Kinomics toolbox-A web platform for analysis and viewing of kinomic peptide array data

Organotypic heterogeneity in microvascular endothelial cell responses in sepsis-a molecular treasure trove and pharmacological Gordian knot

In the last decades, it has become evident that endothelial cells (ECs) in the microvasculature play an important role in the pathophysiology of sepsis-associated multiple organ dysfunction syndrome (MODS). Studies on how ECs orchestrate leukocyte recruitment, control microvascular integrity and permeability, and regulate the haemostatic balance have provided a wealth of knowledge and potential molecular targets that could be considered for pharmacological intervention in sepsis. Yet, this information has not been translated into effective treatments. As MODS affects specific vascular beds, (organotypic) endothelial heterogeneity may be an important contributing factor to this lack of success. On the other hand, given the involvement of ECs in sepsis, this heterogeneity could also be leveraged for therapeutic gain to target specific sites of the vasculature given its full accessibility to drugs. In this review, we describe current knowledge that defines heterogeneity of organ-specific microvascular ECs at the molecular level and elaborate on studies that have reported EC responses across organ systems in sepsis patients and animal models of sepsis. We discuss hypothesis-driven, single-molecule studies that have formed the basis of our understanding of endothelial cell engagement in sepsis pathophysiology, and include recent studies employing high-throughput technologies. The latter deliver comprehensive data sets to describe molecular signatures for organotypic ECs that could lead to new hypotheses and form the foundation for rational pharmacological intervention and biomarker panel development. Particularly results from single cell RNA sequencing and spatial transcriptomics studies are eagerly awaited as they are expected to unveil the full spatiotemporal signature of EC responses to sepsis. With increasing awareness of the existence of distinct sepsis subphenotypes, and the need to develop new drug regimen and companion diagnostics, a better understanding of the molecular pathways exploited by ECs in sepsis pathophysiology will be a cornerstone to halt the detrimental processes that lead to MODS.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Tumor Treating Fields Alter the Kinomic Landscape in Glioblastoma Revealing Therapeutic Vulnerabilities

Treatment for the deadly brain tumor glioblastoma (GBM) has been improved through the non-invasive addition of alternating electric fields, called tumor treating fields (TTFields). Improving both progression-free and overall survival, TTFields are currently approved for treatment of recurrent GBMs as a monotherapy and in the adjuvant setting alongside TMZ for newly diagnosed GBMs. These TTFields are known to inhibit mitosis, but the full molecular impact of TTFields remains undetermined. Therefore, we sought to understand the ability of TTFields to disrupt the growth patterns of and induce kinomic landscape shifts in TMZ-sensitive and -resistant GBM cells. We determined that TTFields significantly decreased the growth of TMZ-sensitive and -resistant cells. Kinomic profiling predicted kinases that were induced or repressed by TTFields, suggesting possible therapy-specific vulnerabilities. Serving as a potential pro-survival mechanism for TTFields, kinomics predicted the increased activity of platelet-derived growth-factor receptor alpha (PDGFRα). We demonstrated that the addition of the PDGFR inhibitor, crenolanib, to TTFields further reduced cell growth in comparison to either treatment alone. Collectively, our data suggest the efficacy of TTFields in vitro and identify common signaling responses to TTFields in TMZ-sensitive and -resistant populations, which may support more personalized medicine approaches.

Omics-Based Investigations of Breast Cancer

Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein-protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

Mapping the Protein Kinome: Current Strategy and Future Direction

The kinome includes over 500 different protein kinases, which form an integrated kinase network that regulates cellular phosphorylation signals. The kinome plays a central role in almost every cellular process and has strong linkages with many diseases. Thus, the evaluation of the cellular kinome in the physiological environment is essential to understand biological processes, disease development, and to target therapy. Currently, a number of strategies for kinome analysis have been developed, which are based on monitoring the phosphorylation of kinases or substrates. They have enabled researchers to tackle increasingly complex biological problems and pathological processes, and have promoted the development of kinase inhibitors. Additionally, with the increasing interest in how kinases participate in biological processes at spatial scales, it has become urgent to develop tools to estimate spatial kinome activity. With multidisciplinary efforts, a growing number of novel approaches have the potential to be applied to spatial kinome analysis. In this paper, we review the widely used methods used for kinome analysis and the challenges encountered in their applications. Meanwhile, potential approaches that may be of benefit to spatial kinome study are explored.

