NRF2 Promotes Tumor Maintenance by Modulating mRNA Translation in Pancreatic Cancer.

Pancreatic cancer is a deadly malignancy that lacks effective therapeutics. We previously reported that oncogenic Kras induced the redox master regulator Nfe2l2/Nrf2 to stimulate pancreatic and lung cancer initiation. Here, we show that NRF2 is necessary to maintain pancreatic cancer proliferation by regulating mRNA translation. Specifically, loss of NRF2 led to defects in autocrine epidermal growth factor receptor (EGFR) signaling and oxidation of specific translational regulatory proteins, resulting in impaired cap-dependent and cap-independent mRNA translation in pancreatic cancer cells. Combined targeting of the EGFR effector AKT and the glutathione antioxidant pathway mimicked Nrf2 ablation to potently inhibit pancreatic cancer ex vivo and in vivo, representing a promising synthetic lethal strategy for treating the disease.

Circulating tumor and invasive cell expression profiling predicts effective therapy in pancreatic cancer.

BACKGROUND: Pancreatic adenocarcinoma (PDAC) remains a refractory disease; however, modern cytotoxic chemotherapeutics can induce tumor regression and extend life. A blood-based, pharmacogenomic, chemosensitivity assay using gene expression profiling of circulating tumor and invasive cells (CTICs) to predict treatment response was previously developed. The combination regimen of 5-fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX) and gemcitabine/nab-paclitaxel (G/nab-P) are established frontline approaches for treating advanced PDAC; however, there are no validated biomarkers for treatment selection. A similar unmet need exists for choosing second-line therapy. METHODS: The chemosensitivity assay was evaluated in metastatic PDAC patients presenting for frontline treatment. A prospective study enrolled patients (n = 70) before receiving either FOLFIRINOX or G/nab-P at a 1:1 ratio. Six milliliters of peripheral blood was collected at baseline and at time of disease progression. CTICs were isolated, gene-expression profiling was performed, and the assay was used to predict effective and ineffective chemotherapeutic agents. Treating physicians were blinded to the assay prediction results. RESULTS: Patients receiving an effective regimen as predicted by the chemosensitivity assay experienced significantly longer median progression-free survival (mPFS; 7.8 months vs. 4.2 months; hazard ratio [HR], 0.35; p = .0002) and median overall survival (mOS; 21.0 months vs. 9.7 months; HR, 0.40; p = .005), compared with an ineffective regimen. Assay prediction for effective second-line therapy was explored. The entire study cohort experienced favorable outcomes compared with historical controls, 7.1-month mPFS and 12.3-month mOS. CONCLUSIONS: Chemosensitivity assay profiling is a promising tool for guiding therapy in advanced PDAC. Further prospective validation is under way (clinicaltrials.gov NCT03033927).

Emerging Proteomic Technologies Provide Enormous and Underutilized Potential for Brain Cancer Research.

High-throughput technologies present immense opportunities to characterize brain cancer biology at a systems level. However, proteomic studies of brain cancers are still relatively scarce. Here we discuss the latest proteomic technologies, their application to profiling and quantitation of brain proteomes and how we expect these technologies will be applied to study brain cancer proteomes in the future. Mass spectrometry based proteomics with increased specificity, coverage and throughput will be pervasive in proteomics investigations of brain. Generated data needs to be captured by the curation of databases, and application of creative data analysis strategies is needed to provide meaningful insights into brain functions and associated pathologies. Overall, proteomics applications to brain cancers are in the earliest stages and the expanded use of these technologies holds enormous potential to improve our understanding of brain functions and pathologies.

Quantitative proteomic analysis reveals effects of epidermal growth factor receptor (EGFR) on invasion-promoting proteins secreted by glioblastoma cells.

