A Scaled Proteomic Discovery Study for Prostate Cancer Diagnostic Markers Using ProteographTM and Trapped Ion Mobility Mass Spectrometry.

There is a significant unmet need for clinical reflex tests that increase the specificity of prostate-specific antigen blood testing, the longstanding but imperfect tool for prostate cancer diagnosis. Towards this endpoint, we present the results from a discovery study that identifies new prostate-specific antigen reflex markers in a large-scale patient serum cohort using differentiating technologies for deep proteomic interrogation. We detect known prostate cancer blood markers as well as novel candidates. Through bioinformatic pathway enrichment and network analysis, we reveal associations of differentially abundant proteins with cytoskeletal, metabolic, and ribosomal activities, all of which have been previously associated with prostate cancer progression. Additionally, optimized machine learning classifier analysis reveals proteomic signatures capable of detecting the disease prior to biopsy, performing on par with an accepted clinical risk calculator benchmark.

Identification and characterization of intact glycopeptides in human urine.

Glycoproteins in urine have the potential to provide a rich class of informative molecules for studying human health and disease. Despite this promise, the urine glycoproteome has been largely uncharacterized. Here, we present the analysis of glycoproteins in human urine using LC-MS/MS-based intact glycopeptide analysis, providing both the identification of protein glycosites and characterization of the glycan composition at specific glycosites. Gene enrichment analysis reveals differences in biological processes, cellular components, and molecular functions in the urine glycoproteome versus the urine proteome, as well as differences based on the major glycan class observed on proteins. Meta-heterogeneity of glycosylation is examined on proteins to determine the variation in glycosylation across multiple sites of a given protein with specific examples of individual sites differing from the glycosylation trends in the overall protein. Taken together, this dataset represents a potentially valuable resource as a baseline characterization of glycoproteins in human urine for future urine glycoproteomics studies.

Allele-Specific Gene Regulation, Phenotypes, and Therapeutic Vulnerabilities in Estrogen Receptor Alpha-Mutant Endometrial Cancer.

Activating estrogen receptor alpha (ER; also known as ESR1) mutations are present in primary endometrial and metastatic breast cancers, promoting estrogen-independent activation of the receptor. Functional characterizations in breast cancer have established unique molecular and phenotypic consequences of the receptor, yet the impact of ER mutations in endometrial cancer has not been fully explored. In this study, we used CRISPR-Cas9 to model the clinically prevalent ER-Y537S mutation and compared results with ER-D538G to discover allele-specific differences between ER mutations in endometrial cancer. We found that constitutive activity of mutant ER resulted in changes in the expression of thousands of genes, stemming from combined alterations to ER binding and chromatin accessibility. The unique gene expression programs resulted in ER-mutant cells developing increased cancer-associated phenotypes, including migration, invasion, anchorage-independent growth, and growth in vivo. To uncover potential treatment strategies, we identified ER-associated proteins via Rapid Immunoprecipitation and Mass Spectrometry of Endogenous Proteins and interrogated two candidates, CDK9 and NCOA3. Inhibition of these regulatory proteins resulted in decreased growth and migration, representing potential novel treatment strategies for ER-mutant endometrial cancer. IMPLICATIONS: This study provides insight into mutant ER activity in endometrial cancer and identifies potential therapies for women with ER-mutant endometrial cancer.

Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions.

SignificanceDeep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamagnetic nanoparticles in comparison to conventional workflows for deep proteomics interrogation. Our automated workflow leverages competitive nanoparticle-protein binding equilibria that quantitatively compress the large dynamic range of proteomes to an accessible scale. Using machine learning, we dissect the contribution of individual physicochemical properties of nanoparticles to the composition of protein coronas. Our results suggest that nanoparticle functionalization can be tailored to protein sets. This work demonstrates the feasibility of deep, precise, unbiased plasma proteomics at a scale compatible with large-scale genomics enabling multiomic studies.

Development of 2-(5,6,7-Trifluoro-1H-Indol-3-yl)-quinoline-5-carboxamide as a Potent, Selective, and Orally Available Inhibitor of Human Androgen Receptor Targeting Its Binding Function-3 for the Treatment of Castration-Resistant Prostate Cancer.

