Quantitating tissue specificity of human genes to facilitate biomarker discovery

Integrated co-expression network analysis uncovers novel tissue-specific genes in major depressive disorder and bipolar disorder

Tissue-specific gene expression has been found to be associated with multiple complex diseases including cancer, metabolic disease, aging, etc. However, few studies of brain-tissue-specific gene expression patterns have been reported, especially in psychiatric disorders. In this study, we performed joint analysis on large-scale transcriptome multi-tissue data to investigate tissue-specific expression patterns in major depressive disorder (MDD) and bipolar disorder (BP). We established the strategies of identifying tissues-specific modules, annotated pathways for elucidating biological functions of tissues, and tissue-specific genes based on weighted gene co-expression network analysis (WGCNA) and robust rank aggregation (RRA) with transcriptional profiling data from different human tissues and genome wide association study (GWAS) data, which have been expanded into overlapping tissue-specific modules and genes sharing with MDD and BP. Nine tissue-specific modules were identified and distributed across the four tissues in the MDD and six modules in the BP. In general, the annotated biological functions of differentially expressed genes (DEGs) in blood were mainly involved in MDD and BP progression through immune response, while those in the brain were in neuron and neuroendocrine response. Tissue-specific genes of the prefrontal cortex (PFC) in MDD-, such as IGFBP2 and HTR1A, were involved in disease-related functions, such as response to glucocorticoid, taste transduction, and tissue-specific genes of PFC in BP-, such as CHRM5 and LTB4R2, were involved in neuroactive ligand-receptor interaction. We also found PFC tissue-specific genes including SST and CRHBP were shared in MDD-BP, SST was enriched in neuroactive ligand-receptor interaction, and CRHBP shown was related to the regulation of hormone secretion and hormone transport.

BrainBase: a curated knowledgebase for brain diseases

Brain is the central organ of the nervous system and any brain disease can seriously affect human health. Here we present BrainBase (https://ngdc.cncb.ac.cn/brainbase), a curated knowledgebase for brain diseases that aims to provide a whole picture of brain diseases and associated genes. Specifically, based on manual curation of 2768 published articles along with information retrieval from several public databases, BrainBase features comprehensive collection of 7175 disease–gene associations spanning a total of 123 brain diseases and linking with 5662 genes, 16 591 drug–target interactions covering 2118 drugs/chemicals and 623 genes, and five types of specific genes in light of expression specificity in brain tissue/regions/cerebrospinal fluid/cells. In addition, considering the severity of glioma among brain tumors, the current version of BrainBase incorporates 21 multi-omics datasets, presents molecular profiles across various samples/conditions and identifies four groups of glioma featured genes with potential clinical significance. Collectively, BrainBase integrates not only valuable curated disease–gene associations and drug–target interactions but also molecular profiles through multi-omics data analysis, accordingly bearing great promise to serve as a valuable knowledgebase for brain diseases.

Computational identification and characterization of glioma candidate biomarkers through multi-omics integrative profiling

BACKGROUND

Glioma is one of the most common malignant brain tumors and exhibits low resection rate and high recurrence risk. Although a large number of glioma studies powered by high-throughput sequencing technologies have led to massive multi-omics datasets, there lacks of comprehensive integration of glioma datasets for uncovering candidate biomarker genes.

RESULTS

In this study, we collected a large-scale assemble of multi-omics multi-cohort datasets from worldwide public resources, involving a total of 16,939 samples across 19 independent studies. Through comprehensive molecular profiling across different datasets, we revealed that PRKCG (Protein Kinase C Gamma), a brain-specific gene detectable in cerebrospinal fluid, is closely associated with glioma. Specifically, it presents lower expression and higher methylation in glioma samples compared with normal samples. PRKCG expression/methylation change from high to low is indicative of glioma progression from low-grade to high-grade and high RNA expression is suggestive of good survival. Importantly, PRKCG in combination with MGMT is effective to predict survival outcomes in a more precise manner.

CONCLUSIONS

PRKCG bears the great potential for glioma diagnosis, prognosis and therapy, and PRKCG-like genes may represent a set of important genes associated with different molecular mechanisms in glioma tumorigenesis. Our study indicates the importance of computational integrative multi-omics data analysis and represents a data-driven scheme toward precision tumor subtyping and accurate personalized healthcare.

