Graph-pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity.

Antigen presentation on MHC class II (pMHCII presentation) plays an essential role in the adaptive immune response to extracellular pathogens and cancerous cells. But it can also reduce the efficacy of large-molecule drugs by triggering an anti-drug response. Significant progress has been made in pMHCII presentation modeling due to the collection of large-scale pMHC mass spectrometry datasets (ligandomes) and advances in machine learning. Here, we develop graph-pMHC, a graph neural network approach to predict pMHCII presentation. We derive adjacency matrices for pMHCII using Alphafold2-multimer and address the peptide-MHC binding groove alignment problem with a simple graph enumeration strategy. We demonstrate that graph-pMHC dramatically outperforms methods with suboptimal inductive biases, such as the multilayer-perceptron-based NetMHCIIpan-4.0 (+20.17% absolute average precision). Finally, we create an antibody drug immunogenicity dataset from clinical trial data and develop a method for measuring anti-antibody immunogenicity risk using pMHCII presentation models. Our model increases receiver operating characteristic curve (ROC)-area under the ROC curve (AUC) by 2.57% compared to just filtering peptides by hits in OASis alone for predicting antibody drug immunogenicity.

PROTACs Targeting BRM (SMARCA2) Afford Selective In Vivo Degradation over BRG1 (SMARCA4) and Are Active in BRG1 Mutant Xenograft Tumor Models.

The identification of VHL-binding proteolysis targeting chimeras (PROTACs) that potently degrade the BRM protein (also known as SMARCA2) in SW1573 cell-based experiments is described. These molecules exhibit between 10- and 100-fold degradation selectivity for BRM over the closely related paralog protein BRG1 (SMARCA4). They also selectively impair the proliferation of the H1944 "BRG1-mutant" NSCLC cell line, which lacks functional BRG1 protein and is thus highly dependent on BRM for growth, relative to the wild-type Calu6 line. In vivo experiments performed with a subset of compounds identified PROTACs that potently and selectively degraded BRM in the Calu6 and/or the HCC2302 BRG1 mutant NSCLC xenograft models and also afforded antitumor efficacy in the latter system. Subsequent PK/PD analysis established a need to achieve strong BRM degradation (>95%) in order to trigger meaningful antitumor activity in vivo. Intratumor quantitation of mRNA associated with two genes whose transcription was controlled by BRM (PLAU and KRT80) also supported this conclusion.

Increasing the Throughput and Reproducibility of Activity-Based Proteome Profiling Studies with Hyperplexing and Intelligent Data Acquisition.

Intelligent data acquisition (IDA) strategies, such as a real-time database search (RTS), have improved the depth of proteome coverage for experiments that utilize isobaric labels and gas phase purification techniques (i.e., SPS-MS3). In this work, we introduce inSeqAPI, an instrument application programing interface (iAPI) program that enables construction of novel data acquisition algorithms. First, we analyze biotinylated cysteine peptides from ABPP experiments to demonstrate that a real-time search method within inSeqAPI performs similarly to an equivalent vendor method. Then, we describe PairQuant, a method within inSeqAPI designed for the hyperplexing approach that utilizes protein-level isotopic labeling and peptide-level TMT labeling. PairQuant allows for TMT analysis of 36 conditions in a single sample and achieves ∼98% coverage of both peptide pair partners in a hyperplexed experiment as well as a 40% improvement in the number of quantified cysteine sites compared with non-RTS acquisition. We applied this method in the ABPP study of ligandable cysteine sites in the nucleus leading to an identification of additional druggable sites on protein- and DNA-interaction domains of transcription regulators and on nuclear ubiquitin ligases.

Systematic discovery of neoepitope-HLA pairs for neoantigens shared among patients and tumor types.

