23rd Human Proteome Organization World Congress

Signalling architecture underlying breast cancer cell motility

Keynote Lecture

Cell migration is vital to a variety of biological processes including wound healing, the immune response, embryonic development, and cancer cell metastasis. Growth factors and proteins in the extracellular matrix (ECM) provide cues to guide migrating cells. However, the specific contribution of each of these signals and potentially their integration via intracellular signalling pathways to promote cell migration are still poorly understood.Here, combining quantitative proteomics and phosphoproteomics with bioinformatics, and functional validation in both breast cancer cell models and patient samples, we investigated how:1) Receptor Tyrosine Kinases affect signalling networks underlying cell motility, mitogenicity, and survival2) non canonical signalling pathways regulate cell migration in response to both ECM proteins and growth factors3) ECM proteins and kinases promote breast cancer bone metastasisOur findings show that a more intricated signalling architecture than anticipated fine tunes the motility of breast cancer cells with profound implications for our understanding of breast cancer metastasis and for improving the therapeutic options available for patients

Keynote lecture

Professor

Combining phospho- (and other) proteomics with biological knowledge into computational models to understand signal transduction

Proteomics in its various forms – from phosphor-proteomics to thermal proteome profiling - provides rich information about cellular processes and their deregulation in disease. Given the complexity of the data, we need computational methods to effectively extract mechanistic information from it. We believe that including biological knowledge in the methods can be instrumental to move from pure correlation to causation in large data sets, and thereby identify the molecular processes that underlie signaling events, that can be ultimately used as therapeutic targets and biomarkers. In this talk I will describe various approaches that follow this strategy, from kinase-activity estimation to signaling network reconstruction, and illustrate them in examples from various contexts.

Illuminating the human phosphoproteome by dose-resolved proteomics of clinical kinase inhibitors

Defining Signaling Networks - Functional PTMs

IntroductionPathological kinase signaling is among the key causes of human diseases, as it shifts the phosphoproteome out of its homeostasis and leads to uncontrolled cell growth or inflammation. Rationally, kinase inhibitors have become a popular treatment strategy to restore the phosphoproteome. Although many phosphorylation sites (p-sites) can now be analyzed by mass spectrometry, the biological contexts and functions of these p-sites remain hidden in the dark for most cases. Consequently, the complete sets of mechanisms of action(s) of kinase inhibitors in cells remain similarly vague. The known polypharmacology of most inhibitors must be carefully considered in any perturbation experiment and can only be dissected by exploiting affinity differences from dose-resolved experiments. Only by systematically screening inhibitors in various cell line models in a dose-dependent manner, it becomes now possible to understand the consequences of kinase inhibition on a systems level.MethodsWe developed a scalable &quot;decryptM&quot; screening platform in a 96-well format and combined it with a mostly automated phosphoproteomic workflow. MS raw files were searched with MaxQuant and boosted with SIMSI and Percolator. Relevant p-site-specific dose-response curves were identified using the novel tool &quot;CurveCurator&quot;. Kinase inhibition estimates were obtained from curated seed p-sites. New kinase substrate relationships were obtained by characteristic potency signatures across the data set.ResultsWe performed systematic and short dose-resolved perturbations of a total of 134 approved and phase 3 clinical kinase inhibitors across 5 different cell lines. This results in a complete data matrix of 715 decryptM experiments that are based on 7,865 individual perturbations at a depth of around 20-25&quot;000 p-sites per drug and cell line. All 28 million dose-response curves were fitted and statistically evaluated using our new analysis tool, CurveCurator, which combines statistical significance with biological effect size into a single relevance score that outperforms traditional Benjamini-Hochberg procedures in terms of specificity and sensitivity. Overall, the global degree of perturbation is between 1-10%, constraining the response always close to the affected pathways. Harnessing the potency dimension of decryptM experiments, which hints at the initially inhibited kinase(s), we identified many known and unknown p-sites that follow their direct upstream kinase inhibition/activation signature across the entire data matrix. Additionally, we also collected clear evidence for numerous questionable kinase-substrate relationships in public databases. On a higher level, we also obtained an activity-based view of the dependencies of different kinases and cellular backgrounds.ConclusionThis is the largest decryptM study existing which allowed a systematic grouping of signaling relevant p-sites into a kinase regulative context by exploiting the potency dimension of drugs.

