Transcriptional Profiling Data Research Articles

High-Content Immunophenotyping and Hierarchical Clustering Reveal Sources of Heterogeneity and New Surface Markers of Human Blood Monocyte Subsets

Blood monocyte subsets are emerging as biomarkers of cardiovascular inflammation. However, our understanding of human monocyte heterogeneity and their immunophenotypic features under healthy and inflammatory conditions is still evolving. In this study, we sought to investigate the immunophenome of circulating human monocyte subsets. Multiplexed, high-throughput flow cytometry screening arrays and computational data analysis were used to analyze the expression and hierarchical relationships of 242 specific surface markers on circulating classical (CD14++CD16-), intermediate (CD14++CD16+), and nonclassical (CD14+CD16++) monocytes in healthy adults. Using generalized linear models and hierarchical cluster analysis, we selected and clustered epitopes that most reliably differentiate between monocyte subsets. We validated existing transcriptional profiling data and revealed potential new surface markers that uniquely define the classical (e.g., BLTR1, CD35, CD38, CD49e, CD89, CD96), intermediate (e.g., CD39, CD275, CD305, CDw328), and nonclassical (e.g., CD29, CD132) subsets. In addition, our analysis revealed phenotypic cell clusters, identified by dendritic markers CMRF-44 and CMRF-56, independent of the traditional monocyte classification. These results reveal an advancement of the clinically applicable multiplexed screening arrays that may facilitate monocyte subset characterization and cytometry-based biomarker selection in various inflammatory disorders.

PRMT1 expression in renal cell tumors- application in differential diagnosis and prognostic relevance

BackgroundProtein arginine methyltransferase-1 (PRMT1) is associated with the progression of various tumor types and the process of epithelial to mesenchymal transition (EMT). However, the expression of PRMT1 in renal cell tumors (RCT) is unknown.MethodsWe evaluated PRMT1 immunohistochemical (IHC) expression on tissue microarray (TMA) of 208 specimens of RCT, including clear cell renal cell carcinomas (ccRCC), papillary RCC type I and II (pRCC I and II), chromophobe RCC (chRCC), renal oncocytomas (RO), collecting duct carcinomas - Bellini (CDC) and multilocular cystic renal cell neoplasms of low malignant potential (MLCRN-LMP). Moreover, a subset of ccRCC, pRCC, chRCC, RO were also studied using conventional sections. PRMT1 expression in tumor tissue was compared to the IHC expression of EMT-related transcription factors (ZEB1, RUNX1, and TWIST1) and cell surface markers (ß-catenin, N- and E-cadherin). Additionally, qRT-PCR expression of PRMT1 in ccRCC, pRCC, and chRCC was evaluated and the results were compared to the mRNA PRMT1 transcript profiling data in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cohort.ResultsPRMT1 immunoreactivity was observed in the majority of ccRCC, RO, all MLCRN-LMP, but in a minority of chRCC (p = 0.044), and it was associated with low grade and low stage ccRCC (p = 0.014; p = 0.044, respectively). ZEB1 immunoreactivity was noted in all RO, in minority of chRCC and neither of MLCRN-LMP (p < 0.001). The majority of PRMT1-negative ccRCC was negative to ZEB1 and showed cytoplasmic expression of TWIST1 (p = 0.028; p < 0.001, respectively). PRMT1 positive ccRCC mostly expressed RUNX1 (p = 0.019). PRMT1 and ZEB1 expression were associated with better cancer-specific survival in patients with ccRCC (p = 0.029; p = 0.009, respectively). In multivariate analysis, ZEB1 expression was an independent prognostic factor for cancer-specific survival (hazard ratio [HR], 0.367; p = 0.026). Significant IHC heterogeneity was observed in PRMT1, ZEB1 and TWIST1 expression (p < 0.001). Homogenous loss of PRMT1 was associated with high grade and high stage ccRCC, while the homogenous loss of PRMT1 and ZEB1 was more frequent in patients who died of ccRCC (p = 0.017; p = 0.040; p = 0.044; p = 0.009, respectively). Relative mRNA-PRMT1 expression in both cohorts was down-regulated in tumor tissue compared to non-tumor parenchyma (p = 0.009). Unlike in our samples, mRNA-PRMT1 expression in the TCGA cohort was not correlated to ccRCC tumor stage or grade. PRMT1, ZEB1, and TWIST1 expression were not associated with EMT related aberrant ß-catenin expression, a gain of N-cadherin or loss of E-cadherin expression. Only RUNX1 was associated with a gain of N-cadherin (p = 0.003).ConclusionsIHC expression of PRMT1 may be characteristic for low grade and low stage ccRCC, while the homogenous loss of PRMT1 may be significant for high grade and high stage ccRCC. Both, PRMT1 and/or ZEB1 expression, could be associated with better survival of the patients with ccRCC.

