Myeloid cells are known to play a crucial role in creating a tumor-promoting and immune suppressive microenvironment. Our previous study demonstrated that primary human monocytes can be polarized into immunosuppressive myeloid-derived suppressor cells (MDSCs) by cancer-associated fibroblasts (CAFs) in a 3D co-culture system. However, the molecular mechanisms underlying the immunosuppressive function of MDSCs, especially CAF-induced MDSCs, remain poorly understood. Using mass spectrometry-based proteomics, we compared cell surface protein changes among monocytes, in vitro differentiated CAF-induced MDSCs, M1/M2 macrophages, and dendritic cells, and identified an extracellular vesicle (EV)-mediated secretory phenotype of MDSCs. Functional assays using an MDSC/T-cell co-culture system revealed that blocking EV generation in CAF-induced MDSCs reversed their ability to suppress T-cell proliferation, while EVs isolated from CAF-induced MDSCs directly inhibited T-cell function. Furthermore, we identified fructose bisphosphatase 1 (FBP1) as a cargo protein that is highly enriched in EVs isolated from CAF-induced MDSCs, and pharmacological inhibition of FBP1 partially reversed the suppressive phenotype of MDSCs. Our findings provide valuable insights into the cell surface proteome of different monocyte-derived myeloid subsets and uncover a novel mechanism underlying the interplay between CAFs and myeloid cells in shaping a tumor-permissive microenvironment.

Kinome abundance dataset containing MaxQuant output for raw chemoproteomic data; the processed and filtered protein kinase dataset and the merged abundance of protein kinases identified in full and chemoproteome datasets.

Supplementary Material and Methods

Metabolome dataset containing processed quantitative data for intracellular metabolites and processed quantitative data for extracellular metabolites.

Phosphorylation site abundance dataset containing filtered, processed and annotated phosphorylation sites; STRING phosphoprotein input and output data for the lapatinib mode of action network and two dimensional enrichment analysis comparing lapatinib treatment of parental cells to phosphorylation changes in resistance (only significant terms).

Proteome abundance dataset containing raw MaxQuant output.

Figure S1. Quality of phospho(proteomic) dataset acquired. Figure S2. (Phospho)proteomic analysis of lapatinib mode of action in parental cells. Figure S3. Signaling reprogramming in lapatinib resistance. Figure S4. Identification of pharmacologically actionable targets and phenotypes based on a breast cancer model of lapatinib resistance. Figure S5. Metabolic changes in lapatinib resistant cell line model.

Phosphorylation site abundance dataset containing raw MaxQuant output data.

Although most cancer drugs modulate the activities of cellular pathways by changing posttranslational modifications (PTMs), little is known regarding the extent and the time- and dose-response characteristics of drug-regulated PTMs. In this work, we introduce a proteomic assay called decryptM that quantifies drug-PTM modulation for thousands of PTMs in cells to shed light on target engagement and drug mechanism of action. Examples range from detecting DNA damage by chemotherapeutics, to identifying drug-specific PTM signatures of kinase inhibitors, to demonstrating that rituximab kills CD20-positive B cells by overactivating B cell receptor signaling. DecryptM profiling of 31 cancer drugs in 13 cell lines demonstrates the broad applicability of the approach. The resulting 1.8 million dose-response curves are provided as an interactive molecular resource in ProteomicsDB.

Source code and structural PDBs that went into the Prediction of ternary complex structures using molecular dynamics and proteomics paper.

DNA-binding proteins are promising therapeutic targets but are notoriously difficult to drug. Here, we evaluate a chemoproteomic DNA interaction platform as a complementary strategy for parallelized compound profiling. To enable this approach, we determined the proteomic binding landscape of 92 immobilized DNA sequences. Perturbation-induced activity changes of captured transcription factors in disease-relevant settings demonstrated functional relevance of the enriched subproteome. Chemoproteomic profiling of >300 cysteine-directed compounds against a coverage optimized bead mixture, which specifically captures >150 DNA binders, revealed competition of several DNA-binding proteins, including the transcription factors ELF1 and ELF2. We also discovered the first compound that displaces the DNA-repair complex MSH2-MSH3 from DNA. Compound binding to cysteine 252 on MSH3 was confirmed using chemoproteomic reactive cysteine profiling. Overall, these results suggested that chemoproteomic DNA bead pull-downs enable the specific readout of transcription factor activity and can identify functional "hotspots" on DNA binders toward expanding the druggable proteome.