Glioblastoma multiforme is a highly invasive and aggressive brain tumor with an invariably poor prognosis. The overexpression of epidermal growth factor receptor (EGFR) is a primary influencer of invasion and proliferation in tumor cells and the constitutively active EGFRvIII mutant, found in 30-65% of Glioblastoma multiforme, confers more aggressive invasion. To better understand how EGFR contributes to tumor aggressiveness, we investigated the effect of EGFR on the secreted levels of 65 rationally selected proteins involved in invasion. We employed selected reaction monitoring targeted mass spectrometry using stable isotope labeled internal peptide standards to quantity proteins in the secretome from five GBM (U87) isogenic cell lines in which EGFR, EGFRvIII, and/or PTEN were expressed. Our results show that cell lines with EGFR overexpression and constitutive EGFRvIII expression differ remarkably in the expression profiles for both secreted and intracellular signaling proteins, and alterations in EGFR signaling result in reproducible changes in concentrations of secreted proteins. Furthermore, the EGFRvIII-expressing mutant cell line secretes the majority of the selected invasion-promoting proteins at higher levels than other cell lines tested. Additionally, the intracellular and extracellular protein measurements indicate elevated oxidative stress in the EGFRvIII-expressing cell line. In conclusion, the results of our study demonstrate that EGFR signaling has a significant effect on the levels of secreted invasion-promoting proteins, likely contributing to the aggressiveness of Glioblastoma multiforme. Further characterization of these proteins may provide candidates for new therapeutic strategies and targets as well as biomarkers for this aggressive disease.

Systems pharmacology modeling: an approach to improving drug safety.

Advances in systems biology in conjunction with the expansion in knowledge of drug effects and diseases present an unprecedented opportunity to extend traditional pharmacokinetic and pharmacodynamic modeling/analysis to conduct systems pharmacology modeling. Many drugs that cause liver injury and myopathies have been studied extensively. Mitochondrion-centric systems pharmacology modeling is important since drug toxicity across a large number of pharmacological classes converges to mitochondrial injury and death. Approaches to systems pharmacology modeling of drug effects need to consider drug exposure, organelle and cellular phenotypes across all key cell types of human organs, organ-specific clinical biomarkers/phenotypes, gene-drug interaction and immune responses. Systems modeling approaches, that leverage the knowledge base constructed from curating a selected list of drugs across a wide range of pharmacological classes, will provide a critically needed blueprint for making informed decisions to reduce the rate of attrition for drugs in development and increase the number of drugs with an acceptable benefit/risk ratio.

Differential secreted proteome approach in murine model for candidate biomarker discovery in colon cancer.

The complexity and heterogeneity of the plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. We used cell culture as a model system and identified differentially expressed, secreted proteins which may constitute serological biomarkers. A stable isotope labeling by amino acids in cell culture (SILAC) approach was used to label the entire secreted proteomes of the CT26 murine colon cancer cell line and normal young adult mouse colon (YAMC) cell line, thereby creating a stable isotope labeled proteome (SILAP) standard. This SILAP standard was added to unlabeled murine CT26 colon cancer cell or normal murine YAMC colon epithelial cell secreted proteome samples. A multidimensional approach combining isoelectric focusing (IEF), strong cation exchange (SCX) followed by reversed phase liquid chromatography was used for extensive protein and peptide separation. A total of 614 and 929 proteins were identified from the YAMC and CT26 cell lines, with 418 proteins common to both cell lines. Twenty highly abundant differentially expressed proteins from these groups were selected for liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS) analysis in sera. Differential secretion into the serum was observed for several proteins when Apc(min) mice were compared with control mice. These findings were then confirmed by Western blot analysis.

Genome-scale metabolic model of the rat liver predicts effects of diet restriction.