Mitochondrial and ribosomal biogenesis are new hallmarks of stemness, oncometabolism and biomass accumulation in cancer: Mito-stemness and ribo-stemness features.

Using proteomics analysis, we previously compared MCF7 breast cancer cells grown as 3D tumor spheres, with the same cell line grown as monolayers. Our results indicated that during 3D anchorage‐independent growth, the cellular machinery associated with i) mitochondrial biogenesis and ii) ribosomal biogenesis, were both significantly increased. Here, for simplicity, we refer to these two new oncogenic hallmarks as “mito‐stemness” and “ribo‐stemness” features. We have now applied this same type of strategy to begin to understand how fibroblasts and MCF7 breast cancer cells change their molecular phenotype, when they are co‐cultured together. We have previously shown that MCF7‐fibroblast co‐cultures are a valuable model of resistance to apoptosis induced by hormonal therapies, such as Tamoxifen and Fulvestrant. Here, we directly show that these mixed co‐cultures demonstrate the induction of mito‐stemness and ribo‐stemness features, likely reflecting a mechanism for cancer cells to increase their capacity for accumulating biomass. In accordance with the onset of a stem‐like phenotype, KRT19 (keratin 19) was induced by ~6‐fold during co‐culture. KRT19 is a well‐established epithelial CSC marker that is used clinically to identify metastatic breast cancer cells in sentinel lymph node biopsies. The potential molecular therapeutic targets that we identified by label‐free proteomics of MCF7‐fibroblast co‐cultures were then independently validated using a bioinformatics approach. More specifically, we employed publically‐available transcriptional profiling data derived from primary tumor samples from breast cancer patients, which were previously subjected to laser‐capture micro‐dissection, to physically separate breast cancer cells from adjacent tumor stroma. This allowed us to directly validate that the proteins up‐regulated in this co‐culture model were also transcriptionally elevated in patient‐derived breast cancer cells in vivo. This powerful approach for target identification and translational validation, including the use of patient outcome data, can now be applied to other tumor types as well, to validate new therapeutic targets that are more clinically relevant, for patient benefit. Moreover, we discuss the therapeutic implications of these findings for new drug development, drug repurposing and Tamoxifen‐resistance, to effectively target mito‐stemness and ribo‐stemness features in breast cancer patients. We also discuss the broad implications of this “organelle biogenesis” approach to cancer therapy.

Abstract 2795: Dissemination score of CD8+ TILs by automated image analysis is a potential marker of immune activity in human cancers

