A Non-catalytic Function of SETD1A Regulates Cyclin K and the DNA Damage Response.

MLL/SET methyltransferases catalyze methylation of histone 3 lysine 4 and play critical roles in development and cancer. We assessed MLL/SET proteins and found that SETD1A is required for survival of acute myeloid leukemia (AML) cells. Mutagenesis studies and CRISPR-Cas9 domain screening show the enzymatic SET domain is not necessary for AML cell survival but that a newly identified region termed the "FLOS" (functional location on SETD1A) domain is indispensable. FLOS disruption suppresses DNA damage response genes and induces p53-dependent apoptosis. The FLOS domain acts as a cyclin-K-binding site that is required for chromosomal recruitment of cyclin K and for DNA-repair-associated gene expression in S phase. These data identify a connection between the chromatin regulator SETD1A and the DNA damage response that is independent of histone methylation and suggests that targeting SETD1A and cyclin K complexes may represent a therapeutic opportunity for AML and, potentially, for other cancers.

SRSF1 interactome determined by proximity labeling reveals direct interaction with spliceosomal RNA helicase DDX23.

SRSF1 is the founding member of the SR protein family. It is required-interchangeably with other SR proteins-for pre-mRNA splicing in vitro, and it regulates various alternative splicing events. Dysregulation of SRSF1 expression contributes to cancer and other pathologies. Here, we characterized SRSF1's interactome using proximity labeling and mass spectrometry. This approach yielded 190 proteins enriched in the SRSF1 samples, independently of the N- or C-terminal location of the biotin-labeling domain. The detected proteins reflect established functions of SRSF1 in pre-mRNA splicing and reveal additional connections to spliceosome proteins, in addition to other recently identified functions. We validated a robust interaction with the spliceosomal RNA helicase DDX23/PRP28 using bimolecular fluorescence complementation and in vitro binding assays. The interaction is mediated by the N-terminal RS-like domain of DDX23 and both RRM1 and the RS domain of SRSF1. During pre-mRNA splicing, DDX23's ATPase activity is essential for the pre-B to B spliceosome complex transition and for release of U1 snRNP from the 5' splice site. We show that the RS-like region of DDX23's N-terminal domain is important for spliceosome incorporation, while larger deletions in this domain alter subnuclear localization. We discuss how the identified interaction of DDX23 with SRSF1 and other SR proteins may be involved in the regulation of these processes.

SETD1A function in leukemia is mediated through interaction with mitotic regulators BuGZ/BUB3.

The H3K4 methyltransferase SETD1A plays a crucial role in leukemia cell survival through its noncatalytic FLOS domain-mediated recruitment of cyclin K and regulation of DNA damage response genes. In this study, we identify a functional nuclear localization signal in and interaction partners of the FLOS domain. Our screen for FLOS domain-binding partners reveals that the SETD1A FLOS domain binds mitosis-associated proteins BuGZ/BUB3. Inhibition of both cyclin K and BuGZ/BUB3-binding motifs in SETD1A shows synergistic antileukemic effects. BuGZ/BUB3 localize to SETD1A-bound promoter-TSS regions and SETD1A-negative H3K4me1-positive enhancer regions adjacent to SETD1A target genes. The GLEBS motif and intrinsically disordered region of BuGZ are required for both SETD1A-binding and leukemia cell proliferation. Cell-cycle-specific SETD1A restoration assays indicate that SETD1A expression at the G1/S phase of the cell cycle promotes both the expression of DNA damage response genes and cell cycle progression in leukemia cells.

Integrative Proteogenomics Using ProteomeGenerator2.

Recent advances in nucleic acid sequencing now permit rapid and genome-scale analysis of genetic variation and transcription, enabling population-scale studies of human biology, disease, and diverse organisms. Likewise, advances in mass spectrometry proteomics now permit highly sensitive and accurate studies of protein expression at the whole proteome-scale. However, most proteomic studies rely on consensus databases to match spectra to peptide and protein sequences, and thus remain limited to the analysis of canonical protein sequences. Here, we develop ProteomeGenerator2 (PG2), based on the scalable and modular ProteomeGenerator framework. PG2 integrates genome and transcriptome sequencing to incorporate protein variants containing amino acid substitutions, insertions, and deletions, as well as noncanonical reading frames, exons, and other variants caused by genomic and transcriptomic variation. We benchmarked PG2 using synthetic data and genomic, transcriptomic, and proteomic analysis of human leukemia cells. PG2 can be integrated with current and emerging sequencing technologies, assemblers, variant callers, and mass spectral analysis algorithms, and is available open-source from https://github.com/kentsisresearchgroup/ProteomeGenerator2.

