An international database and integrated analysis tools for the study of cancer gene expression

Discovery of Exosomes From Tick Saliva and Salivary Glands Reveals Therapeutic Roles for CXCL12 and IL-8 in Wound Healing at the Tick-Human Skin Interface

Ticks secrete various anti-coagulatory, anti-vasoconstrictory, anti-inflammatory, and anti-platelet aggregation factors in their saliva at the bite site during feeding to evade host immunological surveillance and responses. For the first time, we report successful isolation of exosomes (small membrane-bound extracellular signaling vesicles) from saliva and salivary glands of partially fed or unfed ixodid ticks. Our data showed a novel role of these in vivo exosomes in the inhibition of wound healing via downregulation of C-X-C motif chemokine ligand 12 (CXCL12) and upregulation of interleukin-8 (IL-8). Cryo-electron microscopy (cryo-EM) analysis revealed that tick saliva and salivary glands are composed of heterogeneous populations of in vivo exosomes with sizes ranging from 30 to 200 nm. Enriched amounts of tick CD63 ortholog protein and heat shock protein 70 (HSP70) were evident in these exosomes. Treatment of human skin keratinocytes (HaCaT cells) with exosomes derived from tick saliva/salivary glands or ISE6 cells dramatically delayed cell migration, wound healing, and repair process. Wound healing is a highly dynamic process with several individualized processes including secretion of cytokines. Cytokine array profiling followed by immunoblotting and quantitative-PCR analysis revealed that HaCaT cells treated with exosomes derived from tick saliva/salivary glands or ISE6 cells showed enhanced IL-8 levels and reduced CXCL12 loads. Inhibition of IL-8 or CXCL12 further delayed exosome-mediated cell migration, wound healing, and repair process, suggesting a skin barrier protection role for these chemokines at the tick bite site. In contrast, exogenous treatment of CXCL12 protein completely restored this delay and enhanced the repair process. Taken together, our study provides novel insights on how tick salivary exosomes secreted in saliva can delay wound healing at the bite site to facilitate successful blood feeding.

In vitro and in silico validation of CA3 and FHL1 downregulation in oral cancer

Background

Aberrant methylation is a frequent event in oral cancer.

Methods

In order to better characterize these alterations, a search for genes downregulated by aberrant methylation in oral squamous cell carcinoma (OSCC) was conducted through the mining of ORESTES dataset. Findings were further validated in OSCC cell lines and patients’ samples and confirmed using TCGA data. Differentially expressed genes were identified in ORESTES libraries and validated in vitro using RT-PCR in HNSCC cell-lines and OSCC tumor samples. Further confirmation of these results was performed using mRNA expression and methylation data from The Cancer Genome Atlas (TCGA) data.

Results

From the set of genes selected for validation, CA3 and FHL1 were downregulated in 60% (12/20) and 75% (15/20) of OSCC samples, respectively, and in HNSCC cell lines. The treatment of cell lines JHU-13 and FaDu with the demethylating agent 5'-aza-dC was efficient in restoring CA3 and FHL1 expression. TCGA expression and methylation data on OSCC confirms the downregulation of these genes in OSCC samples and also suggests that expression of CA3 and FHL1 is probably regulated by methylation. The downregulation of CA3 and FHL1 observed in silico was validated in HNSCC cell lines and OSCC samples, showing the feasibility of integrating different datasets to select differentially expressed genes in silico.

Conclusions

These results showed that the downregulation of CA3 and FHL1 data observed in the ORESTES libraries was validated in HNSCC cell lines and OSCC samples and in a large cohort of samples from the TCGA database. Moreover, it suggests that expression of CA3 and FHL1 could probably be regulated by methylation having an important role the oral carcinogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4077-3) contains supplementary material, which is available to authorized users.

The use of EST expression matrixes for the quality control of gene expression data

EST expression profiling provides an attractive tool for studying differential gene expression, but cDNA libraries' origins and EST data quality are not always known or reported. Libraries may originate from pooled or mixed tissues; EST clustering, EST counts, library annotations and analysis algorithms may contain errors. Traditional data analysis methods, including research into tissue-specific gene expression, assume EST counts to be correct and libraries to be correctly annotated, which is not always the case. Therefore, a method capable of assessing the quality of expression data based on that data alone would be invaluable for assessing the quality of EST data and determining their suitability for mRNA expression analysis. Here we report an approach to the selection of a small generic subset of 244 UniGene clusters suitable for identification of the tissue of origin for EST libraries and quality control of the expression data using EST expression information alone. We created a small expression matrix of UniGene IDs using two rounds of selection followed by two rounds of optimisation. Our selection procedures differ from traditional approaches to finding "tissue-specific" genes and our matrix yields consistency high positive correlation values for libraries with confirmed tissues of origin and can be applied for tissue typing and quality control of libraries as small as just a few hundred total ESTs. Furthermore, we can pick up tissue correlations between related tissues e.g. brain and peripheral nervous tissue, heart and muscle tissues and identify tissue origins for a few libraries of uncharacterised tissue identity. It was possible to confirm tissue identity for some libraries which have been derived from cancer tissues or have been normalised. Tissue matching is affected strongly by cancer progression or library normalisation and our approach may potentially be applied for elucidating the stage of normalisation in normalised libraries or for cancer staging.

