP6, CPEB4, MMD, and EIF2S3 were selected showed the result in logistic regression analysis (H-L P = 0.460, R2= 0.853, AUC = 0.978, accuracy = 0.949, specificity = 0.818 and sensitivity = 0.971).

CONCLUSION: A novel gene expression profile was associated with CRC and can potentially be applied to blood-based detection assays.

Gene expression profiling of colorectal tumors and normal mucosa by microarrays meta-analysis using prediction analysis of microarray, artificial neural network, classification, and regression trees

BACKGROUND

Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC) research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0).

METHODS

Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances.

RESULTS

The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods.

CONCLUSION

We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%). This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC.

IRS-2 G1057D polymorphism in Turkish patients with colorectal cancer

Introduction

Gene polymorphisms have a broad range of analysis, but are of particular use in molecular medicine due to their potential in revealing the genetic tendency in diseases such as cancer, heart attack etc. These studies basically depend on mutations that can be detected by proper techniques. The genes coding the insulin receptor substrate (IRS) proteins are among the most widely analysed polymorphisms in various cancer types, in which a G1057D mutation is seen.

Aim

To determine the risk of colon cancer by analysing the IRS-2 gene polymorphism in Turkish patients.

Material and methods

A total of 161 newly diagnosed colorectal cancer patients were analysed and compared to 197 unrelated healthy controls. A polymerase chain reaction-based restriction fragment length polymorphism method was carried out.

Results

No differences were observed between the patient and control groups for both allele and genotype frequencies of the IRS-2 G1057D gene.

Conclusions

Our results demonstrated that IRS-2 G1057D polymorphism is not associated with colorectal cancer in the Turkish population. This research is a preliminary and original study in Turkish patients with colorectal cancer. It also provides population-level genetic data on IRS-2 in the Turkish population. Further studies should be performed on larger number of patients and controls for more reliable results about the genetic tendency in colorectal cancer in Turkey. The study is a collaborative work of different universities and scientists.

Current and future molecular diagnostics in colorectal cancer and colorectal adenoma

Colorectal cancer (CRC) is one of the most prevalent cancers in developed countries. On the other hand, CRC is also one of the most curable cancers if it is detected in early stages through regular colonoscopy or sigmoidoscopy. Since CRC develops slowly from precancerous lesions, early detection can reduce both the incidence and mortality of the disease. Fecal occult blood test is a widely used non-invasive screening tool for CRC. Although fecal occult blood test is simple and cost-effective in screening CRC, there is room for improvement in terms of the accuracy of the test. Genetic dysregulations have been found to play an important role in CRC development. With better understanding of the molecular basis of CRC, there is a growing expectation on the development of diagnostic tests based on more sensitive and specific molecular markers and those tests may provide a breakthrough to the limitations of current screening tests for CRC. In this review, the molecular basis of CRC development, the characteristics and applications of different non-invasive molecular biomarkers, as well as the technologies available for the detection were discussed. This review intended to provide a summary on the current and future molecular diagnostics in CRC and its pre-malignant state, colorectal adenoma.

An integrative framework identifies alternative splicing events in colorectal cancer development

Alternative splicing (AS) is a common mechanism which creates diverse RNA isoforms from a single gene, potentially increasing protein variety. Growing evidence suggests that this mechanism is closely related to cancer progression. In this study, whole transcriptome analysis was performed with GeneChip Human exon 1.0 ST Array from 80 samples comprising 23 normal colon mucosa, 30 primary colorectal cancer and 27 liver metastatic specimens from 46 patients, to identify AS events in colorectal cancer progression. Differentially expressed genes and exons were estimated and AS events were reconstructed by combining exon-level analyses with AltAnalyze algorithms and transcript-level estimations (MMBGX probabilistic method). The number of AS genes in the transition from normal colon mucosa to primary tumor was the most abundant, but fell considerably in the next transition to liver metastasis. 206 genes with probable AS events in colon cancer development and progression were identified, that are involved in processes and pathways relevant to tumor biology, as cell-cell and cell-matrix interactions. Several AS events in VCL, CALD1, B3GNT6 and CTHRC1 genes, differentially expressed during tumor development were validated, at RNA and at protein level. Taken together, these results demonstrate that cancer-specific AS is common in early phases of colorectal cancer natural history.

