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

Integrated analysis of intestinal microbiota and host gene expression in colorectal cancer patients

Introduction. Colorectal cancer (CRC) is one of the most common cancers and poses heavy burden on global health. The relationship between mucosal microbiome composition and colorectal gene expression are rarely studied. In this study, we integrated transcriptome data with microbiome data to investigate the relationship between them in colorectal cancer patients.Gap statement. Previous studies have identified the contribution of gut microbiota and DEGs to the pathogenesis of CRC, but the relationship between mucosal microbiome composition and colorectal gene expression are rarely studied.Aim. In this study, we integrated transcriptome data with microbiome data to investigate the relationship between mucosal microbiome composition and colorectal gene expression.Methodology. First, three independent CRC gene expression profiles (GSE184093, GSE156355 and GSE146587) from Gene Expression Omnibus (GEO) were used to identify differentially expressed genes (DEGs). Second, another dataset (GSE163366) was used to analyse gut mucosal microbiome differential abundance. GO (Gene Ontology) function and KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway enrichment analyses of the DEGs were performed. Protein-protein interactions (PPIs) of the DEGs were constructed. The Spearman correlation analysis was computed between host DEGs and gut microbiome abundance data.Results. A total of 1036 upregulated DEGs and 1194 downregulated DEGs between noncancerous tissues and cancerous tissues were identified based on the analysis. One significant module with a score 37.65 was selected out via MCODE including 41 upregulated DEGs, which are were mostly enriched in two pathways, including microtubule binding and tubulin binding. In particular, significant negative correlations are prevalent between Fusobacterium and the 41 DEGs with the correlation ranging between -0.54 and -0.35, and there commonly exist significant positive correlations between Blautia and the 41 DEGs with the correlation ranging between 0.42 and 0.54, indicating that Fusobacterium and Blautia are two of the most important microbes interacting with the gene regulation.Conclusion. Our results demonstrate significant correlation between some gut microbes and DEGs, providing a comprehensive bioinformatics analysis of them for future investigation into the molecular mechanisms and biomarkers.

Exploration of the Effect on Genome-Wide DNA Methylation by miR-143 Knock-Out in Mice Liver

MiR-143 play an important role in hepatocellular carcinoma and liver fibrosis via inhibiting hepatoma cell proliferation. DNA methyltransferase 3 alpha (DNMT3a), as a target of miR-143, regulates the development of primary organic solid tumors through DNA methylation mechanisms. However, the effect of miR-143 on DNA methylation profiles in liver is unclear. In this study, we used Whole-Genome Bisulfite Sequencing (WGBS) to detect the differentially methylated regions (DMRs), and investigated DMR-related genes and their enriched pathways by miR-143. We found that methylated cytosines increased 0.19% in the miR-143 knock-out (KO) liver fed with high-fat diet (HFD), compared with the wild type (WT). Furthermore, compared with the WT group, the CG methylation patterns of the KO group showed lower CG methylation levels in CG islands (CGIs), promoters and hypermethylation in CGI shores, 5'UTRs, exons, introns, 3'UTRs, and repeat regions. A total of 984 DMRs were identified between the WT and KO groups consisting of 559 hypermethylation and 425 hypomethylation DMRs. Furthermore, DMR-related genes were enriched in metabolism pathways such as carbon metabolism (serine hydroxymethyltransferase 2 (Shmt2), acyl-Coenzyme A dehydrogenase medium chain (Acadm)), arginine and proline metabolism (spermine synthase (Sms), proline dehydrogenase (Prodh2)) and purine metabolism (phosphoribosyl pyrophosphate synthetase 2 (Prps2)). In summary, we are the first to report the change in whole-genome methylation levels by miR-143-null through WGBS in mice liver, and provide an experimental basis for clinical diagnosis and treatment in liver diseases, indicating that miR-143 may be a potential therapeutic target and biomarker for liver damage-associated diseases and hepatocellular carcinoma.

Identification of potential biomarkers with colorectal cancer based on bioinformatics analysis and machine learning

