GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data

<p>Abstract</p> <p>Background</p> <p>Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge.</p> <p>Results</p> <p>Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few.</p> <p>Conclusion</p> <p>GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at <url>http://pcarvalho.com/patternlab</url>.</p

Data for: RNA-seq data analysis of stimulated hepatocellular carcinoma cells treated with epigallocatechin gallate and fisetin reveals target genes and action mechanisms (Part1 - epigallocatechin gallate treatment)

In this study, we endeavor to compare gene expression alterations mediated by flavonoids epigallocatechin gallate (EGCG) and fisetin (FIS) through a comprehensive transcriptome analysis based on RNA-seq in human hepatocellular carcinoma HEP3B cells, upon perturbation with a mixture of prototypical stimuli mimicking conditions of tumor microenvironment (STIM), or under constitutive state (MEM). HEP3B cells, seeded the day before in a 6-well plate, were serum-starved for 4h and then treated with EGCG (100μM), FIS (10μM) or DMSO (0.1 % v/v) for 2h. Cells were subsequently exposed to a mixture of stimuli consisting of recombinant interleukins IL-6 (0.1μg/ml), IL-1B (0.01μg/ml) and tumor growth factor A (TGFA) (0.2μg/ml) and were further incubated for 22h. Samples of all possible treatment combinations of HEP3B cells i.e. EGCG, FIS, or DMSO at either MEM or STIM state were subjected to RNA extraction from two independent experiments.Total RNA was isolated using the PureLink RNA Mini Kit (Invitrogen, USA) according to the manufacturer’s instructions. Quantification and quality control of isolated RNA was performed by measuring absorbance at 260nm and 280nm on a NANODROP ONEC spectrophotometer (Thermo Scientific, USA). The RNA-seq run was performed on a NextSeq 500 Illumina platform that provided single-end reads of 85bp length. Quality assessment, library preparation (TruSeqLT) and the actual sequencing run was conducted in the Biomedical Research Foundation of the Academy of Athens (BRFAA) sequencing facility. Herein, we provide (compressed in .bz2 file format) raw sequencing FASTQ files regarding the EGCG treatment, along with a descriptive metadata file (EGCG_metadata.pdf). Due to storage limitations, respective data about FIS treatment are provided in a separate dataset entitled "Data for: RNA-seq data analysis of stimulated hepatocellular carcinoma cells treated with epigallocatechin gallate and fisetin reveals target genes and action mechanisms (Part2 - fisetin treatment)"

Data for: RNA-seq data analysis of stimulated hepatocellular carcinoma cells treated with epigallocatechin gallate and fisetin reveals target genes and action mechanisms (Part2 - fisetin treatment)

In this study, we endeavor to compare gene expression alterations mediated by flavonoids epigallocatechin gallate (EGCG) and fisetin (FIS) through a comprehensive transcriptome analysis based on RNA-seq in human hepatocellular carcinoma HEP3B cells, upon perturbation with a mixture of prototypical stimuli mimicking conditions of tumor microenvironment (STIM), or under constitutive state (MEM). HEP3B cells, seeded the day before in a 6-well plate, were serum-starved for 4h and then treated with EGCG (100μM), FIS (10μM) or DMSO (0.1 % v/v) for 2h. Cells were subsequently exposed to a mixture of stimuli consisting of recombinant interleukins IL-6 (0.1μg/ml), IL-1B (0.01μg/ml) and tumor growth factor A (TGFA) (0.2μg/ml) and were further incubated for 22h. Samples of all possible treatment combinations of HEP3B cells i.e. EGCG, FIS, or DMSO at either MEM or STIM state were subjected to RNA extraction from two independent experiments.Total RNA was isolated using the PureLink RNA Mini Kit (Invitrogen, USA) according to the manufacturer’s instructions. Quantification and quality control of isolated RNA was performed by measuring absorbance at 260nm and 280nm on a NANODROP ONEC spectrophotometer (Thermo Scientific, USA). The RNA-seq run was performed on a NextSeq 500 Illumina platform that provided single-end reads of 85bp length. Quality assessment, library preparation (TruSeqLT) and the actual sequencing run was conducted in the Biomedical Research Foundation of the Academy of Athens (BRFAA) sequencing facility. Herein, we provide (compressed in .bz2 file format) raw sequencing FASTQ files regarding the FIS treatment, along with a descriptive metadata file (FIS_metadata.pdf). Due to storage limitations, respective data about EGCG treatment are provided in a separate dataset entitled "Data for: RNA-seq data analysis of stimulated hepatocellular carcinoma cells treated with epigallocatechin gallate and fisetin reveals target genes and action mechanisms (Part1 - epigallocatechin gallate treatment)"