ToP: a trend-of-disease-progression procedure works well for identifying cancer genes from multi-state cohort gene expression data for human colorectal cancer

Significantly expressed genes extracted from microarray gene expression data have proved very useful for identifying genetic biomarkers of diseases, including cancer. However, deriving a disease related inference from a list of differentially expressed genes has proven less than straightforward. In a systems disease such as cancer, how genes interact with each other should matter just as much as the level of gene expression. Here, in a novel approach, we used the network and disease progression properties of individual genes in state-specific gene-gene interaction networks (GGINs) to select cancer genes for human colorectal cancer (CRC) and obtain a much higher hit rate of known cancer genes when compared with methods not based on network theory. We constructed GGINs by integrating gene expression microarray data from multiple states--healthy control (Nor), adenoma (Ade), inflammatory bowel disease (IBD) and CRC--with protein-protein interaction database and Gene Ontology. We tracked changes in the network degrees and clustering coefficients of individual genes in the GGINs as the disease state changed from one to another. From these we inferred the state sequences Nor-Ade-CRC and Nor-IBD-CRC both exhibited a trend of (disease) progression (ToP) toward CRC, and devised a ToP procedure for selecting cancer genes for CRC. Of the 141 candidates selected using ToP, ∼50% had literature support as cancer genes, compared to hit rates of 20% to 30% for standard methods using only gene expression data. Among the 16 candidate cancer genes that encoded transcription factors, 13 were known to be tumorigenic and three were novel: CDK1, SNRPF, and ILF2. We identified 13 of the 141 predicted cancer genes as candidate markers for early detection of CRC, 11 and 2 at the Ade and IBD states, respectively.

Extensive quantitative remodeling of the proteome between normal colon tissue and adenocarcinoma

In-depth proteomic analysis of microdissected colorectal cancer identifies extensive alterations in the cell-surface and nuclear proteomes between normal mucosa and adenocarcinoma, but observes strikingly little proteomic change between cancer and metastases.

First large-scale proteomic analysis of microdissected tissue from archival formalin-fixed and paraffin-embedded material.

Quantitation of 7576 proteins between patient-matched samples of normal colonic mucosa, primary cancer, and nodal metastasis.

Expression levels of 1808 proteins changed significantly between normal and cancer tissues.

Total Protein Approach (TPA)—a new way to determine protein copy numbers per cell without protein standards.

We report a proteomic analysis of microdissected material from formalin-fixed and paraffin-embedded colorectal cancer, quantifying >7500 proteins between patient matched normal mucosa, primary carcinoma, and nodal metastases. Expression levels of 1808 proteins changed significantly between normal and cancer tissues, a much larger fraction than that reported in transcript-based studies. Tumor cells exhibit extensive alterations in the cell-surface and nuclear proteomes. Functionally similar changes in the proteome were observed comparing rapidly growing and differentiated CaCo-2 cells. In contrast, there was minimal proteomic remodeling between primary cancer and metastases, suggesting that no drastic proteome changes are necessary for the tumor to propagate in a different tissue context. Additionally, we introduce a new way to determine protein copy numbers per cell without protein standards. Copy numbers estimated in enterocytes and cancer cells are in good agreement with CaCo-2 and HeLa cells and with the literature data. Our proteomic data set furthermore allows mapping quantitative changes of functional protein classes, enabling novel insights into the biology of colon cancer.

Integrated analysis of genome-wide copy number alterations and gene expression in microsatellite stable, CpG island methylator phenotype-negative colon cancer

Microsatellite stable (MSS), CpG island methylator phenotype (CIMP)-negative colorectal tumors, the most prevalent molecular subtype of colorectal cancer, are associated with extensive copy number alteration (CNA) events and aneuploidy. We report on the identification of characteristic recurrent CNA (with frequency >25%) events and associated gene expression profiles for a total of 40 paired tumor and adjacent normal colon tissues using genome-wide microarrays. We observed recurrent CNAs, namely gains at 1q, 7p, 7q, 8p12-11, 8q, 12p13, 13q, 20p, 20q, Xp, and Xq and losses at 1p36, 1p31, 1p21, 4p15-12, 4q12-35, 5q21-22, 6q26, 8p, 14q, 15q11-12, 17p, 18p, 18q, 21q21-22, and 22q. Within these genomic regions we identified 356 genes with significant differential expression (P < 0.0001 and ±1.5-fold change) in the tumor compared to adjacent normal tissue. Gene ontology and pathway analyses indicated that many of these genes were involved in functional mechanisms that regulate cell cycle, cell death, and metabolism. An amplicon present in >70% of the tumor samples at 20q11-20q13 contained several cancer-related genes (AHCY, POFUT1, RPN2, TH1L, and PRPF6) that were upregulated and demonstrated a significant linear correlation (P < 0.05) for gene dosage and gene expression. Copy number loss at 8p, a CNA associated with adenocarcinoma and poor prognosis, was observed in >50% of the tumor samples and demonstrated a significant linear correlation for gene dosage and gene expression for two potential tumor suppressor genes, MTUS1 (8p22) and PPP2CB (8p12). The results from our integration analysis illustrate the complex relationship between genomic alterations and gene expression in colon cancer.

