Proteomic Analysis of the Epidermal Growth Factor Receptor (EGFR) Interactome and Post-translational Modifications Associated with Receptor Endocytosis in Response to EGF and Stress

Aberrant expression, activation, and stabilization of epidermal growth factor receptor (EGFR) are causally associated with several human cancers. Post-translational modifications and protein-protein interactions directly modulate the signaling and trafficking of the EGFR. Activated EGFR is internalized by endocytosis and then either recycled back to the cell surface or degraded in the lysosome. EGFR internalization and recycling also occur in response to stresses that activate p38 MAP kinase. Mass spectrometry was applied to comprehensively analyze the phosphorylation, ubiquitination, and protein-protein interactions of wild type and endocytosis-defective EGFR variants before and after internalization in response to EGF ligand and stress. Prior to internalization, EGF-stimulated EGFR accumulated ubiquitin at 7 K residues and phosphorylation at 7 Y sites and at S¹¹⁰⁴. Following internalization, these modifications diminished and there was an accumulation of S/T phosphorylations. EGFR internalization and many but not all of the EGF-induced S/T phosphorylations were also stimulated by anisomycin-induced cell stress, which was not associated with receptor ubiquitination or elevated Y phosphorylation. EGFR protein interactions were dramatically modulated by ligand, internalization, and stress. In response to EGF, different E3 ubiquitin ligases became maximally associated with EGFR before (CBL, HUWE1, and UBR4) or after (ITCH) internalization, whereas CBLB was distinctively most highly EGFR associated following anisomycin treatment. Adaptin subunits of AP-1 and AP-2 clathrin adaptor complexes also became EGFR associated in response to EGF and anisomycin stress. Mutations preventing EGFR phosphorylation at Y⁹⁹⁸ or in the S¹⁰³⁹ region abolished or greatly reduced EGFR interactions with AP-2 and AP-1, and impaired receptor trafficking. These results provide new insight into spatial, temporal, and mechanistic aspects of EGFR regulation.Receptor tyrosine kinases such as the epidermal growth factor receptor (EGFR)¹ are aberrantly activated by mutation and/or over-expression in numerous human cancers (1, 2). Ligand-activated EGFR, similar to many receptor tyrosine kinases, is normally subject to clathrin-mediated endocytosis (CME) involving internalization and followed by sorting through the endosomal compartment (reviewed in 3). From endosomes, and as a function of which ligand is bound, the receptor may be recycled back to the cell surface or down-regulated as a consequence of trafficking to lysosomes for proteolytic degradation (4, 5). The EGFR also undergoes CME-mediated internalization and recycling back to the plasma membrane in response to cellular stresses that activate p38 MAPK, for example in response to the chemotherapeutic agent cisplatin, the antibiotic anisomycin, and the cytokine tumor necrosis factor-α (TNFα) (6–8). Various oncogenic mutations in the EGFR, as well as hetero-dimerization with other ErbB family members impairs EGFR down-regulation (9). This leads to aberrant, sustained EGFR signaling, which elicits cellular responses central to the cancer cell phenotype including cell proliferation, survival, motility/migration, and invasion (reviewed in 10).EGFR signaling and trafficking involve an overlapping set of factors that have been extensively reviewed (10, 11). These processes are products of EGFR protein-protein interactions and post-translational modifications (PTMs) including phosphorylation, ubiquitinylation, and lysine acetylation (12). Extracellular binding of ligand induces EGFR dimerization and trans-autophosphorylation at intracellular tyrosine residues, which serve as binding sites for various enzymes and adaptor proteins (11). These receptor-binding proteins are involved in signaling and/or receptor trafficking, and also lead to further modulation of receptor PTMs. For example, binding of the E3 ubiquitin ligase CBL at EGFR pY¹⁰⁶⁹ (13–15) or indirectly through the adaptor protein Grb2, which binds primarily at pY¹⁰⁹² (16), are both