Quantitative Cell Proteomic Atlas: Pathway-Scale Targeted Mass Spectrometry for High-Resolution Functional Profiling of Cell Signaling.

In spite of extensive studies of cellular signaling, many fundamental processes such as pathway integration, cross-talk, and feedback remain poorly understood. To enable integrated and quantitative measurements of cellular biochemical activities, we have developed the Quantitative Cell Proteomics Atlas (QCPA). QCPA consists of panels of targeted mass spectrometry assays to determine the abundance and stoichiometry of regulatory post-translational modifications of sentinel proteins from most known physiologic and pathogenic signaling pathways in human cells. QCPA currently profiles 1 913 peptides from 469 effectors of cell surface signaling, apoptosis, stress response, gene expression, quiescence, and proliferation. For each protein, QCPA includes triplets of isotopically labeled peptides covering known post-translational regulatory sites to determine their stoichiometries and unmodified protein regions to measure total protein abundance. The QCPA framework incorporates analytes to control for technical variability of sample preparation and mass spectrometric analysis, including TrypQuant, a synthetic substrate for accurate quantification of proteolysis efficiency for proteins containing chemically modified residues. The ability to precisely and accurately quantify most known signaling pathways should enable improved chemoproteomic approaches for the comprehensive analysis of cell signaling and clinical proteomics of diagnostic specimens. QCPA is openly available at https://qcpa.mskcc.org.

Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics.

Recent studies have revealed diverse amino acid, post-translational, and noncanonical modifications of proteins in diverse organisms and tissues. However, their unbiased detection and analysis remain hindered by technical limitations. Here, we present a spectral alignment method for the identification of protein modifications using high-resolution mass spectrometry proteomics. Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. Using synthetic standards and controlled chemical labeling experiments, we demonstrate its high specificity and sensitivity for the discovery of substoichiometric protein modifications in complex cellular extracts. SAMPEI mapping of mouse macrophage differentiation revealed diverse post-translational protein modifications, including distinct forms of cysteine itaconatylation. SAMPEI's robust parametrization and versatility are expected to facilitate the discovery of biological modifications of diverse macromolecules. SAMPEI is implemented as a Python package and is available open-source from BioConda and GitHub (https://github.com/FenyoLab/SAMPEI).

Optimized Cross-Linking Mass Spectrometry for in Situ Interaction Proteomics.

Recent development of mass spectrometer cleavable protein cross-linkers and algorithms for their spectral identification now permits large-scale cross-linking mass spectrometry (XL-MS). Here, we optimized the use of cleavable disuccinimidyl sulfoxide (DSSO) cross-linker for labeling native protein complexes in live human cells. We applied a generalized linear mixture model to calibrate cross-link peptide-spectra matching (CSM) scores to control the sensitivity and specificity of large-scale XL-MS. Using specific CSM score thresholds to control the false discovery rate, we found that higher-energy collisional dissociation (HCD) and electron transfer dissociation (ETD) can both be effective for large-scale XL-MS protein interaction mapping. We found that the coverage of protein-protein interaction maps is significantly improved through the use of multiple proteases. In addition, the use of focused sample-specific search databases can be used to improve the specificity of cross-linked peptide spectral matching. Application of this approach to human chromatin labeled in live cells recapitulated known and revealed new protein interactions of nucleosomes and other chromatin-associated complexes in situ. This optimized approach for mapping native protein interactions should be useful for a wide range of biological problems.

High Sensitivity Quantitative Proteomics Using Automated Multidimensional Nano-flow Chromatography and Accumulated Ion Monitoring on Quadrupole-Orbitrap-Linear Ion Trap Mass Spectrometer.