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.

Serum amino acid profiles and their alterations in colorectal cancer

Mass spectrometry-based serum metabolic profiling is a promising tool to analyse complex cancer associated metabolic alterations, which may broaden our pathophysiological understanding of the disease and may function as a source of new cancer-associated biomarkers. Highly standardized serum samples of patients suffering from colon cancer (n = 59) and controls (n = 58) were collected at the University Hospital Leipzig. We based our investigations on amino acid screening profiles using electrospray tandem-mass spectrometry. Metabolic profiles were evaluated using the Analyst 1.4.2 software. General, comparative and equivalence statistics were performed by R 2.12.2. 11 out of 26 serum amino acid concentrations were significantly different between colorectal cancer patients and healthy controls. We found a model including CEA, glycine, and tyrosine as best discriminating and superior to CEA alone with an AUROC of 0.878 (95% CI 0.815-0.941). Our serum metabolic profiling in colon cancer revealed multiple significant disease-associated alterations in the amino acid profile with promising diagnostic power. Further large-scale studies are necessary to elucidate the potential of our model also to discriminate between cancer and potential differential diagnoses. In conclusion, serum glycine and tyrosine in combination with CEA are superior to CEA for the discrimination between colorectal cancer patients and controls.

Chromosomal copy number alterations are associated with persistent lymph node metastasis after chemoradiation in locally advanced rectal cancer

BACKGROUND

Lymph node metastasis is an important indicator of oncologic outcome for patients with rectal cancer. Identifying predictive biomarkers of lymph node metastasis could therefore be clinically useful.

OBJECTIVE

The aim of this study was to assess whether chromosomal copy number alterations can assist in predicting persistent lymph node metastasis in patients with locally advanced rectal cancer treated with preoperative chemoradiation therapy.

DESIGN

This is a nonrandomized, prospective phase II study.

SETTING

This study took place in a multi-institutional setting.

PATIENTS

Ninety-five patients with stage II (cT3-4, cN0) or stage III (any cT, cN1-2) rectal cancer were included.

INTERVENTION

Patients were treated with preoperative chemoradiation therapy followed by total mesorectal excision. Pretreatment biopsy tumor DNA and surgical margin control DNA were extracted and analyzed by oligonucleotide array-based comparative genomic hybridization. Chromosomal copy number alterations were correlated with persistent lymph node metastasis. Finally, a model for predicting persistent lymph node metastasis was built.

MAIN OUTCOME MEASURES

The primary outcomes assessed were whether chromosomal copy number alterations are associated with persistent lymph node metastasis in patients with rectal cancer and the accuracy of oligonucleotide array-based comparative genomic hybridization for predicting lymph node metastasis.

RESULTS

Twenty-five of 95 (26%) patients had lymph node metastasis after chemoradiation. Losses of 28 chromosomal regions, most notably in chromosome 4, were significantly associated with lymph node metastasis. Our predictive model contained 65 probes and predicted persistent lymph node metastasis with 68% sensitivity, 93% specificity, and positive and negative predictive values of 77% and 89%. The use of this model accurately predicted lymph node status (positive or negative) after chemoradiation therapy in 82 of 95 patients (86%).

LIMITATIONS

The patient cohort was not completely homogeneous, which may have influenced their clinical outcome. In addition, although we performed rigorous, statistically sound internal validation, external validation will be important to further corroborate our findings.

CONCLUSIONS

Copy number alterations can help identify patients with rectal cancer who are at risk of lymph node metastasis after chemoradiation.

Bioinformatic identification of proteins with tissue-specific expression for biomarker discovery

BACKGROUND

There is an important need for the identification of novel serological biomarkers for the early detection of cancer. Current biomarkers suffer from a lack of tissue specificity, rendering them vulnerable to non-disease-specific increases. The present study details a strategy to rapidly identify tissue-specific proteins using bioinformatics.

