Machine-learning Modeling for Personalized Immunotherapy- An Evaluation Module

Immune-cell therapy and targeting therapy are in rapid development to treat tumor diseases. However, current immune-cell therapy and targeting immunotherapy often face three challenges (three Ss): safety challenges such as cytokine releasing syndrome (C.R.S.); specificity targeting problems such as low efficacy caused by off-targeting tumor cells; unsatisfying payment are confounded to clinical patients and physicians. We have been studying immunotherapy for more than thirty years, and recently, personalized immunotherapy to treat tumor disease has been proposed. After we discovered quiescent genes from immune cells within the tumor microenvironment, we set up single-cell genomics analysis, studying heterogeneous immune responses from multiple tumor antigens (neo-antigen); here, we further introduce a new generation of immunotherapy module by using a machine-learning model to assess optimal immunotherapy. The machine-learning model combined with single-cell genomic analysis can predict optimal immune-cell (such as T-cells) and other optimal targeting drugs such as PD1 and CTLA4 inhibitors for the patient to use.

Pathophysiological pathways related to high plasma GDF-15 concentrations in patients with heart failure

AIMS

Elevated concentrations of Growth Differentiation factor 15 (GDF-15) in patients with heart failure (HF) have been consistently associated with worse clinical outcomes, but what disease mechanisms high GDF-15 concentrations represent remains unclear. Here, we aim to identify activated pathophysiological pathways related to elevated GDF-15 expression in patients with HF.

METHODS AND RESULTS

In 2279 patients with HF, we measured circulating levels of 363 biomarkers. Then, we performed a pathway over-representation analysis to identify key biological pathways between patients in the highest and lowest GDF-15 concentration quartiles. Data were validated in an independent cohort of 1705 patients with HF. In both cohorts, the strongest up-regulated biomarkers in those with high GDF-15 were fibroblast growth factor 23 (FGF-23), death receptor 5 (TRAIL-R2), WNT1-inducible-signaling pathway protein 1 (WISP-1), TNF Receptor Superfamily Member 11a (TNFRSF11A), leukocyte immunoglobulin-like receptor subfamily B member 4 (LILRB4), and Trefoil Factor 3 (TFF3). Pathway over-representation analysis revealed that high GDF-15 patients had increased activity of pathways related to inflammatory processes, notably positive regulation of chemokine production; response to interleukin 6 (IL-6); tumour necrosis factor (TNF) and death receptor activity; and positive regulation of T cell differentiation and inflammatory response. Furthermore, we found pathways involved in regulation of insulin-like growth factor (IGF) receptor signalling and regulatory pathways of tissue, bones, and branching structures. GDF-15 quartiles significantly predicted all-cause mortality and HF hospitalization.

CONCLUSION

Patients with HF and high plasma concentrations of GDF-15 are characterized by increased activation of inflammatory pathways and pathways related to IGF-1 regulation and bone/tissue remodelling.

Pathway Enrichment Analysis of Microarray Data Fom Human Penis of Diabetic and Peyronie's Patients, in Comparison with Diabetic Rat Erectile Dysfunction Models

BACKGROUND

Erectile dysfunction (ED) is a debilitating medical condition in which current treatments are minimally effective in diabetic patients due to neuropathy of the cavernous nerve, a peripheral nerve that innervates the penis. Loss of innervation causes apoptosis of penile smooth muscle, remodeling of corpora cavernosa (penile erectile tissue) morphology, and ED.

AIM

In this study, microarray and pathway analysis were used to obtain a global understanding of how signaling mechanisms are altered in diabetic patients and animal models as ED develops, in order to identify novel targets for disease management, and points of intervention for clinical therapy development.

