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Comprehensive, in-depth identification of the human leukocyte antigen HLA-I and HLA-II tumor immunopeptidome can inform the development of cancer immunotherapies. Mass spectrometry (MS) is powerful technology for direct identification of HLA peptides from patient derived tumor samples or cell lines. However, achieving sufficient coverage to detect rare, clinically relevant antigens requires highly sensitive MS-based acquisition methods and large amounts of sample. While immunopeptidome depth can be increased by off-line fractionation prior to MS, its use is impractical when analyzing limited amounts of primary tissue biopsies. To address this challenge, we developed and applied a high throughput, sensitive, single-shot MS-based immunopeptidomics workflow that leverages trapped ion mobility time-of-flight mass spectrometry on the Bruker timsTOF SCP. We demonstrate >2-fold improved coverage of HLA immunopeptidomes relative to prior methods with up to 15,000 distinct HLA-I and HLA-II peptides from 4e7 cells. Our optimized single-shot MS acquisition method on the timsTOF SCP maintains high coverage, eliminates the need for off-line fractionation and reduces input requirements to as few as 1e6 A375 cells for > 800 distinct HLA-I peptides. This depth is sufficient to identify HLA-I peptides derived from cancer-testis antigen, and novel/unannotated open reading frames. We also apply our optimized single-shot SCP acquisition methods to tumor derived samples, enabling sensitive, high throughput and reproducible immunopeptidome profiling with detection of clinically relevant peptides from less than 4e7 cells or 15 mg wet weight tissue.

Interactions between T cell receptors (TCRs) and their cognate tumour antigens are central to antitumour immune responses1–3; however, the relationship between phenotypic characteristics and TCR properties is not well elucidated. Here we show, by linking the antigenic specificity of TCRs and the cellular phenotype of melanoma-infiltrating lymphocytes at single-cell resolution, that tumour specificity shapes the expression state of intratumoural CD8+ T cells. Non-tumour-reactive T cells were enriched for viral specificities and exhibited a non-exhausted memory phenotype, whereas melanoma-reactive lymphocytes predominantly displayed an exhausted state that encompassed diverse levels of differentiation but rarely acquired memory properties. These exhausted phenotypes were observed both among clonotypes specific for public overexpressed melanoma antigens (shared across different tumours) or personal neoantigens (specific for each tumour). The recognition of such tumour antigens was provided by TCRs with avidities inversely related to the abundance of cognate targets in melanoma cells and proportional to the binding affinity of peptide–human leukocyte antigen (HLA) complexes. The persistence of TCR clonotypes in peripheral blood was negatively affected by the level of intratumoural exhaustion, and increased in patients with a poor response to immune checkpoint blockade, consistent with chronic stimulation mediated by residual tumour antigens. By revealing how the quality and quantity of tumour antigens drive the features of T cell responses within the tumour microenvironment, we gain insights into the properties of the anti-melanoma TCR repertoire. The authors use single-cell profiling and T cell receptor specificity screening to show how tumour antigen recognition shapes the phenotypes of CD8+ T cells and antitumour immune responses.

Within the tumour microenvironment, CD4(+) T cells can promote or suppress antitumour responses through the recognition of antigens presented by human leukocyte antigen (HLA) class II molecules(1,2), but how cancers co-opt these physiologic processes to achieve immune evasion remains incompletely understood. Here we performed in-depth analysis of the phenotype and tumour specificity of CD4(+) T cells infiltrating human melanoma specimens, finding that exhausted cytotoxic CD4(+) T cells could be directly induced by melanoma cells through recognition of HLA class II-restricted neoantigens, and also HLA class I-restricted tumour-associated antigens. CD4(+) T regulatory (T(Reg)) cells could be indirectly elicited through presentation of tumour antigens via antigen-presenting cells. Notably, numerous tumour-reactive CD4(+) T(Reg) clones were stimulated directly by HLA class II-positive melanoma and demonstrated specificity for melanoma neoantigens. This phenomenon was observed in the presence of an extremely high tumour neoantigen load, which we confirmed to be associated with HLA class II positivity through the analysis of 116 melanoma specimens. Our data reveal the landscape of infiltrating CD4(+) T cells in melanoma and point to the presentation of HLA class II-restricted neoantigens and direct engagement of immunosuppressive CD4(+) T(Reg) cells as a mechanism of immune evasion that is favoured in HLA class II-positive melanoma.

Summary Protein kinases are key regulators of cellular signal transduction with crucial roles for healthy cell biology and pathogenesis. Accordingly many drugs have been developed to address the dysregulation of these enzymes, notably in oncology. Around 50 small molecule kinase inhibitors have already been approved, and hundreds of such drugs are the object of clinical investigation to combat these disease drivers with targeted therapeutic approaches. Due to the conserved structure of the kinase domain across the kinome, compounds may not only act on their intended targets but may also bind and inhibit other proteins. Thus, many kinase inhibitors display a promiscuous target profile that makes selectivity profiling indispensable in order to understand the positive and negative actions of the drugs regardless of their use as chemical probes or therapeutic agents. Chemical proteomics has developed into a powerful technique for investigating drug–protein interactions. One successful example is the Kinobeads technology that features broadly selective small molecule kinase inhibitors immobilized on sepharose beads for affinity enrichment of native kinases out of any tissue or cell lysates. Target deconvolution of kinase inhibitors is achieved through a competitive set-up in which the lysate is treated with increasing concentrations of an inhibitor of interest before affinity enrichment with the Kinobeads matrix. This results in a competition between the Kinobeads and the compound for the active sites of all targets present in the lysate. For each engaged target, reduced binding to Kinobeads ensues, leading to dose-dependent intensity reduction of the target peptides in the mass spectrometric read-out. Analysis of the many dose–response curves obtained helps to establish the target space of a molecule. In this chapter we describe the principle, experimental details, and applications of the Kinobeads technology. We first draw the reader's attention to the theoretical background and important points to consider when developing a chemical proteomics profiling assay. We then disclose our latest standard operating procedure to achieve a successful Kinobeads profiling assay. Next, we summarize representative application examples of the Kinobeads in different stages of the drug discovery pipeline for human and non-human proteomes. Finally we propose a perspective of the future opportunities of the Kinobeads approach in drug discovery.