The broad application of precision cancer immunotherapies is limited by the number of validated neoepitopes that are common among patients or tumor types. To expand the known repertoire of shared neoantigen-human leukocyte antigen (HLA) complexes, we developed a high-throughput platform that coupled an in vitro peptide-HLA binding assay with engineered cellular models expressing individual HLA alleles in combination with a concatenated transgene harboring 47 common cancer neoantigens. From more than 24,000 possible neoepitope-HLA combinations, biochemical and computational assessment yielded 844 unique candidates, of which 86 were verified after immunoprecipitation mass spectrometry analyses of engineered, monoallelic cell lines. To evaluate the potential for immunogenicity, we identified T cell receptors that recognized select neoepitope-HLA pairs and elicited a response after introduction into human T cells. These cellular systems and our data on therapeutically relevant neoepitopes in their HLA contexts will aid researchers studying antigen processing as well as neoepitope targeting therapies.

AzidoTMT Enables Direct Enrichment and Highly Multiplexed Quantitation of Proteome-Wide Functional Residues.

Recent advances in targeted covalent inhibitors have aroused significant interest for their potential in drug development for difficult therapeutic targets. Proteome-wide profiling of functional residues is an integral step of covalent drug discovery aimed at defining actionable sites and evaluating compound selectivity in cells. A classical workflow for this purpose is called IsoTOP-ABPP, which employs an activity-based probe and two isotopically labeled azide-TEV-biotin tags to mark, enrich, and quantify proteome from two samples. Here we report a novel isobaric 11plex-AzidoTMT reagent and a new workflow, named AT-MAPP, that significantly expands multiplexing power as compared to the original isoTOP-ABPP. We demonstrate its application in identifying cysteine on- and off-targets using a KRAS G12C covalent inhibitor ARS-1620. However, changes in some of these hits can be explained by modulation at the protein and post-translational levels. Thus, it would be crucial to interrogate site-level bona fide changes in concurrence to proteome-level changes for corroboration. In addition, we perform a multiplexed covalent fragment screening using four acrylamide-based compounds as a proof-of-concept. This study identifies a diverse set of liganded cysteine residues in a compound-dependent manner with an average hit rate of 0.07% in intact cell. Lastly, we screened 20 sulfonyl fluoride-based compounds to demonstrate that the AT-MAPP assay is flexible for noncysteine functional residues such as tyrosine and lysine. Overall, we envision that 11plex-AzidoTMT will be a useful addition to the current toolbox for activity-based protein profiling and covalent drug development.

An RNA Damage Response Network Mediates the Lethality of 5-FU in Clinically Relevant Tumor Types.

5-fluorouracil (5-FU) is a successful and broadly used anti-cancer therapeutic. A major mechanism of action of 5-FU is thought to be through thymidylate synthase (TYMS) inhibition resulting in dTTP depletion and activation of the DNA damage response. This suggests that 5-FU should synergize with other DNA damaging agents. However, we found that combinations of 5-FU and oxaliplatin or irinotecan failed to display any evidence of synergy in clinical trials, and resulted in sub-additive killing in a panel of colorectal cancer (CRC) cell lines. In seeking to understand this antagonism, we unexpectedly found that an RNA damage response during ribosome biogenesis dominates the drug's efficacy in tumor types for which 5-FU shows clinical benefit. 5-FU has an inherent bias for RNA incorporation, and blocking this greatly reduced drug-induced lethality, indicating that accumulation of damaged RNA is more deleterious than the lack of new RNA synthesis. Using 5-FU metabolites that specifically incorporate into either RNA or DNA revealed that CRC cell lines and patient-derived colorectal cancer organoids are inherently more sensitive to RNA damage. This difference held true in cell lines from other tissues in which 5-FU has shown clinical utility, whereas cell lines from tumor tissues that lack clinical 5-FU responsiveness typically showed greater sensitivity to the drug's DNA damage effects. Analysis of changes in the phosphoproteome and ubiquitinome shows RNA damage triggers the selective ubiquitination of multiple ribosomal proteins leading to autophagy-dependent rRNA catabolism and proteasome-dependent degradation of ubiquitinated ribosome proteins. Further, RNA damage response to 5-FU is selectively enhanced by compounds that promote ribosome biogenesis, such as KDM2A inhibitors. These results demonstrate the presence of a strong RNA damage response linked to apoptotic cell death, with clear utility of combinatorially targeting this response in cancer therapy.

Driver Mutations Dictate the Immunologic Landscape and Response to Checkpoint Immunotherapy of Glioblastoma.