METHODS AND OUTCOMES

Human corpora cavernosal tissue was obtained from diabetic (n = 4) and Peyronie's (control, n = 3) patients that were undergoing prosthesis implant to treat ED, and BB/WOR diabetic (n = 5) and resistant (n = 5) rats. RNA was extracted using TRIzol, DNase treated, and purified by Qiagen mini kit. Microarray was performed using the Human Gene 2.0 ST Array. (i) Alterations in patient and diabetic rat pathway signaling were examined using several analytical tools (ShinyGO, Metascape, WebGestalt, STRING) and databases, (ii) Strengths/weaknesses of the different pathway analysis tools were compared, and (iii) Comparison of human and rat (BB/WOR and Streptozotocin) pathway analysis was performed. Two technical replicates were performed. P value (FDR) < .15 was used as threshold for differential expression. FDR < 0.05 was considered significant.

RESULTS

Microarray identified 182 differentially expressed protein-coding genes. Pathway analysis revealed similar enrichments with different analytical tools. Down regulated pathways include development, tubular structure, sprouting, cell death, ischemia, angiogenesis, transcription, second messengers, and stem cell differentiation. ED patients, who have diabetes, incur significant loss of normal regulatory processes required for repair and replacement of injured corpora cavernosal tissue. Combined with loss of apoptotic regulatory mechanisms, this results in significant architectural remodeling of the corpora cavernosa, and loss of regenerative capacity in the penis.

CLINICAL TRANSLATION

This first report of microarray and pathway analysis in human corpora cavernosa, is critical for identification of novel pathways pertinent to ED and for validating animal models.

STRENGTHS AND LIMITATIONS

The analysis of tissue specific gene expression profiles provides a means of understanding drivers of disease and identifying novel pathways for clinical intervention.

CONCLUSION

Penis from diabetic ED patients lacks capacity for maintenance of corpora cavernosal architecture and regeneration, which are critical points for intervention for therapy development.

Graph Algorithms for Condensing and Consolidating Gene Set Analysis Results

Gene set analysis plays a critical role in the functional interpretation of omics data. Although this is typically done for one omics experiment at a time, there is an increasing need to combine gene set analysis results from multiple experiments performed on the same or different omics platforms, such as in multi-omics studies. Integrating results from multiple experiments is challenging, and annotation redundancy between gene sets further obscures clear conclusions. We propose to use a weighted set cover algorithm to reduce redundancy of gene sets identified in a single experiment. Next, we use affinity propagation to consolidate similar gene sets identified from multiple experiments into clusters and to automatically determine the most representative gene set for each cluster. Using three examples from over representation analysis and gene set enrichment analysis, we showed that weighted set cover outperformed a previously published set cover method and reduced the number of gene sets by 52-77%. Focusing on overlapping genes between the list of input genes and the enriched gene sets in over-representation analysis and leading-edge genes in gene set enrichment analysis further reduced the number of gene sets. A use case combining enrichment analysis results from RNA-Seq and proteomics data comparing basal and luminal A breast cancer samples highlighted the known difference in proliferation and DNA damage response. Finally, we used these algorithms for a pan-cancer survival analysis. Our analysis clearly revealed prognosis-related pathways common to multiple cancer types or specific to individual cancer types, as well as pathways associated with prognosis in different directions in different cancer types. We implemented these two algorithms in an R package, Sumer, which generates tables and static and interactive plots for exploration and publication. Sumer is publicly available at https://github.com/bzhanglab/sumer.

TCPA v3.0: An Integrative Platform to Explore the Pan-Cancer Analysis of Functional Proteomic Data

Reverse-phase protein arrays represent a powerful functional proteomics approach to characterizing cell signaling pathways and understanding their effects on cancer development. Using this platform, we have characterized ∼8,000 patient samples of 32 cancer types through The Cancer Genome Atlas and built a widely used, open-access bioinformatic resource, The Cancer Proteome Atlas (TCPA). To maximize the utility of TCPA, we have developed a new module called "TCGA Pan-Cancer Analysis," which provides comprehensive protein-centric analyses that integrate protein expression data and other TCGA data across cancer types. We further demonstrate the value of this module by examining the correlations of RPPA proteins with significantly mutated genes, assessing the predictive power of somatic copy-number alterations, DNA methylation, and mRNA on protein expression, inferring the regulatory effects of miRNAs on protein expression, constructing a co-expression network of proteins and pathways, and identifying clinically relevant protein markers. This upgraded TCPA (v3.0) will provide the cancer research community with a more powerful tool for studying functional proteomics and making translational impacts.