Targeted protein degradation (TPD) is a promising approach in drug discovery for degrading proteins implicated in diseases. A key step in this process is the formation of a ternary complex where a heterobifunctional molecule induces proximity of an E3 ligase to a protein of interest (POI), thus facilitating ubiquitin transfer to the POI. In this work, we characterize 3 steps in the TPD process. (1) We simulate the ternary complex formation of SMARCA2 bromodomain and VHL E3 ligase by combining hydrogen-deuterium exchange mass spectrometry with weighted ensemble molecular dynamics (MD). (2) We characterize the conformational heterogeneity of the ternary complex using Hamiltonian replica exchange simulations and small-angle X-ray scattering. (3) We assess the ubiquitination of the POI in the context of the full Cullin-RING Ligase, confirming experimental ubiquitinomics results. Differences in degradation efficiency can be explained by the proximity of lysine residues on the POI relative to ubiquitin. The formation of ternary degrader-protein complexes is a key step in the targeted degradation of proteins of interest. Here, the authors explore the structure and dynamics of such complexes applying high-performance computer simulations augmented with experimental data.

Due to its important roles in oncogenic signaling, AKT has been subjected to extensive drug discovery efforts leading to small molecule inhibitors investigated in advanced clinical trials. To better understand how these drugs exert their therapeutic effects at the molecular level, we combined chemoproteomic target affinity profiling using kinobeads and phosphoproteomics to analyze the five clinical AKT inhibitors AZD5363 (Capivasertib), GSK2110183 (Afuresertib), GSK690693, Ipatasertib, and MK-2206 in BT-474 breast cancer cells. Kinobead profiling identified between four and 29 nM targets for these compounds and showed that AKT1 and AKT2 were the only common targets. Similarly, measuring the response of the phosphoproteome to the same inhibitors identified ∼1700 regulated phosphorylation sites, 276 of which were perturbed by all five compounds. This analysis expanded the known AKT signaling network by 119 phosphoproteins that may represent direct or indirect targets of AKT. Within this new network, 41 regulated phosphorylation sites harbor the AKT substrate motif, and recombinant kinase assays validated 16 as novel AKT substrates. These included CEP170 and FAM83H, suggesting a regulatory function of AKT in mitosis and cytoskeleton organization. In addition, a specific phosphorylation pattern on the ULK1-FIP200-ATG13-VAPB complex was found to determine the active state of ULK1, leading to elevated autophagy in response to AKT inhibition.

Targeted protein degradation (TPD) has emerged as a powerful approach in drug discovery for removing (rather than inhibiting) proteins implicated in diseases. A key step in this approach is the formation of an induced proximity complex, where a degrader molecule recruits an E3 ligase to the protein of interest (POI), facilitating the transfer of ubiquitin to the POI and initiating the proteasomal degradation process. Here, we address three critical aspects of the TPD process: 1) formation of the ternary complex induced by a degrader molecule, 2) conformational heterogeneity of the ternary complex, and 3) assessment of ubiquitination propensity via the full Cullin Ring Ligase (CRL) macromolecular assembly. The novel approach presented here combines experimental biophysical data—in this case hydrogen-deuterium exchange mass spectrometry (HDX-MS, which measures the solvent exposure of protein residues)—with all-atom explicit solvent molecular dynamics (MD) simulations aided by enhanced sampling techniques to predict structural ensembles of ternary complexes at atomic resolution. We present results demonstrating the efficiency, accuracy, and reliability of our approach to predict ternary structure ensembles using the bromodomain of SMARCA2 (SMARCA2 BD ) with the E3 ligase VHL as the system of interest. The simulations reproduce X-ray crystal structures – including prospective simulations validated on a new structure that we determined in this work (PDB ID: 7S4E) – with root mean square deviations (RMSD) of 1.1 to 1.6 Å. The simulations also reveal a structural ensemble of low-energy conformations of the ternary complex within a broad energy basin. To further characterize the structural ensemble, we used snapshots from the aforementioned simulations as seeds for Hamiltonian replica exchange molecular dynamics (HREMD) simulations, and then perform 7.1 milliseconds of aggregate simulation time using Folding@home. The resulting free energy surface identifies the crystal structure conformation within a broad low-energy basin and the dynamic ensemble is consistent with solution-phase biophysical experimental data (HDX-MS and small-angle x-ray scattering, SAXS). Finally, we graft structures from the ternary complexes onto the full CRL and perform enhanced sampling simulations, where we find that differences in degradation efficiency can be explained by the proximity distribution of lysine residues on the POI relative to the E2-loaded ubiquitin. Several of the top predicted ubiquitinated lysine residues are validated prospectively through a ubiquitin mapping proteomics experiment.

