Functional and Clinical Proteomic Exploration of Pancreatic Cancer.

Pancreatic cancer, in most cases being pancreatic ductal adenocarcinoma (PDAC), is one of the most lethal cancers with a median survival time of less than 6 months. Therapeutic options are very limited for patients with PDAC, and surgery is still the most effective treatment, making improvements in early diagnosis critical. One typical characteristic of PDAC is the desmoplastic reaction of its stroma microenvironment, which actively interacts with cancer cells to orchestrate key components in tumorigenesis, metastasis, and chemoresistance. A global exploration of cancer-stroma crosstalk is essential to decipher PDAC biology and design intervention strategies. Over the past decade, the dramatic improvement in proteomics technologies has enabled the profiling of proteins, post-translational modifications (PTMs), and their protein complexes at unprecedented sensitivity and dimensionality. Here, starting with our current understanding of PDAC characteristics, including precursor lesions, progression models, tumor microenvironment, and therapeutic advancements, we describe how proteomics contributes to the functional and clinical exploration of PDAC, providing insights into PDAC carcinogenesis, progression, and chemoresistance. We summarize recent achievements enabled by proteomics to systematically investigate PTMs-mediated intracellular signaling in PDAC, cancer-stroma interactions, and potential therapeutic targets revealed by these functional studies. We also highlight proteomic profiling of clinical tissue and plasma samples to discover and verify useful biomarkers that can aid early detection and molecular classification of patients. In addition, we introduce spatial proteomic technology and its applications in PDAC for deconvolving tumor heterogeneity. Finally, we discuss future prospects of applying new proteomic technologies in comprehensively understanding PDAC heterogeneity and intercellular signaling networks. Importantly, we expect advances in clinical functional proteomics for exploring mechanisms of cancer biology directly by high-sensitivity functional proteomic approaches starting from clinical samples.

Comprehensive Evaluation and Optimization of the Data-Dependent LC-MS/MS Workflow for Deep Proteome Profiling.

Data-dependent liquid chromatography-tandem mass spectrometry (LC-MS/MS) is widely used in proteomic analyses. A well-performed LC-MS/MS workflow, which involves multiple procedures and interdependent metrics, is a prerequisite for deep proteome profiling. Researchers have previously evaluated LC-MS/MS performance mainly based on the number of identified peptides and proteins. However, this is not a comprehensive approach. This motivates us to develop MSRefine, which aims to evaluate and optimize the performance of the LC-MS/MS workflow for data-dependent acquisition (DDA) proteomics. It extracts 47 kinds of metrics, scores the metrics, and reports visual results, assisting users in evaluating the workflow, locating problems, and providing optimizing strategies. In this study, we compared and analyzed multiple pairs of datasets spanning different samples, methods, and instruments and demonstrated that the comprehensive visual metrics and scores in MSRefine enable us to evaluate the performance of the various experiments and provide optimal strategies for the identification of more peptides and proteins.

A fully integrated sample preparation strategy for highly sensitive intact glycoproteomics.

A fully integrated sample preparation technology, termed Intact GlycoSISPROT, was developed for the highly sensitive analysis of site-specific glycopeptides. Through integrating all glycoproteomic sample preparation steps into a single spintip, Intact GlycoSISPROT provided a tool for site-specific glycosylation analysis with low micrograms to even nanograms of protein sample.

Combinatory strategy using nanoscale proteomics and machine learning for T cell subtyping in peripheral blood of single multiple myeloma patients.

T cells play crucial roles in our immunity against hematological tumors by inducing sustained immune responses. Flow cytometry-based detection of a limited number of specific protein markers has been routinely applied for basic research and clinical investigation in this area. In this study, we combined flow cytometry with the simple integrated spintip-based proteomics technology (SISPROT) to characterize the proteome of primary T cell subtypes in the peripheral blood (PB) from single multiple myeloma (MM) patients. Taking advantage of the integrated high pH reversed-phase fractionation in the SISPROT device, the global proteomes of CD3+, CD4+ and CD8+ T cells were firstly profiled with a depth of >7 000 protein groups for each cell type. The sensitivity of single-shot proteomic analysis was dramatically improved by optimizing the SISPROT and data-dependent acquisition parameters for nanogram-level samples. Eight subtypes of T cells were sorted from about 4 mL PB of single MM patients, and the individual subtype-specific proteomes with coverage among 1 702 and 3 699 protein groups were obtained from as low as 70 ng and up to 500 ng of cell lysates. In addition, we developed a two-step machine learning-based subtyping strategy for proof-of-concept classifying eight T cell subtypes, independent of their cell numbers and individual differences. Our strategy demonstrates an easy-to-use proteomic analysis on immune cells with the potential to discover novel subtype-specific protein biomarkers from limited clinical samples in future large scale clinical studies.