Cathepsin L Regulates Metabolic Networks Controlling Rapid Cell Growth and Proliferation

Rapidly proliferating cells reshape their metabolism to satisfy their ever-lasting need for cellular building blocks. This phenomenon is exemplified in certain malignant conditions such as cancer but also during embryonic development when cells rely heavily on glycolytic metabolism to exploit its metabolic intermediates for biosynthetic processes. How cells reshape their metabolism is not fully understood. Here we report that loss of cathepsin L (Cts L) is associated with a fast proliferation rate and enhanced glycolytic metabolism that depend on lactate dehydrogenase A (LDHA) activity. Using mass spectrometry analysis of cells treated with a pan cathepsin inhibitor, we observed an increased abundance of proteins involved in central carbon metabolism. Further inspection of putative Cts L targets revealed an enrichment for glycolytic metabolism that was independently confirmed by metabolomic and biochemical analyses. Moreover, proteomic analysis of Cts L-knockout cells identified LDHA overexpression that was demonstrated to be a key metabolic junction in these cells. Lastly, we show that Cts L inhibition led to increased LDHA protein expression, suggesting a causal relationship between LDHA expression and function. In conclusion, we propose that Cts L regulates this metabolic circuit to keep cell division under control, suggesting the therapeutic potential of targeting this protein and its networks in cancer.

Integrated Analysis of Transcriptomic, miRNA and Proteomic Changes of a Novel Hybrid Yellow Catfish Uncovers Key Roles for miRNAs in Heterosis

Heterosis is a complex biological phenomenon in which hybridization produces offspring that exhibit superior phenotypic characteristics compared with the parents. Heterosis is widely utilized in agriculture, for example in fish farming; however, its underlying molecular basis remains elusive. To gain a comprehensive and unbiased molecular understanding of fish heterosis, we analyzed the mRNA, miRNA, and proteomes of the livers of three catfish species, Pelteobagrus fulvidraco, P. vachelli, and their hybrid, the hybrid yellow catfish "Huangyou-1" (P. fulvidraco ♀ × P. vachelli ♂). Using next-generation sequencing and mass spectrometry, we show that the nonadditive, homoeolog expression bias and expression level dominance pattern were readily identified at the transcriptional, post-transcriptional, or protein levels, providing the evidence for the widespread presence of dominant models during hybridization. A number of predicted miRNA-mRNA-protein pairs were found and validated by qRT-PCR and PRM assays. Furthermore, several diverse key pathways were identified, including immune defense, metabolism, digestion and absorption, and cell proliferation and development, suggesting the vital mechanisms involved in the generation of the heterosis phenotype in progenies. We propose that the high parental expression of genes/proteins (growth, nutrition, feeding, and disease resistance) coupled with low parental miRNAs of the offspring, are inherited from the mother or father, thus indicating that the offspring were enriched with the advantages of the father or mother. We provide new and important information about the molecular mechanisms of heterosis, which represents a significant step toward a more complete elucidation of this phenomenon.

Quantitative Microproteomics Based Characterization of the Central and Peripheral Nervous System of a Mouse Model of Krabbe Disease

Krabbe disease is a rare, childhood lysosomal storage disorder caused by a deficiency of galactosylceramide beta-galactosidase (GALC). The major effect of GALC deficiency is the accumulation of psychosine in the nervous system and widespread degeneration of oligodendrocytes and Schwann cells, causing rapid demyelination. The molecular mechanisms of Krabbe disease are not yet fully elucidated and a definite cure is still missing. Here we report the first in-depth characterization of the proteome of the Twitcher mouse, a spontaneous mouse model of Krabbe disease, to investigate the proteome changes in the Central and Peripheral Nervous System. We applied a TMT-based workflow to compare the proteomes of the corpus callosum, motor cortex and sciatic nerves of littermate homozygous Twitcher and wild-type mice. More than 400 protein groups exhibited differences in expression and included proteins involved in pathways that can be linked to Krabbe disease, such as inflammatory and defense response, lysosomal proteins accumulation, demyelination, reduced nervous system development and cell adhesion. These findings provide new insights on the molecular mechanisms of Krabbe disease, representing a starting point for future functional experiments to study the molecular pathogenesis of Krabbe disease. Data are available via ProteomeXchange with identifier PXD010594.