Quantitative proteomics using high-resolution and accuracy mass spectrometry promises to transform our understanding of biological systems and disease. Recent development of parallel reaction monitoring (PRM) using hybrid instruments substantially improved the specificity of targeted mass spectrometry. Combined with high-efficiency ion trapping, this approach also provided significant improvements in sensitivity. Here, we investigated the effects of ion isolation and accumulation on the sensitivity and quantitative accuracy of targeted proteomics using the recently developed hybrid quadrupole-Orbitrap-linear ion trap mass spectrometer. We leveraged ultrahigh efficiency nano-electrospray ionization under optimized conditions to achieve yoctomolar sensitivity with more than seven orders of linear quantitative accuracy. To enable sensitive and specific targeted mass spectrometry, we implemented an automated, two-dimensional (2D) ion exchange-reversed phase nanoscale chromatography system. We found that automated 2D chromatography improved the sensitivity and accuracy of both PRM and an intact precursor scanning mass spectrometry method, termed accumulated ion monitoring (AIM), by more than 100-fold. Combined with automated 2D nano-scale chromatography, AIM achieved subattomolar limits of detection of endogenous proteins in complex biological proteomes. This allowed quantitation of absolute abundance of the human transcription factor MEF2C at ∼100 molecules/cell, and determination of its phosphorylation stoichiometry from as little as 1 µg of extracts isolated from 10,000 human cells. The combination of automated multidimensional nano-scale chromatography and targeted mass spectrometry should enable ultrasensitive high-accuracy quantitative proteomics of complex biological systems and diseases.

ProteomeGenerator: A Framework for Comprehensive Proteomics Based on de Novo Transcriptome Assembly and High-Accuracy Peptide Mass Spectral Matching.

Modern mass spectrometry now permits genome-scale and quantitative measurements of biological proteomes. However, analysis of specific specimens is currently hindered by the incomplete representation of biological variability of protein sequences in canonical reference proteomes and the technical demands for their construction. Here, we report ProteomeGenerator, a framework for de novo and reference-assisted proteogenomic database construction and analysis based on sample-specific transcriptome sequencing and high-accuracy mass spectrometry proteomics. This enables the assembly of proteomes encoded by actively transcribed genes, including sample-specific protein isoforms resulting from non-canonical mRNA transcription, splicing, or editing. To improve the accuracy of protein isoform identification in non-canonical proteomes, ProteomeGenerator relies on statistical target-decoy database matching calibrated using sample-specific controls. Its current implementation includes automatic integration with MaxQuant mass spectrometry proteomics algorithms. We applied this method for the proteogenomic analysis of splicing factor SRSF2 mutant leukemia cells, demonstrating high-confidence identification of non-canonical protein isoforms arising from alternative transcriptional start sites, intron retention, and cryptic exon splicing as well as improved accuracy of genome-scale proteome discovery. Additionally, we report proteogenomic performance metrics for current state-of-the-art implementations of SEQUEST HT, MaxQuant, Byonic, and PEAKS mass spectral analysis algorithms. Finally, ProteomeGenerator is implemented as a Snakemake workflow within a Singularity container for one-step installation in diverse computing environments, thereby enabling open, scalable, and facile discovery of sample-specific, non-canonical, and neomorphic biological proteomes.

Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease.

Given superior analytical features, MS proteomics is well suited for the basic investigation and clinical diagnosis of human disease. Modern MS enables detailed functional characterization of the pathogenic biochemical processes, as achieved by accurate and comprehensive quantification of proteins and their regulatory chemical modifications. Here, we describe how high-accuracy MS in combination with high-resolution chromatographic separations can be leveraged to meet these analytical requirements in a mechanism-focused manner. We review the quantification methods capable of producing accurate measurements of protein abundance and posttranslational modification stoichiometries. We then discuss how experimental design and chromatographic resolution can be leveraged to achieve comprehensive functional characterization of biochemical processes in complex biological proteomes. Finally, we describe current approaches for quantitative analysis of a common functional protein modification: reversible phosphorylation. In all, current instrumentation and methods of high-resolution chromatography and MS proteomics are poised for immediate translation into improved diagnostic strategies for pediatric and adult diseases.

ProteoModlR for functional proteomic analysis.

BACKGROUND: High-accuracy mass spectrometry enables near comprehensive quantification of the components of the cellular proteomes, increasingly including their chemically modified variants. Likewise, large-scale libraries of quantified synthetic peptides are becoming available, enabling absolute quantification of chemically modified proteoforms, and therefore systems-level analyses of changes of their absolute abundance and stoichiometry. Existing computational methods provide advanced tools for mass spectral analysis and statistical inference, but lack integrated functions for quantitative analysis of post-translationally modified proteins and their modification stoichiometry. RESULTS: Here, we develop ProteoModlR, a program for quantitative analysis of abundance and stoichiometry of post-translational chemical modifications across temporal and steady-state biological states. While ProteoModlR is intended for the analysis of experiments using isotopically labeled reference peptides for absolute quantitation, it also supports the analysis of labeled and label-free data, acquired in both data-dependent and data-independent modes for relative quantitation. Moreover, ProteoModlR enables functional analysis of sparsely sampled quantitative mass spectrometry experiments by inferring the missing values from the available measurements, without imputation. The implemented architecture includes parsing and normalization functions to control for common sources of technical variation. Finally, ProteoModlR's modular design and interchangeable format are optimally suited for integration with existing computational proteomics tools, thereby facilitating comprehensive quantitative analysis of cellular signaling. CONCLUSIONS: ProteoModlR and its documentation are available for download at http://github.com/kentsisresearchgroup/ProteoModlR as a stand-alone R package.