The composition of the tumor immune microenvironment (TIME) is considered a key determinant of patients' response to immunotherapy. The mechanisms underlying TIME formation and development over time are poorly understood. Glioblastoma (GBM) is a lethal primary brain cancer for which there are no curative treatments. GBMs are immunologically heterogeneous and impervious to checkpoint blockade immunotherapies. Utilizing clinically relevant genetic mouse models of GBM, we identified distinct immune landscapes associated with expression of EGFR wild-type and mutant EGFRvIII cancer driver mutations. Over time, accumulation of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) was more pronounced in EGFRvIII-driven GBMs and was correlated with resistance to PD-1 and CTLA-4 combination checkpoint blockade immunotherapy. We determined that GBM-secreted CXCL1/2/3 and PMN-MDSC-expressed CXCR2 formed an axis regulating output of PMN-MDSCs from the bone marrow leading to systemic increase in these cells in the spleen and GBM tumor-draining lymph nodes. Pharmacologic targeting of this axis induced a systemic decrease in the numbers of PMN-MDSC, facilitated responses to PD-1 and CTLA-4 combination checkpoint blocking immunotherapy, and prolonged survival in mice bearing EGFRvIII-driven GBM. Our results uncover a relationship between cancer driver mutations, TIME composition, and sensitivity to checkpoint blockade in GBM and support the stratification of patients with GBM for checkpoint blockade therapy based on integrated genotypic and immunologic profiles.

Targeting MCL-1 and BCL-2 with polatuzumab vedotin and venetoclax overcomes treatment resistance in R/R non-Hodgkin lymphoma: Results from preclinical models and a Phase Ib study.

The treatment of patients with relapsed or refractory lymphoid neoplasms represents a significant clinical challenge. Here, we identify the pro-survival BCL-2 protein family member MCL-1 as a resistance factor for the BCL-2 inhibitor venetoclax in non-Hodgkin lymphoma (NHL) cell lines and primary NHL samples. Mechanistically, we show that the antibody-drug conjugate polatuzumab vedotin promotes MCL-1 degradation via the ubiquitin/proteasome system. This targeted MCL-1 antagonism, when combined with venetoclax and the anti-CD20 antibodies obinutuzumab or rituximab, results in tumor regressions in preclinical NHL models, which are sustained even off-treatment. In a Phase Ib clinical trial (NCT02611323) of heavily pre-treated patients with relapsed or refractory NHL, 25/33 (76%) patients with follicular lymphoma and 5/17 (29%) patients with diffuse large B-cell lymphoma achieved complete or partial responses with an acceptable safety profile when treated with the recommended Phase II dose of polatuzumab vedotin in combination with venetoclax and an anti-CD20 antibody.

Selective PROTAC-mediated degradation of SMARCA2 is efficacious in SMARCA4 mutant cancers.

The mammalian SWItch/Sucrose Non-Fermentable (SWI/SNF) helicase SMARCA4 is frequently mutated in cancer and inactivation results in a cellular dependence on its paralog, SMARCA2, thus making SMARCA2 an attractive synthetic lethal target. However, published data indicates that achieving a high degree of selective SMARCA2 inhibition is likely essential to afford an acceptable therapeutic index, and realizing this objective is challenging due to the homology with the SMARCA4 paralog. Herein we report the discovery of a potent and selective SMARCA2 proteolysis-targeting chimera molecule (PROTAC), A947. Selective SMARCA2 degradation is achieved in the absence of selective SMARCA2/4 PROTAC binding and translates to potent in vitro growth inhibition and in vivo efficacy in SMARCA4 mutant models, compared to wild type models. Global ubiquitin mapping and proteome profiling reveal no unexpected off-target degradation related to A947 treatment. Our study thus highlights the ability to transform a non-selective SMARCA2/4-binding ligand into a selective and efficacious in vivo SMARCA2-targeting PROTAC, and thereby provides a potential new therapeutic opportunity for patients whose tumors contain SMARCA4 mutations.

Shigella ubiquitin ligase IpaH7.8 targets gasdermin D for degradation to prevent pyroptosis and enable infection.