Colorectal cancer (CRC) is one of the most common malignancies worldwide. Biomarker discovery is critical to improve CRC diagnosis, however, machine learning offers a new platform to study the etiology of CRC for this purpose. Therefore, the current study aimed to perform an integrated bioinformatics and machine learning analyses to explore novel biomarkers for CRC prognosis. In this study, we acquired gene expression microarray data from Gene Expression Omnibus (GEO) database. The microarray expressions GSE103512 dataset was downloaded and integrated. Subsequently, differentially expressed genes (DEGs) were identified and functionally analyzed via Gene Ontology (GO) and Kyoto Enrichment of Genes and Genomes (KEGG). Furthermore, protein protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape software to identify hub genes; however, the hub genes were subjected to Support Vector Machine (SVM), Receiver operating characteristic curve (ROC) and survival analyses to explore their diagnostic values. Meanwhile, TCGA transcriptomics data in Gene Expression Profiling Interactive Analysis (GEPIA) database and the pathology data presented by in the human protein atlas (HPA) database were used to verify our transcriptomic analyses. A total of 105 DEGs were identified in this study. Functional enrichment analysis showed that these genes were significantly enriched in biological processes related to cancer progression. Thereafter, PPI network explored a total of 10 significant hub genes. The ROC curve was used to predict the potential application of biomarkers in CRC diagnosis, with an area under ROC curve (AUC) of these genes exceeding 0.92 suggesting that this risk classifier can discriminate between CRC patients and normal controls. Moreover, the prognostic values of these hub genes were confirmed by survival analyses using different CRC patient cohorts. Our results demonstrated that these 10 differentially expressed hub genes could be used as potential biomarkers for CRC diagnosis.

Identification of four novel prognosis biomarkers and potential therapeutic drugs for human colorectal cancer by bioinformatics analysis

Colorectal cancer (CRC) is one of the most deadly cancers in the world with few reliable biomarkers that have been selected into clinical guidelines for prognosis of CRC patients. In this study, mRNA microarray datasets GSE113513, GSE21510, GSE44076, and GSE32323 were obtained from the Gene Expression Omnibus (GEO) and analyzed with bioinformatics to identify hub genes in CRC development. Differentially expressed genes (DEGs) were analyzed using the GEO2R tool. Gene ontology (GO) and KEGG analyses were performed through the DAVID database. STRING database and Cytoscape software were used to construct a protein-protein interaction (PPI) network and identify key modules and hub genes. Survival analyses of the DEGs were performed on GEPIA database. The Connectivity Map database was used to screen potential drugs. A total of 865 DEGs were identified, including 374 upregulated and 491 downregulated genes. These DEGs were mainly associated with metabolic pathways, pathways in cancer, cell cycle and so on. The PPI network was identified with 863 nodes and 5817 edges. Survival analysis revealed that HMMR, PAICS, ETFDH, and SCG2 were significantly associated with overall survival of CRC patients. And blebbistatin and sulconazole were identified as candidate drugs. In conclusion, our study found four hub genes involved in CRC, which may provide novel potential biomarkers for CRC prognosis, and two potential candidate drugs for CRC.

Identification of key genes and expression profiles in osteoarthritis by co-expressed network analysis

BACKGROUND

The underlying molecular characteristics of osteoarthritis (OA), a common age-related joint disease, remains elusive. Here, we aimed to identify potential early diagnostic biomarkers and elucidate underlying mechanisms of OA using weighted gene co-expression network analysis (WGCNA).

MATERIAL AND METHODS

We obtained the gene expression profile dataset GSE55235, GSE55457, and GSE55584, from the Gene Expression Omnibus. WGCNA was used to investigate the changes in co-expressed genes between normal and OA synovial membrane samples. Modules that were highly correlated to OA were subjected to functional enrichment analysis using the R clusterProfiler package. Differentially expressed genes (DEGs) between the two samples were screened using the "limma" package in R. A Venn diagram was constructed to intersect the genes in significant modules and DEGs. RT -PCR was used to further verify the hub gene expression levels between normal and OA samples.

RESULTS

The preserved significant module was found to be highly associated with OA development and progression (P < 1e-200, correlation = 0.92). Functional enrichment analysis suggested that the antiquewhite4 module was highly correlated to FoxO signaling pathway, and the metabolism of fatty acids and 2-oxocarboxylic acid. A total of 13 hub genes were identified based on significant module network topology and DEG analysis, and RT-PCR confirmed that these genes were significantly increased in OA samples compared with that in normal samples.

CONCLUSIONS

We identified 13 hub genes correlated to the development and progression of OA, which may provide new biomarkers and drug targets for OA.

Expression pattern of placenta specific 8 and keratin 20 in different types of gastrointestinal cancer

The aim of the present study was to investigate the expression of keratin 20 (KRT20) and placenta specific 8 (PLAC8) in gastrointestinal (GI) cancer with various differentiation phenotypes. The present study retrospectively investigated archived formalin-fixed paraffin-embedded tissue samples from 12 patients at different stages of GI cancer [four with gastric cancer, four with pancreatic cancer and four with colorectal cancer (CRC)]. The stages were pre-determined, according to differentiation phenotypes, by a pathologist of the Department of Pathology at Sijhih Cathay General Hospital. KRT20 and PLAC8 expression levels were assessed using immunohistochemistry. The CRC cell lines SW620 and Caco-2 were used to assess interactions between KRT20 and PLAC8 via reverse transcription-quantitative PCR. PLAC8 and KRT20 expression was observed consistently only in the well-differentiated CRC tissue samples. Low KRT20 expression levels were observed in the PLAC8 knockdown SW620 cells. In addition, there was a positive association between PLAC8 and KRT20 expression in the differentiated Caco-2 cells. According to the results of the present study, the differentiation status of GI cancer influenced KRT20 expression, particularly in CRC, which may explain why patients with well-differentiated CRC display better clinical outcomes. Therefore, the prognostic significance of KRT20 and PLAC8 may be particularly crucial for patients with CRC displaying a well-differentiated phenotype.