A novel cytogenetic and molecular characterization of renal metanephric adenoma: Identification of partner genes involved in translocation t(9;15)(p24;q24)

Renal metanephric adenoma (MA) is a rare benign tumor frequently misclassified when microscopic features alone are applied. The correct classification of a renal tumor is critical for diagnostic, prognostic, and therapeutic purposes. Despite the advancements in cancer genomics, up until recently relatively few genetic alterations critical to MA development have been recognized. Recent data suggest that 90% of MA have BRAF^V600E mutations; the genetics of the remaining 10% are unclear. To date, only one case of a chromosomal translocation, t(9;15)(p24;q24) associated with MA has been reported. However, the potential role of the KANK1 gene, which lies near the breakpoint of the short arm of chromosome 9p24, in the etiology of MA was not examined. We identified the same cytogenetic aberration utilizing molecular cytogenetic techniques in a 22-year-old female patient, and further investigated the genes involved in the translocation that might have contributed to tumorigenesis. A series of fluorescence in situ hybridization (FISH) probes identified the rearranged genes to be KANK1 on chromosome 9 (9p24.3) and NTRK3 on chromosome 15 (15q25.3). Mate-Pair genome sequencing validated the balanced translocation between 9p24.3 and 15q25.3, involving genes KANK1 and NTRK3, respectively. BRAF^V600E mutational analysis was normal. Our findings indicate that gene fusions may be one mechanism by which functionally relevant genes are altered in the development of MA. Molecular and cytogenetic analyses have elucidated a novel genetic aberration, which helps to provide a better understanding of this genomic change and assist in diagnosis and classification of new subgroups/entities in metanephric adenomas.

Comprehensive comparison of large-scale tissue expression datasets

For tissues to carry out their functions, they rely on the right proteins to be present. Several high-throughput technologies have been used to map out which proteins are expressed in which tissues; however, the data have not previously been systematically compared and integrated. We present a comprehensive evaluation of tissue expression data from a variety of experimental techniques and show that these agree surprisingly well with each other and with results from literature curation and text mining. We further found that most datasets support the assumed but not demonstrated distinction between tissue-specific and ubiquitous expression. By developing comparable confidence scores for all types of evidence, we show that it is possible to improve both quality and coverage by combining the datasets. To facilitate use and visualization of our work, we have developed the TISSUES resource (http://tissues.jensenlab.org), which makes all the scored and integrated data available through a single user-friendly web interface.

BIMA V3: an aligner customized for mate pair library sequencing

Mate pair library sequencing is an effective and economical method for detecting genomic structural variants and chromosomal abnormalities. Unfortunately, the mapping and alignment of mate-pair read pairs to a reference genome is a challenging and time-consuming process for most next-generation sequencing alignment programs. Large insert sizes, introduction of library preparation protocol artifacts (biotin junction reads, paired-end read contamination, chimeras, etc.) and presence of structural variant breakpoints within reads increase mapping and alignment complexity. We describe an algorithm that is up to 20 times faster and 25% more accurate than popular next-generation sequencing alignment programs when processing mate pair sequencing.

Identification of submicroscopic genetic changes and precise breakpoint mapping in myelofibrosis using high resolution mate-pair sequencing

We used high resolution mate-pair sequencing (HRMPS) in 15 patients with primary myelofibrosis (PMF): eight with normal karyotype and seven with PMF-characteristic cytogenetic abnormalities, including der(6)t(1;6)(q21-23;p21.3) (n = 4), der(7)t(1;7)(q10;p10) (n = 2), del(20)(q11.2q13.3) (n = 3), and complex karyotype (n = 1). We describe seven novel deletions/translocations in five patients (including two with normal karyotype) whose breakpoints were PCR-validated and involved MACROD2, CACNA2D4, TET2, SGMS2, LRBA, SH3D19, INTS3, FOP (CHTOP), SCLT1, and PHF17. Deletions with breakpoints involving MACROD2 (lysine deacetylase; 20p12.1) were recurrent and found in two of the 15 study patients. A novel fusion transcript was found in one of the study patients (INTS3-CHTOP), and also in an additional non-study patient with PMF. In two patients with der(6)t(1;6)(q21-23;p21.3), we were able to map the precise translocation breakpoints, which involved KCNN3 and GUSBP2 in one case and HYDIN2 in another. This study demonstrates the utility of HRMPS in uncovering submicroscopic deletions/translocations/fusions, and precise mapping of breakpoints in those with overt cytogenetic abnormalities. The overall results confirm the genetic heterogeneity of PMF, given the low frequency of recurrent specific abnormalities, identified by this screening strategy. Currently, we are pursuing the pathogenetic relevance of some of the aforementioned findings.