5'UTR variants of ribosomal protein S19 transcript determine translational efficiency: implications for Diamond-Blackfan anemia and tissue variability

Background

Diamond-Blackfan anemia (DBA) is a lineage specific and congenital erythroblastopenia. The disease is associated with mutations in genes encoding ribosomal proteins resulting in perturbed ribosomal subunit biosynthesis. The RPS19 gene is mutated in approximately 25% of DBA patients and a variety of coding mutations have been described, all presumably leading to haploinsufficiency. A subset of patients carries rare polymorphic sequence variants within the 5′untranslated region (5′UTR) of RPS19. The functional significance of these variants remains unclear.

Methodology/Principal Findings

We analyzed the distribution of transcriptional start sites (TSS) for RPS19 mRNAs in testis and K562 cells. Twenty-nine novel RPS19 transcripts were identified with different 5′UTR length. Quantification of expressed w.t. 5′UTR variants revealed that a short 5′UTR correlates with high levels of RPS19. The total levels of RPS19 transcripts showed a broad variation between tissues. We also expressed three polymorphic RPS19 5′UTR variants identified in DBA patients. The sequence variants include two insertions (c.-147_-146insGCCA and c.-147_-146insAGCC) and one deletion (c.-144_-141delTTTC). The three 5′UTR polymorphisms are associated with a 20–30% reduction in RPS19 protein levels when compared to the wild-type (w.t.) 5′UTR of corresponding length.

Conclusions

The RPS19 gene uses a broad range of TSS and a short 5′UTR is associated with increased levels of RPS19. Comparisons between tissues showed a broad variation in the total amount of RPS19 mRNA and in the distribution of TSS used. Furthermore, our results indicate that rare polymorphic 5′UTR variants reduce RPS19 protein levels with implications for Diamond-Blackfan anemia.

Integrating forward and reverse proteomics to unravel protein function

To date, proteomics approaches have aimed to either identify novel proteins or change in protein expression/modification in various organisms under normal or disease conditions. One major aspect of functional proteomics is to identify protein biological properties in a given context, however, forward proteomics approaches alone cannot complete this goal. Indeed, with the increasing successes of such proteomics-based research strategies and the subsequent increasing amounts of proteins identified with unknown molecular functions, approaches allowing for systematic analyses of protein functions are desired. In this review, we propose to depict the complementarities of forward and reverse proteomics approaches in the definite understanding of protein functions. This dual strategy requires a data integration loop which allows for systematic characterization of protein function(s). The details of the integrative process combining both in silico and experimental resources and tools are presented. Altogether, we believe that the integration of forward and reverse proteomics approaches supported by bioinformatics will provide an efficient path towards systems biology.

Detecting false expression signals in high-density oligonucleotide arrays by an in silico approach

High-density oligonucleotide arrays have become a popular assay for concurrent measurement of mRNA expression at the genome scale. Much effort has been devoted to the development of statistical analysis tools aimed at reducing experimental noise and normalizing experimental variation in gene expression analysis. However, these investigations do not detect or catalog systematic problems associated with specific oligonucleotide probes. Here, we present an investigation of problematic probes that yield consistent but inaccurate signals across multiple experiments. By evaluating data integrity among gene, probe sequence, and genomic structure we identified a total of 20,696 (10.5%) nonspecific probes that could cross-hybridize to multiple genes and a total of 18,363 (9.3%) probes that miss the target transcript sequences on the Affymetrix GeneChip U95A/Av2 array. The numbers of nonspecific and mistargeted probes on the U133A array are 29,405 (12.1%) and 19,717 (8.0%), respectively. The poor performance of the mistargeted probes was confirmed in two GeneChip experiments, in which these probes showed a 20-30% decrease in detecting present signals compared with normal probes. Comparison of qualitative expression signals obtained from SAGE and EST data with those from GeneChip arrays showed that the consistency of the two platforms is 30% lower in problematic probes than in normal probes. A Web application was developed to apply our results for improving the accuracy of expression analysis.