Identification of key genes for predicting colorectal cancer prognosis by integrated bioinformatics analysis

Colorectal cancer (CRC) is a life-threatening disease with a poor prognosis. Therefore, it is crucial to identify molecular prognostic biomarkers for CRC. The present study aimed to identify potential key genes that could be used to predict the prognosis of patients with CRC. Three CRC microarray datasets (GSE20916, GSE73360 and GSE44861) were downloaded from the Gene Expression Omnibus (GEO) database, and one dataset was obtained from The Cancer Genome Atlas (TCGA) database. The three GEO datasets were analyzed to detect differentially expressed genes (DEGs) using the BRB-ArrayTools software. Functional and pathway enrichment analyses of these DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery tool. A protein-protein interaction (PPI) network of DEGs was constructed, hub genes were extracted, and modules of the PPI network were analyzed. To investigate the prognostic values of the hub genes in CRC, data from the CRC datasets of TCGA were used to perform the survival analyses based on the sample splitting method and Cox regression model. Correlation among the hub genes was evaluated using Spearman's correlation analysis. In the three GEO datasets, a total of 105 common DEGs were identified, including 51 down- and 54 up-regulated genes in CRC compared with normal colorectal tissues. A PPI network consisting of 100 DEGs and 551 edges was constructed, and 44 nodes were identified as hub genes. Among these 44 genes, the four hub genes TIMP metallopeptidase inhibitor 1 (TIMP1), solute carrier family 4 member 4 (SLC4A4), aldo-keto reductase family 1 member B10 (AKR1B10) and ATP binding cassette subfamily E member 1 (ABCE1) were associated with overall survival (OS) in patients with CRC. Three significant modules were extracted from the PPI network. The hub gene TIMP1 was present in Module 1, ABCE1 was involved in Module 2 and SLC4A4 was identified in Module 3. Univariate analysis revealed that TIMP1, SLC4A4, AKR1B10 and ABCE1 were associated with the OS of patients with CRC. Multivariate analysis demonstrated that SLC4A4 may be an independent prognostic factor associated with OS. Furthermore, the results from correlation analysis revealed that there was no correlation between TIMP1, SLC4A4 and ABCE1, whereas AKR1B10 was positively correlated with SLC4A4. In conclusion, the four key genes TIMP1, SLC4A4, AKR1B10 and ABCE1 associated with the OS of patients with CRC were identified by integrated bioinformatics analysis. These key genes may be used as prognostic biomarkers to predict the survival of patients with CRC, and may therefore represent novel therapeutic targets for CRC.

Identification of key pathways and genes in nasopharyngeal carcinoma using bioinformatics analysis

Nasopharyngeal carcinoma (NPC) is one of the most common malignancies in the head and neck. The aim of the current study was to identify the key pathways and genes involved in NPC through bioinformatics analysis and to identify potential molecular mechanisms underlying NPC proliferation and progression. Three gene expression profiles (GSE12452, GSE34573 and GSE64634) were downloaded from the Gene Expression Omnibus database. A total of 76 samples were analyzed, of which 59 were NPC samples and 17 were normal samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently conducted. The protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed using Cytoscape software. Analysis of GSE12452, GSE34573 and GSE64634 datasets identified 1,301 (553 upregulated and 748 downregulated), 1,232 (348 upregulated and 884 downregulated) and 1,218 (555 upregulated and 663 downregulated) DEGs, respectively. Using Venn diagram analysis, 268 DEGs (59 upregulated and 209 downregulated) that intersected all three datasets, were selected for further analysis. The results of GO analysis revealed that upregulated DEGs were significantly enriched in biological processes, including 'cell adhesion', 'cell division', 'mitosis' and 'mitotic cell cycle'. The downregulated DEGs were mainly enriched in 'microtubule-based movement', 'cilium movement', 'cilium axoneme assembly' and 'epithelial cell differentiation'. The KEGG pathway analysis results revealed that the upregulated DEGs were highly associated with several pathways, including 'extracellular matrix-receptor interaction', 'human papillomavirus infection', 'arrhythmogenic right ventricular cardiomyopathy' and 'focal adhesion', whereas the downregulated DEGs were enriched in 'metabolic pathways', 'Huntington's disease', 'fluid shear stress and atherosclerosis' and 'chemical carcinogenesis'. On the basis of the PPI network of the DEGs, the following top 10 hub genes were identified: Dynein axonemal light intermediate chain 1, dynein axonemal intermediate chain 2, calmodulin 1, coiled-coil domain containing 114, dynein axonemal heavy chain 5, radial spoke head 9 homolog, radial spoke head component 4A, NDC80 kinetochore complex component, thymidylate synthetase and coiled-coil domain containing 39. In conclusion, by performing a comprehensive bioinformatics analysis of DEGs, putative targets that could be used to elucidate the molecular mechanisms underlying NPC were identified.