Unanchored ubiquitin chains do not lead to marked alterations in gene expression in Drosophila melanogaster

The small protein modifier ubiquitin regulates various aspects of cellular biology through its chemical conjugation onto proteins. Ubiquitination of proteins presents itself in numerous iterations, from a single mono-ubiquitination event to chains of poly-ubiquitin. Ubiquitin chains can be attached onto other proteins or can exist as unanchored species, i.e. free from another protein. Unanchored ubiquitin chains are thought to be deleterious to the cell and rapidly disassembled into mono-ubiquitin. We recently examined the toxicity and utilization of unanchored poly-ubiquitin in Drosophila melanogaster. We found that free poly-ubiquitin species are largely innocuous to flies and that free poly-ubiquitin can be controlled by being degraded by the proteasome or by being conjugated onto another protein as a single unit. Here, to explore whether an organismal defense is mounted against unanchored chains, we conducted RNA-Seq analyses to examine the transcriptomic impact of free poly-ubiquitin in the fly. We found ∼90 transcripts whose expression is altered in the presence of different types of unanchored poly-ubiquitin. The set of genes identified was essentially devoid of ubiquitin-, proteasome-, or autophagy-related components. The seeming absence of a large and multipronged response to unanchored poly-ubiquitin supports the conclusion that these species need not be toxic in vivo and underscores the need to re-examine the role of free ubiquitin chains in the cell.

Summary: Our Drosophila studies indicate the lack of a marked, coordinated response towards unanchored poly-ubiquitin in flies, suggesting that untethered ubiquitin chains are not necessarily problematic in intact organisms.

A Curated Resource for Phosphosite-specific Signature Analysis

Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM data sets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level because of the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kinase activities and signaling pathways curated from more than 2,500 publications. We adapted the widely used single sample Gene Set Enrichment Analysis approach to utilize PTMsigDB, enabling PTMSignature Enrichment Analysis (PTM-SEA) of quantitative MS data. We used a well-characterized data set of epidermal growth factor (EGF)-perturbed cancer cells to evaluate our approach and demonstrated better representation of signaling events compared with gene-centric methods. We then applied PTM-SEA to analyze the phosphoproteomes of cancer cells treated with cell-cycle inhibitors and detected mechanism-of-action specific signatures of cell cycle kinases. We also applied our methods to analyze the phosphoproteomes of PI3K-inhibited human breast cancer cells and detected signatures of compounds inhibiting PI3K as well as targets downstream of PI3K (AKT, MAPK/ERK) covering a substantial fraction of the PI3K pathway. PTMsigDB and PTM-SEA can be freely accessed at https://github.com/broadinstitute/ssGSEA2.0.

Carcinogenic Helicobacter pylori Strains Selectively Dysregulate the In Vivo Gastric Proteome, Which May Be Associated with Stomach Cancer Progression