Abstract The overall density of CD8+ tumor-infiltrating lymphocytes (TILs) is important for characterizing the level of immune activity in the tumor microenvironment (TME). Beyond the densities of CD8+ TILs, both their location and distributional patterns may also have relevance to immune activity. We evaluated 645 resected tumors encompassing seven cancer types, and correlate location and spatial patterns of CD8+ TILs to immune pathway activity. We integrated image analysis results from digitized immunohistochemistry (IHC) slides with gene expression data from a targeted Ion Torrent Panel. Overall density of CD8+ TILs and the exact position of individual CD8+ lymphocytes were determined from IHC slides. A dissemination score was defined as ratio of global density and average local density of CD8+ TILs. This score is the inverse of the Ripley’s K statistic and becomes high for disseminated spatial patterns. We used this quotient as a continuous metric to identify tumors with a disseminated TIL pattern and to distinguish them from tumors with focal distribution of CD8+ TILs. Within a subset of tumors, the continuous dissemination metric was correlated with biological pathways using targeted mRNA sequencing and gene set enrichment analysis. In addition, association of the dissemination score with overall survival was tested on a subset of cases. CD8+ TIL distributional patterns differed significantly between tumor types. Breast and pancreatic cancers more frequently showed a focal distribution of CD8+ TILs, while lung tumors comparatively exhibited a disseminated pattern. Transcriptional profiling data revealed differences between both image analysis phenotypes. On average, cases with more disseminated patterns of CD8+ T cells were associated with mRNA expression of genes that fall in pathways related to motility, migration and activation status of tumor infiltrating T cells. We also found a trend to better overall survival in patients whose tumors had a disseminated TIL score compared to those with a focal pattern. This trend was significant in non-small cell adenocarcinoma of the lung (log rank p = 0.018). We demonstrate the value of spatial image analysis to automatically score CD8+ TIL dissemination as a marker of immune activity in the TME. Jointly analyzing transcriptional profiles appears to identify a biologically meaningful activation phenotype in tumors with high dissemination scores. Our data further suggests that this phenotype is associated with improved overall survival in some cancer patients. Citation Format: Stefan Bentink, Andreas Spitzmueller, Tze Heng Tan, Hadassah Sade, Song Wu, Brandon W. Higgs, Keith E. Steele. Dissemination score of CD8+ TILs by automated image analysis is a potential marker of immune activity in human cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2795.

Identification of key pathways regulated by a set of competitive long non-coding RNAs in oral squamous cell carcinoma.

ObjectiveThe aim of this study was to identify important pathways regulated by a set of long non-coding RNAs (lncRNAs) in oral squamous cell carcinoma (OSCC).MethodsA lncRNA-mediated competitive endogenous RNA network (LMCN) was constructed using information on microRNA (miRNA)–mRNA interactions and lncRNA–miRNA intersections from the E-GEOD-37991 transcription profiling data in the ArrayExpress database. A random walk with restart ranking algorithm was then applied to evaluate the influences of protein-coding genes regulated by competitive lncRNAs. Pathway enrichment scores were calculated based on the propagation scores of protein-coding genes. Finally, permutation tests were used to estimate the significance of the pathways.ResultsWe obtained lncRNA–mRNA interactions based on miRNAs common to both miRNA–mRNA interactions and lncRNA–miRNA intersections, and used interactions with a z-score > 0.7 to construct a LMCN. Ten lncRNAs were identified as source nodes in the LMCN, and nine pathways with enrichment scores >0.8, including ‘Cell cycle’, ‘Endocytosis’, and ‘Pathways in cancer’, were significantly enriched by these source nodes.ConclusionsNine significant pathways regulated by a set of competitive lncRNAs were identified in OSCC, which may play important roles in the development of OSCC via the cell cycle and endocytosis.