Spatial proteomics for understanding the tissue microenvironment.

The human body comprises rich populations of cells, which are arranged into tissues and organs with diverse functionalities. These cells exhibit a broad spectrum of phenotypes and are often organized as a heterogeneous but sophisticatedly regulated ecosystem - tissue microenvironment, inside which every cell interacts with and is reciprocally influenced by its surroundings through its life span. Therefore, it is critical to comprehensively explore the cellular machinery and biological processes in the tissue microenvironment, which is best exemplified by the tumor microenvironment (TME). The past decade has seen increasing advances in the field of spatial proteomics, the main purpose of which is to characterize the abundance and spatial distribution of proteins and their post-translational modifications in the microenvironment of diseased tissues. Herein, we outline the achievements and remaining challenges of mass spectrometry-based tissue spatial proteomics. Exciting technology developments along with important biomedical applications of spatial proteomics are highlighted. In detail, we focus on high-quality resources built by scalpel macrodissection-based region-resolved proteomics, method development of sensitive sample preparation for laser microdissection-based spatial proteomics, and antibody recognition-based multiplexed tissue imaging. In the end, critical issues and potential future directions for spatial proteomics are also discussed.

Synergistic optimization of Liquid Chromatography and Mass Spectrometry parameters on Orbitrap Tribrid mass spectrometer for high efficient data-dependent proteomics.

Steady improvement in Orbitrap-based mass spectrometry (MS) technologies has greatly advanced the peptide sequencing speed and depth. In-depth analysis of the performance of state-of-the-art MS and optimization of key parameters can improve sequencing efficiency. In this study, we first systematically compared the performance of two popular data-dependent acquisition approaches, with Orbitrap as the first-stage (MS1) mass analyzer and the same Orbitrap (high-high approach) or ion trap (high-low approach) as the second-stage (MS2) mass analyzer, on the Orbitrap Fusion mass spectrometer. High-high approach outperformed high-low approach in terms of better saturation of the scan cycle and higher MS2 identification rate. However, regardless of the acquisition method, there are still more than 60% of peptide features untargeted for MS2 scan. We then systematically optimized the MS parameters using the high-high approach. Increasing the isolation window in the high-high approach could facilitate faster scan speed, but decreased MS2 identification rate. On the contrary, increasing the injection time of MS2 scan could increase identification rate but decrease scan speed and the number of identified MS2 spectra. Dynamic exclusion time should be set properly according to the chromatography peak width. Furthermore, we found that the Orbitrap analyzer, rather than the analytical column, was easily saturated with higher loading amount, thus limited the dynamic range of MS1-based quantification. By using optimized parameters, 10 000 proteins and 110 000 unique peptides were identified by using 20 h of effective liquid chromatography (LC) gradient time. The study therefore illustrated the importance of synchronizing LC-MS precursor ion targeting, fragment ion detection, and chromatographic separation for high efficient data-dependent proteomics.

Multiomic analysis of a dried single-drop plasma sample using an integrated mass spectrometry approach.

An easy-to-use and fast approach was developed for integrated proteomic and metabolic profiling in a dried single-drop plasma sample. Plasma collection, room temperature storage, and sample preparation for both proteins and metabolites were seamlessly integrated in one spintip device. MS-based multiomic profiling using the same nano LC-MS system identified more than 150 proteins and 160 metabolites from the 1 µL plasma sample in 6 hours. Further combination with micro-flow LC and targeted MS made it a promising approach for the fast profiling of molecular biomarkers with high sensitivity and accuracy.

Spatial proteome profiling by immunohistochemistry-based laser capture microdissection and data-independent acquisition proteomics.