Helicobacter pylori is the strongest risk factor for gastric cancer. Initial interactions between H. pylori and its host originate at the microbial-gastric epithelial cell interface, and contact between H. pylori and gastric epithelium activates signaling pathways that drive oncogenesis. One microbial constituent that increases gastric cancer risk is the cag pathogenicity island, which encodes a type IV secretion system that translocates the effector protein, CagA, into host cells. We previously demonstrated that infection of Mongolian gerbils with a carcinogenic cag+H. pylori strain, 7.13, recapitulates many features of H. pylori-induced gastric cancer in humans. Therefore, we sought to define gastric proteomic changes induced by H. pylori that are critical for initiation of the gastric carcinogenic cascade. Gastric cell scrapings were harvested from H. pylori-infected and uninfected gerbils for quantitative proteomic analyses using isobaric tags for relative and absolute quantitation (iTRAQ). Quantitative proteomic analysis of samples from two biological replicate experiments quantified a total of 2764 proteins, 166 of which were significantly altered in abundance by H. pylori infection. Pathway mapping identified significantly altered inflammatory and cancer-signaling pathways that included Rab/Ras signaling proteins. Consistent with the iTRAQ results, RABEP2 and G3BP2 were significantly up-regulated in vitro, ex vivo in primary human gastric monolayers, and in vivo in gerbil gastric epithelium following infection with H. pylori strain 7.13 in a cag-dependent manner. Within human stomachs, RABEP2 and G3BP2 expression in gastric epithelium increased in parallel with the severity of premalignant and malignant lesions and was significantly elevated in intestinal metaplasia and dysplasia, as well as gastric adenocarcinoma, compared with gastritis alone. These results indicate that carcinogenic strains of H. pylori induce dramatic and specific changes within the gastric proteome in vivo and that a subset of altered proteins within pathways with oncogenic potential may facilitate the progression of gastric carcinogenesis in humans.

microRNA-222 Attenuates Mitochondrial Dysfunction During Transmissible Gastroenteritis Virus Infection

Transmissible gastroenteritis virus (TGEV) is a member of Coronaviridae family. Our previous research showed that TGEV infection could induce mitochondrial dysfunction and upregulate miR-222 level. Therefore, we presumed that miR-222 might be implicated in regulating mitochondrial dysfunction induced by TGEV infection. To verify the hypothesis, the effect of miR-222 on mitochondrial dysfunction was tested and we showed that miR-222 attenuated TGEV-induced mitochondrial dysfunction. To investigate the underlying molecular mechanism of miR-222 in TGEV-induced mitochondrial dysfunction, a quantitative proteomic analysis of PK-15 cells that were transfected with miR-222 mimics and infected with TGEV was performed. In total, 4151 proteins were quantified and 100 differentially expressed proteins were obtained (57 upregulated, 43 downregulated), among which thrombospondin-1 (THBS1) and cluster of differentiation 47 (CD47) were downregulated. THBS1 was identified as the target of miR-222. Knockdown of THBS1 and CD47 decreased mitochondrial Ca2+ level and increased mitochondrial membrane potential (MMP) level. Reversely, overexpression of THBS1 and CD47 elevated mitochondrial Ca2+ level and reduced mitochondrial membrane potential (MMP) level. Together, our data establish a significant role of miR-222 in regulating mitochondrial dysfunction in response to TGEV infection.

Doxorubicin-induced DNA Damage Causes Extensive Ubiquitination of Ribosomal Proteins Associated with a Decrease in Protein Translation

Protein posttranslational modifications (PTMs) play a central role in the DNA damage response. In particular, protein phosphorylation and ubiquitination have been shown to be essential in the signaling cascade that coordinates break repair with cell cycle progression. Here, we performed whole-cell quantitative proteomics to identify global changes in protein ubiquitination that are induced by DNA double-strand breaks. In total, we quantified more than 9,400 ubiquitin sites and found that the relative abundance of ∼10% of these sites was altered in response to DNA double-strand breaks. Interestingly, a large proportion of ribosomal proteins, including those from the 40S as well as the 60S subunit, were ubiquitinated in response to DNA damage. In parallel, we discovered that DNA damage leads to the inhibition of ribosome function. Taken together, these data uncover the ribosome as a major target of the DNA damage response.