METHODS

Previous studies have focused on either gene or protein expression databases for the identification of candidates. We developed a strategy that mines six publicly available gene and protein databases for tissue-specific proteins, selects proteins likely to enter the circulation, and integrates proteomic datasets enriched for the cancer secretome to prioritize candidates for further verification and validation studies.

RESULTS

Using colon, lung, pancreatic and prostate cancer as case examples, we identified 48 candidate tissue-specific biomarkers, of which 14 have been previously studied as biomarkers of cancer or benign disease. Twenty-six candidate biomarkers for these four cancer types are proposed.

CONCLUSIONS

We present a novel strategy using bioinformatics to identify tissue-specific proteins that are potential cancer serum biomarkers. Investigation of the 26 candidates in disease states of the organs is warranted.

Tumor immunosurveillance in human cancers

Until now, the anatomic extent of tumor (TNM classification) has been by far the most important factor to predict the prognosis of colorectal cancer patients. However, in recent years, data collected from large cohorts of human cancers demonstrated that the immune contexture of the primary tumors is an essential prognostic factor for patients’ disease-free and overall survival. Tumoral and immunological markers predicted by systems biology methods are involved in the shaping of an efficient immune reaction and can serve as targets for novel therapeutic approaches. Global analysis of tumor microenvironment showed that the nature, the functional orientation, the density, and the location of adaptive immune cells within distinct tumor regions influence the risk of relapse events. The density and the immune cell location within the tumor have a prognostic value that is superior to the TNM classification, and tumor invasion is statistically dependent on the host-immune reaction. Thus, the strength of the immune reaction could advance our understanding of cancer evolution and have important consequences in clinical practice.

Molecular alterations associated with liver metastases development in colorectal cancer patients

Background:

Understanding the molecular biology of colorectal cancer (CRC) provides opportunities for effective personalised patient management. We evaluated whether chromosomal aberrations, mutations in the PI(3)K signalling pathway and the CpG-island methylator phenotype (CIMP) in primary colorectal tumours can predict liver metastases.

Methods:

Formalin-fixed paraffin-embedded material from primary colorectal tumours of three different groups were investigated: patients with CRC without metastases (M0, n=39), patients who were treated with hyperthermal intraperitoneal chemotherapy for CRC metastases confined to the peritoneum (PM, n=46) and those who had isolated hepatic perfusion for CRC metastases confined to the liver (LM, n=48).

Results:

All samples were analysed for DNA copy number changes, PIK3CA, KRAS, BRAF mutations, CIMP and microsatellite instability. The primary CRCs of the LM group had significantly higher frequency of amplified chromosome 20q (P=0.003), significantly fewer mutations in the PI(3)K signalling pathway (P=0.003) and fewer CIMP high tumours (P=0.05). There was a strong inverse correlation between 20q and the PI(3)K pathway mutations.

Conclusion:

The development of CRC liver metastases is associated with amplification of chromosome 20q and not driven by mutations in the PI(3)K signalling pathway.

Consensus pathways implicated in prognosis of colorectal cancer identified through systematic enrichment analysis of gene expression profiling studies

Background

A large number of gene expression profiling (GEP) studies on prognosis of colorectal cancer (CRC) has been performed, but no reliable gene signature for prediction of CRC prognosis has been found. Bioinformatic enrichment tools are a powerful approach to identify biological processes in high-throughput data analysis.

Principal Findings

We have for the first time collected the results from the 23 so far published independent GEP studies on CRC prognosis. In these 23 studies, 1475 unique, mapped genes were identified, from which 124 (8.4%) were reported in at least two studies, with 54 of them showing consisting direction in expression change between the single studies. Using these data, we attempted to overcome the lack of reproducibility observed in the genes reported in individual GEP studies by carrying out a pathway-based enrichment analysis. We used up to ten tools for overrepresentation analysis of Gene Ontology (GO) categories or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in each of the three gene lists (1475, 124 and 54 genes). This strategy, based on testing multiple tools, allowed us to identify the oxidative phosphorylation chain and the extracellular matrix receptor interaction categories, as well as a general category related to cell proliferation and apoptosis, as the only significantly and consistently overrepresented pathways in the three gene lists, which were reported by several enrichment tools.

Conclusions

Our pathway-based enrichment analysis of 23 independent gene expression profiling studies on prognosis of CRC identified significantly and consistently overrepresented prognostic categories for CRC. These overrepresented categories have been functionally clearly related with cancer progression, and deserve further investigation.