involved in EGFR ubiquitinylation and down-regulation (17). Although not an exclusive mechanism, EGFR internalization mainly involves clathrin and the AP-2 clathrin adaptor complex (12, 18–22) in addition to Grb2 (18, 23, 24). EGFR internalization and recycling in response to stress-induced p38 MAPK activation requires AP-2, but not Grb2 (18), and is reportedly independent of receptor kinase activity, tyrosine phosphorylation, and ubiquitination (6–8). Trafficking of endocytosed EGFR to the lysosome, but not the initial internalization step itself, requires CBL (25, 26), and is associated with ubiquitination at up to six lysine residues within the EGFR kinase domain (14). Additionally, ubiquitin-interacting endocytosis factors including Hrs, STAM, and STAM2 become tyrosine phosphorylated in response to EGFR activation (27), and EGFR ubiquitination is required for endosomal sorting (3). Gill and colleagues identified in the EGFR a region spanning residues 997–1046 as conferring endocytic function to otherwise endocytosis-defective EGF receptors truncated after the kinase domain (28). Consistent with this, EGFR phosphorylation sites linked with receptor trafficking are present within or proximal to this part of the receptor. For example, EGFR phosphorylation at S⁹⁹¹ and Y⁹⁹⁸ accumulate with relatively slow kinetics following stimulation of cells with EGF (29). Phosphorylation-defective variants Y998F and S991A are impaired for ligand-stimulated down-regulation relative to wild type (WT) EGFR, but remain proficient for rapid EGFR-to-ERK signaling (29). Non-phosphorylated Y⁹⁹⁸ was cited as part of an AP-2 binding motif (Y⁹⁹⁸RAL) (22), while a nearby di-leucine motif (LL^1034/35) also serves as an AP-2 binding site (22, 30). Phosphorylations at EGFR S¹⁰³⁹ and T¹⁰⁴¹ occur downstream of p38 MAPK in response to anisomycin-induced cell stress, and are also phosphorylated at lower levels as part of the normal cellular response to EGFR activation by EGF (29). The adaptor protein Odin (ANKS1A) becomes tyrosine phosphorylated prior to EGFR internalization following EGF treatment of cells, and functions as an effector of EGFR recycling (31). Therefore, in response to diverse extracellular signals a multitude of reversible PTMs and interacting proteins govern EGFR internalization, trafficking, and ultimately, stability and signaling. However, our understanding of spatial-temporal and mechanistic relationships of individual EGFR PTMs and protein interactions, and their biological consequences are largely qualitative and incomplete.The objective of the current study was to characterize and compare aspects of the initial, pre- and post-internalization stages of EGFR endocytosis in response to EGF and cell stress. A battery of methods was applied to identify and absolutely or relatively quantify EGFR phosphorylation, ubiquitination, and protein-protein interactions. These included fluorescence microscopic imaging, and quantitative LC-MS/MS including targeted measurements by selected reaction monitoring (SRM), and comprehensive quantification by using ultra high resolution MS. These were applied with an established model system based on human HEK293 cells engineered to express defined levels of wild type and various phosphorylation-defective EGFR variants tagged with the Flag epitope. The comprehensive analysis revealed distinctive patterns of EGFR modifications and interactions that correlated with receptor activation and internalization. Generally, EGF-stimulated EGFR tyrosine phosphorylations and lysine ubiquitinations, which were maximal prior to internalization, decreased 15-min after receptor internalization was initiated, whereas S/T phosphorylations increased. A subset of EGF-stimulated S/T phosphorylations including pS⁹⁹¹ and pS¹⁰³⁹ and proximal S/T residues accumulated to an even greater extent in response to anisomycin. EGFR variants with amino acid substitutions at these positions were largely impaired for AP-1 and AP-2 interactions, showed altered patterns of ubiquitination, and resistance to EGF-stimulated receptor down-regulation. These results provide new insight into the dynamics and molecular events associated with EGFR function.     