Integrated Analysis of Quantitative Proteome and Transcriptional Profiles Reveals the Dynamic Function of Maternally Expressed Proteins After Parthenogenetic Activation of Buffalo Oocyte

Maternal-effect genes are especially critical for early embryonic development after fertilization and until massive activation of the embryonic genome occurs. By applying a tandem mass tag (TMT)-labeled quantitative proteomics combined with RNA sequencing approach, the proteome of the buffalo was quantitatively analyzed during parthenogenesis of mature oocytes and the two-cell stage embryo. Of 1908 quantified proteins, 123 differed significantly. The transcriptome was analyzed eight stages (GV, MII, 2-cell, 4-cell, 8-cell, 16-cell, morula, blastocyst) of Buffalo using the RNA sequencing approach, and a total of 3567 unique genes were identified to be differently expressed between all consecutive stages of pre-implantation development. Validation of proteomics results (TUBB3, CTNNA1, CDH3, MAP2K1), which are involved in tight junction and gap junction, revealing that the maternal expression of the proteins possibly plays a role in the formation of cellular junctions firstly after parthenogenetic activation. Correlation and hierarchical analyses of transcriptional profiles and the expression of NPM2 and NLRP5 mRNA of buffalo in vitro developed oocytes and parthenogenetic embryos indicated that the "maternal-to-zygotic transition" (MZT) process might exist in the model of parthenogenesis, which is similar to a normally fertilized embryo, and may occur between the 8-cell to 16-cell stage. These data provide a rich resource for further studies on maternal proteins and genes and are conducive to improving nuclear transfer technology.

Differentiation among prostate cancer patients with Gleason score of 7 using histopathology whole-slide image and genomic data

Prostate cancer is the most common non-skin related cancer affecting 1 in 7 men in the United States. Treatment of patients with prostate cancer still remains a difficult decision-making process that requires physicians to balance clinical benefits, life expectancy, comorbidities, and treatment-related side effects. Gleason score (a sum of the primary and secondary Gleason patterns) solely based on morphological prostate glandular architecture has shown as one of the best predictors of prostate cancer outcome. Significant progress has been made on molecular subtyping prostate cancer delineated through the increasing use of gene sequencing. Prostate cancer patients with Gleason score of 7 show heterogeneity in recurrence and survival outcomes. Therefore, we propose to assess the correlation between histopathology images and genomic data with disease recurrence in prostate tumors with a Gleason 7 score to identify prognostic markers. In the study, we identify image biomarkers within tissue WSIs by modeling the spatial relationship from automatically created patches as a sequence within WSI by adopting a recurrence network model, namely long short-term memory (LSTM). Our preliminary results demonstrate that integrating image biomarkers from CNN with LSTM and genomic pathway scores, is more strongly correlated with patients recurrence of disease compared to standard clinical markers and engineered image texture features. The study further demonstrates that prostate cancer patients with Gleason score of 4+3 have a higher risk of disease progression and recurrence compared to prostate cancer patients with Gleason score of 3+4.

WITHDRAWN: Heralds of parallel MS: Data-independent acquisition surpassing sequential identification of data dependent acquisition in proteomics

This article has been withdrawn by the authors. This article did not comply with the editorial guidelines of MCP. Specifically, single peptide based protein identifications of 9-19% were included in the analysis and discussed in the results and conclusions. We wish to withdraw this article and resubmit a clarified, corrected manuscript for review.

Core Canonical Pathways Involved in Developing Human Glioblastoma Multiforme (GBM)

Glioblastoma multiforme (GBM) is the most common and aggressive type of the primary brain tumors with pathologic hallmarks of necrosis and vascular proliferation. The diagnosis of GBM is currently mostly based on histological examination of brain tumor tissues, after radiological characterization and surgical biopsy. The ability to characterize tumors comprehensively at the molecular level raises the possibility that diagnosis can be made based on molecular profiling with or without histological examination, rather than solely on histological phenotype. The development of novel genomic and proteomic techniques will foster in the identification of such diagnostic and prognostic molecular markers. We analyzed the global differential gene expression of a GBM cell line HTB15 in comparison to normal human Astrocytes, and established a few canonical pathways that are important in determining the molecular mechanisms of cancer using global gene expression microarray, coupled with the Ingenuity Pathway Analysis (IPA®). Overall, we revealed a discrete gene expression profile in the experimental model that resembled progression of GBM cancer. The canonical pathway analysis showed the involvement of genes that differentially expressed in such a disease condition that included Inositol pathway, Polo like kinases, nNOS signaling, and Tetrapyrrole biosynthesis. Our findings established that the gene expression pattern of this dreaded brain cancer will probably help the cancer research community by finding out newer therapeutic strategies to combat this dreaded cancer type that leads to the identification of high-risk population in this category, with almost hundred percent mortality rate.