Understanding the tumor heterogeneity through spatially resolved proteome profiling is important for biomedical research and clinical application. Laser capture microdissection (LCM) is a powerful technology for exploring local cell populations without losing spatial information. Conventionally, tissue sections are stained with hematoxylin and eosin (H&E) for cell-type identification before LCM. However, it generally requires experienced pathologists to distinguish different cell types, which limits the application of LCM to broad cancer research field. Here, we designed an immunohistochemistry (IHC)-based workflow for cell type-resolved proteome analysis of tissue samples. Firstly, targeted cell type was marked by IHC using antibody targeting cell-type specific marker to improve accuracy and efficiency of LCM. Secondly, to increase protein recovery from chemically crosslinked IHC tissues, we optimized a decrosslinking procedure to seamlessly combine with the integrated spintip-based sample preparation technology SISPROT. This newly developed approach, termed IHC-SISPROT, has comparable performance as H&E staining-based proteomic analysis. High sensitivity and reproducibility of IHC-SISPROT were achieved by combining with data independent acquisition proteomics. More than 3500 proteins were identified from only 0.2 mm2 and 12 µm thickness of hepatocellular carcinoma (HCC) tissue section. Furthermore, using 5 mm2 and 12 µm thickness of HCC tissue section, 6660 and 6052 protein groups were quantified from cancer cells and cancer-associated fibroblasts (CAFs) by the IHC-SISPROT workflow. Bioinformatic analysis revealed the enrichment of cell type-specific ligands and receptors and potentially new communications between cancer cells and CAFs by these signaling proteins. Therefore, IHC-SISPROT is a sensitive and accurate proteomic approach for spatial profiling of cell type-specific proteome from tissues.

AutoProteome Chip System for Fully Automated and Integrated Proteomics Sample Preparation and Peptide Fractionation.

With recent advances in LC-MS systems, current MS-based proteomics has an increasing need for automated, high-throughput sample preparation with neglectable sample loss. In this study, we developed a microfluidic system for fully automated proteomics sample preparation. All of the required proteomics sample preparation steps for both protein digestion and peptide fractionation are fully integrated into a disposable plastic chip device (named AutoProteome Chip). The AutoProteome Chip packed with mixed-mode ion exchange beads and C18 membrane in tandem could be fabricated with very low cost and high stability in organic reagents. Benefiting from its low backpressure, the AutoProteome Chip could be precisely driven by gas pressure, which could be easily multiplexed. As low as 2 ng of standard protein BSA could be trapped into the AutoProteome chip and processed within 2 h. Fully automated processing of 10 µg of protein extracts of HEK 293T cells achieved more than 97% of digestion efficiency with missed cleavage less than 2 and comparable performance with conventional approaches. More than 4700 proteins could be readily identified within 80 min of LC-MS analysis with good label-free quantification performance (Pearson correlation coefficient >0.99). Furthermore, deep proteome profiling by integrated high-pH RP fractionation in the same AutoProteome Chip resulted in more than 7500 proteins being identified from only 20 µg of protein extracts of HEK 293T cells and comparable reprodicibility as single-shot analysis. The AutoProteome Chip system provided a valuable prototype for developing a fully automated proteome analysis workflow and for proteomic applications with high demand for processing throughput, reproducibility, and sensitivity.

High-Throughput and Integrated Chemical Proteomic Approach for Profiling Phosphotyrosine Signaling Complexes.

Phosphotyrosine (pTyr) signaling complexes are important resources of biomarkers and drug targets which often need to be profiled with enough throughput. Current profiling approaches are not feasible to meet this need due to either biased profiling by antibody-based detection or low throughput by traditional affinity purification-mass spectrometry approach (AP-MS), as exemplified by our previously developed photo-pTyr-scaffold approach. To address these limitations, we developed a 96-well microplate-based sample preparation and fast data independent proteomic analysis workflow. By assembling the photo-pTyr-scaffold probe into a 96-well microplate, we achieved steric hindrance-free photoaffinity capture of pTyr signaling complexes, selective enrichment under denaturing conditions, and efficient in-well digestion in a fully integrated manner. EGFR signaling complex proteins could be efficiently captured and identified by using 300 times less cell lysate and 100 times less photo-pTyr-scaffold probe as compared with our previous approach operated in an Eppendorf tube. Furthermore, the lifetime of the photo-pTyr-scaffold probe in a 96-well microplate was significantly extended from 1 week up to 1 month. More importantly, by combining with high-flow nano LC separation and data independent acquisition on the Q Exactive HF-X mass spectrometer, LC-MS time could be significantly reduced to only 35 min per sample without increasing sample loading amount and compromising identification and quantification performance. This new high-throughput proteomic approach allowed us to rapidly and reproducibly profile dynamic pTyr signaling complexes with EGF stimulation at five time points and EGFR inhibitor treatment at five different concentrations. We are therefore optimized for its generic application in biomarkers discovery and drug screening in a high-throughput fashion.