Selecting Potential Targetable Biomarkers for Imaging Purposes in Colorectal Cancer Using TArget Selection Criteria (TASC): A Novel Target Identification Tool

Peritoneal carcinomatosis (PC) of colorectal origin is associated with a poor prognosis. However, cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy is available for a selected group of PC patients, which significantly increases overall survival rates up to 30%. As a consequence, there is substantial room for improvement. Tumor targeting is expected to improve the treatment efficacy of colorectal cancer (CRC) further through 1) more sensitive preoperative tumor detection, thus reducing overtreatment; 2) better intraoperative detection and surgical elimination of residual disease using tumor-specific intraoperative imaging; and 3) tumor-specific targeted therapeutics. This review focuses, in particular, on the development of tumor-targeted imaging agents. A large number of biomarkers are known to be upregulated in CRC. However, to date, no validated criteria have been described for the selection of the most promising biomarkers for tumor targeting. Such a scoring system might improve the selection of the correct biomarker for imaging purposes. In this review, we present the TArget Selection Criteria (TASC) scoring system for selection of potential biomarkers for tumor-targeted imaging. By applying TASC to biomarkers for CRC, we identified seven biomarkers (carcinoembryonic antigen, CXC chemokine receptor 4, epidermal growth factor receptor, epithelial cell adhesion molecule, matrix metalloproteinases, mucin 1, and vascular endothelial growth factor A) that seem most suitable for tumor-targeted imaging applications in colorectal cancer. Further cross-validation studies in CRC and other tumor types are necessary to establish its definitive value.

Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

Background:

A large number of gene expression profiling (GEP) studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis.

Materials and Methods:

We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9%) had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO) categories or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration.

Results:

Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities.

Conclusions:

We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation.

Epigenomic analysis of aberrantly methylated genes in colorectal cancer identifies genes commonly affected by epigenetic alterations

BACKGROUND

Determination of the profile of genes that are commonly methylated aberrantly in colorectal cancer (CRC) will have substantial value for diagnostic and therapeutic applications. However, there is limited knowledge of the DNA methylation pattern in CRC.

MATERIALS AND METHODS

We analyzed the methylation profile of 27,578 CpG sites spanning more than 14,000 genes in CRC and in the adjacent normal mucosa with bead-chip array-based technology.

RESULTS

We identified 621 CpG sites located in promoter regions and CpG islands that were greatly hypermethylated in CRC compared to normal mucosa. The genes on chromosome 18 showed promoter hypermethylation most frequently. According to gene ontology analysis, the most common biologically relevant class of genes affected by methylation was the class associated with the cadherin signaling pathway. Compared to the genome-wide expression array, mRNA expression was more likely to be downregulated in the genes demonstrating promoter hypermethylation, even though this was not statistically significant. We validated ten CpG sites that were hypermethylated (ADHFE1, BOLL, SLC6A15, ADAMTS5, TFPI2, EYA4, NPY, TWIST1, LAMA1, GAS7) and 2 CpG sites showing hypomethylation (MAEL, SFT2D3) in CRC compared to the normal mucosa in the array studies using pyrosequencing. The methylation status measured by pyrosequencing was consistent with the methylation array data.

CONCLUSIONS

Methylation profiling based on bead-chip arrays is an effective method for screening aberrantly methylated genes in CRC. In addition, we identified novel methylated genes that are candidate diagnostic or prognostic markers for CRC.

Specific genomic aberrations in primary colorectal cancer are associated with liver metastases

BACKGROUND

Accurate staging of colorectal cancer (CRC) with clinicopathological parameters is important for predicting prognosis and guiding treatment but provides no information about organ site of metastases. Patterns of genomic aberrations in primary colorectal tumors may reveal a chromosomal signature for organ specific metastases.

METHODS

Array Comparative Genomic Hybridization (aCGH) was employed to asses DNA copy number changes in primary colorectal tumors of three distinctive patient groups. This included formalin-fixed, paraffin-embedded tissue of patients who developed liver metastases (LM; n = 36), metastases (PM; n = 37) and a group that remained metastases-free (M0; n = 25).A novel statistical method for identifying recurrent copy number changes, KC-SMART, was used to find specific locations of genomic aberrations specific for various groups. We created a classifier for organ specific metastases based on the aCGH data using Prediction Analysis for Microarrays (PAM).

