An integrated analysis of the cancer genome atlas data discovers a hierarchical association structure across thirty three cancer types.

Cancer cells harbor molecular alterations at all levels of information processing. Genomic/epigenomic and transcriptomic alterations are inter-related between genes, within and across cancer types and may affect clinical phenotypes. Despite the abundant prior studies of integrating cancer multi-omics data, none of them organizes these associations in a hierarchical structure and validates the discoveries in extensive external data. We infer this Integrated Hierarchical Association Structure (IHAS) from the complete data of The Cancer Genome Atlas (TCGA) and compile a compendium of cancer multi-omics associations. Intriguingly, diverse alterations on genomes/epigenomes from multiple cancer types impact transcriptions of 18 Gene Groups. Half of them are further reduced to three Meta Gene Groups enriched with (1) immune and inflammatory responses, (2) embryonic development and neurogenesis, (3) cell cycle process and DNA repair. Over 80% of the clinical/molecular phenotypes reported in TCGA are aligned with the combinatorial expressions of Meta Gene Groups, Gene Groups, and other IHAS subunits. Furthermore, IHAS derived from TCGA is validated in more than 300 external datasets including multi-omics measurements and cellular responses upon drug treatments and gene perturbations in tumors, cancer cell lines, and normal tissues. To sum up, IHAS stratifies patients in terms of molecular signatures of its subunits, selects targeted genes or drugs for precision cancer therapy, and demonstrates that associations between survival times and transcriptional biomarkers may vary with cancer types. These rich information is critical for diagnosis and treatments of cancers.

Integrative pathway enrichment analysis of multivariate omics data.

Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations.

Analysis of spatial-temporal gene expression patterns reveals dynamics and regionalization in developing mouse brain.

Allen Brain Atlas (ABA) provides a valuable resource of spatial/temporal gene expressions in mammalian brains. Despite rich information extracted from this database, current analyses suffer from several limitations. First, most studies are either gene-centric or region-centric, thus are inadequate to capture the superposition of multiple spatial-temporal patterns. Second, standard tools of expression analysis such as matrix factorization can capture those patterns but do not explicitly incorporate spatial dependency. To overcome those limitations, we proposed a computational method to detect recurrent patterns in the spatial-temporal gene expression data of developing mouse brains. We demonstrated that regional distinction in brain development could be revealed by localized gene expression patterns. The patterns expressed in the forebrain, medullary and pontomedullary, and basal ganglia are enriched with genes involved in forebrain development, locomotory behavior, and dopamine metabolism respectively. In addition, the timing of global gene expression patterns reflects the general trends of molecular events in mouse brain development. Furthermore, we validated functional implications of the inferred patterns by showing genes sharing similar spatial-temporal expression patterns with Lhx2 exhibited differential expression in the embryonic forebrains of Lhx2 mutant mice. These analysis outcomes confirm the utility of recurrent expression patterns in studying brain development.

Putative effectors for prognosis in lung adenocarcinoma are ethnic and gender specific.

Lung adenocarcinoma possesses distinct patterns of EGFR/KRAS mutations between East Asian and Western, male and female patients. However, beyond the well-known EGFR/KRAS distinction, gender and ethnic specific molecular aberrations and their effects on prognosis remain largely unexplored. Association modules capture the dependency of an effector molecular aberration and target gene expressions. We established association modules from the copy number variation (CNV), DNA methylation and mRNA expression data of a Taiwanese female cohort. The inferred modules were validated in four external datasets of East Asian and Caucasian patients by examining the coherence of the target gene expressions and their associations with prognostic outcomes. Modules 1 (cis-acting effects with chromosome 7 CNV) and 3 (DNA methylations of UBIAD1 and VAV1) possessed significantly negative associations with survival times among two East Asian patient cohorts. Module 2 (cis-acting effects with chromosome 18 CNV) possessed significantly negative associations with survival times among the East Asian female subpopulation alone. By examining the genomic locations and functions of the target genes, we identified several putative effectors of the two cis-acting CNV modules: RAC1, EGFR, CDK5 and RALBP1. Furthermore, module 3 targets were enriched with genes involved in cell proliferation and division and hence were consistent with the negative associations with survival times. We demonstrated that association modules in lung adenocarcinoma with significant links of prognostic outcomes were ethnic and/or gender specific. This discovery has profound implications in diagnosis and treatment of lung adenocarcinoma and echoes the fundamental principles of the personalized medicine paradigm.

Suppression of the SOX2 neural effector gene by PRDM1 promotes human germ cell fate in embryonic stem cells.