Pancreatic adenocarcinoma (PDAC) is among the most lethal cancer types and has been largely recalcitrant to traditional immunotherapy. A large subset of PDAC tumors is computationally predicted to harbor potentially immunogenic peptides for MHC class I (MHC-I) presentation, but the nature, expression, and immunogenicity of these peptides has yet to be determined. By investigating the PDAC immunopeptidome, we can uncover and exploit novel immune-based targets for PDAC and render it vulnerable to immunotherapy. Prior efforts to study the immunopeptidome in PDAC have largely focused on profiling MHC-associated peptides (MAPs) from bulk tumor samples. This approach is severely limited by the contribution of MAPs from the non-malignant compartments, which constitutes most of the cellular mass in PDAC. We can overcome this limitation by using patient-derived organoids (PDOs) to expand a pure cancer cell population for MHC-I immunoprecipitation, followed by LC/MS-MS. We applied this approach and detected 17,000-20,500 unique MAPs per sample, a dramatic increase in depth and resolution over prior efforts. To ascertain which MAPs may be PDAC-restricted, we first analyzed bulk RNA-sequencing data from the Genotype-Tissue Expression Project (767 patients, 30 tissues) to generate a set of genes that are functionally undetectable (Q90 Citation Format: Zackery A. Ely, William A. Freed-Pastor, Zachary J. Kulstad, Jennifer G. Abelin, Eva Verzani, Kevin S. Kapner, Susan Klaeger, Karl R. Clauser, Miles Agus, Alex M. Jaeger, Nimisha B. Pattada, Arjun Bhutkar, Andrew J. Aguirre, Steven A. Carr, Tyler Jacks. Broadening the repertoire of PDAC-specific targets for immune-based therapy through high-resolution immunopeptidomics [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr C014.

Multiomic characterization of patient tissues provides insights into the function of different biological pathways in the context of disease. Much work has been done to serialize proteome and post-translational modification (PTM) analyses to conserve precious patient samples. However, characterizing clinically relevant tissues with multi-ome workflows that have distinct sample processing requirements remains challenging. To overcome the obstacles of combining enrichment workflows that have unique input amounts and utilize both label free and chemical labeling strategies, we developed a highly-sensitive multi-omic networked tissue enrichment (MONTE) workflow for the full analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome and acetylome all from the same tissue sample. The MONTE workflow enables identification of a median of 9,000 HLA-I peptides, 6,000 HLA-II peptides, 10,000 Ub sites, 12,000 proteins, 20,000 phosphorylation sites and 15,000 acetylation sites from patient LUAD tumors. Because all omes are generated from the exact same tissue sample, there is less biological variability in the data enabling more robust integration. The information available in MONTE datasets facilitates the identification of putative immunotherapeutic targets, such as CT antigens and neoantigens presented by HLA complexes, as well as reveal insights into how disease-specific changes in protein expression, protein degradation, cell signaling, metabolic, and epigenetic pathways are involved in disease pathology and treatment.

Immunotherapies have emerged to treat diseases by selectively modulating a patient’s immune response. Although the roles of T and B cells in adaptive immunity have been well studied, it remains difficult to select targets for immunotherapeutic strategies. Because human leukocyte antigen class II (HLA-II) peptides activate CD4+ T cells and regulate B cell activation, proliferation, and differentiation, these peptide antigens represent a class of potential immunotherapy targets and biomarkers. To better understand the molecular basis of how HLA-II antigen presentation is involved in disease progression and treatment, systematic HLA-II peptidomics combined with multiomic analyses of diverse cell types in healthy and diseased states is required. For this reason, MS-based innovations that facilitate investigations into the interplay between disease pathologies and the presentation of HLA-II peptides to CD4+ T cells will aid in the development of patient-focused immunotherapies., Graphical Abstract, Highlights • HLA-II alleles are highly polymorphic and have unique peptide-binding motifs. • HLA-II processing and presentation pathways are complex and challenging to predict. • MS-based HLA-II peptidomics enables insights into HLA-II biology. • Peptide antigens bound to HLA-II may be a source of immunotherapeutic targets., In Brief Although challenges remain in leveraging MS-based HLA-II peptidomics, investigations into the interplay between disease pathologies and the presentation of HLA-II peptides to CD4+ T cells will enable the development of future immunotherapies. In this Review article, we discuss our current understanding of HLA-II peptidomics and outstanding questions in the field and how MS-based innovations will enable us to fill knowledge gaps and help improve our ability to select HLA-II-presented antigens as targets for personalized immunotherapies.

Mass spectrometry is the most effective method to directly identify peptides presented on HLA molecules. However, current standard approaches often require many millions of cells for input material to achieve high coverage of the immunopeptidome and are therefore not compatible with the often limited amounts of tissue available from clinical tumor samples. Here, we evaluated microscaled basic reversed-phase fractionation to separate HLA peptide samples off-line followed by ion mobility coupled to LC-MS/MS for analysis. The combination of these two separation methods enabled identification of 20% to 50% more peptides compared to samples analyzed without either prior fractionation or use of ion mobility alone. We demonstrate coverage of HLA immunopeptidomes with up to 8,107 distinct peptides starting with as few as 100 million cells or 150 milligrams of wet weight tumor tissue. This increased sensitivity can improve HLA binding prediction algorithms and enable detection of clinically relevant epitopes such as neoantigens.