Mapping network analysis in cells and tissues can provide insights into metabolic adaptations to changes in external environment, pathological conditions, and nutrient deprivation. Here, we reconstructed a genome-scale metabolic network of the rat liver that will allow for exploration of systems-level physiology. The resulting in silico model (iRatLiver) contains 1,882 reactions, 1,448 metabolites, and 994 metabolic genes. We then used this model to characterize the response of the liver's energy metabolism to a controlled perturbation in diet. Transcriptomics data were collected from the livers of Sprague Dawley rats at 4 or 14 days of being subjected to 15%, 30%, or 60% diet restriction. These data were integrated with the iRatLiver model to generate condition-specific metabolic models, allowing us to explore network differences under each condition. We observed different pathway usage between early and late time points. Network analysis identified several highly connected "hub" genes (Pklr, Hadha, Tkt, Pgm1, Tpi1, and Eno3) that showed differing trends between early and late time points. Taken together, our results suggest that the liver's response varied with short- and long-term diet restriction. More broadly, we anticipate that the iRatLiver model can be exploited further to study metabolic changes in the liver under other conditions such as drug treatment, infection, and disease.

On the use of overlapping lattices for screening to find pairs of nearby points in two and three dimensions.

In designing an algorithm to find pairs of points that are within Euclidean distance d it is effective to use a screening procedure to reject most pairs of points that are far apart. A procedure based on multiple, overlapping lattices can efficiently identify close points and exclude distant ones.

Quantitative sequence-function relationships in proteins based on gene ontology.

BACKGROUND: The relationship between divergence of amino-acid sequence and divergence of function among homologous proteins is complex. The assumption that homologs share function--the basis of transfer of annotations in databases--must therefore be regarded with caution. Here, we present a quantitative study of sequence and function divergence, based on the Gene Ontology classification of function. We determined the relationship between sequence divergence and function divergence in 6828 protein families from the PFAM database. Within families there is a broad range of sequence similarity from very closely related proteins--for instance, orthologs in different mammals--to very distantly-related proteins at the limit of reliable recognition of homology. RESULTS: We correlated the divergence in sequences determined from pairwise alignments, and the divergence in function determined by path lengths in the Gene Ontology graph, taking into account the fact that many proteins have multiple functions. Our results show that, among homologous proteins, the proportion of divergent functions decreases dramatically above a threshold of sequence similarity at about 50% residue identity. For proteins with more than 50% residue identity, transfer of annotation between homologs will lead to an erroneous attribution with a totally dissimilar function in fewer than 6% of cases. This means that for very similar proteins (about 50 % identical residues) the chance of completely incorrect annotation is low; however, because of the phenomenon of recruitment, it is still non-zero. CONCLUSION: Our results describe general features of the evolution of protein function, and serve as a guide to the reliability of annotation transfer, based on the closeness of the relationship between a new protein and its nearest annotated relative.

The maize unstable factor for orange1 is a dominant epigenetic modifier of a tissue specifically silent allele of pericarp color1.

We have characterized Unstable factor for orange1 (Ufo1), a dominant, allele-specific modifier of expression of the maize pericarp color1 (p1) gene. The p1 gene encodes an Myb-homologous transcriptional activator of genes required for biosynthesis of red phlobaphene pigments. The P1-wr allele specifies colorless kernel pericarp and red cobs, whereas Ufo1 modifies P1-wr expression to confer pigmentation in kernel pericarp, as well as vegetative tissues, which normally do not accumulate significant amounts of phlobaphene pigments. In the presence of Ufo1, P1-wr transcript levels and transcription rate are increased in kernel pericarp. The P1-wr allele contains approximately six p1 gene copies present in a hypermethylated and multicopy tandem array. In P1-wr Ufo1 plants, methylation of P1-wr DNA sequences is reduced, whereas the methylation state of other repetitive genomic sequences was not detectably affected. The phenotypes produced by the interaction of P1-wr and Ufo1 are unstable, exhibiting somatic mosaicism and variable penetrance. Moreover, the changes in P1-wr expression and methylation are not heritable: meiotic segregants that lack Ufo1 revert to the normal P1-wr expression and methylation patterns. These results demonstrate the existence of a class of modifiers of gene expression whose effects are associated with transient changes in DNA methylation of specific loci.

Metabolic signature of sun exposed skin suggests catabolic pathway overweighs anabolic pathway.