Cancer target discovery using SAGE

Cancer is a genetic disease. Genetic events including mutations, chromosomal gains, losses and rearrangements, along with epigenetic alterations, lead to significant transcriptional changes in cancer cells. Changes in the expression of many genes associated with the onset and progression of cancer likely contribute to the cancerous phenotype. SAGE (Serial Analysis of Gene Expression) is an expression profiling method that allows for global, unbiased and quantitative characterisation of transcriptomes. The expression of thousands of genes can be analysed simultaneously without prior knowledge of their sequence, thus leading to the discovery of novel transcripts. In addition to characterising normal and malignant gene expression patterns, SAGE can be used to identify downstream targets of tumour suppressors and oncogenes and further annotate genomes. Comprehensive analyses of expression profiles using SAGE will yield many new diagnostic and prognostic markers as well as therapeutic targets in cancer.

Gene expression arrays in cancer research: methods and applications

During the last 5 years, the number of papers describing data obtained by microarray technology increased exponentially with about 3000 papers in 2003. Undoubtedly, cancer is by far the disease that received most of the attention as far as the amount of data generated. As array technology is rather new and highly dependent on bioinformatics, mathematics and statistics, a clear understanding of the knowledge and information derived from array-based experiments is not widely appreciated. We shall review herein some of the issues related to the construction of DNA arrays, quantities and heterogeneity of probes and targets, the consequences of the physical characteristics of the probes, data extraction and data analysis as well as the applications of array technology. Our goal is to bring to the general audience, some of the basics of array technology and its possible application in oncology. By discussing some of the basic aspects of the methodology, we hope to stimulate criticism concerning the conclusions proposed by authors, especially in the light of the very low degree of reproducibility already proven when commercially available platforms were compared . Regardless of its pitfalls, it is unquestionable that array technology will have a great impact in the management of cancer and its applications will range from the discovery of new drug targets, new molecular tools for diagnosis and prognosis as well as for a tailored treatment that will take into account the molecular determinants of a given tumor. Hence, we shall also highlight some of the already available and promising applications of array technology on the day-to-day practice of oncology.

Common denominator procedure: a novel approach to gene-expression data mining for identification of phenotype-specific genes

MOTIVATION

We have established a novel data mining procedure for the identification of genes associated with pre-defined phenotypes and/or molecular pathways. Based on the observation that these genes are frequently expressed in the same place or in close proximity at about the same time, we have devised an approach termed Common Denominator Procedure. One unusual feature of this approach is that the specificity and probability to identify genes linked to the desired phenotype/pathway increase with greater diversity of the input data.

RESULT

To show the feasibility of our approach, the Cancer Genome Anatomy Project expression data combined with a defined set of angiogenic factors was used to identify additional and novel angiogenesis-associated genes. A multitude of these additional genes were known to be associated with angiogenesis according to published data, verifying our approach. For some of the remaining candidate genes, application of a high-throughput functional genomics platform (XantoScreen) provided further experimental evidence for association with angiogenesis.

Loss of annexin A1 expression in human breast cancer detected by multiple high-throughput analyses

To test the efficacy of combined high-throughput analyses (HTA) in target gene identification, screening criteria were set using >fivefold difference by microarray and statistically significant changes (p<0.01) in SAGE and EST. Microarray analysis of two normal and seven breast cancer samples found 129 genes with >fivefold changes. Further SAGE and EST analyses of these genes identified four qualified genes, ERBB2, GATA3, AGR2, and ANXA1. Their expression pattern was validated by RT-PCR in both breast cell lines and tissue samples. Loss of ANXA1 in breast cancer was further confirmed at mRNA level by Human Breast Cancer Tissue Profiling Array and at protein level by immunohistochemical staining. This study demonstrated that combined HTA effectively narrowed the number of genes for further study, while retaining the sensitivity in identifying biologically important genes such as ERBB2 and ANXA1. A distinctive loss of ANXA1 in breast cancer suggests its involvement in maintaining normal breast biology.

Molecular biomarkers in drug development

Arguably, the most immediately promising reverberation of the genomics era has been the application of biomarkers to drug development. The promise of applying biomarkers to early drug development is that they might aid in preclinical and early clinical decisions such as dose ranging, definition of treatment regimen, or even a preview of efficacy. Later in the clinic, biomarkers could be used to facilitate patient stratification, selection and the description of surrogate endpoints. Information derived from biomarkers should result in a better understanding of preclinical and clinical data, which ultimately benefits patients and drug developers. If the promise of biomarkers is realized, they will become a routine component of drug development and companions to newly discovered therapies.

Oncogenomics and the development of new cancer therapies

Scientists have sequenced the human genome and identified most of its genes. Now it is time to use these genomic data, and the high-throughput technology developed to generate them, to tackle major health problems such as cancer. To accelerate our understanding of this disease and to produce targeted therapies, further basic mutational and functional genomic information is required. A systematic and coordinated approach, with the results freely available, should speed up progress. This will best be accomplished through an international academic and pharmaceutical oncogenomics initiative.