Prostate cancer (PCa) patients undergoing androgen deprivation therapy almost invariably develop castration-resistant prostate cancer (CRPC). Targeting the androgen receptor (AR) Binding Function-3 (BF3) site offers a promising option to treat CRPC. However, BF3 inhibitors have been limited by poor potency or inadequate metabolic stability. Through extensive medicinal chemistry, molecular modeling, and biochemistry, we identified 2-(5,6,7-trifluoro-1H-Indol-3-yl)-quinoline-5-carboxamide (VPC-13789), a potent AR BF3 antagonist with markedly improved pharmacokinetic properties. We demonstrate that VPC-13789 suppresses AR-mediated transcription, chromatin binding, and recruitment of coregulatory proteins. This novel AR antagonist selectively reduces the growth of both androgen-dependent and enzalutamide-resistant PCa cell lines. Having demonstrated in vitro efficacy, we developed an orally bioavailable prodrug that reduced PSA production and tumor volume in animal models of CRPC with no observed toxicity. VPC-13789 is a potent, selective, and orally bioavailable antiandrogen with a distinct mode of action that has a potential as novel CRPC therapeutics.

Development of an Androgen Receptor Inhibitor Targeting the N-Terminal Domain of Androgen Receptor for Treatment of Castration Resistant Prostate Cancer.

Prostate cancer patients undergoing androgen deprivation therapy almost invariably develop castration-resistant prostate cancer. Resistance can occur when mutations in the androgen receptor (AR) render anti-androgen drugs ineffective or through the expression of constitutively active splice variants lacking the androgen binding domain entirely (e.g., ARV7). In this study, we are reporting the discovery of a novel AR-NTD covalent inhibitor 1-chloro-3-[(5-([(2S)-3-chloro-2-hydroxypropyl]amino)naphthalen-1-yl)amino]propan-2-ol (VPC-220010) targeting the AR-N-terminal Domain (AR-NTD). VPC-220010 inhibits AR-mediated transcription of full length and truncated variant ARV7, downregulates AR response genes, and selectively reduces the growth of both full-length AR- and truncated AR-dependent prostate cancer cell lines. We show that VPC-220010 disrupts interactions between AR and known coactivators and coregulatory proteins, such as CHD4, FOXA1, ZMIZ1, and several SWI/SNF complex proteins. Taken together, our data suggest that VPC-220010 is a promising small molecule that can be further optimized into effective AR-NTD inhibitor for the treatment of CRPC.

ERG-Mediated Coregulator Complex Formation Maintains Androgen Receptor Signaling in Prostate Cancer.

The TMPRSS2-ERG fusion is the most common genomic rearrangement in human prostate cancer. However, in established adenocarcinoma, it is unknown how the ERG oncogene promotes a cancerous phenotype and maintains downstream androgen receptor (AR) signaling pathways. In this study, we utilized a murine prostate organoid system to explore the effects of ERG on tumorigenesis and determined the mechanism underlying prostate cancer dependence on ERG. Prostate organoids lacking PTEN and overexpressing ERG (Pten-/- R26-ERG) faithfully recapitulated distinct stages of prostate cancer disease progression. In this model, deletion of ERG significantly dampened AR-dependent gene expression. While ERG was able to reprogram the AR cistrome in the process of prostate carcinogenesis, ERG knockout in established prostate cancer organoids did not drastically alter AR binding, H3K27ac enhancer, or open chromatin profiles at these reprogrammed sites. Proteomic analysis of DNA-bound AR complexes demonstrated that ERG deletion causes a loss of recruitment of critical AR coregulators and basal transcriptional machinery, including NCOA3 and RNA polymerase II, but does not alter AR binding itself. Together, these data reveal a novel mechanism of ERG oncogene addiction in prostate cancer, whereby ERG facilitates AR signaling by maintaining coregulator complexes at AR bound sites across the genome. SIGNIFICANCE: These findings exploit murine organoid models to uncover the mechanism of ERG-mediated tumorigenesis and subsequent oncogenic dependencies in prostate cancer.

A Robust Protocol for Protein Extraction and Digestion.

Proteins play a key role in all aspects of cellular homeostasis. Proteomics, the large-scale study of proteins, provides in-depth data on protein properties, including abundances and post-translational modification states, and as such provides a rich avenue for the investigation of biological and disease processes. While proteomic tools such as mass spectrometry have enabled exquisitely sensitive sample analysis, sample preparation remains a critical unstandardized variable that can have a significant impact on downstream data readouts. Consistency in sample preparation and handling is therefore paramount in the collection and analysis of proteomic data.Here we describe methods for performing protein extraction from cell culture or tissues, digesting the isolated protein into peptides via in-solution enzymatic digest, and peptide cleanup with final preparations for analysis via liquid chromatography-mass spectrometry. These protocols have been optimized and standardized for maximum consistency and maintenance of sample integrity.