Multiple myeloma (MM) is the second most common hematological malignancy and remains incurable, thus demanding for new therapeutic targets. While the pathophysiology of MM is poorly understood, the substantial responsiveness of MM patients to proteasomal inhibitors (PIs) like bortezomib or carfilzomib hints towards a central role of the ubiquitin proteasome system (UPS). Deubiquitylases (DUBs) are therapeutically targetable components of the UPS, whose inhibition can destabilize oncoproteins. However, the identities of oncoprotein-regulating DUBs remain largely elusive. To identify new vulnerabilities in MM, a CRISPR/Cas9 screen targeting all human DUBs was performed. For validated candidates, phenotypical analysis regarding proliferation and cell cycle progression was performed, as well affinity and non-affinity mass spectrometry-based screens to identify substrates. We thereby identified OTUD6B as a novel oncogene that drives G1/S-transition. LIN28B, a suppressor of microRNA biogenesis, was delineated as both a cell cycle-specific deubiquitylation substrate and activator of OTUD6B. RNA-Seq and qPCR analyses of OTUD6B and LIN28B depleted MM cells revealed that the stabilization of LIN28B drives MYC expression and activity at the G1/S transition, which in turn allows for rapid S-phase entry. Thus, silencing of OTUD6B as well as LIN28B inhibited MM outgrowth in xenograft experiments. Analyses of large MM patient cohorts revealed a progressive increase of OTUD6B expression along the transition from normal plasma cells to MGUS to MM and that high expression of OTUD6B was associated with a significantly adverse overall survival. Furthermore, OTUD6B expression was found to strongly correlate with MYC expression and significantly reduced progression-free survival in patients treated with the PI bortezomib. Knockout of OTUD6B in MM cells significantly enhance the anti-myeloma activity of the drug when using sub-lethal doses. Together, these results validate OTUD6B as a new therapeutically targetable oncogene, dependency, and prognostic factor in MM, that eventually serves as a master regulator of MYC activity to drive cell cycle progression. Citation Format: Ria Spallek, Carmen Paulmann, Oleksandra Karpiuk, Jana Zecha, Susan Klaeger, Isabell Schaeffer, Rupert Öllinger, Thomas Engleitner, Jan Krönke, Matthias Wirth, Ullrich Keller, Roland Rad, Bernahrd Kuster, Florian Bassermann. OTUD6B is a dependency in multiple myeloma that drives S-phase entry via MYC activation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2298.

MS is the most effective method to directly identify peptides presented on human leukocyte antigen (HLA) molecules. However, current standard approaches often use 500 million or more cells as input to achieve high coverage of the immunopeptidome, and therefore, these methods are not compatible with the often limited amounts of tissue available from clinical tumor samples. Here, we evaluated microscaled basic reversed-phase fractionation to separate HLA peptide samples offline followed by ion mobility coupled to LC–MS/MS for analysis. The combination of these two separation methods enabled identification of 20% to 50% more peptides compared with samples analyzed without either prior fractionation or use of ion mobility alone. We demonstrate coverage of HLA immunopeptidomes with up to 8107 distinct peptides starting with as few as 100 million cells. The increased sensitivity obtained using our methods can provide data useful to improve HLA-binding prediction algorithms as well as to enable detection of clinically relevant epitopes such as neoantigens., Graphical Abstract, Highlights • Deep immunopeptidome coverage using liquid and gas phase separation. • Up to 50% more HLA-I peptides using microscaled basic reversed-phase fractionation. • Ion mobility separation (FAIMS) increases HLA-I peptide identifications by up to 58%. • Increased sensitivity provided by these methods enables detection of neoantigens., In Brief Here, we evaluated off-line microscaled basic reversed-phase fractionation as well as the use of ion mobility coupled to LC–MS/MS for analysis of peptides presented on HLA-I. The two separation methods enabled identification of 20% to 50% more peptides compared with samples analyzed without either prior fractionation or use of ion mobility alone starting with as few as 100 million cells. The increased sensitivity obtained using our methods can enable detection of low abundant but clinically relevant epitopes such as neoantigens.

Interactions between T cell receptors (TCRs) and their cognate tumour antigens are central to antitumour immune responses

T cell-mediated immunity plays an important role in controlling SARS-CoV-2 infection; yet the repertoire of naturally processed and presented viral epitopes on HLA class I remains uncharacterized. Here, we report the first HLA-I immunopeptidome of SARS-CoV-2 in two cell lines at different times post-infection using mass spectrometry. We found HLA-I peptides derived not only from canonical ORFs, but also from internal out-of-frame ORFs in Spike and Nucleocapsid not captured by current vaccines. Some peptides from out-of-frame ORFs elicited T cell responses in a humanized mouse model and COVID-19 patients that exceeded responses to canonical peptides including some of the strongest epitopes reported to date. Whole proteome analysis of infected cells revealed that early expressed viral proteins contribute more to HLA-I presentation and immunogenicity. These biological insights as well as the discovery of out-of-frame ORF epitopes will facilitate selection of peptides for immune monitoring and vaccine development., Analysis of the HLA-1 peptidome of SARS-CoV-2 infection identifies peptides derived from canonical and out- of-frame ORFs in viral S and N protein that are not captured by current vaccines and yield potent T cell responses in a mouse model as well as patients with COVID-19.

T cell-mediated immunity may play a critical role in controlling and establishing protective immunity against SARS-CoV-2 infection; yet the repertoire of viral epitopes responsible for T cell response activation remains mostly unknown. Identification of viral peptides presented on class I human leukocyte antigen (HLA-I) can reveal epitopes for recognition by cytotoxic T cells and potential incorporation into vaccines. Here, we report the first HLA-I immunopeptidome of SARS-CoV-2 in two human cell lines at different times post-infection using mass spectrometry. We found HLA-I peptides derived not only from canonical ORFs, but also from internal out-of-frame ORFs in Spike and Nucleoprotein not captured by current vaccines. Proteomics analyses of infected cells revealed that SARS-CoV-2 may interfere with antigen processing and immune signaling pathways. Based on the endogenously processed and presented viral peptides that we identified, we estimate that a pool of 24 peptides would provide one or more peptides for presentation by at least one HLA allele in 99% of the human population. These biological insights and the list of naturally presented SARS-CoV-2 peptides will facilitate data-driven selection of peptides for immune monitoring and vaccine development.

Epigenetic dysregulation is a defining feature of tumorigenesis that is implicated in immune escape1,2. Here, to identify factors that modulate the immune sensitivity of cancer cells, we performed in vivo CRISPR-Cas9 screens targeting 936 chromatin regulators in mouse tumour models treated with immune checkpoint blockade. We identified the H3K9 methyltransferase SETDB1 and other members of the HUSH and KAP1 complexes as mediators of immune escape3-5. We also found that amplification of SETDB1 (1q21.3) in human tumours is associated with immune exclusion and resistance to immune checkpoint blockade. SETDB1 represses broad domains, primarily within the open genome compartment. These domains are enriched for transposable elements (TEs) and immune clusters associated with segmental duplication events, a central mechanism of genome evolution6. SETDB1 loss derepresses latent TE-derived regulatory elements, immunostimulatory genes, and TE-encoded retroviral antigens in these regions, and triggers TE-specific cytotoxic T cell responses in vivo. Our study establishes SETDB1 as an epigenetic checkpoint that suppresses tumour-intrinsic immunogenicity, and thus represents a candidate target for immunotherapy.