Combined analysis and validation for DNA methylation and gene expression profiles associated with prostate cancer

BACKGROUND

Prostate cancer (PCa) is a malignancy cause of cancer deaths and frequently diagnosed in male. This study aimed to identify tumor suppressor genes, hub genes and their pathways by combined bioinformatics analysis.

METHODS

A combined analysis method was used for two types of microarray datasets (DNA methylation and gene expression profiles) from the Gene Expression Omnibus (GEO). Differentially methylated genes (DMGs) were identified by the R package minfi and differentially expressed genes (DEGs) were screened out via the R package limma. A total of 4451 DMGs and 1509 DEGs, identified with nine overlaps between DMGs, DEGs and tumor suppressor genes, were screened for candidate tumor suppressor genes. All these nine candidate tumor suppressor genes were validated by TCGA (The Cancer Genome Atlas) database and Oncomine database. And then, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed by DAVID (Database for Annotation, Visualization and Integrated Discovery) database. Protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape. At last, Kaplan-Meier analysis was performed to validate these genes.

RESULTS

The candidate tumor suppressor genes were IKZF1, PPM1A, FBP1, SMCHD1, ALPL, CASP5, PYHIN1, DAPK1 and CASP8. By validation in TCGA database, PPM1A, DAPK1, FBP1, PYHIN1, ALPL and SMCHD1 were significant. The hub genes were FGFR1, FGF13 and CCND1. These hub genes were identified from the PPI network, and sub-networks revealed by these genes were involved in significant pathways.

CONCLUSION

In summary, the study indicated that the combined analysis for identifying target genes with PCa by bioinformatics tools promote our understanding of the molecular mechanisms and underlying the development of PCa. And the hub genes might serve as molecular targets and diagnostic biomarkers for precise diagnosis and treatment of PCa.

Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis

Background

Gastric cancer (GC) is a prevalent malignant cancer of digestive system. To identify key genes in GC, mRNA microarray GSE27342, GSE29272, and GSE33335 were downloaded from GEO database.

Methods

Differentially expressed genes (DEGs) were obtained using GEO2R. DAVID database was used to analyze function and pathways enrichment of DEGs. Protein-protein interaction (PPI) network was established by STRING and visualized by Cytoscape software. Then, the influence of hub genes on overall survival (OS) was performed by the Kaplan-Meier plotter online tool. Module analysis of the PPI network was performed using MCODE. Additionally, potential stem loop miRNAs of hub genes were predicted by miRecords and screened by TCGA dataset. Transcription factors (TFs) of hub genes were detected by NetworkAnalyst.

Results

In total, 67 DEGs were identified; upregulated DEGs were mainly enriched in biological process (BP) related to angiogenesis and extracellular matrix organization and the downregulated DEGs were mainly enriched in BP related to ion transport and response to bacterium. KEGG pathways analysis showed that the upregulated DEGs were enriched in ECM-receptor interaction and the downregulated DEGs were enriched in gastric acid secretion. A PPI network of DEGs was constructed, consisting of 43 nodes and 87 edges. Twelve genes were considered as hub genes owing to high degrees in the network. Hsa-miR-29c, hsa-miR-30c, hsa-miR-335, hsa-miR-33b, and hsa-miR-101 might play a crucial role in hub genes regulation. In addition, the transcription factors-hub genes pairs were displayed with 182 edges and 102 nodes. The high expression of 7 out of 12 hub genes was associated with worse OS, including COL4A1, VCAN, THBS2, TIMP1, COL1A2, SERPINH1, and COL6A3.

Conclusions

The miRNA and TFs regulation network of hub genes in GC may promote understanding of the molecular mechanisms underlying the development of gastric cancer and provide potential targets for GC diagnosis and treatment.

Electronic supplementary material

The online version of this article (10.1186/s12957-018-1409-3) contains supplementary material, which is available to authorized users.

Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis

Rheumatoid arthritis (RA) and osteoarthritis (OA) comprise the most common forms of arthritis. The aim of this study was to identify differentially expressed genes (DEGs) and associated biological processes between RA and OA using a bioinformatics approach to elucidate their potential pathogenesis.The gene expression profiles of the GSE55457 datasets, originally produced through use of the high-throughput Affymetrix Human Genome U133A Array, were downloaded from the Gene Expression Omnibus (GEO) database. The GSE55457 dataset contains information from 33 samples, including 10 normal control (NC) samples, 13 RA samples, and 10 OA samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed to identify functional categories and associated molecular and biochemical pathways, respectively, for the identified DEGs, and a protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape software.GO and KEGG results suggested that several biological pathways (ie, "immune response," "inflammation," and "osteoclast differentiation") are commonly involved in the development of both RA and OA, whereas several other pathways (eg, "MAPK signaling pathway," and "ECM-receptor interaction") presented significant differences between these disorders.This study provides further insights into the underlying pathogenesis of RA and OA, which may facilitate the diagnosis and treatment of these diseases.

Identification of key pathways and genes in colorectal cancer using bioinformatics analysis

Colorectal cancer (CRC) is the most common malignant tumor of digestive system. The aim of this study was to identify gene signatures during CRC and uncover their potential mechanisms. The gene expression profiles of GSE21815 were downloaded from GEO database. The GSE21815 dataset contained 141 samples, including 132 CRC and 9 normal colon epitheliums. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed by Cytoscape software. In total, 3500 DEGs were identified in CRC, including 1370 up-regulated genes and 2130 down-regulated genes. GO analysis results showed that up-regulated DEGs were significantly enriched in biological processes (BP), including cell cycle, cell division, and cell proliferation; the down-regulated DEGs were significantly enriched in biological processes, including immune response, intracellular signaling cascade and defense response. KEGG pathway analysis showed the up-regulated DEGs were enriched in cell cycle and DNA replication, while the down-regulated DEGs were enriched in drug metabolism, metabolism of xenobiotics by cytochrome P450, and retinol metabolism pathways. The top 10 hub genes, GNG2, AGT, SAA1, ADCY5, LPAR1, NMU, IL8, CXCL12, GNAI1, and CCR2 were identified from the PPI network, and sub-networks revealed these genes were involved in significant pathways, including G protein-coupled receptors signaling pathway, gastrin-CREB signaling pathway via PKC and MAPK, and extracellular matrix organization. In conclusion, the present study indicated that the identified DEGs and hub genes promote our understanding of the molecular mechanisms underlying the development of CRC, and might be used as molecular targets and diagnostic biomarkers for the treatment of CRC.

Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements

Background

Gene expression profiling is an important approach for detecting diagnostic and prognostic biomarkers, and predicting drug safety. The development of a wide range of technologies and platforms for measuring mRNA expression makes the evaluation and standardization of transcriptomic data problematic due to differences in protocols, data processing and analysis methods. Thus, universal RNA standards, such as those developed by the External RNA Controls Consortium (ERCC), are proposed to aid validation of research findings from diverse platforms such as microarrays and RT-qPCR, and play a role in quality control (QC) processes as transcriptomic profiling becomes more commonplace in the clinical setting.

Results

Panels of ERCC RNA standards were constructed in order to test the utility of these reference materials (RMs) for performance characterization of two selected gene expression platforms, and for discrimination of biomarker profiles between groups. The linear range, limits of detection and reproducibility of microarray and RT-qPCR measurements were evaluated using panels of RNA standards. Transcripts of low abundance (≤ 10 copies/ng total RNA) showed more than double the technical variability compared to higher copy number transcripts on both platforms. Microarray profiling of two simulated 'normal' and 'disease' panels, each consisting of eight different RNA standards, yielded robust discrimination between the panels and between standards with varying fold change ratios, showing no systematic effects due to different labelling and hybridization runs. Also, comparison of microarray and RT-qPCR data for fold changes showed agreement for the two platforms.

Conclusions

ERCC RNA standards provide a generic means of evaluating different aspects of platform performance, and can provide information on the technical variation associated with quantification of biomarkers expressed at different levels of physiological abundance. Distinct panels of standards serve as an ideal quality control tool kit for determining the accuracy of fold change cut-off threshold and the impact of experimentally-derived noise on the discrimination of normal and disease profiles.

Integration of genetic signature and TNM staging system for predicting the relapse of locally advanced colorectal cancer

PURPOSE

To identify potential genetic markers in treated stage II-III colorectal cancer patients and predict 3-year tumor relapse using statistical models based on important clinical factors and significant genetic markers.