Antibody-Drug Conjugates (ADCs) Derived from Interchain Cysteine Cross-Linking Demonstrate Improved Homogeneity and Other Pharmacological Properties over Conventional Heterogeneous ADCs.

Conventional antibody-drug conjugates (ADCs) are heterogeneous mixtures of chemically distinct molecules that vary in both drugs/antibody (DAR) and conjugation sites. Suboptimal properties of heterogeneous ADCs have led to new site-specific conjugation methods for improving ADC homogeneity. Most site-specific methods require extensive antibody engineering to identify optimal conjugation sites and introduce unique functional groups for conjugation with appropriately modified linkers. Alternative nonrecombinant methods have emerged in which bifunctional linkers are utilized to cross-link antibody interchain cysteines and afford ADCs containing four drugs/antibody. Although these methods have been shown to improve ADC homogeneity and stability in vitro, their effect on the pharmacological properties of ADCs in vivo is unknown. In order to determine the relative impact of interchain cysteine cross-linking on the therapeutic window and other properties of ADCs in vivo, we synthesized a derivative of the known ADC payload, MC-MMAF, that contains a bifunctional dibromomaleimide (DBM) linker instead of a conventional maleimide (MC) linker. The DBM-MMAF derivative was conjugated to trastuzumab and a novel anti-CD98 antibody to afford ADCs containing predominantly four drugs/antibody. The pharmacological properties of the resulting cross-linked ADCs were compared with analogous heterogeneous ADCs derived from conventional linkers. The results demonstrate that DBM linkers can be applied directly to native antibodies, without antibody engineering, to yield highly homogeneous ADCs via cysteine cross-linking. The resulting ADCs demonstrate improved pharmacokinetics, superior efficacy, and reduced toxicity in vivo compared to analogous conventional heterogeneous ADCs.

CD39 is a promising therapeutic antibody target for the treatment of soft tissue sarcoma.

Soft tissue sarcoma (STS) is a heterogenous tumor arising from the embryonic mesoderm represented by approximately 50 histological subtypes. Effective therapeutic intervention is lacking for recurrent, late stage and metastatic disease. CD39, a cell-surface ectonucleotidase, has previously been shown to be upregulated in hematological malignancies and various epithelial tumors, but not in STS. Here, we show by mass spectrometry and immunohistochemistry that CD39 is highly expressed in primary patient sarcoma samples. Moreover, CD39 nucleotidase activity is enhanced in fibrosarcoma compared with normal control cells. We demonstrate that an inhibitory monoclonal anti-CD39 antibody, abrogates CD39 enzymatic activity significantly and prolongs survival in a lethal metastatic patient-derived sarcoma model. Taken together, the data suggest CD39 is a novel therapeutic target for the treatment of STS.

Ccq1p and the condensin proteins Cut3p and Cut14p prevent telomere entanglements in the fission yeast Schizosaccharomyces pombe.

The Schizosaccharomyces pombe telomere-associated protein Ccq1p has previously been shown to participate in telomerase recruitment, heterochromatin formation, and suppression of checkpoint activation. Here we characterize a critical role for Ccq1p in mitotic transit. We show that mitotic cells lacking Ccq1p lose minichromosomes at high frequencies but that conditional knockdown of Ccq1p expression results in telomere bridging within one cell cycle. Elevating Ccq1p expression resolves the telomere entanglements caused by decreased Taz1p activity. Ccq1p affects telomere resolution in the absence of changes in telomere size, indicating a role for Ccq1p that is independent of telomere length regulation. Using affinity purification, we identify the condensin proteins Cut3p and Cut14p as candidate Ccq1p interactors in this activity. Condensin loss-of-function disrupts Ccq1p telomeric localization and normal intertelomere clustering, while condensin overexpression relieves the chromosome segregation defects associated with conditional Ccq1p knockdown. These data suggest that Ccq1p and condensins collaborate to mediate resolution of telomeres in mitosis and regulate intertelomeric clustering during interphase.

Assessing bias in experiment design for large scale mass spectrometry-based quantitative proteomics.

Mass spectrometry-based proteomics holds great promise as a discovery tool for biomarker candidates in the early detection of diseases. Recently much emphasis has been placed upon producing highly reliable data for quantitative profiling for which highly reproducible methodologies are indispensable. The main problems that affect experimental reproducibility stem from variations introduced by sample collection, preparation, and storage protocols and LC-MS settings and conditions. On the basis of a formally precise and quantitative definition of similarity between LC-MS experiments, we have developed Chaorder, a fully automatic software tool that can assess experimental reproducibility of sets of large scale LC-MS experiments. By visualizing the similarity relationships within a set of experiments, this tool can form the basis of systematic quality control and thus help assess the comparability of mass spectrometry data over time, across different laboratories, and between instruments. Applying Chaorder to data from multiple laboratories and a range of instruments, experimental protocols, and sample complexities revealed biases introduced by the sample processing steps, experimental protocols, and instrument choices. Moreover we show that reducing bias by correcting for just a few steps, for example randomizing the run order, does not provide much gain in statistical power for biomarker discovery.