Tumor epitopes – peptides that are presented on surface-bound MHC I proteins - provide targets for cancer immunotherapy and have been identified extensively in the annotated protein-coding regions of the genome. Motivated by the recent discovery of translated novel unannotated open reading frames (nuORFs) using ribosome profiling (Ribo-seq), we hypothesized that cancer-associated processes could generate nuORFs that can serve as a new source of tumor antigens that harbor somatic mutations or show tumor-specific expression. To identify cancer-specific nuORFs, we generated Ribo-seq profiles for 29 malignant and healthy samples, developed a sensitive analytic approach for hierarchical ORF prediction, and constructed a high-confidence database of translated nuORFs across tissues. Peptides from 3,555 unique translated nuORFs were presented on MHC I, based on analysis of an extensive dataset of MHC I-bound peptides detected by mass spectrometry, with >20-fold more nuORF peptides detected in the MHC I immunopeptidomes compared to whole proteomes. We further detected somatic mutations in nuORFs of cancer samples and identified nuORFs with tumor-specific translation in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs thus expand the pool of MHC I-presented, tumor-specific peptides, targetable by immunotherapies.

Tumor-associated epitopes presented on MHC-I that can activate the immune system against cancer cells are typically identified from annotated protein-coding regions of the genome, but whether peptides originating from novel or unannotated open reading frames (nuORFs) can contribute to antitumor immune responses remains unclear. Here we show that peptides originating from nuORFs detected by ribosome profiling of malignant and healthy samples can be displayed on MHC-I of cancer cells, acting as additional sources of cancer antigens. We constructed a high-confidence database of translated nuORFs across tissues (nuORFdb) and used it to detect 3,555 translated nuORFs from MHC-I immunopeptidome mass spectrometry analysis, including peptides that result from somatic mutations in nuORFs of cancer samples as well as tumor-specific nuORFs translated in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs are an unexplored pool of MHC-I-presented, tumor-specific peptides with potential as immunotherapy targets. New tumor epitopes are discovered by ribosome profiling and immunopeptidome mass spectrometry.

BackgroundWithin the tumor microenvironment, distinct CD4+ T cell subsets can play different and even opposite roles either promoting or suppressing anti-tumor responses through the recognition of antigens presented by human leukocyte antigen (HLA) class II molecules. However, how cancers co-opt these processes to shape the intratumoral CD4+ landscape and achieve immune evasion remains incompletely understood.MethodsWe performed single-cell characterization of CD4+ tumor infiltrating lymphocytes (TILs) collected from four human melanoma with low or high HLA-class II expression and we utilized TCR reconstruction and antigen specificity screening to unambiguously discover the tumor reactivity of CD4+ TILs. By testing TCR-transduced T cells against autologous patient-derived melanoma cell lines or against autologous antigen presenting cells (APCs) loaded with tumor lysates, we assessed the capacity of CD4+ TCRs to directly or indirectly recognize tumor cells. We defined the antigen-specificity of antitumor CD4+ TCRs by assessing their reactivity towards personal neoantigens (NeoAg) or public melanoma associated antigens (MAAs). Finally, we correlated NeoAg burden and HLA-class II expression in a series of 116 melanoma specimens from 4 independent cohorts of patients.ResultsAnalysis of single-cell data showed that the cluster distribution of cells within each CD4+ TCR clonotype family was highly homogeneous and appeared to follow 3 distinct major phenotypes, corresponding to non-exhausted memory cells, exhausted cells and regulatory cells (TRegs). Strikingly, clonally expanded CD4+ TReg-TILs were highly abundant within the tumor microenvironment of HLA class IIpos melanomas. We found that TCRs from exhausted cytotoxic CD4+ T cells could be directly triggered by melanoma cells not only through recognition of HLA class II restricted antigens, but also through presentation of HLA class I restricted MAAs. TReg-TCRs could be indirectly elicited through presentation of tumor antigens via APCs. Notably, numerous tumor-reactive CD4+ TReg-TCRs were directly stimulated by HLA class IIpos melanoma and demonstrated specificity for melanoma NeoAgs. In HLA class IIpos melanomas, the clonal expansion of numerous tumor-reactive and NeoAg-specific TRegs-clones appeared to be favored by a dramatically high tumor NeoAg load. Analysis of 116 melanoma specimens confirmed the association of elevated HLA-class II expression with extremely high NeoAg burden.ConclusionsOur data elucidate the landscape of infiltrating CD4+ T cells in melanoma and point to presentation of HLA-class II restricted NeoAgs and direct engagement of immunosuppressive CD4+ TRegs as a novel mechanism of immune evasion favored in HLA class IIpos melanoma.

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.

Transport Protein Particle II (TRAPPII) is essential for exocytosis, endocytosis, protein sorting and cytokinesis. In spite of a considerable understanding of its biological role, little information is known about Arabidopsis TRAPPII complex topology and molecular function. In this study, independent proteomic approaches initiated with TRAPP components or Rab-A GTPase variants converge on the TRAPPII complex. We show that the Arabidopsis genome encodes the full complement of 13 TRAPPC subunits, including four previously unidentified components. A dimerization model is proposed to account for binary interactions between TRAPPII subunits. Preferential binding to dominant negative (GDP-bound) versus wild-type or constitutively active (GTP-bound) RAB-A2a variants discriminates between TRAPPII and TRAPPIII subunits and shows that Arabidopsis complexes differ from yeast but resemble metazoan TRAPP complexes. Analyzes of Rab-A mutant variants in trappii backgrounds provide genetic evidence that TRAPPII functions upstream of RAB-A2a, allowing us to propose that TRAPPII is likely to behave as a guanine nucleotide exchange factor (GEF) for the RAB-A2a GTPase. GEFs catalyze exchange of GDP for GTP; the GTP-bound, activated, Rab then recruits a diverse local network of Rab effectors to specify membrane identity in subsequent vesicle fusion events. Understanding GEF-Rab interactions will be crucial to unravel the co-ordination of plant membrane traffic.