The generation and utilization of a cancer-oriented representation of the human transcriptome by using expressed sequence tags

Whereas genome sequencing defines the genetic potential of an organism, transcript sequencing defines the utilization of this potential and links the genome with most areas of biology. To exploit the information within the human genome in the fight against cancer, we have deposited some two million expressed sequence tags (ESTs) from human tumors and their corresponding normal tissues in the public databases. The data currently define approximately 23,500 genes, of which only approximately 1,250 are still represented only by ESTs. Examination of the EST coverage of known cancer-related (CR) genes reveals that <1% do not have corresponding ESTs, indicating that the representation of genes associated with commonly studied tumors is high. The careful recording of the origin of all ESTs we have produced has enabled detailed definition of where the genes they represent are expressed in the human body. More than 100,000 ESTs are available for seven tissues, indicating a surprising variability of gene usage that has led to the discovery of a significant number of genes with restricted expression, and that may thus be therapeutically useful. The ESTs also reveal novel nonsynonymous germline variants (although the one-pass nature of the data necessitates careful validation) and many alternatively spliced transcripts. Although widely exploited by the scientific community, vindicating our totally open source policy, the EST data generated still provide extensive information that remains to be systematically explored, and that may further facilitate progress toward both the understanding and treatment of human cancers.

A palmitoylated RING finger ubiquitin ligase and its homologue in the brain membranes

Ubiquitin (Ub) ligation is implicated in active protein metabolism and subcellular trafficking and its impairment is involved in various neurologic diseases. In rat brain, we identified two novel Ub ligases, Momo and Sakura, carrying double zinc finger motif and RING finger domain. Momo expression is enriched in the brain gray matter and testis, and Sakura expression is more widely detected in the brain white matter as well as in many peripheral organs. Both proteins associate with the cell membranes of neuronal and/or glial cells. We examined their Ub ligase activity in vivo and in vitro using viral expression vectors carrying myc-tagged Momo and Sakura. Overexpression of either Momo or Sakura in mixed cortical cultures increased total polyubiquitination levels. In vitro ubiquitination assay revealed that the combination of Momo and UbcH4 and H5c, or of Sakura and UbcH4, H5c and H6 is required for the reaction. Deletion mutagenesis suggested that the E3 Ub ligase activity of Momo and Sakura depended on their C-terminal domains containing RING finger structure, while their N-terminal domains influenced their membrane association. In agreement, Sakura associating with the membrane was specifically palmitoylated. Although the molecular targets of their Ub ligation remain to be identified, these findings imply a novel function of the palmitoylated E3 Ub ligase(s).

Sequence-based cancer genomics: progress, lessons and opportunities

Technologies that provide a genome-wide view offer an unprecedented opportunity to scrutinize the molecular biology of the cancer cell. The information that is derived from these technologies is well suited to the development of public databases of alterations in the cancer genome and its expression. Here, we describe the synergistic efforts of research programmes in Brazil, the United Kingdom and the United States towards building integrated databases that are widely accessible to the research community, to enable basic and applied applications in cancer research.

Serial analysis of gene expression and cancer

Serial analysis of gene expression has been widely used to characterize gene expression patterns associated with tumor formation. These studies resulted in the identification of tumor-specific markers, transcriptional pathways, or therapeutic targets. In this review, recent applications and developments of serial analysis of gene expression and their impact on the diagnosis and treatment of cancer are discussed. A combination of serial analysis of gene expression and small-scale microarray analysis represents a strategy that should facilitate the identification and exploitation of tumor-specific gene expression for diagnostic or therapeutic purposes. In addition, cancer diagnosis and treatment may benefit from a complementation between serial analysis of gene expression and quantitative proteomics in the future.

Ribosomal protein S19 expression during erythroid differentiation

The gene encoding ribosomal protein S19 (RPS19) has been shown to be mutated in 25% of the patients affected by Diamond-Blackfan anemia (DBA), a congenital erythroblastopenia. As the role of RPS19 in erythropoiesis is still to be defined, we performed studies on RPS19 expression during terminal erythroid differentiation. Comparative analysis of the genomic sequences of human and mouse RPS19 genes enabled the identification of 4 conserved sequence elements in the 5' region. Characterization of transcriptional elements allowed the identification of the promoter in the human RPS19 gene and the localization of a strong regulatory element in the third conserved sequence element. By Northern blot and Western blot analyses of murine splenic erythroblasts infected with the anemia-inducing strain Friend virus (FAV cells), RPS19 mRNA and protein expression were shown to decrease during terminal erythroid differentiation. We anticipate that these findings will contribute to further development of our understanding of the contribution of RPS19 to erythropoiesis.