Skin chronically exposed to sun results in phenotypic changes referred as photoaging. This aspect of aging has been studied extensively through genomic and proteomic tools. Metabolites, the end product are generated as a result of biochemical reactions are often studied as a culmination of complex interplay of gene and protein expression. In this study, we focused exclusively on the metabolome to study effects from sun-exposed and sun-protected skin sites from 25 human subjects. We generated a highly accurate metabolomic signature for the skin that is exposed to sun. Biochemical pathway analysis from this data set showed that sun-exposed skin resides under high oxidative stress and the chains of reactions to produce these metabolites are inclined toward catabolism rather than anabolism. These catabolic activities persuade the skin cells to generate metabolites through the salvage pathway instead of de novo synthesis pathways. Metabolomic profile suggests catabolic pathways and reactive oxygen species operate in a feed forward fashion to alter the biology of sun exposed skin.

Mechanistic modeling of aberrant energy metabolism in human disease.

Dysfunction in energy metabolism-including in pathways localized to the mitochondria-has been implicated in the pathogenesis of a wide array of disorders, ranging from cancer to neurodegenerative diseases to type II diabetes. The inherent complexities of energy and mitochondrial metabolism present a significant obstacle in the effort to understand the role that these molecular processes play in the development of disease. To help unravel these complexities, systems biology methods have been applied to develop an array of computational metabolic models, ranging from mitochondria-specific processes to genome-scale cellular networks. These constraint-based (CB) models can efficiently simulate aspects of normal and aberrant metabolism in various genetic and environmental conditions. Development of these models leverages-and also provides a powerful means to integrate and interpret-information from a wide range of sources including genomics, proteomics, metabolomics, and enzyme kinetics. Here, we review a variety of mechanistic modeling studies that explore metabolic functions, deficiency disorders, and aberrant biochemical pathways in mitochondria and related regions in the cell.

Analysis of the human pancreatic stellate cell secreted proteome.

OBJECTIVE: Pancreatic stellate cells (PSCs) are important players in pancreatic fibrosis and are major contributors to the extracellular matrix proteins observed with the stromal response characteristic of pancreatic ductal adenocarcinoma (PDAC). Pancreatic stellate cells are also believed to secrete soluble factors that promote tumor progression; however, no comprehensive analysis of the PSC proteome in either the quiescent or the activated state has been reported. METHODS: Using 2-dimensional tandem mass spectrometry and the RLT-PSC cell line, we present the first comprehensive study describing and comparing the quiescent and activated human PSC-secreted proteomes. RESULTS: Very few proteins are secreted in the quiescent state. In stark contrast, activated PSCs secreted a vast array of proteins. Many of these proteins differed from those secreted by PDAC-derived cell lines. Proteins associated with wound healing, proliferation, apoptosis, fibrosis, and invasion were characterized. Selected proteins were verified in human tissue samples from PDAC, dysplastic pancreas, and normal pancreas using Western blot analysis and immunohistochemical staining. CONCLUSIONS: Our study represents the first comprehensive analysis of proteins secreted by PSCs. These findings lay the foundation for characterizing PSC-derived proteins involved in stroma-tumor interactions and the promotion of pancreatitis and PDAC.

Stable isotope dilution multidimensional liquid chromatography-tandem mass spectrometry for pancreatic cancer serum biomarker discovery.