A Fully Integrated Spintip-Based Approach for Sensitive and Quantitative Profiling of Region-Resolved in Vivo Brain Glycoproteome.

Region- and cell type-resolved global proteome and specific post-translational modifications (PTMs) profiling of tissues has drawn great attention recently for interpreting the heterogeneous multicellular microenvironment of various in vivo systems. Due to access to low microgram of proteins and low abundance of glycoproteins, spatially resolved glycoproteome analysis of in vivo tissue sections remains challenging. Several glycoproteomics sample preparation strategies were established for processing microgram-level of protein samples, but these strategies were not either fully integrated or directly compatible with tissue samples when considering protein extraction in strong lysis buffers. Moreover, these approaches mainly focused on identification of glycosylation sites, but pay less attention to quantification, all of which limit their applications. Here we designed a fully integrated spintip-based glycoproteomic approach (FISGlyco) which achieves all the steps of glycoprotein enrichment, digestion, deglycosylation, and desalting in single spintip device. Sample loss is significantly reduced, and the total processing time is reduced to 4 h, while detection sensitivity and label-free quantification precision is greatly improved. 607 N-glycosylation sites were successfully identified and quantified from only 5 µg of mouse brain proteins. By seamlessly combining with laser capture microdissection (LCM), the first region-resolved N-glycoproteome profiling of four mouse brain regions, including isocortex, hippocampus, thalamus, and hypothalamus, was achieved, with 1875, 1794, 1801, and 1417 N-glycosites identified, respectively. Our approach could be a generic approach for region and even cell type specific glycoproteome analysis of in vivo tissue sections.

An integrated strategy for high-sensitive and multi-level glycoproteome analysis from low micrograms of protein samples.

Glycosylation, as a biologically important protein post-translational modification, often alters on both glycosites and glycans, simultaneously. However, most of current approaches focused on biased profiling of either glycosites or glycans, and limited by time-consuming process and milligrams of starting protein material. We describe here a simple and integrated spintip-based glycoproteomics technology (termed Glyco-SISPROT) for achieving a comprehensive view of glycoproteome with shorter sample processing time and low microgram starting material. By carefully integrating and optimizing SCX, C18 and Concanavalin A (Con A) packing material and their combination in spintip format, both predigested peptides and protein lysates could be processed by Glyco-SISPROT with high efficiency. More importantly, deglycopeptide, intact glycopeptide and glycans released by multiple glycosidases could be readily collected from the same Glyco-SISPROT workflow for LC-MS analysis. In total, above 1850 glycosites in ˜1770 unique deglycopeptides were characterized from mouse liver by using either 100 µg of predigested peptides or directly using 100 µg of protein lysates, in which about 30% of glycosites were released by both PNGase F and Endos. To the best of our knowledge, this approach should be one of the most comprehensive glycoproteomic approaches by using limited protein starting material. One significant benefit of Glyco-SISPROT is that whole processing time is dramatically reduced from a few days to less than 6 h with good reproducibility when protein lysates were directly processed by Glyco-SISPROT. We expect that this method will be suitable for multi-level glycoproteome analysis of rare biological samples with high sensitivity.