METHODS

Gene expression profiling by cDNA-mediated Annealing, Selection, extension and Ligation assay was performed in a prospectively collected 95 stage II-III colorectal cancer patients with Fluorouracil-based adjuvant chemotherapy. We studied the gene expression level of 502 genes for patients with different outcomes. The prognostic effect of genetic signature was evaluated in multivariate analysis. We further integrated the genetic signature to clinical Classification of Malignant Tumors (TNM) staging system for predicting of 3-year tumor relapse.

RESULTS

An 8-gene signature was identified to well discriminate patients with different treatment outcomes. An integrated risk factor, which including 8-gene signature and TNM staging has been developed. ROC curve revealed that our integrated risk factor was better than genetic signature or current sixth edition TNM staging system alone.

CONCLUSIONS

Our 8-gene signature was promising in predicting 3-year disease-free survival rate for locally advanced colorectal cancer. The integrated risk factor, which combining genetic signature with clinical TNM staging system may further improve the outcome prediction.

Transcriptional changes in Schistosoma mansoni during early schistosomula development and in the presence of erythrocytes

Background

Schistosomes cause more mortality and morbidity than any other human helminth, but control primarily relies on a single drug that kills adult worms. The newly transformed schistosomulum stage is susceptible to the immune response and is a target for vaccine development and rational drug design.

Methodology/Principal Findings

To identify genes which are up-regulated during the maturation of Schistosoma mansoni schistosomula in vitro, we cultured newly transformed parasites for 3 h or 5 days with and without erythrocytes and compared their transcriptional profiles using cDNA microarrays. The most apparent changes were in the up-regulation of genes between 3 h and 5 day schistosomula involved in blood feeding, tegument and cytoskeletal development, cell adhesion, and stress responses. The most highly up-regulated genes included a tegument tetraspanin Sm-tsp-3 (1,600-fold up-regulation), a protein kinase, a novel serine protease and serine protease inhibitor, and intestinal proteases belonging to distinct mechanistic classes. The inclusion of erythrocytes in the culture medium resulted in a general but less pronounced increase in transcriptional activity, with the highest up-regulation of genes involved in iron metabolism, proteolysis, and transport of fatty acids and sugars.

Conclusions

We have identified the genes that are up-regulated during the first 5 days of schistosomula development in vitro. Using a combination of gene silencing techniques and murine protection studies, some of these highly up-regulated transcripts can be targeted for future development of new vaccines and drugs.

Schistosome blood flukes cause more mortality and morbidity than any other human worm infection, but current control methods primarily rely on a single drug. There is a desperate need for new approaches to control this parasite, including vaccines. People become infected when the free-swimming larva, the cercaria, enters through the skin and becomes the schistosomulum. Schistosomula are susceptible to immune responses during their first few days in the host before they become adult parasites. We characterised the genes that these newly transformed parasites switch on when they enter the host to identify molecules that are critical for survival in the human host. Some of these highly up-regulated genes can be targeted for future development of new vaccines and drugs.

Ligand-based vascular targeting of disease

This review illustrates the basic principles of ligand-based vascular targeting and presents some of the most advanced results obtained in this field, not only in terms of biopharmaceuticals, which are currently being investigated in clinical and preclinical studies, but also in terms of enabling technologies that facilitate target and ligand discovery. Whereas most of the vascular targeting research activities have so far concentrated on tumoral angiogenesis, the development of non-oncological applications has recently gained momentum and is likely to become an important area of modern pharmaceutical research.

Chromosomal breakpoints in primary colon cancer cluster at sites of structural variants in the genome

Genomic aberrations on chromosome 8 are common in colon cancer, and are associated with lymph node and distant metastases as well as with disease susceptibility. This prompted us to generate a high-resolution map of genomic imbalances of chromosome 8 in 51 primary colon carcinomas using a custom-designed genomic array consisting of a tiling path of BAC clones. This analysis confirmed the dominant role of this chromosome. Unexpectedly, the position of the breakpoints suggested colocalization with structural variants in the human genome. In order to map these sites with increased resolution and to extend the analysis to the entire genome, we analyzed a subset of these tumors (n = 32) by comparative genomic hybridization on a 185K oligonucleotide array platform. Our comprehensive map of the colon cancer genome confirmed recurrent and specific low-level copy number changes of chromosomes 7, 8, 13, 18, and 20, and unveiled additional, novel sites of genomic imbalances including amplification of a histone gene cluster on chromosome 6p21.1-21.33 and deletions on chromosome 4q34-35. The systematic comparison of segments of copy number change with gene expression profiles showed that genomic imbalances directly affect average expression levels. Strikingly, we observed a significant association of chromosomal breakpoints with structural variants in the human genome: 41% of all copy number changes occurred at sites of such copy number variants (P < 2.2e(-16)). Such an association has not been previously described and reveals a yet underappreciated plasticity of the colon cancer genome; it also points to potential mechanisms for the induction of chromosomal breakage in cancer cells.