The role of beta93 Cys in the inhibition of Hb S fiber formation.

Recent studies have suggested that nitric oxide (NO) binding to hemoglobin (Hb) may lead to the inhibition of sickle cell fiber formation and the dissolution of sickle cell fibers. NO can react with Hb in at least 3 ways: 1) formation of Hb(II)NO, 2) formation of methemoglobin, and 3) formation of S-nitrosohemoglobin, through nitrosylation of the beta93 Cys residue. In this study, the role of beta93 Cys in the mechanism of sickle cell fiber inhibition is investigated through chemical modification with N-ethylmaleimide. UV resonance Raman, FT-IR and electrospray ionization mass spectroscopic methods in conjunction with equilibrium solubility and kinetic studies are used to characterize the effect of beta93 Cys modification on Hb S fiber formation. Both FT-IR spectroscopy and electrospray mass spectrometry results demonstrate that modification can occur at both the beta93 and alpha104 Cys residues under relatively mild reaction conditions. Equilibrium solubility measurements reveal that singly-modified Hb at the beta93 position leads to increased amounts of fiber formation relative to unmodified or doubly-modified Hb S. Kinetic studies confirm that modification of only the beta93 residue leads to a faster onset of polymerization. UV resonance Raman results indicate that modification of the alpha104 residue in addition to the beta93 residue significantly perturbs the alpha(1)beta(2) interface, while modification of only beta93 does not. These results in conjunction with the equilibrium solubility and kinetic measurements are suggestive that modification of the alpha104 Cys residue and not the beta93 Cys residue leads to T-state destabilization and inhibition of fiber formation. These findings have implications for understanding the mechanism of NO binding to Hb and NO inhibition of Hb S fiber formation.

Computational prediction of proteotypic peptides for quantitative proteomics.

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Although such analyses typically assume that a protein's peptide fragments are observed with equal likelihood, only a few so-called 'proteotypic' peptides are repeatedly and consistently identified for any given protein present in a mixture. Using >600,000 peptide identifications generated by four proteomic platforms, we empirically identified >16,000 proteotypic peptides for 4,030 distinct yeast proteins. Characteristic physicochemical properties of these peptides were used to develop a computational tool that can predict proteotypic peptides for any protein from any organism, for a given platform, with >85% cumulative accuracy. Possible applications of proteotypic peptides include validation of protein identifications, absolute quantification of proteins, annotation of coding sequences in genomes, and characterization of the physical principles governing key elements of mass spectrometric workflows (e.g., digestion, chromatography, ionization and fragmentation).

An ent-kaurene that inhibits mitotic chromosome movement and binds the kinetochore protein ran-binding protein 2.

Using a chemical genetics screen, we have identified ent-15-oxokaurenoic acid (EKA) as a chemical that causes prolonged mitotic arrest at a stage resembling prometaphase. EKA inhibits the association of the mitotic motor protein centromeric protein E with kinetochores and inhibits chromosome movement. Unlike most antimitotic agents, EKA does not inhibit the polymerization or depolymerization of tubulin. To identify EKA-interacting proteins, we used a cell-permeable biotinylated form that retains biological activity to isolate binding proteins from living cells. Mass spectrometric analysis identified six EKA-binding proteins, including Ran-binding protein 2, a kinetochore protein whose depletion by small interfering RNA causes a similar mitotic arrest phenotype.

Quantitative proteomic analysis of the budding yeast cell cycle using acid-cleavable isotope-coded affinity tag reagents.

Quantitative profiling of proteins, the direct effectors of nearly all biological functions, will undoubtedly complement technologies for the measurement of mRNA. Systematic proteomic measurement of the cell cycle is now possible by using stable isotopic labeling with isotope-coded affinity tag reagents and software tools for high-throughput analysis of LC-MS/MS data. We provide here the first such study achieving quantitative, global proteomic measurement of a time-course gene expression experiment in a model eukaryote, the budding yeast Saccharomyces cerevisiae, during the cell cycle. We sampled 48% of all predicted ORFs, and provide the data, including identifications, quantitations, and statistical measures of certainty, to the community in a sortable matrix. We do not detect significant concordance in the dynamics of the system over the time-course tested between our proteomic measurements and microarray measures collected from similarly treated yeast cultures. Our proteomic dataset therefore provides a necessary and complementary measure of eukaryotic gene expression, establishes a rich database for the functional analysis of S. cerevisiae proteins, and will enable further development of technologies for global proteomic analysis of higher eukaryotes.