MAPK/ERK signaling pathway-induced hyper-O-GlcNAcylation enhances cancer malignancy. Mol Cell Biochem. 2015;410:101-110. [PMID: 26318312 DOI: 10.1007/s11010-015-2542-8]

Dysregulated MAPK/ERK signaling is implicated in one-third of human tumors and represents an attractive target for the development of anticancer drugs. Similarly, elevated protein O-GlcNAcylation and O-GlcNAc transferase (OGT) are detected in various cancers and serve as attractive novel cancer-specific therapeutic targets. However, the potential connection between them remains unexplored. Here, a positive correlation was found between the activated MAPK/ERK signaling and hyper-O-GlcNAcylation in various cancer types and inhibition of the MAPK/ERK signaling by 10 µM U0126 significantly decreased the expression of OGT and O-GlcNAcylation in H1299, BPH-1 and DU145 cells; then, the pathway analysis of the potential regulators of OGT obtained from the UCSC Genome Browser was done, and ten downstream targets of ERK pathway were uncovered; the following results showed that ELK1, one of the ten targets of ERK pathway, mediated ERK signaling-induced OGT upregulation; finally, the MTT assay and the soft agar assay showed that the inhibition of MAPK/ERK signaling reduced the promotion effect of hyper-O-GlcNAcylation on cancer cell proliferation and anchorage-independent growth. Taken together, our data originally provided evidence for the regulatory mechanism of hyper-O-GlcNAcylation in tumors, which will be helpful for the development of anticancer drugs targeting to hyper-O-GlcNAcylation. This study also provided a new mechanism by which MAPK/ERK signaling-enhanced cancer malignancy. Altogether, the recently discovered oncogenic factor O-GlcNAc was linked to the classical MAPK/ERK signaling which is essential for the maintenance of malignant phenotype of cancers.

Alcohol Dependence Genetics: Lessons Learned From Genome-Wide Association Studies (GWAS) and Post-GWAS Analyses

BACKGROUND

Alcohol dependence (AD) is a complex psychiatric disorder and a significant public health problem. Twin and family-based studies have consistently estimated its heritability to be approximately 50%, and many studies have sought to identify specific genetic variants associated with susceptibility to AD. These studies have been primarily linkage or candidate gene based and have been mostly unsuccessful in identifying replicable risk loci. Genome-wide association studies (GWAS) have improved the detection of specific loci associated with complex traits, including AD. However, findings from GWAS explain only a small proportion of phenotypic variance, and alternative methods have been proposed to investigate the associations that do not meet strict genome-wide significance criteria.

METHODS

This review summarizes all published AD GWAS and post-GWAS analyses that have sought to exploit GWAS data to identify AD-associated loci.

RESULTS

Findings from AD GWAS have been largely inconsistent, with the exception of variants encoding the alcohol-metabolizing enzymes. Analyses of GWAS data that go beyond standard association testing have demonstrated the polygenic nature of AD and the large contribution of common variants to risk, nominating novel genes and pathways for AD susceptibility.

CONCLUSIONS

Findings from AD GWAS and post-GWAS analyses have greatly increased our understanding of the genetic etiology of AD. However, it is clear that larger samples will be necessary to detect loci in addition to those that encode alcohol-metabolizing enzymes, which may only be possible through consortium-based efforts. Post-GWAS approaches to studying the genetic influences on AD are increasingly common and could greatly increase our knowledge of both the genetic architecture of AD and the specific genes and pathways that influence risk.