Preoperative interleukin-6 production by mononuclear blood cells predicts survival after radical surgery for colorectal carcinoma

BACKGROUND

Colorectal cancer is one of the most common forms of cancer in the Western world. Staging based on histopathology is currently the most accurate predictor of outcome after surgery. Colorectal cancer is curable if treated at an early stage (stage I-III). However, for tumors in stages II and III there is a great need for tests giving more accurate prognostic information defining the patient population in need of closer follow-up and/or adjuvant therapy. Furthermore, tests that provide prognostic information preoperatively could provide a guide both for preoperative oncologic treatment and the surgical procedure.

METHODS

Peripheral blood mononuclear cells (PBMCs) were isolated preoperatively, within a week before primary surgery, from 39 patients undergoing surgery for colorectal cancer. The PBMCs were cultured in vitro for 24 hours in the presence of autologous serum and lipopolysaccharide (LPS). Interleukin-6 (IL-6) production was measured with enzyme-linked immunosorbent assay (ELISA). Staging based on histopathology was performed in all patients. Patients were followed for at least 54 months.

RESULTS

A production of >5000 pg/mL of IL-6 identified colorectal cancer patients with a poor prognosis. Eight out of 13 patients with >5000 pg/mL IL-6 died from cancer within the follow-up period, whereas no cancer-related deaths were recorded among 21 patients with 5000 pg/mL IL-6 or less. A multivariate Cox regression analysis, stratified for T- and N-stage, identified IL-6 production as an independent prognostic factor.

CONCLUSIONS

IL-6 production in vitro by PBMC can predict survival after radical surgery for colorectal cancer.

Multiplexing molecular diagnostics and immunoassays using emerging microarray technologies

Enzyme-linked immunosorbent assays (ELISA) are frequently used for quantitative measurement of the presence of protein, for single-analyte testing, in a sample. The application of ELISA in a microarray format has the potential to simultaneously measure the presence and/or concentrations of numerous proteins, in multiplex testing, all contained in a small drop of test fluid. Microspot microarray technology, in combination with protein biomarkers and nucleic acid diagnostics, appears to be the future high-performance analytical platform of choice. Validation of a large number of disease markers in both molecular and protein diagnostics has paved the way for the emergence of the multiplex assay. Initially, simple low-throughput multiplex assays were tested using the immunoassay format. These were followed by low-level multiplexing and high-throughput array-based immunoassays. More recently, two types of high-level multiplexing and high-throughput diagnostic methods using microspot arrays and bead arrays have been successfully developed to complement single-analyte assays. The value in rapid diagnostic evaluation for high-throughput multiplex, diagnostic test systems based on sound assay design must take into account data screening, normalization and statistical evaluation of possible concentration measurement, data errors and automated operation. Benefits of using multiplex array platforms include improved-quality patient care, as well as cost effectiveness and time saving. These multiplex methods also set the stage for future protein/nucleic acid codetection. Currently, the one analyte at a time test scheme is still dominant; nonetheless, the multiplex microspot microarray tests evaluated in a single multiassay analyzer are expected to become a significant part of clinical diagnostic testing within the next 5-10 years. This review is focused on microspot array and bead array methods for providing high throughput and a high degree of multiplexing in diagnostic testing.

Tissue factor and vascular endothelial growth factor expression in colorectal cancer: relation with cancer recurrence

OBJECTIVE

This study was undertaken to quantify tissue factor (TF) and vascular endothelial growth factor (VEGF) in colorectal cancer and to evaluate their possible relationship with recurrence.

METHOD

TF and VEGF were measured by enzyme-linked immunosorbent assay in surgical tumour specimens and normal mucosa from 50 consecutive patients with colorectal cancer who were followed up for 3 years for the assessment of disease recurrence.

RESULTS

TF and VEGF antigens were detected in all tumour samples. VEGF, but not TF, was much higher in tumour than in normal mucosa (P < 0.0001), as also confirmed by measurement of specific mRNAs. There was a strong correlation between TF and VEGF antigens (P < 0.0005) in tumour tissue but not in normal mucosa. Neither protein was related to tumour stage, grade or size. Local or distant recurrence was statistically related to pTNM stage. High VEGF, but not TF, levels in tumour extracts were associated with an increased risk of recurrence both by univariate (RR, 4.00, 95% CI: 1.45-11.0) and multivariate analyses (RR, 3.65, 95% CI: 1.33-10.0).