Genomics of primary chemoresistance and remission induction failure in paediatric and adult acute myeloid leukaemia.

Cure rates of children and adults with acute myeloid leukaemia (AML) remain unsatisfactory partly due to chemotherapy resistance. We investigated the genetic basis of AML in 107 primary cases by sequencing 670 genes mutated in haematological malignancies. SETBP1, ASXL1 and RELN mutations were significantly associated with primary chemoresistance. We identified genomic alterations not previously described in AML, together with distinct genes that were significantly overexpressed in therapy-resistant AML. Defined gene mutations were sufficient to explain primary induction failure in only a minority of cases. Thus, additional genetic or molecular mechanisms must cause primary chemoresistance in paediatric and adult AML.

Quantitative analysis of a phosphoproteome readily altered by the protein kinase CK2 inhibitor quinalizarin in HEK-293T cells.

CK2 is an extremely pleiotropic Ser/Thr protein kinase, responsible for the generation of a large proportion of the human phosphoproteome and implicated in a wide variety of biological functions. CK2 plays a global role as an anti-apoptotic agent, a property which is believed to partially account for the addiction of many cancer cells to high CK2 levels. To gain information about the CK2 targets whose phosphorylation is primarily implicated in its pro-survival signaling advantage has been taken of quinalizarin (QZ) a cell permeable fairly specific CK2 inhibitor, previously shown to be able to block endogenous CK2 triggering an apoptotic response. HEK-293T cells either treated or not for 3h with 50µM QZ were exploited to perform a quantitative SILAC phosphoproteomic analysis of phosphosites readily responsive to QZ treatment. Our analysis led to the identification of 4883 phosphosites, belonging to 1693 phosphoproteins. 71 phosphosites (belonging to 47 proteins) underwent a 50% or more decreased occupancy upon QZ treatment. Almost 50% of these fulfilled the typical consensus sequence recognized by CK2 (S/T-x-x-E/D/pS) and in several cases were validated as bona fide substrates of CK2 either based on data in the literature or by performing in vitro phosphorylation experiments with purified proteins. The majority of the remaining phosphosites drastically decreased upon QZ treatment display the pS/T-P motif typical of proline directed protein kinases and a web logo extracted from them differentiates from the web logo extracted from all the proline directed phosphosites quantified during our analysis (1151 altogether). A paradoxical outcome of our study was the detection of 116 phosphosites (belonging to 92 proteins altogether) whose occupancy is substantially increased (50% or more), rather than decreased by QZ treatment: 40% of these display the typical motif recognized by proline directed kinases, while about 25% fulfill the CK2 consensus. Collectively taken our data on one side have led to the disclosure of a subset of CK2 targets which are likely to be implicated in the early steps of CK2 signaling counteracting apoptosis, on the other they provide evidence for the existence of side and off-target effects of the CK2 inhibitor quinalizarin, paving the road toward the detection of other kinases susceptible to this compound. This article is part of a Special Issue entitled: Medical Proteomics.

Proteomic analysis of breast tumors confirms the mRNA intrinsic molecular subtypes using different classifiers: a large-scale analysis of fresh frozen tissue samples.