Integrated analysis of genomes, transcriptomes, proteomes and drug responses of cancer cell lines (CCLs) is an emerging approach to uncover molecular mechanisms of drug action. We extend this paradigm to measuring proteome activity landscapes by acquiring and integrating quantitative data for 10,000 proteins and 55,000 phosphorylation sites (p-sites) from 125 CCLs. These data are used to contextualize proteins and p-sites and predict drug sensitivity. For example, we find that Progesterone Receptor (PGR) phosphorylation is associated with sensitivity to drugs modulating estrogen signaling such as Raloxifene. We also demonstrate that Adenylate kinase isoenzyme 1 (AK1) inactivates antimetabolites like Cytarabine. Consequently, high AK1 levels correlate with poor survival of Cytarabine-treated acute myeloid leukemia patients, qualifying AK1 as a patient stratification marker and possibly as a drug target. We provide an interactive web application termed ATLANTiC (http://atlantic.proteomics.wzw.tum.de), which enables the community to explore the thousands of novel functional associations generated by this work.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Chemical proteomic approaches utilizing immobilized, broad-selective kinase inhibitors (Kinobeads) have proven valuable for the elucidation of a compound's target profile under close-to-physiological conditions and often revealed potentially synergistic or toxic off-targets. Current Kinobeads enrich more than 300 native protein kinases from cell line or tissue lysates but do not systematically cover phosphatidylinositol 3-kinases (PI3Ks) and phosphatidylinositol 3-kinase-related kinases (PIKKs). Some PIKKs and PI3Ks show aberrant activation in many human diseases and are indeed validated drug targets. Here, we report the development of a novel version of Kinobeads that extends kinome coverage to these proteins. This is achieved by inclusion of two affinity probes derived from the clinical PI3K/MTOR inhibitors Omipalisib and BGT226. We demonstrate the utility of the new affinity matrix by the profiling of 13 clinical and preclinical PIKK/PI3K inhibitors. The large discrepancies between the PI3K affinity values obtained and reported results from recombinant assays led us to perform a phosphoproteomic experiment showing that the chemoproteomic assay is the better approximation of PI3K inhibitor action in cellulo. The results further show that NVP-BEZ235 is not a PI3K inhibitor. Surprisingly, the designated ATM inhibitor CP466722 was found to bind strongly to ALK2, identifying a new chemotype for drug discovery to treat fibrodysplasia ossificans progressiva.

The MYC oncogene is upregulated in human cancers by translocation, amplification, and mutation of cellular pathways that regulate Myc. Myc/Max heterodimers bind to E box sequences in the promoter regions of genes and activate transcription. The MYC inhibitor Omomyc can reduce the ability of MYC to bind specific box sequences in promoters of MYC target genes by binding directly to E box sequences as demonstrated by chromatin immunoprecipitation (CHIP). Here, we demonstrate by both a proximity ligation assay (PLA) and double chromatin immunoprecipitation (ReCHIP) that Omomyc preferentially binds to Max, not Myc, to mediate inhibition of MYC-mediated transcription by replacing MYC/MAX heterodimers with Omomyc/MAX heterodimers. The formation of Myc/Max and Omomyc/Max heterodimers occurs cotranslationally; Myc, Max, and Omomyc can interact with ribosomes and Max RNA under conditions in which ribosomes are intact. Taken together, our data suggest that the mechanism of action of Omomyc is to bind DNA as either a homodimer or a heterodimer with Max that is formed cotranslationally, revealing a novel mechanism to inhibit the MYC oncogene. We find that in vivo, Omomyc distributes quickly to kidneys and liver and has a short effective half-life in plasma, which could limit its use in vivo.

MicroRNAs (miRNAs) have been described to simultaneously inhibit hundreds of targets, albeit to a modest extent. It was recently proposed that there could exist more specific, exceptionally strong binding to a subgroup of targets. However, it is unknown, whether this is the case and how such targets can be identified. Using Argonaute2-ribonucleoprotein immunoprecipitation and in vivo competitive binding assays, we demonstrate for miRNAs-21, -199-3p and let-7 exceptional regulation of a subset of targets, which are characterized by preferential miRNA binding. We confirm this finding by analysis of independent quantitative proteome and transcriptome datasets obtained after miRNA silencing. Our data suggest that mammalian miRNA activity is guided by preferential binding of a small set of 3 '-untranslated regions, thereby shaping a steep gradient of regulation between potential targets. Our approach can be applied for transcriptome-wide identification of such targets independently of the presence of seed complementary sequences or other predictors.