An SMC-domain protein in fission yeast links telomeres to the meiotic centrosome.

Abnormal centrosomal structures similar to those occurring in human cancers are induced in fission yeast by overexpression of the pericentrin homolog Pcp1p. Analysis of abnormal Pcp1p-containing structures with quantitative mass spectrometry and isotope-coded affinity tags identified a coiled-coil, structural maintenance of chromosomes (SMC) domain protein. This protein, termed Ccq1p (coiled-coil protein quantitatively enriched), localizes with Taz1p to telomeres in normal vegetative cells. Fluorescence resonance energy transfer (FRET) measurements indicate that Ccq1p also interacts with centrosomal Pcp1p in mating pheromone-stimulated cells containing centrosomally clustered telomeres. We provide evidence that the Ccq1p-Pcp1p interaction, while essential for meiosis, is deleterious when forced to occur during vegetative growth. Cells lacking one ccq1 allele exhibit a loss-of-function phenotype including abnormally long cell length, chromosome segregation failure, telomeric shortening, and defective telomeric clustering during meiotic prophase. Our data indicate a mechanism underlying meiotic chromosomal bouquet formation and suggest a recruitment model for supernumerary centrosome toxicity.

Gene expression analyzed by high-resolution state array analysis and quantitative proteomics: response of yeast to mating pheromone.

The transcriptome provides the database from which a cell assembles its collection of proteins. Translation of individual mRNA species into their encoded proteins is regulated, producing discrepancies between mRNA and protein levels. Using a new modeling approach to data analysis, a striking diversity is revealed in association of the transcriptome with the translational machinery. Each mRNA has its own pattern of ribosome loading, a circumstance that provides an extraordinary dynamic range of regulation, above and beyond actual transcript levels. Using this approach together with quantitative proteomics, we explored the immediate changes in gene expression in response to activation of a mitogen-activated protein kinase pathway in yeast by mating pheromone. Interestingly, in 26% of those transcripts where the predicted protein synthesis rate changed by at least 3-fold, more than half of these changes resulted from altered translational efficiencies. These observations underscore that analysis of transcript level, albeit extremely important, is insufficient by itself to describe completely the phenotypes of cells under different conditions.

Proteomic approaches for the identification of cell cycle-related drug targets.

Drugs affecting the cell cycle provide insights into mechanisms underlying cancer and suggest strategies for ablating uncontrolled growth. Essential to an understanding of the activity of such compounds is the identification of the set of proteins affected, either directly or indirectly, by the drug. The combination of novel technologies for stable isotope protein tagging, chromatographic separation, tandem mass spectrometry, and data processing is an extremely powerful means for providing such identifications and, in addition, for establishing a proteome-wide profile of all proteins whose abundance levels or phosphorylation state are affected by the drug.

The centrosomal proteins pericentrin and kendrin are encoded by alternatively spliced products of one gene.

Pericentrin, a critical centrosome component first identified in mouse, recruits factors required for assembly of the mitotic spindle apparatus. A similar yet larger human protein named kendrin was recently identified, but its relationship to pericentrin was not clear. Extensive sequence homology between the mouse chromosome 10 region encoding pericentrin and the human chromosome 21 region encoding kendrin indicates that these proteins are encoded by syntenic loci. However, comparison of the published mouse pericentrin cDNA sequence to mouse genomic DNA sequences revealed two important differences: the stop codon present in the published mouse pericentrin cDNA is not found in the mouse genomic sequence, and the 3' end of the published mouse pericentrin cDNA is a fragment from a different mouse chromosome. To resolve these discrepancies, we sequenced a mouse expressed sequence tag (EST) that corresponds to the 3' end for a 7.1-kb mouse pericentrin RNA encoded on chromosome 10. Extensive northern blot analysis revealed that the pericentrin gene displays a complex expression pattern in both mouse and human: a 10-kb kendrin transcript is found in most tissues, whereas smaller transcripts are detected in a limited subset of tissues. These analyses demonstrate that pericentrin and kendrin are encoded by one gene, correct the previously published pericentrin cDNA sequence, and describe the complex expression pattern for a gene important for centrosome function in normal and transformed cells.