Abstract B153: Human NK cell distribution memory and residence in tissue sites

Abstract Natural killer (NK) cells are innate immune cells with the ability to kill tumor cells without prior exposure. NK cells express multiple activating and inhibitory receptors in addition to the low-affinity immunoglobulin G binding receptor CD16. Accumulating evidence implicates a role of NK cells in not only direct killing of tumor cells, but also in cancer immunosurveillance and preventing metastasis to tissues sites. However, at present the distribution, diversity and tissue driven differences in NK cell function are not well characterized which may have an implication on the anti-cancer potential of tissue NK cells. Through collaboration with LiveOnNY our local organ procurement organization, we receive blood, bone marrow (BM), lung, intestines, tonsil and associated lymph nodes (LN) from research consented organ donors. Here we used this unique tissue resource to investigate the distribution, phenotypic, functional and transcriptional diversity of NK cell subsets in human tissues. We found that NK cells are ubiquitously distributed in human tissues comprising up to 40% of the CD45+ CD14/19- cells in blood, BM, spleen and lung, while only a small fraction (up to 2%) in the intestine and the LN. While blood, BM, spleen and lung are dominated by mature NK cells (CD56dim CD16+), majority of the NK cells in intestine and LN are immature (CD56hi CD16-). Age, sex and CMV sero-status do not show any correlation with NK cell distribution or subset frequency in tissues. Notably, NK cell subset distribution seems to drive functional differences between tissue NK cells, with lymphoid site NK cells expressing lower levels of effector molecules granzyme B, TNFα, Prf, Ifnγ and displaying reduced degranulation compared with their counterparts from blood, BM and spleen. For an in-depth analysis of tissue-mediated effects on NK cell subset functionality, we performed whole-transcriptome profiling on immature and mature NK cells isolated from blood, BM, spleen, lung and LN. Our analysis identified several effector molecules and NK cell surface receptors being differentially expressed between immature and mature NK cells. Furthermore, while mature NK cells of blood and tissues have similar transcriptional profiles, the transcriptional profiles of immature blood and tissue NK cells show tissue driven heterogeneity with differential expression of transcription factors, metabolic enzymes and NK cell surface receptors. Interestingly, the transcriptional signature of immature NK cells is reminiscent of the transcriptional signature of tissue resident memory T-cells showing increased expression of CD103, CD49a, CXCR6. We validated the expression of these markers using multiparameter flow cytometry and found that subset of immature NK cells in mucosal sites (lung and intestine) do indeed express markers of tissue residence. Additionally, by applying trajectory projection algorithm on NK cells from tissue sites, we show that resident NK cells comprise a distinct population from immature NK cells. Our study has identified novel, previously unidentified diversity of tissue NK cells. Phenotypic and transcriptional profiling data provide evidence for putative resident NK cells being present in certain tissue sites. Blood NK cells differ from their counterparts in tissues; especially, immature NK cells in tissues may be specifically trained to function in the tissue environment. Finally, due to the uniqueness of phenotypic, functional and transcriptional features of tissue NK cells, they may be more suited to fight cancer in situ in tissues. Citation Format: Pranay Dogra, Takashi Senda, Peter Szabo, Dustin Carpenter, Marta Toth, Puspa Thapa, Mark Snyder, Michelle Miron, Brahma Kumar, Donna L. Farber. Human NK cell distribution memory and residence in tissue sites [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B153.

Transcript analysis of abscisic acid-inducible genes in response to different abiotic disturbances in two indica rice varieties

The present study focused upon comprehensive analysis of the expression of stress-responsive genes at different time points in two indica rice varieties, IR-64 (moderately salt-sensitive) and Nonabokra (salt-tolerant), under salinity, dehydration and cold, and exogenous ABA treatment. The massively parallel signature sequencing and publicly-available microarray data indicated the physiological role of the concerned genes in different tissues. Gene expression through semi-quantitative reverse transcriptase-polymerase chain reaction followed by factorial analyses of variance identified that members of the antioxidant genes (OsCAT, OsSOD, OsGR2 and OsAPX8) showed early response and higher expression under different abiotic stresses in IR-64. The TFs and LEA family (TRAB1 and Osem), osmolyte (OsBADH1, OsP5CS) and polyamine (SAMDC) metabolic genes were more up regulated in the salt-tolerant cultivar, whereas the proline (ProDH) and polyamine (DAO and PAO) catabolic genes were significantly up regulated in the salt-sensitive one. The higher accumulation of TRAB1 transcript and protein in the tolerant cultivar during various stresses suggested it as an important component in stress signaling pathway, which participates in mediating cross-talk signaling between diverse metabolic pathways to withstand various forms of abiotic stress. Heat map data further corroborated differential transcript abundance in the two varieties, coinciding with the transcript profiling data. We envisage that the identified genes in this study, linked with tolerance against various abiotic stress factors, are the chief candidates involved in regulating the complexity of multiple stress responses in rice. The finding of the candidate genes in this study would be helpful in generating multiple abiotic stress tolerance in rice.

Drug and disease signature integration identifies synergistic combinations in glioblastoma

Glioblastoma (GBM) is the most common primary adult brain tumor. Despite extensive efforts, the median survival for GBM patients is approximately 14 months. GBM therapy could benefit greatly from patient-specific targeted therapies that maximize treatment efficacy. Here we report a platform termed SynergySeq to identify drug combinations for the treatment of GBM by integrating information from The Cancer Genome Atlas (TCGA) and the Library of Integrated Network-Based Cellular Signatures (LINCS). We identify differentially expressed genes in GBM samples and devise a consensus gene expression signature for each compound using LINCS L1000 transcriptional profiling data. The SynergySeq platform computes disease discordance and drug concordance to identify combinations of FDA-approved drugs that induce a synergistic response in GBM. Collectively, our studies demonstrate that combining disease-specific gene expression signatures with LINCS small molecule perturbagen-response signatures can identify preclinical combinations for GBM, which can potentially be tested in humans.