Targeting LIF-mediated paracrine interaction for pancreatic cancer therapy and monitoring.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis largely owing to inefficient diagnosis and tenacious drug resistance. Activation of pancreatic stellate cells (PSCs) and consequent development of dense stroma are prominent features accounting for this aggressive biology1,2. The reciprocal interplay between PSCs and pancreatic cancer cells (PCCs) not only enhances tumour progression and metastasis but also sustains their own activation, facilitating a vicious cycle to exacerbate tumorigenesis and drug resistance3-7. Furthermore, PSC activation occurs very early during PDAC tumorigenesis8-10, and activated PSCs comprise a substantial fraction of the tumour mass, providing a rich source of readily detectable factors. Therefore, we hypothesized that the communication between PSCs and PCCs could be an exploitable target to develop effective strategies for PDAC therapy and diagnosis. Here, starting with a systematic proteomic investigation of secreted disease mediators and underlying molecular mechanisms, we reveal that leukaemia inhibitory factor (LIF) is a key paracrine factor from activated PSCs acting on cancer cells. Both pharmacologic LIF blockade and genetic Lifr deletion markedly slow tumour progression and augment the efficacy of chemotherapy to prolong survival of PDAC mouse models, mainly by modulating cancer cell differentiation and epithelial-mesenchymal transition status. Moreover, in both mouse models and human PDAC, aberrant production of LIF in the pancreas is restricted to pathological conditions and correlates with PDAC pathogenesis, and changes in the levels of circulating LIF correlate well with tumour response to therapy. Collectively, these findings reveal a function of LIF in PDAC tumorigenesis, and suggest its translational potential as an attractive therapeutic target and circulating marker. Our studies underscore how a better understanding of cell-cell communication within the tumour microenvironment can suggest novel strategies for cancer therapy.

Mixed-mode ion exchange-based integrated proteomics technology for fast and deep plasma proteome profiling.

Plasma proteome profiling by LC-MS based proteomics has drawn great attention recently for biomarker discovery from blood liquid biopsy. Due to standard multi-step sample preparation could potentially cause plasma protein degradation and analysis variation, integrated proteomics sample preparation technologies became promising solution towards this end. Here, we developed a fully integrated proteomics sample preparation technology for both fast and deep plasma proteome profiling under its native pH. All the sample preparation steps, including protein digestion and two-dimensional fractionation by both mixed-mode ion exchange and high-pH reversed phase mechanism were integrated into one spintip device for the first time. The mixed-mode ion exchange beads design achieved the sample loading at neutral pH and protein digestion within 30 min. Potential sample loss and protein degradation by pH changing could be voided. 1 µL of plasma sample with depletion of high abundant proteins was processed by the developed technology with 12 equally distributed fractions and analyzed with 12 h of LC-MS gradient time, resulting in the identification of 862 proteins. The combination of the Mixed-mode-SISPROT and data-independent MS method achieved fast plasma proteome profiling in 2 h with high identification overlap and quantification precision for a proof-of-concept study of plasma samples from 5 healthy donors. We expect that the Mixed-mode-SISPROT become a generally applicable sample preparation technology for clinical oriented plasma proteome profiling.

Proteomic Analysis of Secreted Proteins from Cell Microenvironment.

Cell microenvironment consists of various types of cells which communicate with each other by vast number of secreted proteins. An unbiased profiling of these secreted proteins on a global scale is often critical for understanding the intercellular signaling in an autocrine or paracrine manner. Mass spectrometry-based proteomics has become one of the most popular technology for characterization of the secreted proteins. In this chapter, we discuss the standard workflow for secreted proteins characterization, including harvesting secreted proteins from conditioned media, digesting the obtained proteins, liquid chromatography-mass spectrometry analysis, and downstream data analysis.

Facile synthesis of carboxymethyl-ß-cyclodextrin conjugated magnetic nanoparticles for selective enrichment of glycopeptides.