NDRG4 Is Required for Cell Cycle Progression and Survival in Glioblastoma Cells

NDRG4 is a largely unstudied member of the predominantly tumor suppressive N-Myc downstream-regulated gene (NDRG) family. Unlike its family members NDRG1–3, which are ubiquitously expressed, NDRG4 is expressed almost exclusively in the heart and brain. Given this tissue-specific expression pattern and the established tumor suppressive roles of the NDRG family in regulating cellular proliferation, we investigated the cellular and biochemical functions of NDRG4 in the context of astrocytes and glioblastoma multiforme (GBM) cells. We show that, in contrast to NDRG2, NDRG4 expression is elevated in GBM and NDRG4 is required for the viability of primary astrocytes, established GBM cell lines, and both CD133⁺ (cancer stem cell (CSC)-enriched) and CD133⁻ primary GBM xenograft cells. While NDRG4 overexpression has no effect on cell viability, NDRG4 knockdown causes G₁ cell cycle arrest followed by apoptosis. The initial G₁ arrest is associated with a decrease in cyclin D1 expression and an increase in p27^Kip1 expression, and the subsequent apoptosis is associated with a decrease in the expression of XIAP and survivin. As a result of these effects on cell cycle progression and survival, NDRG4 knockdown decreases the tumorigenic capacity of established GBM cell lines and GBM CSC-enriched cells that have been implanted intracranially into immunocompromised mice. Collectively, these data indicate that NDRG4 is required for cell cycle progression and survival, thereby diverging in function from its tumor suppressive family member NDRG2 in astrocytes and GBM cells.The N-Myc downstream-regulated gene (NDRG)⁵ family consists of four genes (NDRG1–4) that can be divided into two subfamilies based on sequence homology: NDRG1 and NDRG3 are in the first subfamily, and NDRG2 and NDRG4 make up the second subfamily. Although the four NDRG family members show distinct spatiotemporal expression patterns during embryonic development and in adult tissues (1–10), all four are highly expressed in the brain (4). To date, however, NDRG2 is the only NDRG family member that has been studied in the context of GBM cells and astrocytes. NDRG2 mRNA and protein levels are lower in GBM than in normal brain tissue, normal glial cells, and low grade astrocytomas (11–14), suggesting a tumor suppressive function. Data from experimental and clinical studies support this hypothesis: NDRG2 overexpression inhibits GBM cell proliferation (15), and decreased NDRG2 expression correlates with decreased GBM patient survival (13).In contrast to its subfamily member NDRG2, NDRG4 has not been studied in GBM cells or astrocytes. Nevertheless, available evidence supports the hypothesis that NDRG4 has an important role in this context that is similar to the role of NDRG2. First, unlike the relatively ubiquitous expression patterns of NDRG1–3, NDRG4 expression is restricted to a small number of tissues including the brain, where it is expressed at particularly high levels (7, 10). This restricted expression pattern suggests that NDRG4 plays an important role within the central nervous system. Second, NDRG4 is more than 60% identical in amino acid sequence to NDRG2. This sequence similarity is likely behind the overlapping functions of these two proteins in certain cell types within the brain. For example, in PC12 neuronal cells, both NDRG4 and NDRG2 promote neurite extension (16–18). In combination with the brain-specific expression pattern of NDRG4, these functional and sequence similarities suggest that NDRG4 may recapitulate the tumor suppressive function of NDRG2 in primary brain neoplasms.To determine if the similarities between NDRG2 and NDRG4 extend to the context of GBM, we investigated the role of NDRG4 in GBM cell lines and primary human astrocytes. In contrast to the established roles of NDRG2 and other NDRG family members, we found that the role of NDRG4 in GBM is not tumor suppressive. On the contrary, both astrocytes and GBM cells require the presence of NDRG4 for cell cycle progression and survival.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Systems Biological Analysis of Epidermal Growth Factor Receptor Internalization Dynamics for Altered Receptor Levels