RESULTS

Specifically in the tumors of primary CRC patients who subsequently developed liver metastasis, KC-SMART analysis identified genomic aberrations on chromosome 20q. LM-PAM, a shrunken centroids classifier for liver metastases occurrence, was able to distinguish the LM group from the other groups (M0&PM) with 80% accuracy (78% sensitivity and 86% specificity). The classification is predominantly based on chromosome 20q aberrations.

CONCLUSION

Liver specific CRC metastases may be predicted with a high accuracy based on specific genomic aberrations in the primary CRC tumor. The ability to predict the site of metastases is important for improvement of personalized patient management.

Modeling oncogenic signaling in colon tumors by multidirectional analyses of microarray data directed for maximization of analytical reliability

Background

Clinical progression of colorectal cancers (CRC) may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence.

Methodology/Principal Findings

Studies were performed on normal mucosa, adenoma, and carcinoma samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data was generated using two normalization algorithms: MAS5.0 and GCRMA with least-variant set (LVS). The data was evaluated using pair-wise comparisons and data decomposition into singular value decomposition (SVD) modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Expressional profiles obtained in 105 samples of whole tissue sections were used to establish oncogenic signaling alterations in progression of CRC, while those representing 40 microdissected specimens were used to select differences in KEGG pathways between epithelium and mucosa. Based on a consensus of the results obtained by two normalization algorithms, and two probe set sorting criteria, we identified 14 and 17 KEGG signaling and metabolic pathways that are significantly altered between normal and tumor samples and between benign and malignant tumors, respectively. Several of them were also selected from the raw microarray data of 2 recently published studies (GSE4183 and GSE8671).

Conclusion/Significance

Although the proposed strategy is computationally complex and labor–intensive, it may reduce the number of false results.

Gene expression profile and genomic alterations in colonic tumours induced by 1,2-dimethylhydrazine (DMH) in rats

BACKGROUND

Azoxymethane (AOM) or 1,2-dimethylhydrazine (DMH)-induced colon carcinogenesis in rats shares many phenotypical similarities with human sporadic colon cancer and is a reliable model for identifying chemopreventive agents. Genetic mutations relevant to human colon cancer have been described in this model, but comprehensive gene expression and genomic analysis have not been reported so far. Therefore, we applied genome-wide technologies to study variations in gene expression and genomic alterations in DMH-induced colon cancer in F344 rats.

METHODS

For gene expression analysis, 9 tumours (TUM) and their paired normal mucosa (NM) were hybridized on 4 x 44K Whole rat arrays (Agilent) and selected genes were validated by semi-quantitative RT-PCR. Functional analysis on microarray data was performed by GenMAPP/MappFinder analysis. Array-comparative genomic hybridization (a-CGH) was performed on 10 paired TUM-NM samples hybridized on Rat genome arrays 2 x 105K (Agilent) and the results were analyzed by CGH Analytics (Agilent).

RESULTS

Microarray gene expression analysis showed that Defcr4, Igfbp5, Mmp7, Nos2, S100A8 and S100A9 were among the most up-regulated genes in tumours (Fold Change (FC) compared with NM: 183, 48, 39, 38, 36 and 32, respectively), while Slc26a3, Mptx, Retlna and Muc2 were strongly down-regulated (FC: -500; -376, -167, -79, respectively). Functional analysis showed that pathways controlling cell cycle, protein synthesis, matrix metalloproteinases, TNFalpha/NFkB, and inflammatory responses were up-regulated in tumours, while Krebs cycle, the electron transport chain, and fatty acid beta oxidation were down-regulated. a-CGH analysis showed that four TUM out of ten had one or two chromosomal aberrations. Importantly, one sample showed a deletion on chromosome 18 including Apc.

CONCLUSION

The results showed complex gene expression alterations in adenocarcinomas encompassing many altered pathways. While a-CGH analysis showed a low degree of genomic imbalance, it is interesting to note that one of the alterations concerned Apc, a key gene in colorectal carcinogenesis. The fact that many of the molecular alterations described in this study are documented in human colon tumours confirms the relevance of DMH-induced cancers as a powerful tool for the study of colon carcinogenesis and chemoprevention.

Meta-analysis for pathway enrichment analysis when combining multiple genomic studies

MOTIVATION

Many pathway analysis (or gene set enrichment analysis) methods have been developed to identify enriched pathways under different biological states within a genomic study. As more and more microarray datasets accumulate, meta-analysis methods have also been developed to integrate information among multiple studies. Currently, most meta-analysis methods for combining genomic studies focus on biomarker detection and meta-analysis for pathway analysis has not been systematically pursued.