The mechanisms of transcriptional regulation underlying human primordial germ cell (PGC) differentiation are largely unknown. The transcriptional repressor Prdm1/Blimp-1 is known to play a critical role in controlling germ cell specification in mice. Here, we show that PRDM1 is expressed in developing human gonads and contributes to the determination of germline versus neural fate in early development. We show that knockdown of PRDM1 in human embryonic stem cells (hESCs) impairs germline potential and upregulates neural genes. Conversely, ectopic expression of PRDM1 in hESCs promotes the generation of cells that exhibit phenotypic and transcriptomic features of early PGCs. Furthermore, PRDM1 suppresses transcription of SOX2. Overexpression of SOX2 in hESCs under conditions favoring germline differentiation skews cell fate from the germline to the neural lineage. Collectively, our results demonstrate that PRDM1 serves as a molecular switch to modulate the divergence of neural or germline fates through repression of SOX2 during human development.

An integrative characterization of recurrent molecular aberrations in glioblastoma genomes.

Glioblastoma multiforme (GBM) is the most common and malignant primary brain tumor in adults. Decades of investigations and the recent effort of the Cancer Genome Atlas (TCGA) project have mapped many molecular alterations in GBM cells. Alterations on DNAs may dysregulate gene expressions and drive malignancy of tumors. It is thus important to uncover causal and statistical dependency between 'effector' molecular aberrations and 'target' gene expressions in GBMs. A rich collection of prior studies attempted to combine copy number variation (CNV) and mRNA expression data. However, systematic methods to integrate multiple types of cancer genomic data-gene mutations, single nucleotide polymorphisms, CNVs, DNA methylations, mRNA and microRNA expressions and clinical information-are relatively scarce. We proposed an algorithm to build 'association modules' linking effector molecular aberrations and target gene expressions and applied the module-finding algorithm to the integrated TCGA GBM data sets. The inferred association modules were validated by six tests using external information and datasets of central nervous system tumors: (i) indication of prognostic effects among patients; (ii) coherence of target gene expressions; (iii) retention of effector-target associations in external data sets; (iv) recurrence of effector molecular aberrations in GBM; (v) functional enrichment of target genes; and (vi) co-citations between effectors and targets. Modules associated with well-known molecular aberrations of GBM-such as chromosome 7 amplifications, chromosome 10 deletions, EGFR and NF1 mutations-passed the majority of the validation tests. Furthermore, several modules associated with less well-reported molecular aberrations-such as chromosome 11 CNVs, CD40, PLXNB1 and GSTM1 methylations, and mir-21 expressions-were also validated by external information. In particular, modules constituting trans-acting effects with chromosome 11 CNVs and cis-acting effects with chromosome 10 CNVs manifested strong negative and positive associations with survival times in brain tumors. By aligning the information of association modules with the established GBM subclasses based on transcription or methylation levels, we found each subclass possessed multiple concurrent molecular aberrations. Furthermore, the joint molecular characteristics derived from 16 association modules had prognostic power not explained away by the strong biomarker of CpG island methylator phenotypes. Functional and survival analyses indicated that immune/inflammatory responses and epithelial-mesenchymal transitions were among the most important determining processes of prognosis. Finally, we demonstrated that certain molecular aberrations uniquely recurred in GBM but were relatively rare in non-GBM glioma cells. These results justify the utility of an integrative analysis on cancer genomes and provide testable characterizations of driver aberration events in GBM.

Functional proteomics reveals the protective effects of saffron ethanolic extract on hepatic ischemia-reperfusion injury.

Hepatic ischemia-reperfusion (IR) injury is a common clinical problem and ROS may be a contributing factor on IR injury. The current study evaluates the potential protective effect of saffron ethanol extract (SEE) in a rat model upon hepatic IR injury. Caspases 3 and terminal deoxynucleotidyl transferase-mediated dUTP biotin nick end labeling (TUNEL) results showed increased cell death in the IR samples; reversely, minor apoptosis was detected in the SEE/IR group. Pretreatment with SEE significantly restored the content of antioxidant enzymes (SOD1 and catalase) and remarkably inhibited the intracellular ROS concentration in terms of reducing p47phox translocation. Proteome tools revealed that 20 proteins were significantly modulated in protein intensity between IR and SEE/IR groups. Particularly, SEE administration could attenuate the carbonylation level of several chaperone proteins. Network analysis suggested that saffron extract could alleviate IR-induced ER stress and protein ubiquitination, which finally lead to cell apoptosis. Taken together, SEE could reduce hepatic IR injury through modulating protein oxidation and our results might help to develop novel therapeutic strategies against ROS-caused diseases.

Functional proteomics reveals hepatotoxicity and the molecular mechanisms of different forms of chromium delivered by skin administration.