A novel approach to pancreatic cancer biomarker discovery has been developed, which employs a stable isotope labeled proteome (SILAP) standard coupled with extensive multidimensional separation coupled with tandem mass spectrometry (MS/MS). Secreted proteins from CAPAN-2 human pancreatic cancer derived cells were collected after conducting stable isotope labeling by amino acids in cell culture (SILAC). The resulting SILAP standard contained <0.5% of individual unlabeled proteins. Pooled sera from patients with early stage pancreatic cancer or controls were prepared, and an equal amount of the SILAP standard was added to each sample. Proteins were separated by isoelectric focusing (IEF) prior to two-dimensional liquid chromatography (2D-LC)-MS/MS analysis. A total of 1065 proteins were identified of which 121 proteins were present at 1.5-fold or greater concentrations in the sera of patients with pancreatic cancer. ELISA validation of these findings was successfully performed for two proteins, ICAM-1 and BCAM. Results of these studies have provided proof of principle that a SILAP standard derived from the CAPAN-2 secreted proteome can be used in combination with extensive multidimensional LC-MS/MS for the identification and relative quantitation of potential biomarkers of pancreatic cancer. This technique allows for the detection of low-abundance proteins, and focuses only on biologically relevant proteins derived from pancreatic cancer cells.

Identification and quantification of preterm birth biomarkers in human cervicovaginal fluid by liquid chromatography/tandem mass spectrometry.

Spontaneous preterm birth (PTB) before 37 completed weeks of gestation resulting from preterm labor (PTL) is a leading contributor of perinatal morbidity and mortality. Early identification of at-risk women by reliable screening tests could alleviate this health issue; however, conventional methods such as obstetric history and clinical risk factors, uterine activity monitoring, biochemical markers, and cervical sonography for screening women at risk for PTB have proven unsuccessful in lowering the rate of PTB. Cervicovaginal fluid (CVF) might prove to be a useful, readily available biological fluid for identifying diagnostic PTB biomarkers. Human columnar epithelial endocervical-1 (End1) and vaginal (Vk2) cell secretomes were employed to generate a stable isotope labeled proteome (SILAP) standard to facilitate characterization and relative quantification of proteins present in CVF. The SILAP standard was prepared using stable isotope labeling by amino acids in cell culture (SILAC) of End1 and Vk2 through seven passages. The labeled secreted proteins from both cell lines were combined and characterized by liquid-chromatography-tandem mass spectrometry (LC-MS/MS). In total, 1211 proteins were identified in the End1-Vk2 SILAP standard, with 236 proteins being consistently identified in each of the replicates analyzed. Individual proteins were found to contain <0.5% of the endogenous unlabeled forms. Identified proteins were screened to provide a set of 15 candidates that have either previously been identified as potential PTB biomarkers or could be linked mechanistically to PTB. Stable isotope dilution LC-multiple reaction monitoring (MRM/MS) assays were then developed for conducting relative quantification of the 15 candidate biomarkers in human CVF samples from term and PTB cases. Three proteins were significantly elevated in PTB cases (desmoplakin isoform 1, stratifin, and thrombospondin 1 precursor), providing a foundation for further validation in larger patient cohorts.

Comparative structural and functional characterization of sorghum and maize duplications containing orthologous myb transcription regulators of 3-deoxyflavonoid biosynthesis.

Sequence characterization of the genomic region of sorghum yellow seed 1 shows the presence of two genes that are arranged in a head to tail orientation. The two duplicated gene copies, y1 and y2 are separated by a 9.084 kbp intergenic region, which is largely composed of highly repetitive sequences. The y1 is the functional copy, while the y2 may represent a pseudogene; there are several sequence indels and rearrangements within the putative coding region of y2. The y1 gene encodes a R2R3 type of Myb domain protein that regulates the expression of chalcone synthase, chalcone isomerase and dihydroflavonol reductase genes required for the biosynthesis of 3-deoxyflavonoids. Expression of y1 can be observed throughout the plant and it represents a combination of expression patterns produced by different alleles of the maize p1. Comparative sequence analysis within the coding regions and flanking sequences of y1, y2 and their maize and teosinte orthologs show local rearrangements and insertions that may have created modified regulatory regions. These micro-colinearity modifications possibly are responsible for differential patterns of expression in maize and sorghum floral and vegetative tissues. Phylogenetic analysis indicates that sorghum y1 and y2 sequences may have arisen by gene duplication mechanisms and represent an evolutionarily parallel event to the duplication of maize p2 and p1 genes.