RESULTS

We investigated two approaches of meta-analysis for pathway enrichment (MAPE) by combining statistical significance across studies at the gene level (MAPE_G) or at the pathway level (MAPE_P). Simulation results showed increased statistical power of meta-analysis approaches compared to a single study analysis and showed complementary advantages of MAPE_G and MAPE_P under different scenarios. We also developed an integrated method (MAPE_I) that incorporates advantages of both approaches. Comprehensive simulations and applications to real data on drug response of breast cancer cell lines and lung cancer tissues were evaluated to compare the performance of three MAPE variations. MAPE_P has the advantage of not requiring gene matching across studies. When MAPE_G and MAPE_P show complementary advantages, the hybrid version of MAPE_I is generally recommended.

AVAILABILITY

http://www.biostat.pitt.edu/bioinfo/

CONTACT

ctseng@pitt.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Association of the actin-binding protein transgelin with lymph node metastasis in human colorectal cancer

Metastatic dissemination of primary tumors is responsible for 90% of colorectal cancer (CRC) deaths. The presence of positive lymph nodes, which separates stage I/II from stage III CRC, is a particularly key factor in patient management. Here, we describe results of a quantitative proteomic survey to identify molecular correlates of node status. Laser capture microdissection and two-dimensional difference gel electrophoresis were used to establish expression profiles for 980 discrete protein features in 24 human CRC specimens. Protein abundances were determined with a median technical coefficient of variation of 10%, which provided an ability to detect small differences between cancer subtypes. Transgelin, a 23-kDa actin-binding protein, emerged as a top-ranked candidate biomarker of node status. The area under the receiver operating characteristic curve for transgelin in predicting node status was 0.868 (P = .002). Significantly increased frequency of moderate- and high-level transgelin expression in node-positive CRC was also seen using semiquantitative immunohistochemistry to analyze 94 independent CRC specimens on tissue microarrays (P = .036). Follow-up studies in CRC cell lines demonstrated roles for transgelin in promoting invasion, survival, and resistance to anoikis. Transgelin localizes to the nucleus of CRC cells, and its sequence and properties suggest that it may participate in regulation of the transcriptional program associated with the epithelial-to-mesenchymal transition.

Integrative analysis of cancer pathway progression and coherence

We analyzed the cancer pathways in the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. The database provides a collective of signaling pathway members involved in cancer progression. However, the KEGG cancer pathways, unlike signaling pathways, have not been analyzed extensively with gene expression and mutation data. We transformed the colorectal cancer pathway into discrete X and Y scales and analyzed the relative expression levels of adenoma and carcinoma samples as well as the distribution of mutation targets. The X scale corresponds to the downstream location in a pathway, whereas the Y scale corresponds to the stage of the tumor. The gene expression values of the early stage pathway members are significantly higher than of the rest of the pathway members in colorectal adenoma tissues. The colorectal cancer pathway shows some degree of coherence in the carcinoma samples. The correlated gene pairs responsible for the coherence of the colorectal cancer pathway in the carcinoma samples are supported, in part, by the literature and may suggest novel regulatory associations. Finally, there are more mutation targets in the nucleus as well as the late tumor stages of the KEGG colorectal cancer pathway.

Heterogeneity and Power in Clinical Biomarker Studies

Purpose

Many recent studies have suggested the possibility that a variety of different biomarkers may be associated with treatment outcome. However, it is also apparent that some of these biomarkers are heterogeneously distributed within a tumor. Due to this heterogeneous distribution of the biomarker, the association sought may appear weak or nonexistent. Thus, there is a wide range of conclusions in the literature on the association between a biomarker and an outcome.

Results

This article presents how to quantify the heterogeneity and how it influences the observed effect size and the ability to detect it (power of the study). It can be shown that the estimated effect size and the power of the study are diminished when the biomarker is measured with error. The estimated effect of the association with outcome of the average of several replicates per patient is closer to the true effect size when the number of replicates increases.

Conclusion

The first step in designing a study of association between a biomarker and outcome is to conduct a pilot study in which several measurements per patient are taken. Based on these data, the heterogeneity of the marker within and between individuals can be estimated and used in the process of designing an appropriate study of the association between the biomarker and outcome.