Epidermal growth factor (EGF) receptor (EGFR) overexpression is a hallmark of many cancers. EGFR endocytosis is a critical step in signal attenuation, raising the question of how receptor expression levels affect the internalization process. Here we combined quantitative experimental and mathematical modeling approaches to investigate the role of the EGFR expression level on the rate of receptor internalization. Using tetramethylrhodamine-labeled EGF, we established assays for quantifying EGF-triggered EGFR internalization by both high resolution confocal microscopy and flow cytometry. We determined that the flow cytometry approach was more sensitive for examining large populations of cells. Mathematical modeling was used to investigate the relationship between EGF internalization kinetics, EGFR expression, and internalization machinery. We predicted that the standard parameter used to assess internalization kinetics, the temporal evolution r(t) of the ratio of internalized versus surface-located ligand·receptor complexes, does not describe a straight line, as proposed previously. Instead, a convex or concave curve occurs depending on whether initial receptor numbers or internalization adaptors are limiting the uptake reaction, respectively. To test model predictions, we measured EGF-EGFR binding and internalization in cells expressing different levels of green fluorescent protein-EGFR. As expected, surface binding of rhodamine-labeled EGF increased with green fluorescent protein-EGFR expression level. Unexpectedly, internalization of ligand· receptor complexes increased linearly with increasing receptor expression level, suggesting that receptors and not internalization adaptors were limiting the uptake in our experimental model. Finally, determining the ratio of internalized versus surface-located ligand·receptor complexes for this cell line confirmed that it follows a convex curve, supporting our model predictions.The epidermal growth factor receptor (EGFR)³ belongs to the family of transmembrane receptor tyrosine kinases and mediates diverse actions, including proliferation, differentiation, and apoptosis (1, 2). Overexpression and/or mutations of the EGFR occur in ∼40% of neoblastomas (3) and correlate with poor prognosis (4–6). Unstimulated EGFR is located at the plasma membrane as a monomer and pre-formed dimer (7). Upon ligand binding, EGFR forms a dimer, and trans-phosphorylation occurs at specific residues of the cytoplasmic domain (8). Phosphorylated EGFR recruits adaptor proteins from which different conserved signaling pathways are activated, namely the MAPK (9), phosphatidylinositol 3-kinase, and protein kinase C pathways (10).Furthermore, activated EGFR recruits various adaptor proteins that mediate receptor internalization by endocytosis (2). Endocytosis occurs via the recruitment of adaptor proteins to phosphorylated tyrosine residues of the receptor and formation of membrane invaginations, which eventually pinch off to form internalized early endosomes (2, 11) (see Fig. 1). Both constitutive endocytosis and ligand-induced EGFR endocytosis are critical events in EGF signal regulation (2, 12). Endosomal EGFR can be transited back to the plasma membrane or to the late endosome/lysosome for degradation (2). As the majority of internalized receptors are targeted for lysosomal degradation upon EGF stimulation (13), endocytic entry of active EGFR is a crucial step for signal attenuation, which is also highlighted by the findings that impaired or delayed internalization is highly oncogenic (14, 15).Open in a separate windowFIGURE 1.Scheme of ligand-induced internalization. EGF binds membrane-located EGFR to give rise to surface-bound EGF·EGFR complex RE_s. Via diffusion events, the activated receptor binds internalization adaptors IC, which leads to internalized receptors R_i.In light of the role of endocytosis in EGFR signal attenuation and the oncogenicity of EGFR overexpression, it is important to elucidate the relationship between high receptor expression levels relative to internalization pathway capacity and their effect on internalization dynamics.Mathematical modeling is an important tool in elucidating EGFR signaling, at the level of EGFR internalization (16–19) and, more recently, at the level of the integration of input signals into signaling events downstream of the EGFR, such as the MAPK cascade (20, 21). In earlier models, pioneering concepts such as the nonlinearity of the uptake reaction, because of the existence of alternative pathways that are entered with different affinities, were developed (16, 19). Also, the notion of saturability of the EGFR endocytosis system, in contrast to internalization of the transferrin receptor, for example, was introduced (18).Importantly, in mathematical formulations of EGFR endocytosis, the standard parameter used to estimate the rate of the internalization step (16) and to assess the effect of certain perturbations on internalization (22–24) is the temporal evolution of the ratio of internalized versus surface-located ligand·receptor complexes r(t). In Refs. 