Tandem mass tag (TMT)-based quantitation is a strong modality for quantitative proteomics, as samples can be multiplexed, creating large-scale data sets with high precision and minimal missing values. However, coisolation/cofragmentation of near isobaric, coeluting precursor peptide analytes has been well-documented to show ratio compression, compromising the accuracy of peptide/protein quantitation. Advanced peak determination (APD) is a new peak-picking algorithm that shows improved identification of peak detection in survey scans (MS1) to increase the number of precursors selected for unimolecular dissociation (MS2). To increase the number of these "features" selected for MS2 APD purposefully selects multiple peptide precursors of very similar m/ z that often derive from different proteins-a major source of ratio compression in TMT quantification. Here, we evaluate the effects of various data acquisition parameters combined with APD on ratio compression. We find that data acquisition with APD enabled results in more coisolated precursors, more mixed spectra, and in turn, fewer peptide spectral matches, especially at standard on-column loads. We conclude that APD should not be utilized for isobaric tagging, MS2-based experiments.

Epigenetic alterations are defining features of many tumor types and have recently been implicated in tumor immunity. However, the epigenetic mechanisms that mediate immune sensitivity or resistance in cancer cells are poorly characterized. To systematically identify epigenetic regulators of immune evasion in cancer, we performed in vivo loss of function CRISPR screens against 936 chromatin regulator genes in syngeneic murine tumor models treated with immune checkpoint blockade. These screens identified SETDB1, an H3K9-methyltransferase, and associated members of the HUSH and KAP1 complexes as intrinsic mediators of immune evasion in cancer cells. We also found that amplification of SETDB1 (1q21) in certain human tumors is associated with immune exclusion and resistance to immune checkpoint blockade. Mechanistically, we find that SETDB1 targets broad domains, hundreds of kilobases in size, that are predominantly located within the open genome compartment “A” (i.e., euchromatin). These SETDB1 domains show strong enrichment for transposable elements (TEs) of the LTR family, and gene loci that arose through segmental duplication events, a key driver of mammalian genome evolution. Setdb1 KO derepresses latent regulatory elements at TEs within these regions and leads to the transcriptional up-regulation of nearby immune genes, including canonical stimulatory ligands of the NKG2D receptor. SETDB1 loss also triggers the activation of hundreds of TEs with the potential to encode retroviral proteins (Gag, Pol, Env), and promotes immune responses dependent on CD8+ T cells and tumor expression of MHC Class I. Our study establishes SETDB1 as an epigenetic checkpoint that represses intrinsic immunogenicity in cancer cells, and thus represents a novel target to enhance the efficacy and scope of immunotherapy. Citation Format: Jingyi Wu, Arvin Iracheta-Vellve, James Patti, Jeffrey Hsu, Thomas Davis, Deborah Dele-Oni, Peter Du, Jeffrey Ishizuka, Sarah Kim, Susan Klaeger, Nelson Knudsen, Brian Miller, Tung Nguyen, Emily Robitschek, Emily Schneider, Margaret Zimmer, Jacob Jaffe, John Doench, W. Nicholas Haining, Kathleen Yates, Robert Manguso, Bradley Bernstein, Gabriel K. Griffin. Epigenetic silencing by SETDB1 represses tumor-cell intrinsic immunogenicity [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2020 Oct 19-20. Philadelphia (PA): AACR; Cancer Immunol Res 2021;9(2 Suppl):Abstract nr PO009.

Despite the considerable interest in protein kinase C-related kinase 1 (PRK1) as a target in cancer research, there is still a lack of PRK1 inhibitors with suitable selectivity profiles and physicochemical properties. To identify new PRK1 inhibitors we applied a virtual screening approach, which combines ensemble docking, minimization of the protein-ligand complex, binding free energy calculations, and application of quantitative structure-activity relationship (QSAR) models for predicting in vitro activity. The developed approach was then applied in a prospective manner to screen available libraries of kinase inhibitors from Selleck and GlaxoSmithKline (GSK). Compounds that showed favorable prediction were then tested in vitro for PRK1 inhibition. Some of the hits were found to inhibit PRK1 in the low-nanomolar range. Three in vitro hits were additionally tested in a mass-spectrometry-based cellular kinase profiling assay to examine selectivity. Our findings show that nanomolar and drug-like inhibitors can be identified by the virtual screening approach presented herein. The identified inhibitors are valuable tools for gaining a better understanding of PRK1 inhibition, and the identified hits can serve as starting points for further chemical optimization.

Mutants of the FLT3 receptor tyrosine kinase (RTK) with duplications in the juxtamembrane domain (FLT3-ITD) act as drivers of acute myeloid leukemia (AML). Potent tyrosine kinase inhibitors (TKi) of FLT3-ITD entered clinical trials and showed a promising, but transient success due to the occurrence of secondary drug-resistant AML clones. A further caveat of drugs targeting FLT3-ITD is the co-targeting of other RTKs which are required for normal hematopoiesis. This is observed quite frequently. Therefore, novel drugs are necessary to treat AML effectively and safely. Recently bis(1H-indol-2-yl)methanones were found to inhibit FLT3 and PDGFR kinases. In order to optimize these agents we synthesized novel derivatives of these methanones with various substituents. Methanone 16 and its carbamate derivative 17b inhibit FLT3-ITD at least as potently as the TKi AC220 (quizartinib). Models indicate corresponding interactions of 16 and quizartinib with FLT3. The activity of 16 is accompanied by a high selectivity for FLT3-ITD.

Colorectal cancer (CRC) is one of the top three most common cancers and among the top four causes of cancer-related deaths worldwide (Torre et al., 2015). CRC patients are well characterised on the transcriptome and proteome level, but proteomics data on representative cell lines as model systems for pre-clinical drug sensitivity studies lag behind. Here, label-free quantitative mass spectrometry was used to characterise the kinomes and full proteomes of 65 CRC cell lines, collectively termed the CRC65 cell line panel. This data was integrated with proteomics data on patient samples, as well as public transcriptome and drug sensitivity datasets, which were reanalysed from raw data in order to unify and streamline the data processing. Protein/mRNA ratios were constant across these datasets, enabling linear prediction of protein abundance from mRNA abundance after appropriate adjustment, which was used for mRNA-guided missing value imputation. An exploration of secondary imputation methods prompted the development of a complementary method for minimum-guided missing value imputation. Combining the proteomics datasets on cell lines and patients led to the discovery of integrated proteomic subtypes of CRC and enabled the identification of representative cell lines for each of them. Modelling publicly available dose-response data generated by four large-scale drug sensitivity studies as a function of kinome/full proteome profiles fuelled the prediction of drug sensitivity for cell lines and patients, allowed the identification of drugs differentially effective between the different integrated proteomic subtypes and revealed MERTK as a predictive biomarker for resistance towards MEK1/2 inhibitors. This predictive role of MERTK was subsequently confirmed using in vitro experiments, while immunohistochemistry of TMAs from 1,074 tumours generated as part of the QUASAR2 clinical trial unveiled that MERTK is also a prognostic biomarker in CRC. This dataset will be made available to the scientific community to facilitate the design of prospective clinical studies.