MACC1, a newly identified key regulator of HGF-MET signaling, predicts colon cancer metastasis

We identified a previously undescribed gene associated with colon cancer by genome-wide expression analysis in primary and metastatic carcinomas: metastasis-associated in colon cancer-1, MACC1. MACC1 expression in tumor specimens is an independent prognostic indicator of metastasis formation and metastasis-free survival. We show that the gene encoding the hepatocyte growth factor (HGF) receptor, MET, is a transcriptional target of MACC1. MACC1 promotes proliferation, invasion and HGF-induced scattering of colon cancer cells in cell culture and tumor growth and metastasis in mouse models. These phenotypes are lost in cells expressing MACC1 mutants lacking the SH3 domain or the proline-rich motif. For clinical practice, MACC1 will be useful for the identification of poor prognosis subjects with colorectal cancer and is a promising new target for intervention in metastasis formation.

Integrating chromosomal aberrations and gene expression profiles to dissect rectal tumorigenesis

Background

Accurate staging of rectal tumors is essential for making the correct treatment choice. In a previous study, we found that loss of 17p, 18q and gain of 8q, 13q and 20q could distinguish adenoma from carcinoma tissue and that gain of 1q was related to lymph node metastasis. In order to find markers for tumor staging, we searched for candidate genes on these specific chromosomes.

Methods

We performed gene expression microarray analysis on 79 rectal tumors and integrated these data with genomic data from the same sample series. We performed supervised analysis to find candidate genes on affected chromosomes and validated the results with qRT-PCR and immunohistochemistry.

Results

Integration of gene expression and chromosomal instability data revealed similarity between these two data types. Supervised analysis identified up-regulation of EFNA1 in cases with 1q gain, and EFNA1 expression was correlated with the expression of a target gene (VEGF). The BOP1 gene, involved in ribosome biogenesis and related to chromosomal instability, was over-expressed in cases with 8q gain. SMAD2 was the most down-regulated gene on 18q, and on 20q, STMN3 and TGIF2 were highly up-regulated. Immunohistochemistry for SMAD4 correlated with SMAD2 gene expression and 18q loss.

Conclusion

On basis of integrative analysis this study identified one well known CRC gene (SMAD2) and several other genes (EFNA1, BOP1, TGIF2 and STMN3) that possibly could be used for rectal cancer characterization.

Metastatic susceptibility locus, an 8p hot-spot for tumour progression disrupted in colorectal liver metastases: 13 candidate genes examined at the DNA, mRNA and protein level

Background

Mortality from colorectal cancer is mainly due to metastatic liver disease. Improved understanding of the molecular events underlying metastasis is crucial for the development of new methods for early detection and treatment of colorectal cancer. Loss of chromosome 8p is frequently seen in colorectal cancer and implicated in later stage disease and metastasis, although a single metastasis suppressor gene has yet to be identified. We therefore examined 8p for genes involved in colorectal cancer progression.

Methods

Loss of heterozygosity analyses were used to map genetic loss in colorectal liver metastases. Candidate genes in the region of loss were investigated in clinical samples from 44 patients, including 6 with matched colon normal, colon tumour and liver metastasis. We investigated gene disruption at the level of DNA, mRNA and protein using a combination of mutation, semi-quantitative real-time PCR, western blotting and immunohistochemical analyses.

Results

We mapped a 2 Mb region of 8p21-22 with loss of heterozygosity in 73% of samples; 8/11 liver metastasis samples had loss which was not present in the corresponding matched primary colon tumour. 13 candidate genes were identified for further analysis. Both up and down-regulation of 8p21-22 gene expression was associated with metastasis. ADAMDEC1 mRNA and protein expression decreased during both tumourigenesis and tumour progression. Increased STC1 and LOXL2 mRNA expression occurred during tumourigenesis. Liver metastases with low DcR1/TNFRSF10C mRNA expression were more likely to present with extrahepatic metastases (p = 0.005). A novel germline truncating mutation of DR5/TNFRSF10B was identified, and DR4/TNFRSF10A SNP rs4872077 was associated with the development of liver metastases (p = 0.02).

Conclusion

Our data confirm that genes on 8p21-22 are dysregulated during colorectal cancer progression. Interestingly, however, instead of harbouring a single candidate colorectal metastasis suppressor 8p21-22 appears to be a hot-spot for tumour progression, encoding at least 13 genes with a putative role in carcinoma development. Thus, we propose that this region of 8p comprises a metastatic susceptibility locus involved in tumour progression whose disruption increases metastatic potential.