The pore-forming protein gasdermin D (GSDMD) executes lytic cell death called pyroptosis to eliminate the replicative niche of intracellular pathogens. Evolution favors pathogens that circumvent this host defense mechanism. Here, we show that the Shigella ubiquitin ligase IpaH7.8 functions as an inhibitor of GSDMD. Shigella is an enteroinvasive bacterium that causes hemorrhagic gastroenteritis in primates, but not rodents. IpaH7.8 contributes to species specificity by ubiquitinating human, but not mouse, GSDMD and targeting it for proteasomal degradation. Accordingly, infection of human epithelial cells with IpaH7.8-deficient Shigella flexneri results in increased GSDMD-dependent cell death compared with wild type. Consistent with pyroptosis contributing to murine disease resistance, eliminating GSDMD from NLRC4-deficient mice, which are already sensitized to oral infection with Shigella flexneri, leads to further enhanced bacterial replication and increased disease severity. This work highlights a species-specific pathogen arms race focused on maintenance of host cell viability.

Antibody toolkit reveals N-terminally ubiquitinated substrates of UBE2W.

The ubiquitin conjugating enzyme UBE2W catalyzes non-canonical ubiquitination on the N-termini of proteins, although its substrate repertoire remains unclear. To identify endogenous N-terminally-ubiquitinated substrates, we discover four monoclonal antibodies that selectively recognize tryptic peptides with an N-terminal diglycine remnant, corresponding to sites of N-terminal ubiquitination. Importantly, these antibodies do not recognize isopeptide-linked diglycine (ubiquitin) modifications on lysine. We solve the structure of one such antibody bound to a Gly-Gly-Met peptide to reveal the molecular basis for its selective recognition. We use these antibodies in conjunction with mass spectrometry proteomics to map N-terminal ubiquitination sites on endogenous substrates of UBE2W. These substrates include UCHL1 and UCHL5, where N-terminal ubiquitination distinctly alters deubiquitinase (DUB) activity. This work describes an antibody toolkit for enrichment and global profiling of endogenous N-terminal ubiquitination sites, while revealing functionally relevant substrates of UBE2W.

Sensitive and Quantitative Detection of MHC-I Displayed Neoepitopes Using a Semiautomated Workflow and TOMAHAQ Mass Spectrometry.

Advances in several key technologies, including MHC peptidomics, have helped fuel our understanding of basic immune regulatory mechanisms and the identification of T cell receptor targets for the development of immunotherapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables characterization of dynamic changes in the ligandome due to cellular perturbations. However, the current multistep analytical process is challenging, and improvements in throughput and reproducibility would enable rapid characterization of multiple conditions in parallel. Here, we describe a robust and quantitative method whereby peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines such as MC38, can be enriched in a semiautomated fashion on reusable, dry-storage, customized antibody cartridges. Using this method, a researcher, with very little hands-on time and in a single day, can perform up to 96 simultaneous enrichments at a similar level of quality as a manual workflow. TOMAHAQ (Triggered by Offset, Multiplexed, Accurate-mass, High-resolution, and Absolute Quantification), a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity, was employed to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation. This unique combination of robust semiautomated MHC-I peptide isolation and high-throughput multiplexed targeted quantitation allows for both the routine analysis of >4000 unique MHC-I peptides from 250 million cells using nontargeted methods, as well as quantitative sensitivity down to the low amol/µl level using TOMAHAQ targeted MS.

Machine-Learning and Chemicogenomics Approach Defines and Predicts Cross-Talk of Hippo and MAPK Pathways.