Candidate serum biomarkers for prostate adenocarcinoma identified by mRNA differences in prostate tissue and verified with protein measurements in tissue and blood

BACKGROUND

Improved tests are needed for detection and management of prostate cancer. We hypothesized that differential gene expression in prostate tissue could help identify candidate blood biomarkers for prostate cancer and that blood from men with advanced prostate disease could be used to verify the biomarkers presence in circulation.

METHODS

We identified candidate markers using mRNA expression patterns from laser-capture microdissected prostate tissue and confirmed tissue expression using immunohistochemistry (IHC) for the subset of candidates having commercial antisera. We analyzed tissue extracts with tandem mass spectrometry (MS/MS) and measured blood concentrations using immunoassays and MS/MS of trypsin-digested, immunoextracted peptides.

RESULTS

We selected 35 novel candidate prostate adenocarcinoma biomarkers. For all 13 markers having commercial antisera for IHC, tissue expression was confirmed; 6 showed statistical discrimination between nondiseased and malignant tissue, and only 5 were detected in tissue extracts by MS/MS. Sixteen of the 35 candidate markers were successfully assayed in blood. Four of 8 biomarkers measured by ELISA and 3 of 10 measured by targeted MS showed statistically significant increases in blood concentrations of advanced prostate cancer cases, compared with controls.

CONCLUSIONS

Seven novel biomarkers identified by gene expression profiles in prostate tissue were shown to have statistically significant increased concentrations in blood from men with advanced prostate adenocarcinoma compared with controls: apolipoprotein C1, asporin, cartilage oligomeric matrix protein, chemokine (C-X-C motif) ligand 11 (CXCL11), CXCL9, coagulation factor V, and proprotein convertase subtilisin/kexin 6.

VeryGene: linking tissue-specific genes to diseases, drugs, and beyond for knowledge discovery

In addition to many other genes, tissue-specific genes (TSGs) represent a set of genes of great importance for human physiology. However, the links among TSGs, diseases, and potential therapeutic agents are often missing, hidden, or too scattered to find. There is a need to establish a knowledgebase for researchers to share this and additional information in order to speed up discovery and clinical practice. As an initiative toward systems biology, the VeryGene web server was developed to fill this gap. A significant effort has been made to integrate TSGs from two large-scale data analyses with respective information on subcellular localization, Gene Ontology, Reactome, KEGG pathway, Mouse Genome Informatics (MGI) Mammalian Phenotype, disease association, and targeting drugs. The current release carefully selected 3,960 annotated TSGs derived from 127 normal human tissues and cell types, including 5,672 gene-disease and 2,171 drug-target relationships. In addition to being a specialized source for TSGs, VeryGene can be used as a discovery tool by generating novel inferences. Some inherently useful but hidden relations among genes, diseases, drugs, and other important aspects can be inferred to form testable hypotheses. VeryGene is available online at http://www.verygene.com.

Discovery of recurrent t(6;7)(p25.3;q32.3) translocations in ALK-negative anaplastic large cell lymphomas by massively parallel genomic sequencing

The genetics of peripheral T-cell lymphomas are poorly understood. The most well-characterized abnormalities are translocations involving ALK, occurring in approximately half of anaplastic large cell lymphomas (ALCLs). To gain insight into the genetics of ALCLs lacking ALK translocations, we combined mate-pair DNA library construction, massively parallel ("Next Generation") sequencing, and a novel bioinformatic algorithm. We identified a balanced translocation disrupting the DUSP22 phosphatase gene on 6p25.3 and adjoining the FRA7H fragile site on 7q32.3 in a systemic ALK-negative ALCL. Using fluorescence in situ hybridization, we demonstrated that the t(6;7)(p25.3;q32.3) was recurrent in ALK-negative ALCLs. Furthermore, t(6;7)(p25.3;q32.3) was associated with down-regulation of DUSP22 and up-regulation of MIR29 microRNAs on 7q32.3. These findings represent the first recurrent translocation reported in ALK-negative ALCL and highlight the utility of massively parallel genomic sequencing to discover novel translocations in lymphoma and other cancers.