Insights into ABA-mediated regulation of guard cell primary metabolism revealed by systems biology approaches

Despite the fact that guard cell abscisic acid (ABA) signalling pathway is well documented, our understanding concerning how and to which extent ABA regulates guard cell metabolism remains fragmentary. Here we have adopted different systems approaches to investigate how ABA modulates guard cell central metabolism by providing genes that are possibly ABA-regulated. By using previous published Arabidopsis guard cell transcript profiling data, we carried out an extensive co-expression network analysis using ABA-related genes and those related to the metabolism and transport of sugars, starch and organic acids. Next, we investigated the presence of ABA responsive elements (ABRE) in the promoter of genes that are highly expressed in guard cells, responsive to ABA and co-expressed with ABA-related genes. Together, these analyses indicated that 44 genes are likely regulated by ABA and 8 of them are highly expressed in guard cells in both the presence and absence of ABA, including genes of the tricarboxylic acid cycle and those related to sucrose and hexose transport and metabolism. It seems likely that ABA may modulate both sucrose transport through guard cell plasma membrane and sucrose metabolism within guard cells. In this context, genes associated with sucrose synthase, sucrose phosphate synthase, trehalose-6-phosphate, invertase, UDP-glucose epimerase/pyrophosphorylase and different sugar transporters contain ABRE in their promoter and are thus possibly ABA regulated. Although validation experiments are required, our study highlights the importance of systems biology approaches to drive new hypothesis and to unravel genes and pathways that are regulated by ABA in guard cells.

TEAD4 overexpression promotes epithelial-mesenchymal transition and associates with aggressiveness and adverse prognosis in head neck squamous cell carcinoma

BackgroundDeregulated Hippo signaling has been uncovered to be intricately involved in tumorigenesis. Transcriptional factor TEADs serve as key mediators of Hippo signaling and have been increasingly appreciated as putative oncogenes driving cancer initiation and progression. However, its expression pattern and oncogenic role of TEAD4 in head and neck squamous cell carcinoma (HNSCC) remain largely unexplored.MethodsTEAD4 mRNA expression in HNSCC was determined by data mining and analyses from TCGA dataset and four independent cohorts with transcriptional profiling data publically available. The protein abundance of TEAD4 was measured by immunohistochemistry in 105 primary HNSCC samples and associations between its expression and clinicopathological parameters and patient survival were evaluated. The oncogenic roles of TEAD4 was further determined by 4-nitroquinoline 1-oxide (4NQO)-induced animal model, both knockdown/overexpression assay and TGF-β1-induced epithelia-mesenchymal transition (EMT) in vitro.ResultsBoth mRNA and protein abundance of TEAD4 were significantly increased in HNSCC as compared to its non-tumor counterparts. Overexpression of TEAD4 significantly associated with high pathological grade, cervical node metastasis, advanced clinical stage and reduced overall and disease-free survival. In the 4NQO-induced HNSCC mouse model, increased TEAD4 immunostaining was found associated with disease progression. TEAD4 knockdown significantly inhibited cell proliferation, migration and invasion, and induced cell apoptosis in HNSCC cells, while its overexpression resulted in opposite effects and EMT. Moreover, TEAD4 was critically involved in TGF-β1-induced EMT in HNSCC cells.ConclusionsOur findings reveal that TEAD4 serves as a novel prognostic biomarker and putative oncogene for HNSCC by promoting cell proliferation, migration and invasion, and EMT.

Molecular Signature of CAID Syndrome: Noncanonical Roles of SGO1 in Regulation of TGF-β Signaling and Epigenomics.