Oral presentation

Proteomics of neuroinflammatory signalling: illuminating cellular mechanisms driving neurodegenerative diseases

Alzheimer"s (AD) and Parkinson"s disease (PD) are prevalent neurodegenerative diseases, but their underlying mechanisms remain poorly understood. Emerging evidence suggests that neuroinflammation, characterized by the release of pro-inflammatory cytokines like IL-1β, TNF-α, and INF-γ, plays a pivotal role in these diseases, challenging the conventional focus on protein aggregates (Aβ, αSyn). In AD, it has been shown that elevated IL-1β levels induce the translocation of NEDD8 from the nucleus to the cytoplasm, where it co-localizes with the E3-ligase Parkin. Together with the kinase PINK1, Parkin is crucial for the removal of defective mitochondria, with loss-of-function mutations in these genes being the primary cause of early-onset PD. Intriguingly, phosphorylated NEDD8 can activate Parkin, implicating a more complex interconnection between neuroinflammation, NEDD8-and Parkin-regulated phosphorylation-dependent signaling in brain cells. Yet, a mechanistic understanding of cellular processes triggered by neuroinflammation remain elusive.This study aims to investigate spatiotemporal (phospho-)proteome changes in response to neuroinflammatory stress elicited by pro-inflammatory cytokines and αSyn fibrils. To achieve this, spatial-proteomics using subcellular fractionation is combined with high-sensitivity narrow-window data-independent acquisition (nDIA) using the Orbitrap Astral mass spectrometer. This workflow resulted in identification and quantification of ⁓8000 protein groups and between ⁓6000 and 15,000 localized phosphorylation sites per subcellular fraction. IL-1β-dependent subcellular relocation of hundreds of (phospho)proteins was determined in initial analyses of neuronal cell line models. This strategy will be extended to a more physiologically-relevant model system of hPSC derived neurons, astrocytes, microglia, and co-cultures thereof. This system enhances the translational relevance by mimicking neuroinflammation in the complex tissue architecture of the brain. The data obtained reveals the cellular protein abundance changes and phosphorylation site regulation induced under neuroinflammatory stress. This study aspires to unravel the cellular mechanisms underlying neuroinflammation, potentially unlocking new avenues for therapeutic strategies against neurodegenerative diseases.

Prof.

Time- and spatially-resolved TRAP analysis identifies drug targets and deciphers signaling network in vitro and in vivo

Target identification reveals how drugs act, and the discovered targets represent a valuable repertoire for therapeutic target discovery. Current approaches mostly investigate the direct binding targets (directTs) for drugs and lack the ability to decipher the downstream effector proteins (defined as "indirectTs"). Previously, we developed a target-responsive accessibility profiling (TRAP) approach, which measures ligand-binding induced changes in accessibility for target identification by global labeling of reactive proteinaceous lysines via reductive demethylation (Nat Chem Biol., 2023, 19, 1480–1491). We proposed that when the directTs bind to its indirectTs, the chemical accessibility also changes and can thus be detected by TRAP. Since the engagement between the drug and its directTs precedes the engagement between the directTs and the indirectTs, we sought to perform time-resolved TRAP to simultaneously identify the direct -indirect target networks.To meet the high throughput requirements of time-resolved TRAP, data-independent acquisition (DIA) (Nature, 2016, 537, 347–355) is incorporated into the TRAP workflow for label-free quantification of TRAP-labelled peptides. Using TEPP-46 as a model compound, we incubated it with cells and then performed TRAP labelling at 6 different time points after administration (0, 5 min, 15 min, 30 min, 1 hr, 2 hr). Subsequent DIA-TRAP analysis allowed us to identify its bona fide target, PKM2, which showed the most significant decrease in accessibility at the earliest time point (5 min). Interestingly, changes in the accessibility of glycolytic enzymes such as ALDOA and GAPDH were observed at 30 min post-administration. These proteins have been annotated as interacting proteins of PKM2. Surprisingly, at a later time point (2 h), we observed that proteins involved in the cellular response to stress and the organic cyclic compounds metabolic process, which have not been linked to PKM2, also showed altered accessibility. AlphaFold was used to assess the possibility of interactions and biochemical experiments are ongoing to elucidate the signaling pathways involved.With the analysis power enabled by DIA-TRAP, we asked whether we can assess ligands-induced accessibility changes in vivo and identify targets in a spatially-resolved manner. As a proof-of-concept, we administered TEPP-46 to mice inoculated with transplanted tumors and performed TRAP analysis on divided tumor tissues (core and periphery). TRAP analysis showed that the target PKM2 most significantly responded among all quantified TRAP peptides in all assayed regions. Notably, TRAP ratio of PKM2 extracted from tumor periphery most markedly changed when compared to the core, agreeing with the in vivo distribution of TEPP-46.Overall, we demonstrate that DIA-TRAP enables time and spatially-resolved TRAP analysis. It allows us to identify targets for bioactive ligands and profile the downstream effectors, and is applicable to in situ contexts.

Session
Defining signaling networks – functional PTMs

Termin

Vorsitzende

Programm

SessionDefining signaling networks – functional PTMs

Termin

Vorsitzende

Programm

Session
Defining signaling networks – functional PTMs