16, 17, it was mathematically determined that, under certain assumptions, this ratio describes a straight line with the slope corresponding to the rate of the internalization step. These assumptions were as follows: (i) that the number of surface-bound ligand·receptor complexes (RE_s) remains approximately constant during the measurements, and (ii) that the internalization step is a first-order process, i.e. it is directly proportional to RE_s and independent of a potentially limiting availability of internalization adaptors.The presence of multiple endocytotic routes (23, 25) and different EGFR affinities for EGF (26) argue against first-order kinetics. Moreover, the possible limited capacity of internalization adaptors may restrict EGFR internalization in cells expressing abnormally high numbers of EGFR (18). In this work we investigated the potential of EGFR internalization to occur as a nonlinear process by combining mathematical modeling with novel quantitative, live cell measurements of EGF internalization.We extended the previous derivation of the ratio of internalized versus surface-located ligand·receptor complexes r(t) (16, 17, 19) by eliminating above assumptions i and ii, which allowed us to investigate in silico different scenarios for the shape of r(t) as a function of the relative concentrations of EGFR and internalization adaptors. We predicted that r(t) is not a straight line as derived previously but is a convex or concave curve depending on whether receptors or internalization components are limiting the reaction, respectively.In earlier studies, quantitative measurements of parameters of EGFR endocytosis have been performed using classical biochemical techniques to detect cellular ligand uptake using radioactively labeled EGF (16, 24, 27) or biotin-labeled EGF (28). Importantly, both methods do not reach single cell precision and instead yield an integrated signal over a population of cells. To test our mathematical predictions we combined the following: (i) quantitative laser scanning confocal microscopy, and (ii) multiple parametric flow cytometry, using a custom Beckman Coulter FC500 equipped with a 488 and 561 nm laser excitation, to quantitatively measure the temporal and spatial dynamics of EGFR endocytosis using tetramethylrhodamine-tagged EGF (Rh-EGF) and GFP-EGFR. We show that both quantitative imaging and flow cytometry measurements were highly sensitive, allowing for live cell investigations and confirmation of the mathematical predictions.     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.     

Targeted Proteomics to Assess the Response to Anti-Angiogenic Treatment in Human Glioblastoma (GBM)

Glioblastoma (GBM) is a highly aggressive primary brain tumor with dismal outcome for affected patients. Because of the significant neo-angiogenesis exhibited by GBMs, anti-angiogenic therapies have been intensively evaluated during the past years. Recent clinical studies were however disappointing, although a subpopulation of patients may benefit from such treatment. We have previously shown that anti-angiogenic targeting in GBM increases hypoxia and leads to a metabolic adaptation toward glycolysis, suggesting that combination treatments also targeting the glycolytic phenotype may be effective in GBM patients. The aim of this study was to identify marker proteins that are altered by treatment and may serve as a short term readout of anti-angiogenic therapy. Ultimately such proteins could be tested as markers of efficacy able to identify patient subpopulations responsive to the treatment. We applied a proteomics approach based on selected reaction monitoring (SRM) to precisely quantify targeted protein candidates, selected from pathways related to metabolism, apoptosis and angiogenesis. The workflow was developed in the context of patient-derived intracranial GBM xenografts developed in rodents and ensured the specific identification of human tumor versus rodent stroma-derived proteins. Quality control experiments were applied to assess sample heterogeneity and reproducibility of SRM assays at different levels. The data demonstrate that tumor specific proteins can be precisely quantified within complex biological samples, reliably identifying small concentration differences induced by the treatment. In line with previous work, we identified decreased levels of TCA cycle enzymes, including isocitrate dehydrogenase, whereas malectin, calnexin, and lactate dehydrogenase A were augmented after treatment. We propose the most responsive proteins of our subset as potential novel biomarkers to assess treatment response after anti-angiogenic therapy that warrant future analysis in clinical GBM