Background & AimsA generalized human pacemaking syndrome, chronic atrial and intestinal dysrhythmia (CAID) (OMIM 616201), is caused by a homozygous SGO1 mutation (K23E), leading to chronic intestinal pseudo-obstruction and arrhythmias. Because CAID patients do not show phenotypes consistent with perturbation of known roles of SGO1, we hypothesized that noncanonical roles of SGO1 drive the clinical manifestations observed.MethodsTo identify a molecular signature for CAID syndrome, we achieved unbiased screens in cell lines and gut tissues from CAID patients vs wild-type controls. We performed RNA sequencing along with stable isotope labeling with amino acids in cell culture. In addition, we determined the genome-wide DNA methylation and chromatin accessibility signatures using reduced representative bisulfite sequencing and assay for transposase-accessible chromatin with high-throughput sequencing. Functional studies included patch-clamp, quantitation of transforming growth factor-β (TGF-β) signaling, and immunohistochemistry in CAID patient gut biopsy specimens.ResultsProteome and transcriptome studies converge on cell-cycle regulation, cardiac conduction, and smooth muscle regulation as drivers of CAID syndrome. Specifically, the inward rectifier current, an important regulator of cellular function, was disrupted. Immunohistochemistry confirmed overexpression of Budding Uninhibited By Benzimidazoles 1 (BUB1) in patients, implicating the TGF-β pathway in CAID pathogenesis. Canonical TGF-β signaling was up-regulated and uncoupled from noncanonical signaling in CAID patients. Reduced representative bisulfite sequencing and assay for transposase-accessible chromatin with high-throughput sequencing experiments showed significant changes of chromatin states in CAID, pointing to epigenetic regulation as a possible pathologic mechanism.ConclusionsOur findings point to impaired inward rectifier potassium current, dysregulation of canonical TGF-β signaling, and epigenetic regulation as potential drivers of intestinal and cardiac manifestations of CAID syndrome. Transcript profiling and genomics data are as follows: repository URL: https://www.ncbi.nlm.nih.gov/geo; SuperSeries GSE110612 was composed of the following subseries: GSE110309, GSE110576, and GSE110601.

A Trihelix Family Transcription Factor Is Associated with Key Genes in Mixed-Linkage Glucan Accumulation.

Mixed-linkage glucan (MLG) is a polysaccharide that is highly abundant in grass endosperm cell walls and present at lower amounts in other tissues. Cellulose synthase-like F (CSLF) and cellulose synthase-like H genes synthesize MLG, but it is unknown if other genes participate in the production and restructuring of MLG. Using Brachypodium distachyon transcriptional profiling data, we identified a B distachyon trihelix family transcription factor (BdTHX1) that is highly coexpressed with the B distachyon CSLF6 gene (BdCSLF6), which suggests that BdTHX1 is involved in the regulation of MLG biosynthesis. To determine the genes regulated by this transcription factor, we conducted chromatin immunoprecipitation sequencing (ChIP-seq) experiments using immature B distachyon seeds and an anti-BdTHX1 polyclonal antibody. The ChIP-seq experiment identified the second intron of BdCSLF6 as one of the most enriched sequences. The binding of BdTHX1 to the BdCSLF6 intron sequence was confirmed using electrophoretic mobility shift assays (EMSA). ChIP-seq also showed that a gene encoding a grass-specific glycoside hydrolase family 16 endotransglucosylase/hydrolase (BdXTH8) is bound by BdTHX1, and the binding was confirmed by EMSA. Radiochemical transglucanase assays showed that BdXTH8 exhibits predominantly MLG:xyloglucan endotransglucosylase activity, a hetero-transglycosylation reaction, and can thus produce MLG-xyloglucan covalent bonds; it also has a lower xyloglucan:xyloglucan endotransglucosylase activity. B distachyon shoots regenerated from transformed calli overexpressing BdTHX1 showed an abnormal arrangement of vascular tissue and seedling-lethal phenotypes. These results indicate that the transcription factor BdTHX1 likely plays an important role in MLG biosynthesis and restructuring by regulating the expression of BdCSLF6 and BdXTH8.

Novel approach to functional SNPs discovery from genome-wide data reveals promising variants for colon cancer risk.