CONCLUSION

These findings suggest that VEGF content in colorectal cancer is an independent risk factor for tumour recurrence and might help select patients who might benefit from adjuvant therapy.

Correlation of K-ras codon 12 mutations in human feces and ages of patients with colorectal cancer (CRC)

Colorectal cancer (CRC) is the predominant gastrointestinal malignancy and constitutes a major medical and economic burden worldwide. A thorough understanding of the oncogenes or genes related to tumorigenesis is the key to developing successful therapeutic strategies. Molecular analysis of feces constitutes a potentially potent and noninvasive method for detection of CRC. Using nested reverse transcription-polymerase chain reaction (RT-PCR) and amplified restriction fragment length polymorphism analysis, sloughed cells from the entire length of the colon and rectum were analyzed for expression of activating K-ras codon 12 mutants, which are becoming attractive targets for antisense treatment. K-ras codon 12 mutant sequences were detected in feces of 5% (1/20) of healthy controls, in feces of 41% (12/29) of CRC patients, in 10% (3/29) of isolates of tissue complementary DNA (cDNA), and in 14% (4/29) of isolates of genomic DNA. Age of patient was significantly associated with K-ras codon 12 sequences in feces: Patients with wild-type K-ras codon 12 sequences were significantly younger than those with mutated forms of K-ras codon 12. Fecal ribonucleic acid (RNA) analysis was demonstrated to be a useful for diagnosis of CRC. This technique may be suitable for screening and determining the clinical significance of active mutations of the K-ras gene in feces and would possibly be useful for identifying patients that would benefit from antisense therapy.

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

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

Identification of mRNA Markers for Molecular Staging of Lymph Nodes in Colorectal Cancer

Background: One evolving approach to improved prognostication of cancer patients is the identification of previously occult disease by use of quantitative reverse transcription-PCR. Surprisingly, no systematic analysis of potential mRNA markers for colorectal cancer has been reported. We therefore performed an extensive mRNA marker survey for colorectal cancers.

Methods: We identified potential markers through literature and database searches. We analyzed all markers by quantitative reverse transcription-PCR on a limited set of primary tumors and benign lymph nodes. Selected markers were further evaluated on a larger tissue set with positive lymph nodes.

Results: We evaluated 43 markers and undertook further analysis of 6 in the secondary screening. Five gene markers—CDX1, carcinoembryonic antigen (CEA), CK20, TACSTD1, and Villin1 (VIL1)—provided perfect classification of lymph node status.

Conclusions: Several mRNA markers are capable of providing exceptionally accurate characterization of lymph node status in colorectal cancer. An automated, multimarker, quantitative reverse transcription-PCR assay for characterization of lymph nodes from colorectal cancer patients may be useful for improved staging and therapeutic decision making in colorectal cancer.

Real-time reverse transcription PCR (qRT-PCR) and its potential use in clinical diagnosis

qRT-PCR (real-time reverse transcription-PCR) has become the benchmark for the detection and quantification of RNA targets and is being utilized increasingly in novel clinical diagnostic assays. Quantitative results obtained by this technology are not only more informative than qualitative data, but simplify assay standardization and quality management. qRT-PCR assays are most established for the detection of viral load and therapy monitoring, and the development of SARS (severe acute respiratory syndrome)-associated coronavirus qRT-PCR assays provide a textbook example of the value of this technology for clinical diagnostics. The widespread use of qRT-PCR assays for diagnosis and the detection of disease-specific prognostic markers in leukaemia patients provide further examples of their usefulness. Their value for the detection of disease-associated mRNA expressed by circulating tumour cells in patients with solid malignancies is far less apparent, and the clinical significance of results obtained from such tests remains unclear. This is because of conceptual reservations as well as technical limitations that can interfere with the diagnostic specificity of qRT-PCR assays. Therefore, although it is evident that qRT-PCR assay has become a useful and important technology in the clinical diagnostic laboratory, it must be used appropriately and it is essential to be aware of its limitations if it is to fulfil its potential.

Targeted therapy for colorectal cancer: mapping the way

In spite of the significant advances in conventional therapeutic approaches to colorectal cancer (CRC), most patients ultimately die of their disease. Dissecting the molecular mechanisms underlying CRC progression will not only accelerate the development of novel cancer-selective drugs but will also enable the therapeutic regimen to be personalized according to the molecular features of individual patients and tumors. Here, we report on the novel insights into CRC biology that are paving the way to the development of molecular therapies and summarize the results from recent clinical trials demonstrating that agents targeting tumor-specific molecular derangements can significantly improve the therapeutic efficacy of conventional chemotherapy. Only a broader clinical implementation of these concepts will provide patients with CRC the best chance of a cure.