Hippo pathway dysregulation occurs in multiple cancers through genetic and nongenetic alterations, resulting in translocation of YAP to the nucleus and activation of the TEAD family of transcription factors. Unlike other oncogenic pathways such as RAS, defining tumors that are Hippo pathway-dependent is far more complex due to the lack of hotspot genetic alterations. Here, we developed a machine-learning framework to identify a robust, cancer type-agnostic gene expression signature to quantitate Hippo pathway activity and cross-talk as well as predict YAP/TEAD dependency across cancers. Further, through chemical genetic interaction screens and multiomics analyses, we discover a direct interaction between MAPK signaling and TEAD stability such that knockdown of YAP combined with MEK inhibition results in robust inhibition of tumor cell growth in Hippo dysregulated tumors. This multifaceted approach underscores how computational models combined with experimental studies can inform precision medicine approaches including predictive diagnostics and combination strategies. SIGNIFICANCE: An integrated chemicogenomics strategy was developed to identify a lineage-independent signature for the Hippo pathway in cancers. Evaluating transcriptional profiles using a machine-learning method led to identification of a relationship between YAP/TAZ dependency and MAPK pathway activity. The results help to nominate potential combination therapies with Hippo pathway inhibition.This article is highlighted in the In This Issue feature, p. 521.

Automated Big Data Analytics for the Radiation Oncology Alternative Payment Model Proposal Using a Novel Health Care Software Technology.

INTRODUCTION: The proposed Radiation Oncology Alternative Payment Model (RO-APM) aims to test prospective episode-based payments for radiotherapy episodes. Practices will need a tool that can calculate historical episode reimbursements to succeed in this new model. An automated software-based technology was created to calculate historical episode reimbursements within a large Network of community oncology practices. MATERIALS AND METHODS: Claims data between January 1, 2017, and July 31, 2019, were cleaned, organized into episodes, and analyzed with a series of Python computer programs per proposed RO-APM methodology. Averaged Winsorized historical episode reimbursements were first calculated over the entire Network, then over 24 of the largest Practices, and then rerun after application of Clinical Rules to remove misattributed episodes. RESULTS: A total of 79,418 RO-APM-defined episodes were generated from 6,512,375 claims lines. A total of 7,086 episodes (8.9%) were removed because of no treatment delivery code within 28 days of treatment planning. The Network of practices had more bone metastases, and breast, cervical, and uterine cancers but less lung and prostate cancer than the RO-APM dataset. Combination-modality episodes were more costly and required more providers than single-modality episodes. Clinical Rules reattributed 2,495 episodes (3.4%) and increased episode reimbursement by +5.8% over all disease sites (+3.7% using volume weighting; P = .001). CONCLUSION: As payment models continue to shift from volume to value, practices will need an automated analytics technology to measure historical costs and prepare for operational and financial transformation. This automated approach can be adapted to future versions of the RO-APM. Our analysis suggests that future iterations of the RO-APM could incorporate Clinical Rules to remove misattributed palliative care episodes and could implement a separate payment for episodes with multiple radiation therapy modalities.

Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

Chaperone mediated detection of small molecule target binding in cells.

The ability to quantitatively measure a small molecule's interactions with its protein target(s) is crucial for both mechanistic studies of signaling pathways and in drug discovery. However, current methods to achieve this have specific requirements that can limit their application or interpretation. Here we describe a complementary target-engagement method, HIPStA (Heat Shock Protein Inhibition Protein Stability Assay), a high-throughput method to assess small molecule binding to endogenous, unmodified target protein(s) in cells. The methodology relies on the change in protein turnover when chaperones, such as HSP90, are inhibited and the stabilization effect that drug-target binding has on this change. We use HIPStA to measure drug binding to three different classes of drug targets (receptor tyrosine kinases, nuclear hormone receptors, and cytoplasmic protein kinases), via quantitative fluorescence imaging. We further demonstrate its utility by pairing the method with quantitative mass spectrometry to identify previously unknown targets of a receptor tyrosine kinase inhibitor.

PPEF2 Opposes PINK1-Mediated Mitochondrial Quality Control by Dephosphorylating Ubiquitin.