Chromium compounds are known to be associated with cytotoxicity and carcinogenicity when applied via the skin. However, there is no perspective research to elucidate the causations between chromium exposure and hepatotoxicity. In the present study, the impact of hexavalent/trivalent chromium on the liver and the underlying pathogenic processes were revealed in the female nude mice model. The liver damage under different treatments was evaluated by histologic examination. Functional proteome tools combined with a network analysis revealed statistically significant candidate protein networks predicted to be changed in the presence of chromium compounds. RNA interference-mediated silencing and immunohistochemistry were used to confirm whether the candidate protein was capable of resulting in hepatotoxicity elicited by chromium. Potassium chromate as the Cr(VI) compound generated greater oxidative stress, apoptosis and hepatotoxicity compared to chromium nitrate [Cr(III)]-treated samples. The most meaningful changes were observed amongst proteins involved in carbohydrate metabolism, endoplasmic reticulum (ER) stress, calcium homeostasis and apoptosis. Furthermore, abrogation of transitional ER ATPase (VCP) led to significant inhibition in hepatic cell viability under Cr(VI) administration, and the expression profiles of cytokeratin were closely correlated with apoptotic degrees of liver tissue. Collectively, our findings suggest that Cr(VI) might induce the accumulation of misfolded proteins and adverse effects leading to cell apoptosis and liver injury. These signature networks represent an approach to discover novel relationships in complex data, and functional proteomics of liver may provide solid evidence of chromium-caused hepatic damage via the skin.

Prospective highlights of serum glycoproteins in spontaneous tolerance after orthotopic liver transplantation.

BACKGROUND: We examined the effects and the mechanisms of serum glycoproteins on spontaneous tolerance after orthotopic liver transplantation (OLT) between DA (RT-1(a)) and PVG (RT-1(c)) rats. METHODS: A functional proteome analysis was introduced to investigate differently expressed proteins involved in overcoming major histocompatibility complex (MHC) barriers and lectin blotting was applied to survey the levels of fucosylated proteins. RESULTS: Two-dimensional difference gel electrophoresis (2D-DIGE) coupled with mass spectrometry revealed statistically significant changes in the intensity of 19 proteins at 14 and 60 post-OLT days which respectively corresponded to rejection and tolerance. An interaction network analysis of the identified proteins indicated that the interleukin (IL)-6 signaling pathway might be correlated with the immune events in this model. The peak of IL-6 expression occurred during the recovery period might play a role in the remarkable shifts in the immune response towards spontaneous tolerance. Furthermore, increased levels of IL-6-modulated fucosylation of Igh-6 were also observed during the rejection response while fucosylated hemopexin and haptoglobin were obviously upregulated in the tolerogenic period. CONCLUSIONS: These findings suggest that IL-6 and glycoproteins may play critical roles in this spontaneous tolerogenic DA/PVG OLT model and shed light on prolonging hepatic allograft survival in the future.

Functional proteomic and structural insights into molecular targets related to the growth inhibitory effect of tanshinone IIA on HeLa cells.

Certain antitumor agents have recently been extracted from the roots of Salvia miltiorrhiza Bunge. The diterpene derivative, tanshinone IIA, possesses cytotoxic activity against several human carcinoma cell lines. It also inhibits invasion and metastasis of cancer cells. In the present study, we isolated tanshinone IIA from S. miltiorrhiza, and it exhibited strong growth inhibition against human cervical cancer cells in dose- and time-dependent manners with a 50% cell growth inhibition value of 2.5 microg/mL (8.49 microM). Flow cytometric analysis of cell cycle progression revealed that G(2)/M arrest was initiated after a 24 h exposure to the drug. It also resulted in DNA fragmentation and degradation of poly (ADP-ribose) polymerase indicating that tanshinone IIA may be a potential antitumor agent. Furthermore, we performed a comprehensive proteomic analysis to survey global protein changes induced by tanshinone IIA treatment on HeLa cells. Significant changes in the levels of cytoskeleton proteins as well as stress-associated proteins were observed. Immunoblot analysis and immunofluorescence staining were used to confirm the levels of protein expression. Overexpression of the vimentin rescued these tanshinone IIA-induced events. Computational docking methods indicated that tanshinone IIA could stably bind to the beta-subunit of the microtubule protein. An interaction network analysis of these 12 proteins using MetaCore software suggested that tanshinone IIA treatment regulated the expressions of proteins involved in apoptotic processes, spindle assembly, and p53 activation, including vimentin, Maspin, alpha- and beta-tubulin, and GRP75. Taken together, our results suggest that tanshinone IIA strongly inhibited the growth of cervical cancer cells through interfering in the process of microtubule assembly, leading to G(2)/M phase arrest and sequent apoptosis. The success of this large-scale effort was assessed by a bioinformatics analysis of proteins through predictions of protein domains and possible functional roles. The possible contributions of these proteins to the cytotoxicity of tanshinone IIA provide potential opportunities for the development of cancer therapeutics.