Contains fulltext : 190745.pdf (Publisher’s version ) (Closed access) Individuals with acute myeloid leukemia (AML) harboring an internal tandem duplication (ITD) in the gene encoding Fms-related tyrosine kinase 3 (FLT3) who relapse after allogeneic hematopoietic cell transplantation (allo-HCT) have a 1-year survival rate below 20%. We observed that sorafenib, a multitargeted tyrosine kinase inhibitor, increased IL-15 production by FLT3-ITD(+) leukemia cells. This synergized with the allogeneic CD8(+) T cell response, leading to long-term survival in six mouse models of FLT3-ITD(+) AML. Sorafenib-related IL-15 production caused an increase in CD8(+)CD107a(+)IFN-gamma(+) T cells with features of longevity (high levels of Bcl-2 and reduced PD-1 levels), which eradicated leukemia in secondary recipients. Mechanistically, sorafenib reduced expression of the transcription factor ATF4, thereby blocking negative regulation of interferon regulatory factor 7 (IRF7) activation, which enhanced IL-15 transcription. Both IRF7 knockdown and ATF4 overexpression in leukemia cells antagonized sorafenib-induced IL-15 production in vitro. Human FLT3-ITD(+) AML cells obtained from sorafenib responders following sorafenib therapy showed increased levels of IL-15, phosphorylated IRF7, and a transcriptionally active IRF7 chromatin state. The mitochondrial spare respiratory capacity and glycolytic capacity of CD8(+) T cells increased upon sorafenib treatment in sorafenib responders but not in nonresponders. Our findings indicate that the synergism of T cells and sorafenib is mediated via reduced ATF4 expression, causing activation of the IRF7-IL-15 axis in leukemia cells and thereby leading to metabolic reprogramming of leukemia-reactive T cells in humans. Therefore, sorafenib treatment has the potential to contribute to an immune-mediated cure of FLT3-ITD-mutant AML relapse, an otherwise fatal complication after allo-HCT.

Polo-like kinase 1 (Plk1) is a central regulator of mitosis and has been validated as a target for antitumor therapy. The polo-box domain (PBD) of Plk1 regulates its kinase activity and mediates the subcellular localization of Plk1 and its interactions with a subset of its substrates. Functional inhibition of the Plk1 PBD by low-molecular weight inhibitors has been shown to represent a viable strategy by which to inhibit the enzyme, while avoiding selectivity issues caused by the conserved nature of the ATP binding site. Here, we report structure-activity relationships and mechanistic analysis for the first reported Plk1 PBD inhibitor, Poloxin. We present the identification of the optimized analog Poloxin-2, displaying significantly improved potency and selectivity over Poloxin. Poloxin-2 induces mitotic arrest and apoptosis in cultured human tumor cells at low micromolar concentrations, highlighting it as a valuable tool compound for exploring the function of the Plk1 PBD in living cells.

An atlas for drug interactions Kinase inhibitors are an important class of drugs that block certain enzymes involved in diseases such as cancer and inflammatory disorders. There are hundreds of kinases within the human body, so knowing the kinase “target” of each drug is essential for developing successful treatment strategies. Sometimes clinical trials can fail because drugs bind more than one target. Yet sometimes off-target effects can be beneficial, and drugs can be repurposed for treatment of additional diseases. Klaeger et al. performed a comprehensive analysis of 243 kinase inhibitors that are either approved for use or in clinical trials. They provide an open-access resource of target summaries that could help researchers develop better drugs, understand how existing drugs work, and design more effective clinical trials. Science , this issue p. eaan4368

Although substantial progress has been made regarding the use of molecularly targeted cancer therapies, resistance almost invariably develops and presents a major clinical challenge. The tumor microenvironment can rescue cancer cells from kinase inhibitors by growth-factor mediated induction of pro-survival pathways. Here we show that epidermal growth factor receptor (EGFR) inhibition by Gefitinib is counteracted by growth factors, notably FGF2, and we assessed the global molecular consequences of this resistance at the proteome and phosphoproteome level in A431 cells. Tandem mass tag peptide labeling and quantitative mass spectrometry allowed the identification and quantification of 22 000 phosphopeptides and 8800 proteins in biological triplicates without missing values. The data show that FGF2 protects the cells from the antiproliferative effect of Gefitinib and largely prevents reprogramming of the proteome and phosphoproteome. Simultaneous EGFR/FGFR or EGFR/GSG2 (Haspin) inhibition overcomes this resistance, and the phosphoproteomic experiments further prioritized the RAS/MEK/ERK as well as the PI3K/mTOR axis for combination treatment. Consequently, the MEK inhibitor Trametinib prevented FGF2-mediated survival of EGFR inhibitor-resistant cells when used in combination with Gefitinib. Surprisingly, the PI3K/mTOR inhibitor Omipalisib reversed resistance mediated by all four growth factors tested, making it an interesting candidate for mitigating the effects of the tumor microenvironment.

The receptor tyrosine kinase EPHA2 (Ephrin type-A receptor 2) plays important roles in oncogenesis, metastasis, and treatment resistance, yet therapeutic targeting, drug discovery, or investigation of EPHA2 biology is hampered by the lack of appropriate inhibitors and structural information. Here, we used chemical proteomics to survey 235 clinical kinase inhibitors for their kinase selectivity and identified 24 drugs with submicromolar affinities for EPHA2. NMR-based conformational dynamics together with nine new cocrystal structures delineated drug-EPHA2 interactions in full detail. The combination of selectivity profiling, structure determination, and kinome wide sequence alignment allowed the development of a classification system in which amino acids in the drug binding site of EPHA2 are categorized into key, scaffold, potency, and selectivity residues. This scheme should be generally applicable in kinase drug discovery, and we anticipate that the provided information will greatly facilitate the development of selective EPHA2 inhibitors in particular and the repurposing of clinical kinase inhibitors in general.