BACKGROUND: Breast cancer is a complex and heterogeneous disease that is usually characterized by histological parameters such as tumor size, cellular arrangements/rearrangments, necrosis, nuclear grade and the mitotic index, leading to a set of around twenty subtypes. Together with clinical markers such as hormone receptor status, this classification has considerable prognostic value but there is a large variation in patient response to therapy. Gene expression profiling has provided molecular profiles characteristic of distinct subtypes of breast cancer that reflect the divergent cellular origins and degree of progression. METHODS: Here we present a large-scale proteomic and transcriptomic profiling study of 477 sporadic and hereditary breast cancer tumors with matching mRNA expression analysis. Unsupervised hierarchal clustering was performed and selected proteins from large-scale tandem mass spectrometry (MS/MS) analysis were transferred into a highly multiplexed targeted selected reaction monitoring assay to classify tumors using a hierarchal cluster and support vector machine with leave one out cross-validation. RESULTS: The subgroups formed upon unsupervised clustering agree very well with groups found at transcriptional level; however, the classifiers (genes or their respective protein products) differ almost entirely between the two datasets. In-depth analysis shows clear differences in pathways unique to each type, which may lie behind their different clinical outcomes. Targeted mass spectrometry analysis and supervised clustering correlate very well with subgroups determined by RNA classification and show convincing agreement with clinical parameters. CONCLUSIONS: This work demonstrates the merits of protein expression profiling for breast cancer stratification. These findings have important implications for the use of genomics and expression analysis for the prediction of protein expression, such as receptor status and drug target expression. The highly multiplexed MS assay is easily implemented in standard clinical chemistry practice, allowing rapid and cheap characterization of tumor tissue suitable for directing the choice of treatment.

Molecular Portrait of Breast-Cancer-Derived Cell Lines Reveals Poor Similarity with Tumors.

Breast-cancer-derived cell lines are an important sample source for cancer proteomics and can be classified on the basis of transcriptomic analysis into subgroups corresponding to the molecular subtypes observed in mammary tumors. This study describes a tridimensional fractionation method that allows high sequence coverage and proteome-wide estimation of protein expression levels. This workflow has been used to conduct an in-depth quantitative proteomic survey of five breast cancer cell lines matching all major cancer subgroups and shows that despite their different classification, these cell lines display a very high level of similarity. A proteome-wide comparison with the RNA levels observed in the same samples showed very little to no correlation. Finally, we demonstrate that the proteomes of in vitro models of breast cancer display surprisingly little overlap with those of clinical samples.

A High-Efficiency Cellular Extraction System for Biological Proteomics.

Recent developments in quantitative high-resolution mass spectrometry have led to significant improvements in the sensitivity and specificity of the biochemical analyses of cellular reactions, protein-protein interactions, and small-molecule-drug discovery. These approaches depend on cellular proteome extraction that preserves native protein activities. Here, we systematically analyzed mechanical methods of cell lysis and physical protein extraction to identify those that maximize the extraction of cellular proteins while minimizing their denaturation. Cells were mechanically disrupted using Potter-Elvehjem homogenization, probe- or adaptive-focused acoustic sonication, and were in the presence of various detergents, including polyoxyethylene ethers and esters, glycosides, and zwitterions. Using fluorescence spectroscopy, biochemical assays, and mass spectrometry proteomics, we identified the combination of adaptive focused acoustic (AFA) sonication in the presence of a binary poloxamer-based mixture of octyl-ß-glucoside and Pluronic F-127 to maximize the depth and yield of the proteome extraction while maintaining native protein activity. This binary poloxamer extraction system allowed for native proteome extraction comparable in coverage to the proteomes extracted using denaturing SDS or guanidine-containing buffers, including the efficient extraction of all major cellular organelles. This high-efficiency cellular extraction system should prove useful for a variety of cell biochemical studies, including structural and functional proteomics.

MARK2/MARK3 kinases are catalytic co-dependencies of YAP/TAZ in human cancer.

The Hippo signaling pathway is commonly dysregulated in human cancer, which leads to a powerful tumor dependency on the YAP/TAZ transcriptional coactivators. Here, we used paralog co-targeting CRISPR screens to identify the kinases MARK2/3 as absolute catalytic requirements for YAP/TAZ function in diverse carcinoma and sarcoma contexts. Underlying this observation is direct MARK2/3-dependent phosphorylation of NF2 and YAP/TAZ, which effectively reverses the tumor suppressive activity of the Hippo module kinases LATS1/2. To simulate targeting of MARK2/3, we adapted the CagA protein from H. pylori as a catalytic inhibitor of MARK2/3, which we show can regress established tumors in vivo. Together, these findings reveal MARK2/3 as powerful co-dependencies of YAP/TAZ in human cancer; targets that may allow for pharmacology that restores Hippo pathway-mediated tumor suppression.

Integrative proteogenomics using ProteomeGenerator2.