In the majority of colorectal cancer (CRC) cases, the genetic basis of predisposition remains unexplained. The goal of the study was to assess the regulatory SNPs (rSNPs) in the human genome and to reveal СRC drivers based on the available chromatin immunoprecipitation sequencing (ChIP-Seq, ChIA-PET) and transcriptional profiling (RNA-Seq) data. We combined positional (locations within genome regulatory elements) and functional (associated with allele-specific binding and expression) criteria followed by an analysis using genome-wide association studies (GWAS) and minor allele frequency (MAF) datasets. DeSeq2 analysis through 70 CRC patients reinforced the regulatory potential. rSNPs (1,476) that were associated with significant (P<0.01) allele-specific events resulting in thirty that exhibited a link with CRC according to the MAF and 27, with a risk of malignancy in general according to GWAS. Selected rSNPs may modify the expression of genes for tumor suppressors and the regulators of signaling pathways, including noncoding RNAs. However, the rSNPs from the most represented group affect the expression of genes related to splicing. Our findings strongly suggest that the identified variants might contribute to CRC susceptibility, which indicates that aberrant splicing is one of the key mechanisms for unraveling disease etiopathogenesis and provides useful inputs for interpreting how genotypic variation corresponds to phenotypic outcome.

Defective decidualization during and after severe preeclampsia reveals a possible maternal contribution to the etiology

In preeclampsia (PE), cytotrophoblast (CTB) invasion of the uterus and spiral arteries is often shallow. Thus, the placenta's role has been a focus. In this study, we tested the hypothesis that decidual defects are an important determinant of the placental phenotype. We isolated human endometrial stromal cells from nonpregnant donors with a previous pregnancy that was complicated by severe PE (sPE). Compared with control cells, they failed to decidualize in vitro as demonstrated by morphological criteria and the analysis of stage-specific antigens (i.e., IGFBP1, PRL). These results were bolstered by global transcriptional profiling data that showed they were transcriptionally inert. Additionally, we used laser microdissection to isolate the decidua from tissue sections of the maternal-fetal interface in sPE. Global transcriptional profiling revealed defects in gene expression. Also, decidual cells from patients with sPE, which dedifferentiated in vitro, failed to redecidualize in culture. Conditioned medium from these cells failed to support CTB invasion. To mimic aspects of the uterine environment in normal pregnancy, we added PRL and IGFBP1, which enhanced invasion. These data suggested that failed decidualization is an important contributor to down-regulated CTB invasion in sPE. Future studies will be aimed at determining whether this discovery has translational potential with regard to assessing a woman's risk of developing this pregnancy complication.

Transcriptome sequencing reveals potential mechanisms of diapause preparation in bivoltine silkworm Bombyx mori (Lepidoptera: Bombycidae)

In the bivoltine strain of the silkworm, Bombyx mori, embryonic diapause is induced transgenerationally as a maternal effect. Progeny diapause ability is determined by the environmental condition such as temperature and lightness that mothers experience during their own embryonic development. Diapause preparation is a crucial phase of this process; diapause-destined individuals undergo a series of preparatory events before the entry into developmental arrest. However, the molecular regulatory mechanisms of diapause preparation have largely remained unknown. In the present study, we sequenced the transcriptome of bivoltine silkworm Qiufeng's ovaries resulted in laying of diapause destined or non-diapause eggs, using high-throughput RNA-Seq technology. Differential expression analyses identified 183 genes with higher expression, and 106 with lower expression under diapause-inducing conditions. GO and KEGG analysis revealed that the enrichment of several functional terms related to peroxisome, glycerolipid metabolism, steroid biosynthesis, longevity regulating pathway - multiple species, three signaling transductions, insect hormone biosynthesis, and cytoskeleton components. We conducted a detailed comparison of transcript profile data of ovaries from diapause-inducing and non-diapause conditions, the results imply up-regulation of peroxisomal metabolism, triacylglycerides accumulation, cryoprotectant production, and ecdysteroid biosynthesis in diapause-inducing group. Differential expression of genes related to actin cytoskeleton implies the occurrence of shifts in cellular structure and composition between diapause-inducing and non-diapause-inducing groups. The Hippo and FOXO signaling pathways may play an important role in preparing for entering diapause. This study provides an insight into the molecular events of insect diapause, in particular for the preparatory phase.

Joint principal trend analysis for longitudinal high-dimensional data.

We consider a research scenario motivated by integrating multiple sources of information for better knowledge discovery in diverse dynamic biological processes. Given two longitudinal high-dimensional datasets for a group of subjects, we want to extract shared latent trends and identify relevant features. To solve this problem, we present a new statistical method named as joint principal trend analysis (JPTA). We demonstrate the utility of JPTA through simulations and applications to gene expression data of the mammalian cell cycle and longitudinal transcriptional profiling data in response to influenza viral infections.