Somatic mutations in cancer cells can generate neoantigens which can be recognized by immune cells and trigger an immune response. Patients vaccinated with neoantigen-based peptides display expanded neoantigen-specific T cells, suggesting that this could be a promising avenue for cancer treatment. Currently, neoantigen predictions are based on mutations detected by whole exome sequencing, which covers a pre-determined set of annotated exons, and often falls short for cancers with few somatic mutations. Ribosome profiling (Ribo-seq), which allows to monitor mRNA translation, has predicted a plethora of translated novel unannotated ORFs (nuORFs). Here we hypothesized that nuORFs can provide another source of neoantigens in cancer cells. In particular, we focused on nuORFs in the following categories: 1) nuORFs expressed in healthy and cancer cells, that have acquired tumor-specific somatic mutations; 2) nuORFs upregulated in or specific to cancer cells. To explore this hypothesis, we performed Ribo-seq on primary healthy and cancer cells and cell lines from melanoma, glioblastoma, colon carcinoma and chronic lymphocytic leukemia. Using this extensive dataset, we performed hierarchical ORF prediction analysis to build a database of highest confidence predicted translated nuORFs across healthy and cancer cell types. To determine if peptides from nuORFs can be a source of antigens, we searched our collection of mono-allelic MHC class I immunopeptidome mass spectrometry (MS) spectra from 94 common HLA alleles against our pan-tissue nuORF database. Additionally, we performed MHC class I immunoprecipitation followed by MS on the same cells used for Ribo-seq. We found HLA-presented unmutated peptides derived from thousands of nuORFs, found within, but out-of-frame with annotated protein-coding ORFs, within 5’ and 3’ untranslated regions of annotated protein-coding transcripts, long non-coding RNAs (lncRNAs), pseudogenes, and other RNA species. The HLA-binding motifs of peptides from nuORFs correspond to the expected motifs for given HLA types, indicating that 1) nuORFs are translated and 2) nuORF-derived peptides are presented on MHC I. To identify tumor-specific somatic mutations in nuORFs, we performed whole genome sequencing on patient-matched healthy and cancer cells and mapped somatic mutations to annotated ORFs and nuORFs. Finally, to identify nuORFs upregulated in or specific to cancer cells, we compared translation levels of nuORFs between healthy and cancer cells of the same origin. We found translated nuORFs with cancer-specific somatic mutations and nuORFs highly upregulated in and specific to cancer cells, suggesting that they can give rise to neoantigens. In conclusion, nuORFs are translated, contribute peptides to MHC I presentation, acquire somatic mutations, are expressed in tissue- and cancer-dependent manner and should be considered in the search for neoantigens in cancer. Citation Format: Tamara Ouspenskaia, Travis E. Law, Karl R. Clauser, Susan Klaeger, Derin B. Keskin, Bo Li, Elena Christian, Yuen Ting Chow, Phuong M. Le, Joshua Gould, Zhe Ji, Wandi Zhang, Pavan Bachireddy, Siranush Sarkizova, Nir Hacohen, Steven A. Carr, Catherine J. Wu, Aviv Regev. Neoantigens from translated unannotated open reading frames in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 566.

Introduction: Cancer vaccine therapies rely on accurate personalized selection of immunizing peptides in order to potentiate tumor-specific immune responses against neoepitopes derived from somatic mutations. Given the unique accumulation of mutations in each tumor as well as the patient’s particular complement of HLA class I alleles, the ability to accurately predict which epitopes will be presented by tumor cells is a fundamental prerequisite for successful vaccine design. By utilizing a mono-allelic mass spectrometry (MS) strategy for profiling the endogenous HLA class I peptidome, we recently showed that prediction of endogenous presentation can be drastically improved when model training integrates peptide sequence along with intracellular signals such as likelihood of proteasomal processing and peptide abundance. Yet the limited set of mono-allelic data did not allow for deep comparative analysis across HLA- A, B, and C alleles, which can better inform pan-allele predictor design. Moreover, the significant variability in per-allele model performance remains unexplained. Methods: We recently developed a scalable mono-allelic MS technique to profile naturally presented peptides on HLA molecules, whereby the HLA class I deficient B721.221 cell line is transfected with HLA expression vectors coding for a single allele of interest and eluted HLA peptides are analyzed by LC-MS/MS. In addition, endogenously presented antigens on primary tumor-derived cell lines from 4 melanoma patients were also identified via MS. To extract knowledge from this unique dataset, we implemented computational tools to summarize, visualize, and compare the characteristics of HLA- A, B, C, and G alleles and developed a novel approach to define allele similarity that takes into account the collection of sub-motifs per allele. We trained neural network prediction models, validated their performance on internal and external datasets, and analyzed the variability in performance across alleles. Results: To date, we have generated binding data for 92 HLA- A, B, C and G alleles, identifying more than 190,000 peptides and covering the most frequent alleles in the population. Extensive mono-allelic profiling revealed that some alleles present non-9-mer peptides with high frequency. The availability of large number of non-9-mer peptides allowed us to build length-specific models that often performed better than the corresponding non-length-specific models currently used. We observe that HLA- A and B alleles present more peptides of length 10 and 11 than C alleles, while C alleles have a higher propensity for 8-mers. Correlation-based analysis of binding motifs revealed that HLA-A and B motifs are more specific whereas C motifs are less stringent and thus share more overlapping binders. Since binding data are available only for a fraction of all known alleles, pan-allele models implicitly embed allele similarity to predict for uncharacterized alleles based on the sequence of the binding pocket. By clustering allele-specific peptides into sub-motifs, we propose a novel explicit approach to delineate allele similarity at finer granularity that can improve pan-allele model design. We show that our allele-specific models are better at discriminating tumor-presented epitopes than state of the art predictors and investigate the relationship between false discovery rate and natural abundance of anchor residues to better understand differences in model accuracy amongst alleles. Finally, deconvolution of tumor-presented peptides demonstrated that ~10% of peptides are presented on HLA-C, which has been historically understudied. Conclusions: We have vastly expanded the collection of endogenous HLA-specific peptides deriving biologic insights into the principles of epitope presentations and valuable considerations for prediction model design and epitope selection for tumor vaccines. Citation Format: Siranush Sarkizova, Susan Klaeger, Derin B. Keskin, Karl Clauser, Hasmik Keshishian, Christina R. Hartigan, Nir Hacohen, Steven A. Carr, Catherine J. Wu. Broad analysis and more accurate predictions of HLA class I epitope binding in 92 common HLA alleles profiled by mono-allelic mass spectrometry [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B042.