Recent advances in nucleic acid sequencing now permit rapid and genome-scale analysis of genetic variation and transcription, enabling population-scale studies of human biology, disease, and diverse organisms. Likewise, advances in mass spectrometry proteomics now permit highly sensitive and accurate studies of protein expression at the whole proteome-scale. However, most proteomic studies rely on consensus databases to match spectra to peptide and proteins sequences, and thus remain limited to the analysis of canonical protein sequences. Here, we develop ProteomeGenerator2 (PG2), based on the scalable and modular ProteomeGenerator framework. PG2 integrates genome and transcriptome sequencing to incorporate protein variants containing amino acid substitutions, insertions, and deletions, as well as non-canonical reading frames, exons, and other variants caused by genomic and transcriptomic variation. We benchmarked PG2 using synthetic data and genomic, transcriptomic, and proteomic analysis of human leukemia cells. PG2 can be integrated with current and emerging sequencing technologies, assemblers, variant callers, and mass spectral analysis algorithms, and is available open-source from https://github.com/kentsisresearchgroup/ProteomeGenerator2 .

Two related families of metal transferases, ZNG1 and ZNG2, are involved in acclimation to poor Zn nutrition in Arabidopsis.

Metal homeostasis has evolved to tightly modulate the availability of metals within the cell, avoiding cytotoxic interactions due to excess and protein inactivity due to deficiency. Even in the presence of homeostatic processes, however, low bioavailability of these essential metal nutrients in soils can negatively impact crop health and yield. While research has largely focused on how plants assimilate metals, acclimation to metal-limited environments requires a suite of strategies that are not necessarily involved in metal transport across membranes. The identification of these mechanisms provides a new opportunity to improve metal-use efficiency and develop plant foodstuffs with increased concentrations of bioavailable metal nutrients. Here, we investigate the function of two distinct subfamilies of the nucleotide-dependent metallochaperones (NMCs), named ZNG1 and ZNG2, that are found in plants, using Arabidopsis thaliana as a reference organism. AtZNG1 (AT1G26520) is an ortholog of human and fungal ZNG1, and like its previously characterized eukaryotic relatives, localizes to the cytosol and physically interacts with methionine aminopeptidase type I (AtMAP1A). Analysis of AtZNG1, AtMAP1A, AtMAP2A, and AtMAP2B transgenic mutants are consistent with the role of Arabidopsis ZNG1 as a Zn transferase for AtMAP1A, as previously described in yeast and zebrafish. Structural modeling reveals a flexible cysteine-rich loop that we hypothesize enables direct transfer of Zn from AtZNG1 to AtMAP1A during GTP hydrolysis. Based on proteomics and transcriptomics, loss of this ancient and conserved mechanism has pleiotropic consequences impacting the expression of hundreds of genes, including those involved in photosynthesis and vesicle transport. Members of the plant-specific family of NMCs, ZNG2A1 (AT1G80480) and ZNG2A2 (AT1G15730), are also required during Zn deficiency, but their target protein(s) remain to be discovered. RNA-seq analyses reveal wide-ranging impacts across the cell when the genes encoding these plastid-localized NMCs are disrupted.

Plasma cells in human pancreatic ductal adenocarcinoma secrete antibodies against self-antigens.

Intratumoral B cell responses are associated with more favorable clinical outcomes in human pancreatic ductal adenocarcinoma (PDAC). However, the antigens driving these B cell responses are largely unknown. We sought to discover these antigens by using single-cell RNA sequencing (scRNA-Seq) and immunoglobulin (Ig) sequencing of tumor-infiltrating immune cells from 7 primary PDAC samples. We identified activated T and B cell responses and evidence of germinal center reactions. Ig sequencing identified plasma cell (PC) clones expressing isotype-switched and hypermutated Igs, suggesting the occurrence of T cell-dependent B cell responses. We assessed the reactivity of 41 recombinant antibodies that represented the products of 235 PCs and 12 B cells toward multiple cell lines and PDAC tissues and observed frequent staining of intracellular self-antigens. Three of these antigens were identified: the filamentous actin (F-actin), the nucleic protein RuvB like AAA ATPase 2 (RUVBL2), and the mitochondrial protein heat shock protein family D (Hsp60) member 1 (HSPD1). Antibody titers against F-actin and HSPD1 were substantially elevated in the plasma of patients with PDAC compared with healthy donors. Thus, PCs in PDAC produce autoantibodies reacting with intracellular self-antigens, which may result from promotion of preexisting, autoreactive B cell responses. These observations indicate the chronic inflammatory microenvironment of PDAC can support the adaptive immune response.