RATIONALE: Selective enrichment of glycopeptides prior to mass spectrometry (MS) analysis is essential due to the low abundance of the modified glycopeptides in complex samples, ion suppression effects during MS ionization and detection caused by the co-presence of non-glycosylated peptides, etc. Among different enrichment approaches, hydrophilic interaction liquid chromatography (HILIC)-based magnetic separation has become one of the most popular methods in recent years, due to its high efficiency and selectivity for glycopeptide enrichment. METHODS: Herein, novel carboxymethyl-ß-cyclodextrin (CMCD)-modified magnetic nanoparticles (MNPs) were synthesized via a carbodiimide activation method. CMCD was covalently bonded with the -OH group on the surface of MNPs through carbodiimide, and the proposed procedure provides a rapid and efficient alternative for glycopeptide enrichment due to its stable interaction, time-saving, and easy operation. RESULTS: The prepared absorbents with a mean diameter of 15 nm demonstrated a strong magnetic response to an externally applied magnetic field. The results of thermogravimetric analysis showed the content of bound CMCD was 3 wt%. The outer CMCD layer conjugated on the Fe3 O4 core showed high hydrophilic surface property. In the analysis of a complex mouse liver sample, a total of 666 unique N-glycosylation sites corresponding to 494 glycosylated proteins were identified successfully. CONCLUSIONS: The study demonstrated an easy-to-use CMCD-modified MNPs-based approach with high selectivity and high capacity in the enrichment of low-abundance glycopeptides from complex biological samples. Copyright © 2016 John Wiley & Sons, Ltd.

Poly(ADP-Ribose) Glycohydrolase (PARG) Silencing Suppresses Benzo(a)pyrene Induced Cell Transformation.

Benzo(a)pyrene (BaP) is a ubiquitously distributed environmental pollutant and known carcinogen, which can induce malignant transformation in rodent and human cells. Poly(ADP-ribose) glycohydrolase (PARG), the primary enzyme that catalyzes the degradation of poly(ADP-ribose) (PAR), has been known to play an important role in regulating DNA damage repair and maintaining genomic stability. Although PARG has been shown to be a downstream effector of BaP, the role of PARG in BaP induced carcinogenesis remains unclear. In this study, we used the PARG-deficient human bronchial epithelial cell line (shPARG) as a model to examine how PARG contributed to the carcinogenesis induced by chronic BaP exposure under various concentrations (0, 10, 20 and 40 µM). Our results showed that PARG silencing dramatically reduced DNA damages, chromosome abnormalities, and micronuclei formations in the PARG-deficient human bronchial epithelial cells compared to the control cells (16HBE cells). Meanwhile, the wound healing assay showed that PARG silencing significantly inhibited BaP-induced cell migration. Furthermore, silencing of PARG significantly reduced the volume and weight of tumors in Balb/c nude mice injected with BaP induced transformed human bronchial epithelial cells. This was the first study that reported evidences to support an oncogenic role of PARG in BaP induced carcinogenesis, which provided a new perspective for our understanding in BaP exposure induced cancer.

[Research progress in carcinogenicity of trichloroethylene and its metabolites].

Trichlorethylene (TCE) is a widely used organic solvent and an important industrial material. It's easily released into the environment through manufacture, use and disposal process, so there is a wide range of occupationally and environmentally exposed population. Based on accumulated research data, International Agency for Research on Cancer (IARC) increased the carcinogenic rating of TCE from probable human carcinogen to certain human carcinogen in 2012. This paper is a review of the carcinogenic effects of TCE and its metabolites from the aspects of epidemiological data, experimental evidence on animals as well as the mechanisms of carcinogenesis.

Phosphoproteomic analyses of L-02 liver cells exposed to trichloroethylene.

Trichloroethylene (TCE) is an environmental and occupational toxicant that has been shown to cause serious hepatotoxicity. However, the mechanisms underlying the hepatotoxicity of TCE remain unclear. Previously, we identified several apoptosis-related proteins in TCE-induced hepatic cytotoxicity. This study is aimed to analyze the changes in phosphoproteins in L-02 liver cells exposed to TCE using iTRAQ labeling, IMAC enrichment and LC-MS/MS. We identified 1878 phosphorylation sites in 107 proteins and found that 20 sites in 16 phosphoproteins were differentially phosphorylated in L-02 cells after TCE treatment. Among these phosphoproteins, 20% were protein localization and formation processes-related proteins, 38% were metabolism-related proteins and 42% were cellular process-related proteins, including transcriptional regulation and biogenesis. Moreover, two phosphoproteins, 4E-BP1 (37T) and MCM2 (139S), were validated as TCE-induced alteration of phosphorylation at specific sites by Western-blot analysis. Taken together, our study demonstrated that TCE exposure changed the levels of multiple phosphoproteins in L-02 liver cells, and the functional analysis suggested that these differentially expressed phosphoproteins might be involved in TCE-induced hepatic cytotoxicity.