The role of desmoglein-3 in the diagnosis of squamous cell carcinoma of the lung

Results from several microarray-based studies have led to the identification of up-regulated expression levels of the DSG3 gene in pulmonary squamous cell carcinomas (SQCCs). The purpose of this study was to determine the role of DSG3 expression in the diagnosis of SQCCs of the lung and to compare DSG3 with p63, CK5, and CK6, as markers of squamous cell differentiation. Expression of DSG3 mRNA was evaluated in bulk laser capture microdissection-derived microarray data and by quantitative reverse transcription PCR on both SQCCs and adenocarcinomas. Expression levels of p63, CK5, and CK6 were evaluated in microarray data from the same set. An immunohistochemical study using antibodies directed against DSG3, p63, and CK5/6 was also performed. DSG3 was over-expressed in SQCCs but had very limited expression in both adenocarcinomas and non-neoplastic lungs. The microarray data showed that DSG3 had a sensitivity and specificity of 88% and 98%, respectively, in detecting SQCC versus adenocarcinoma. In comparison, sensitivity and specificity was 92% and 82% for p63, and 85% and 96% for CK5, respectively. The correlation coefficient between the microarray and immunohistochemical data for these genes was greater than or equal to 0.9. Using immunohistochemistry, sensitivity and specificity of DSG3 for lung cancers were 98% and 99%, respectively. Therefore, DSG3 can be a useful ancillary marker to separate SQCC from other subtypes of lung cancer.

Novel markers for enterochromaffin cells and gastrointestinal neuroendocrine carcinomas

The gene expression profile of metastasizing serotonin-producing neuroendocrine carcinomas, which arise from enterochromaffin cells in the jejunum and ileum, is still largely unknown. The aim of this study was to identify genes and proteins, which are preferentially expressed by neuroendocrine carcinoma and enterochromaffin cells and therefore potential novel biomarkers and/or therapeutic targets. Six carcinoma specimens and six normal ileal mucosas were profiled by Affymetrix microarrays. Advanced bioinformatics identified differentially and specifically expressed genes, which were validated by quantitative real-time-PCR on tumor cells extracted by laser capture microdissection and normal enterochromaffin cells extracted by immunolaser capture microdissection. We identified six novel marker genes for neuroendocrine carcinoma cells: paraneoplastic antigen Ma2 (PNMA2), testican-1 precursor (SPOCK1), serpin A10 (SERPINA10), glutamate receptor ionotropic AMPA 2 (GRIA2), G protein-coupled receptor 112 (GPR112) and olfactory receptor family 51 subfamily E member 1 (OR51E1). GRIA2 is specifically expressed by neuroendocrine carcinoma cells whereas the others are also expressed by normal enterochromaffin cells. GPR112 and OR51E1 encode proteins associated with the plasma membrane and may therefore become targets for antibody-based diagnosis and therapy. Hierarchical clustering shows high similarity between primary lesions and liver metastases. However, chemokine C-X-C motif ligand 14 (CXCL14) and NK2 transcription factor related locus 3 Drosophila (NKX2-3) are expressed to a lower level in liver metastases than in primary tumors and normal enterochromaffin cells, which implies a role in neuroendocrine carcinoma differentiation. In conclusion, this study provides a list of genes, which possess relatively specific expression to enterochromaffin and neuroendocrine carcinoma cells and genes with differential expression between primary tumors and metastases. We verified six novel marker genes that may be developed as biomarkers and/or therapeutic targets.

Switch-like genes populate cell communication pathways and are enriched for extracellular proteins

BACKGROUND

Recent studies have placed gene expression in the context of distribution profiles including housekeeping, graded, and bimodal (switch-like). Single-gene studies have shown bimodal expression results from healthy cell signaling and complex diseases such as cancer, however developing a comprehensive list of human bimodal genes has remained a major challenge due to inherent noise in human microarray data. This study presents a two-component mixture analysis of mouse gene expression data for genes on the Affymetrix MG-U74Av2 array for the detection and annotation of switch-like genes. Two-component normal mixtures were fit to the data to identify bimodal genes and their potential roles in cell signaling and disease progression.

RESULTS

Seventeen percent of the genes on the MG-U74Av2 array (1519 out of 9091) were identified as bimodal or switch-like. KEGG pathways significantly enriched for bimodal genes included ECM-receptor interaction, cell communication, and focal adhesion. Similarly, the GO biological process "cell adhesion" and cellular component "extracellular matrix" were significantly enriched. Switch-like genes were found to be associated with such diseases as congestive heart failure, Alzheimer's disease, arteriosclerosis, breast neoplasms, hypertension, myocardial infarction, obesity, rheumatoid arthritis, and type I and type II diabetes. In diabetes alone, over two hundred bimodal genes were in a different mode of expression compared to normal tissue.

CONCLUSION

This research identified and annotated bimodal or switch-like genes in the mouse genome using a large collection of microarray data. Genes with bimodal expression were enriched within the cell membrane and extracellular environment. Hundreds of bimodal genes demonstrated alternate modes of expression in diabetic muscle, pancreas, liver, heart, and adipose tissue. Bimodal genes comprise a candidate set of biomarkers for a large number of disease states because their expressions are tightly regulated at the transcription level.