KRSA: An R package and R Shiny web application for an end-to-end upstream kinase analysis of kinome array data

Phosphorylation by serine-threonine and tyrosine kinases is critical for determining protein function. Array-based platforms for measuring reporter peptide signal levels allow for differential phosphorylation analysis between conditions for distinct active kinases. Peptide array technologies like the PamStation12 from PamGene allow for generating high-throughput, multi-dimensional, and complex functional proteomics data. As the adoption rate of such technologies increases, there is an imperative need for software tools that streamline the process of analyzing such data. We present Kinome Random Sampling Analyzer (KRSA), an R package and R Shiny web-application for analyzing kinome array data to help users better understand the patterns of functional proteomics in complex biological systems. KRSA is an All-In-One tool that reads, formats, fits models, analyzes, and visualizes PamStation12 kinome data. While the underlying algorithm has been experimentally validated in previous publications, we demonstrate KRSA workflow on dorsolateral prefrontal cortex (DLPFC) in male (n = 3) and female (n = 3) subjects to identify differential phosphorylation signatures and upstream kinase activity. Kinase activity differences between males and females were compared to a previously published kinome dataset (11 female and 7 male subjects) which showed similar global phosphorylation signals patterns.

PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis

Peptide microarrays consisting of defined phosphorylation target sites are an effective approach for high throughput analysis of cellular kinase (kinome) activity. Kinome peptide arrays are highly customizable and do not require species-specific reagents to measure kinase activity, making them amenable for kinome analysis in any species. Our group developed software, Platform for Integrated, Intelligent Kinome Analysis (PIIKA), to enable more effective extraction of meaningful biological information from kinome peptide array data. A subsequent version, PIIKA2, unveiled new statistical tools and data visualization options. Here we introduce PIIKA 2.5 to provide two essential quality control metrics and a new background correction technique to increase the accuracy and consistency of kinome results. The first metric alerts users to improper spot size and informs them of the need to perform manual resizing to enhance the quality of the raw intensity data. The second metric uses inter-array comparisons to identify outlier arrays that sometimes emerge as a consequence of technical issues. In addition, a new background correction method, background scaling, can sharply reduce spatial biases within a single array in comparison to background subtraction alone. Collectively, the modifications of PIIKA 2.5 enable identification and correction of technical issues inherent to the technology and better facilitate the extraction of meaningful biological information. We show that these metrics demonstrably enhance kinome analysis by identifying low quality data and reducing batch effects, and ultimately improve clustering of treatment groups and enhance reproducibility. The web-based and stand-alone versions of PIIKA 2.5 are freely accessible at via http://saphire.usask.ca.

Novel Mechanism for an Old Drug: Phenazopyridine is a Kinase Inhibitor Affecting Autophagy and Cellular Differentiation

Phenazopyridine is a widely used drug against urinary tract pain. The compound has also been shown to enhance neural differentiation of pluripotent stem cells. However, its mechanism of action is not understood. Based on its chemical structure, we hypothesized that phenazopyridine could be a kinase inhibitor. Phenazopyridine was investigated in the following experimental systems: 1) activity of kinases in pluripotent stem cells; 2) binding to recombinant kinases, and 3) functional impact on pluripotent stem cells. Upon addition to pluripotent stem cells, phenazopyridine induced changes in kinase activities, particularly involving Mitogen-Activated Protein Kinases, Cyclin-Dependent Kinases, and AKT pathway kinases. To identify the primary targets of phenazopyridine, we screened its interactions with 401 human kinases. Dose-inhibition curves showed that three of these kinases interacted with phenazopyridine with sub-micromolar binding affinities: cyclin-G-associated kinase, and the two phosphatidylinositol kinases PI4KB and PIP4K2C, the latter being known for participating in pain induction. Docking revealed that phenazopyridine forms strong H-bonds with the hinge region of the ATP-binding pocket of these kinases. As previous studies suggested increased autophagy upon inhibition of the phosphatidyl-inositol/AKT pathway, we also investigated the impact of phenazopyridine on this pathway and found an upregulation. In conclusion, our study demonstrates for the first time that phenazopyridine is a kinase inhibitor, impacting notably phosphatidylinositol kinases involved in nociception.