Multiple network-constrained regressions expand insights into influenza vaccination responses.

MotivationSystems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology.ResultsHere we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability.Availability and implementationThe R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer.Supplementary information Supplementary data are available at Bioinformatics online.

Prediction of synergistic anti-cancer drug combinations based on drug target network and drug induced gene expression profiles.

Synergistic drug combinations are promising therapies for cancer treatment. However, effective prediction of synergistic drug combinations is quite challenging as mechanisms of drug synergism are still unclear. Various features such as drug response, and target networks may contribute to prediction of synergistic drug combinations. In this study, we aimed to construct a computational model to predict synergistic drug combinations. We designed drug physicochemical features and network features, including drug chemical structure similarity, target distance in protein-protein network and targeted pathway similarity. At the same time, we designed fifteen pharmacogenomics features using drug treated gene expression profiles based on the background of cancer-related biology network. Based on these eighteen features, we built a prediction model for Synergistic Drug combination using Random forest algorithm (SyDRa). Our model achieved a quite good performance with AUC value of 0.89 and Out-of-bag estimate error rate of 0.15 in training dataset. Using the random anti-cancer drug combinations which have transcriptional profile data in the Connectivity Map dataset as the testing dataset, we identified 28 potentially synergistic drug combinations, three out of which had been reported to be effective drug combinations by literatures. We studied eighteen features for drug combinations and built a computational model using random forest algorithm. The model was evaluated using an independent test dataset. Our model provides an efficient strategy to identify potentially synergistic drug combinations for cancer and may help reduce the search space for high-throughput synergistic drug combinations screening.

Reconstructing context-specific gene regulatory network and identifying modules and network rewiring through data integration.

Reconstructing context-specific transcriptional regulatory network is crucial for deciphering principles of regulatory mechanisms underlying various conditions. Recently studies that reconstructed transcriptional networks have focused on individual organisms or cell types and relied on data repositories of context-free regulatory relationships. Here we present a comprehensive framework to systematically derive putative regulator-target pairs in any given context by integrating context-specific transcriptional profiling and public data repositories of gene regulatory networks. Moreover, our framework can identify core regulatory modules and signature genes underlying global regulatory circuitry, and detect network rewiring and core rewired modules in different contexts by considering gene modules and edge (gene interaction) modules collaboratively. We applied our methods to analyzing Autism RNA-seq experiment data and produced biologically meaningful results. In particular, all 11 hub genes in a predicted rewired autistic regulatory subnetwork have been linked to autism based on literature review. The predicted rewired autistic regulatory network may shed some new insight into disease mechanism.

Identification of potential biomarkers of sepsis using bioinformatics analysis.

Sepsis is defined as the systemic inflammatory response to infection and is one of the leading causes of mortality in critically ill patients. The goal of the present study is to elucidate the molecular mechanism of sepsis. Transcription profile data (GSE12624) were downloaded that had a total of 70 samples (36 sepsis samples and 34 non-sepsis samples) from the Gene Expression Omnibus database. Protein-protein interaction network analysis was conducted in order to comprehensively understand the interactions of genes in all samples. Hierarchical clustering and analysis of covariance (ANCOVA) global test were performed to identify the differentially expressed clusters in the networks, followed by function and pathway enrichment analyses. Finally, a support vector machine (SVM) was performed to classify the clusters, and 10-fold cross-validation method was performed to evaluate the classification results. A total of 7,672 genes were obtained after preprocessing of the mRNA expression profile data. The PPI network of genes under sepsis and non-sepsis status collected 1,996/2,147 genes and 2,645/2,783 interactions. Moreover, following the ANCOVA global test (P<0.05), 24 differentially expressed clusters with 12 clusters in septic and 12 clusters in non-septic samples were identified. Finally, 207 biomarker genes, including CDC42, CSF3R, GCA, HMGB2, RHOG, SERPINB1, TYROBP SERPINA1, FCER1 G and S100P in the top six clusters, were collected using the SVM method. The SERPINA1, FCER1 G and S100P genes are thought to be potential biomarkers. Furthermore, Gene oncology terms, including the intracellular signaling cascade, regulation of programmed cell death, regulation of cell death, regulation of apoptosis and leukocyte activation may participate in sepsis.