Cancer vaccines have been envisioned as a key tool for generating effective cancer therapy. Tumor neoantigens are ideal targets because of their exquisite tumor-specific expression (arising from somatic mutations of the tumor) and high level of immunogenicity (lacking of central tolerance against them). Recently, we and others have demonstrated that personalized neoantigen-targeting vaccines are safe, feasible and highly immunogenic in phase I trials of stage III/IV resected high-risk melanoma (Ott & Hu, Nature 2017; Sahin, Nature 2017). Our neoantigen vaccine (NeoVax), consisting of up to 20 long peptides and poly-ICLC, induced strong polyfunctional neoantigen-specific T-cells that recognized patient tumor in vitro. In addition, 2 patients who were vaccinated and received anti-PD1 checkpoint blockade (CPB) therapy upon relapse had durable complete responses (CRs). Thus far, these vaccine studies have been performed in the adjuvant setting, preventing direct assessment of on-target tumor killing in vivo due to the lack of evaluable tumor. On the other hand, the detection of epitope spreading (the broadening of the immune response from the initially targeted epitope to others) would indirectly suggest therapy-induced tumor lysis, whereby the release of additional tumor antigens leads to further tumor-specific T-cell activation. To explore the hypothesis that NeoVax+/- CPB generates epitope spreading, we evaluated the T-cell responses against neoantigens and tumor associated antigens (TAAs) that were not included in the original vaccine in 3 patients. We performed experiments for a patient with stage III melanoma who has remained disease-free (Pt.3) after vaccination and 2 patients with resected stage IV disease who recurred but achieved CR after CPB (Pts. 2&6). For the assessment of CD8+ T-cell responses, we designed 9-10 aa epitope length peptides (predicted by NetMHCpan and/or a mass spectrometry [MS]-based prediction algorithm (Abelin, Immunity 2017) or detected physically on the tumor’s surface class I complexes by MS) arising from 3 categories of antigens: (i) neoantigen peptides; (ii) TAA peptides based on high tumor gene expression; (iii) TAA peptides, detected on the tumor by MS (available for 2 of the 3 patients). For testing of CD4+ T-cell responses, we designed 15-16 aa peptides that spanned predicted neoepitopes from category i. Per patient, we designed peptides against up to 70 genes (~20 for each category). PBMCs from pre- , week 16 post-vaccination and post-CPB were stimulated with peptide pools (~10 peptides/pool) for 2 weeks, followed by restimulation with individual peptides in IFN-γ ELISPOT assays to deconvolute the peptides. Thus far, we have tested CD8+ T-cells against 71 neoantigens (category i) and 22 TAAs (ii) from Pts. 2 and 6, and CD4+ T-cells against 30 neoantigens from all 3 patients. We identified CD4+ T-cells specific for 3 peptides (mut-AGAP3 [Pt.2], -EYA3 and -P2RY4 [Pt.3]) in the week 16 samples that were not included in the original respective vaccines; these populations were expanded only post, but not pre-vaccination. For Pt.2, an additional CD4+ T-cell response against a different neoantigen peptide derived from mut-AGAP3 was detected only after CPB therapy. Lastly, all four lines of CD4+ T-cells reactive against these identified neoantigens were able to discriminate between the mutated and wild-type forms of the peptides, suggesting tumor specificity and lack of cross reactivity with normal tissues. Therefore, our results demonstrate that epitope spreading occurred in 2 patients after vaccination, and further spreading was detected in one of the two following CPB therapy. Ongoing studies are focused on screening additional peptides and investigating the association of epitope spreading and any residual tumor burden. The newly activated antigen-specific T-cells can target additional tumor antigens provided by epitope spreading, thus potentially enhancing therapeutic efficacy. Citation Format: Zhuting Hu, Donna Leet, Siranush Sarkizova, Rebecca Holden, Jing Sun, Susan Klaeger, Karl R. Clauser, Sachet A. Shukla, Wandi Zhang, Steven A. Carr, Edward F. Fritsch, Bradley L. Pentelute, Nir Hacohen, Derin B. Keskin, Patrick A. Ott, Catherine J. Wu. Personalized neoantigen-targeting vaccines for high-risk melanoma generate epitope spreading [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr A010.

Aim: The histone kinase PRK1 has been identified as a potential target to combat prostate cancer but selective PRK1 inhibitors are lacking. The US FDA -approved JAK1–3 inhibitor tofacitinib also potently inhibits PRK1 in vitro. Results: We show that tofacitinib also inhibits PRK1 in a cellular setting. Using tofacitinib as a starting point for structure–activity relationship studies, we identified a more potent and another more selective PRK1 inhibitor compared with tofacitinib. Furthermore, we found two potential PRK1/JAK3-selectivity hotspots. Conclusion: The identified inhibitors and the selectivity hotspots lay the basis for the development of selective PRK1 inhibitors. The identification of PRK1, but also of other cellular tofacitinib targets, has implications on its clinical use and on future development of tofacitinib-like JAK inhibitors. [Formula: see text]

Many protein kinases are valid drug targets in oncology because they are key components of signal transduction pathways. The number of clinical kinase inhibitors is on the rise, but these molecules often exhibit polypharmacology, potentially eliciting desired and toxic effects. Therefore, a comprehensive assessment of a compound's target space is desirable for a better understanding of its biological effects. The enzyme ferrochelatase (FECH) catalyzes the conversion of protoporphyrin IX into heme and was recently found to be an off-target of the BRAF inhibitor Vemurafenib, likely explaining the phototoxicity associated with this drug in melanoma patients. This raises the question of whether FECH binding is a more general feature of kinase inhibitors. To address this, we applied a chemical proteomics approach using kinobeads to evaluate 226 clinical kinase inhibitors for their ability to bind FECH. Surprisingly, low or submicromolar FECH binding was detected for 29 of all compounds tested and isothermal dose response measurements confirmed target engagement in cells. We also show that Vemurafenib, Linsitinib, Neratinib, and MK-2461 reduce heme levels in K562 cells, verifying that drug binding leads to a loss of FECH activity. Further biochemical and docking experiments identified the protoporphyrin pocket in FECH as one major drug binding site. Since the genetic loss of FECH activity leads to photosensitivity in humans, our data strongly suggest that FECH inhibition by kinase inhibitors is the molecular mechanism triggering photosensitivity in patients. We therefore suggest that a FECH assay should generally be part of the preclinical molecular toxicology package for the development of kinase inhibitors.