Dysregulation of mitophagy, whereby damaged mitochondria are labeled for degradation by the mitochondrial kinase PINK1 and E3 ubiquitin ligase Parkin with phosphorylated ubiquitin chains (p-S65 ubiquitin), may contribute to neurodegeneration in Parkinson's disease. Here, we identify a phosphatase antagonistic to PINK1, protein phosphatase with EF-hand domain 2 (PPEF2), that can dephosphorylate ubiquitin and suppress PINK1-dependent mitophagy. Knockdown of PPEF2 amplifies the accumulation of p-S65 ubiquitin in cells and enhances baseline mitophagy in dissociated cortical cultures. Overexpressing enzymatically active PPEF2 reduces the p-S65 ubiquitin signal in cells, and partially purified PPEF2 can dephosphorylate recombinant p-S65 ubiquitin chains in vitro. Using a mass spectrometry approach, we have identified several p-S65-ubiquitinated proteins following mitochondrial damage that are inversely regulated by PPEF2 and PINK1. Interestingly, many of these proteins are involved in nuclear processes such as DNA repair. Collectively, PPEF2 functions to suppress mitochondrial quality control on a cellular level through dephosphorylation of p-S65 ubiquitin.

Transposable element expression in tumors is associated with immune infiltration and increased antigenicity.

Profound global loss of DNA methylation is a hallmark of many cancers. One potential consequence of this is the reactivation of transposable elements (TEs) which could stimulate the immune system via cell-intrinsic antiviral responses. Here, we develop REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observe increased expression of over 400 TE subfamilies, of which 262 appear to result from a proximal loss of DNA methylation. The most recurrent TEs are among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent results in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing inflammation and the display of potentially immunogenic neoantigens.

TomahaqCompanion: A Tool for the Creation and Analysis of Isobaric Label Based Multiplexed Targeted Assays.

Triggered by Offset, Multiplexed, Accurate mass, High resolution, and Absolute Quantitation (TOMAHAQ) is a recently introduced targeted proteomics method that combines peptide and sample multiplexing. TOMAHAQ assays enable sensitive and accurate multiplexed quantification by implementing an intricate data collection scheme that comprises multiple MSn scans, mass inclusion lists, and data-driven filters. Consequently, manual creation of TOMAHAQ methods can be time-consuming and error prone, while the resulting TOMAHAQ data may not be compatible with common mass spectrometry analysis pipelines. To address these concerns we introduce TomahaqCompanion, an open-source desktop application that enables rapid creation of TOMAHAQ methods and analysis of TOMAHAQ data. Starting from a list of peptide sequences, a user can perform each step of TOMAHAQ assay development including (1) generation of priming run target list, (2) analysis of priming run data, (3) generation of TOMAHAQ method file, and (4) analysis and export of quantitative TOMAHAQ data. We demonstrate the flexibility of TomahaqCompanion by creating a variety of methods testing TOMAHAQ parameters (e.g., number of SPS notches, run length, etc.). Lastly, we analyze an interference sample comprising heavy yeast peptides, a standard human peptide mixture, TMT11-plex, and super heavy TMT (shTMT) isobaric labels to demonstrate ∼10-200 attomol limit of quantification within a complex background using TOMAHAQ.

Discovery and Qualification of Candidate Urinary Biomarkers of Disease Activity in Lupus Nephritis.

Lupus nephritis (LN) is a severe clinical manifestation of systemic lupus erythematosus (SLE) associated with significant morbidity and mortality. Assessment of severity and activity of renal involvement in SLE requires a kidney biopsy, an invasive procedure with limited prognostic value. Noninvasive biomarkers are needed to inform treatment decisions and to monitor disease activity. Proteinuria is associated with disease progression in LN; however, the composition of the LN urinary proteome remains incompletely characterized. To address this, we profiled LN urine samples using complementary mass spectrometry-based methods:  protein gel fractionation, chemical labeling using tandem mass tags, and data-independent acquisition. Combining results from these approaches yielded quantitative information on 2573 unique proteins in urine from LN patients. A multiple-reaction monitoring (MRM) method was established to confirm eight proteins in an independent cohort of LN patients, and seven proteins (transferrin, α-2-macroglobulin, haptoglobin, afamin, α-1-antitrypsin, vimentin, and ceruloplasmin) were confirmed to be elevated in LN urine compared to healthy controls. In this study, we demonstrate that deep mass spectrometry profiling of a small number of patient samples can identify high-quality biomarkers that replicate in an independent LN disease cohort. These biomarkers are being used to inform clinical biomarker strategies to support longitudinal and interventional studies focused on evaluating disease progression and treatment efficacy of novel LN therapeutics.