samples.In the context of glioblastoma (GBM)¹, the quest for effective biomarkers is vital given that GBM is the most aggressive primary brain tumor in adults and no curative treatment is currently available (1). GBM is characterized by extensive invasion into the brain parenchyma, a high proliferation rate, neo-angiogenesis and significant cellular and molecular heterogeneity. Current treatment involves neurosurgery, radiotherapy and chemotherapy, yet the median life expectancy of affected patients is less than fifteen months. Recent efforts have focused on targeting the vascular endothelial growth factor (VEGF) system which is critical for tumor angiogenesis, however GBM quickly develop escape mechanisms leading to tumor progression (2, 3). Previous work from our group demonstrated that GBMs adapt to anti-VEGF treatment via a metabolic switch in tumor cells toward increased glycolysis (4, 5). This was accompanied by increased hypoxia and tumor cell invasion, with little or no effect on tumor growth (4). In agreement with these preclinical studies, two large scale clinical trials addressing the impact of bevacizumab, a VEGF targeting antibody, in newly diagnosed GBM patients reported disappointing results: although progression free survival appeared to be improved, no effect on overall survival was observed (6, 7). The evaluation of such studies are complicated by the fact that anti-angiogenic agents affect blood vessel permeability thereby directly modulating neuroimaging parameters used to determine treatment effects (8, 9). Thus there is a need for molecular biomarkers to adequately determine treatment response to anti-angiogenic agents.MS-based proteomics (10, 11) is widely used in the field of cancer research in particular in the context of biomarker development including discovery and verification. The application of the selected reaction monitoring (SRM) approach to proteomics reinforced the importance of MS in biomarker development (12–14). Indeed, SRM is a targeted proteomics approach that allows a precise and absolute quantification of previously selected marker candidates (15, 16). Moreover it can be applied in a supervised discovery phase for potential biomarkers (17, 18), i.e. the precise quantification of a wider range of selected biomarkers of interest by the use of stable isotope labeled (SIL) peptides in crude quality. Because of its high selectivity, sensitivity and accuracy, SRM, also named multiple reaction monitoring (MRM), is currently the reference method in targeted proteomics (14, 19).The aim of this study was to identify proteins that are altered by anti-angiogenic treatment, thereby providing biomolecular signatures of tumor response in GBM. Ultimately such protein markers could be evaluated for their utility as markers of efficacy that allow to discriminate responders from nonresponders. The study was focused on target proteins that may exhibit significant differences in protein expression reflecting the metabolic switch exhibited during anti-angiogenic therapy. An SRM workflow designed on a triple quadrupole platform (20), was developed and optimized in the context of GBM xenografts treated with bevacizumab in order to perform, in a supervised manner, a precise relative quantification of target proteins. We have previously shown that patient derived GBM xenografts developed in rodents faithfully reflect human pathology and allow a detailed analysis of the tumor and stromal compartments (4, 21–24). Furthermore xenograft models facilitate the access to control samples as well as the possibility of controlled interventional studies (25). The results presented herein demonstrate the feasibility of SRM to precisely quantify small changes in protein concentration after treatment. We highlight the importance of peptide selection, data normalization and consideration of the variability of target proteins within complex biological samples before assessing their concentration changes in subsequent comparative studies. From an initial set of 100 candidates, we screened 74 proteins and identified 32 responsive to anti-angiogenic treatment. We propose malectin, calnexin, lactate dehydrogenase A (LDHA), and isocitrate dehydrogenase (IDH) as novel response markers to anti-angiogenic therapy.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

The Wavelet-Based Cluster Analysis for Temporal Gene Expression Data

A variety of high-throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Common methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy can be applied in the analysis of data sets of thousands of genes under different conditions.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]