Computational analysis of transcriptomic and proteomic data for deciphering molecular heterogeneity and drug responsiveness in model human hepatocellular carcinoma cell lines

Hepatocellular carcinoma (HCC) is associated with high mortality due to its inherent heterogeneity, aggressiveness, and limited therapeutic regimes. Herein, we analyzed 21 human HCC cell lines (HCC lines) to explore intertumor molecular diversity and pertinent drug sensitivity. We used an integrative computational approach based on exploratory and single-sample gene-set enrichment analysis of transcriptome and proteome data from the Cancer Cell Line Encyclopedia, followed by correlation analysis of drug-screening data from the Cancer Therapeutics Response Portal with curated gene-set enrichment scores. Acquired results classified HCC lines into two groups, a poorly and a well-differentiated group, displaying lower/higher enrichment scores in a “Specifically Upregulated in Liver” gene-set, respectively. Hierarchical clustering based on a published epithelial–mesenchymal transition gene expression signature further supported this stratification. Between-group comparisons of gene and protein expression unveiled distinctive patterns, whereas downstream functional analysis significantly associated differentially expressed genes with crucial cancer-related biological processes/pathways and revealed concrete driver-gene signatures. Finally, correlation analysis highlighted a diverse effectiveness of specific drugs against poorly compared to well-differentiated HCC lines, possibly applicable in clinical research with patients with analogous characteristics. Overall, this study expanded the knowledge on the molecular profiles, differentiation status, and drug responsiveness of HCC lines, and proposes a cost-effective computational approach to precision anti-HCC therapies. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

RNA-seq data analysis of stimulated hepatocellular carcinoma cells treated with epigallocatechin gallate and fisetin reveals target genes and action mechanisms

Hepatocellular carcinoma (HCC) is an essentially incurable inflammation-related cancer. We have previously shown by network analysis of proteomic data that the flavonoids epigallocatechin gallate (EGCG) and fisetin (FIS) efficiently downregulated pro-tumor cytokines released by HCC through inhibition of Akt/mTOR/RPS6 phospho-signaling. However, their mode of action at the global transcriptome level remains unclear. Herein, we endeavor to compare gene expression alterations mediated by these compounds through a comprehensive transcriptome analysis based on RNA-seq in HEP3B, a responsive HCC cell line, upon perturbation with a mixture of prototypical stimuli mimicking conditions of tumor microenvironment or under constitutive state. Analysis of RNA-seq data revealed extended changes on HEP3B transcriptome imposed by test nutraceuticals. Under stimulated conditions, EGCG and FIS significantly modified, compared to the corresponding control, the expression of 922 and 973 genes, respectively, the large majority of which (695 genes), was affected by both compounds. Hierarchical clustering based on the expression data of shared genes demonstrated an almost identical profile in nutraceutical-treated stimulated cells which was virtually opposite in cells exposed to stimuli alone. Downstream enrichment analyses of the co-modified genes uncovered significant associations with cancer-related transcription factors as well as terms of Gene Ontology/Reactome Pathways and highlighted ECM dynamics as a nodal modulation point by nutraceuticals along with angiogenesis, inflammation, cell motility and growth. RNA-seq data for selected genes were independently confirmed by RT-qPCR. Overall, the present systems approach provides novel evidence stepping up the mechanistic understanding of test nutraceuticals, thus rationalizing their clinical exploitation in new preventive/therapeutic modalities against HCC. © 2020 The Author

Mastic oil inhibits the metastatic phenotype of mouse lung adenocarcinoma cells

Mastic oil from Pistacia lentiscus variation chia, a natural combination of bioactive terpenes, has been shown to exert anti-tumor growth effects against a broad spectrum of cancers including mouse Lewis lung adenocarcinomas (LLC). However, no studies have addressed its anti-metastatic actions. In this study, we showed that treatment of LLC cells with mastic oil within a range of non-toxic concentrations (0.01-0.04% v/v): (a) abrogated their Matrigel invasion and migration capabilities in transwell assays; (b) reduced the levels of secreted MMP-2; (c) restricted phorbol ester-induced actin remodeling and (d) limited the length of neo-vessel networks in tumor microenvironment in the model of chick embryo chorioallantoic membrane. Moreover, exposure of LLC and endothelial cells to mastic oil impaired their adhesive interactions in a co-culture assay and reduced the expression of key adhesion molecules by endothelial cells upon their stimulation with tumor necrosis factor-alpha. Overall, this study provides novel evidence supporting a multipotent role for mastic oil in prevention of crucial processes related to cancer metastasis. © 2011 by the authors; licensee MDPI, Basel, Switzerland