PamgeneAnalyzeR: open and reproducible pipeline for kinase profiling

 

Protein phosphorylation––catalyzed by protein kinases–is the most common post-translational modification. It increases the functional diversity of the proteome and influences various aspects of normal physiology and can be altered in disease states. High throughput profiling of kinases is becoming an essential experimental approach to investigate their activity and this can be achieved using technologies such as PamChip^® arrays provided by PamGene for kinase activity measurement. Here, we present ‘pamgeneAnalyzeR’, an R package developed as an alternative to the manual steps necessary to extract the data from PamChip^® peptide microarrays images in a reproducible and robust manner. The extracted data can be directly used for downstream analysis.

Availability and implementation

PamgeneAnalyzeR is implemented in R and can be obtained from https://github.com/amelbek/pamgeneAnalyzeR.

Intratumoral spatial heterogeneity of BTK kinomic activity dictates distinct therapeutic response within a single glioblastoma tumor

OBJECTIVE

Despite significant recent efforts applied toward the development of efficacious therapies for glioblastoma (GBM) through exploration of GBM's genome and transcriptome, curative therapeutic strategies remain highly elusive. As such, novel and effective therapeutics are urgently required. In this study, the authors sought to explore the kinomic landscape of GBM from a previously underutilized approach (i.e., spatial heterogeneity), followed by validation of Bruton's tyrosine kinase (BTK) targeting according to this stepwise kinomic-based novel approach.

METHODS

Twelve GBM tumor samples were obtained and characterized histopathologically from 2 patients with GBM. PamStation peptide-array analysis of these tissues was performed to measure the kinomic activity of each sample. The Ivy GBM database was then utilized to determine the intratumoral spatial localization of BTK activity by investigating the expression of BTK-related transcription factors (TFs) within tumors. Genetic inhibition of BTK family members through lentiviral short hairpin RNA (shRNA) knockdown was performed to determine their function in the core-like and edge-like GBM neurosphere models. Finally, the small-molecule inhibitor of BTK, ONO/GS-4059, which is currently under clinical investigation in nonbrain cancers, was applied for pharmacological inhibition of regionally specified newly established GBM edge and core neurosphere models.

RESULTS

Kinomic investigation identified two major subclusters of GBM tissues from both patients exhibiting distinct profiles of kinase activity. Comparatively, in these spatially defined subgroups, BTK was the centric kinase differentially expressed. According to the Ivy GBM database, BTK-related TFs were highly expressed in the tumor core, but not in edge counterparts. Short hairpin RNA-mediated gene silencing of BTK in previously established edge- and core-like GBM neurospheres demonstrated increased apoptotic activity with predominance of the sub-G1 phase of core-like neurospheres compared to edge-like neurospheres. Lastly, pharmacological inhibition of BTK by ONO/GS-4059 resulted in growth inhibition of regionally derived GBM core cells and, to a lesser extent, their edge counterparts.

CONCLUSIONS

This study identifies significant heterogeneity in kinase activity both within and across distinct GBM tumors. The study findings indicate that BTK activity is elevated in the classically therapy-resistant GBM tumor core. Given these findings, targeting GBM's resistant core through BTK may potentially provide therapeutic benefit for patients with GBM.

Differential escape mechanisms in cetuximab-resistant head and neck cancer cells

Acquired cetuximab resistance is a challenge for oncologists treating advanced head and neck carcinoma (HNC). While intrinsic cetuximab resistance mechanism in colorectal cancer is known, resistance in HNC is unclear. We established two different cetuximab resistant HNC cell lines by culturing epidermal growth factor (EGFR) expressing UM-SCC-1 and UM-SCC-6 cell lines in the presence of 5 μg/ml cetuximab. We then explored potential mechanisms of resistance. We found that the 2 cell lines developed resistance by different mechanisms. Specifically, we found that UM-SCC-1 resistant cells (UM-SCC-1R) showed enhanced EGF-induced downstream signals while UM-SCC-6 resistant cells (UM-SCC-6R) demonstrated EGF-independent signaling. Global kinase activity (kinomic) profiling revealed unique signaling differences in the two resistant cell lines. However, both of the resistant lines demonstrated increased phospho-serine 727 and total STAT3 expression compared to the parental lines. STAT3 knockdown promoted increased cytotoxicity both in the presence and absence of cetuximab in the resistant lines suggesting that STAT3 may be a common target in cetuximab resistance.