Highly Reproducible Quantitative Proteomics Analysis of Pancreatic Cancer Cells Reveals Proteome-Level Effects of a Novel Combination Drug Therapy That Induces Cancer Cell Death via Metabolic Remodeling and Activation of the Extrinsic Apoptosis Pathway.

Pancreatic cancer patients have poor survival rates and are frequently treated using gemcitabine (Gem). However, initial tumor sensitivity often gives way to rapid development of resistance. Gem-based drug combinations are employed to increase efficacy and mitigate resistance, but our understanding of molecular-level drug interactions, which could assist in the development of more effective therapeutic regimens, is limited. Global quantitative proteomic analysis could provide novel mechanistic insights into drug combination interactions, but it is challenging to achieve high-quality quantitative proteomics analysis of the large sample sets that are typically required for drug combination studies. Here, we investigated molecular-level temporal interactions of Gem with BGJ398 (infigratinib), a recently approved pan-FGFR inhibitor, in multiple treatment groups (N = 42 samples) using IonStar, a robust large-scale proteomics method that employs well-controlled, ultrahigh-resolution MS1 quantification. A total of 5514 proteins in the sample set were quantified without missing data, requiring >2 unique peptides/protein, <1% protein false discovery rate (FDR), <0.1% peptide FDR, and CV < 10%. Functional analysis of the differentially altered proteins revealed drug-dysregulated processes such as metabolism, apoptosis, and antigen presentation pathways. These changes were validated experimentally using Seahorse metabolic assays and immunoassays. Overall, in-depth analysis of large-scale proteomics data provided novel insights into possible mechanisms by which FGFR inhibitors complement and enhance Gem activity in pancreatic cancers.

Expression conditions and characterization of a novelly constructed lipoprotein intended as a vaccine to prevent human Haemophilus influenzae infections.

Bacterial lipoproteins are structurally divided into two groups, based on their lipid moieties: diacylated (present in Gram-positive bacteria) and triacylated (present in some Gram-positive and most Gram-negative bacteria). Diacylated and triacylated lipid moieties differ by a single amide-linked fatty acid chain. Lipoproteins induce host innate immune responses by the mammalian Toll-like receptor 2 (TLR2). In this study, we added a lipid moiety to recombinant OMP26, a native nonlipidated (NL) membrane protein of Haemophilus influenzae, and characterized it extensively under different expression conditions using flow cytometry, LC/MS, and MALDI-TOF. We also investigated the ability of NL and lipidated (L) OMP26 to induce in vitro stimulation of HEK Blue-hTLR2-TR1 and hTLR-TLR6 cells. Our L-OMP26 was predominantly expressed in diacylated form, so we employed an additional gene copy of apolipoprotein N-acetyltransferase enzyme (Lnt)-rich Escherichia coli strain that further acylates the diacyl lipoproteins to enhance the production of triacylated L-OMP26. The diacyl and triacyl versions of L-OMP26, intended as a vaccine for use in humans, were characterized and evaluated as protein vaccine components in a mouse model. We found that the diacyl and triacyl L-OMP26 protein formulations differed markedly in their immune-stimulatory activity, with diacylated L-OMP26 stimulating higher adaptive immune responses compared with triacylated L-OMP26 and both stimulating higher adaptive immune response compared to NL-OMP26. We also constructed and characterized an L-OMP26φNL-P6 fusion protein, where NL-P6 protein (a commonly studied H. influenzae vaccine candidate) was recombinantly fused to L-OMP26. We observed a similar pattern of lipidation (predominantly diacylated) in the L-OMP26φNL-P6 fusion protein.

High-quality and robust protein quantification in large clinical/pharmaceutical cohorts with IonStar proteomics investigation.

Robust, reliable quantification of large sample cohorts is often essential for meaningful clinical or pharmaceutical proteomics investigations, but it is technically challenging. When analyzing very large numbers of samples, isotope labeling approaches may suffer from substantial batch effects, and even with label-free methods, it becomes evident that low-abundance proteins are not reliably measured owing to unsufficient reproducibility for quantification. The MS1-based quantitative proteomics pipeline IonStar was designed to address these challenges. IonStar is a label-free approach that takes advantage of the high sensitivity/selectivity attainable by ultrahigh-resolution (UHR)-MS1 acquisition (e.g., 120-240k full width at half maximum at m/z = 200) which is now widely available on ultrahigh-field Orbitrap instruments. By selectively and accurately procuring quantitative features of peptides within precisely defined, very narrow m/z windows corresponding to the UHR-MS1 resolution, the method minimizes co-eluted interferences and substantially enhances signal-to-noise ratio of low-abundance species by decreasing noise level. This feature results in high sensitivity, selectivity, accuracy and precision for quantification of low-abundance proteins, as well as fewer missing data and fewer false positives. This protocol also emphasizes the importance of well-controlled, robust experimental procedures to achieve high-quality quantification across a large cohort. It includes a surfactant cocktail-aided sample preparation procedure that achieves high/reproducible protein/peptide recoveries among many samples, and a trapping nano-liquid chromatography-mass spectrometry strategy for sensitive and reproducible acquisition of UHR-MS1 peptide signal robustly across a large cohort. Data processing and quality evaluation are illustrated using an example dataset ( http://proteomecentral.proteomexchange.org ), and example results from pharmaceutical project and one clinical project (patients with acute respiratory distress syndrome) are shown. The complete IonStar pipeline takes ~1-2 weeks for a sample cohort containing ~50-100 samples.

In-depth mapping of protein localizations in whole tissue by micro-scaffold assisted spatial proteomics (MASP).

Accurate, in-depth mapping of proteins on whole-tissue levels provides comprehensive insights into the spatially-organized regulatory processes/networks in tissues, but is challenging. Here we describe a micro-scaffold assisted spatial proteomics (MASP) strategy, based on spatially-resolved micro-compartmentalization of tissue using a 3D-printed micro-scaffold, capable of mapping thousands of proteins across a whole-tissue slice with excellent quantitative accuracy/precision. The pipeline includes robust tissue micro-compartmentalization with precisely-preserved spatial information, reproducible procurement and preparation of the micro-specimens, followed by sensitive LC-MS analysis and map generation by a MAsP app. The mapping accuracy was validated by comparing the MASP-generated maps of spiked-in peptides and brain-region-specific markers with known patterns, and by correlating the maps of the two protein components of the same heterodimer. The MASP was applied in mapping >5000 cerebral proteins in the mouse brain, encompassing numerous important brain markers, regulators, and transporters, where many of these proteins had not previously been mapped on the whole-tissue level.

Comparative Proteomic Analysis Identifies Key Metabolic Regulators of Gemcitabine Resistance in Pancreatic Cancer.

Pancreatic adenocarcinoma (PDAC) is highly refractory to treatment. Standard-of-care gemcitabine (Gem) provides only modest survival benefits, and development of Gem resistance (GemR) compromises its efficacy. Highly GemR clones of Gem-sensitive MIAPaCa-2 cells were developed to investigate the molecular mechanisms of GemR and implemented global quantitative differential proteomics analysis with a comprehensive, reproducible ion-current-based MS1 workflow to quantify ∼6000 proteins in all samples. In GemR clone MIA-GR8, cellular metabolism, proliferation, migration, and 'drug response' mechanisms were the predominant biological processes altered, consistent with cell phenotypic alterations in cell cycle and motility. S100 calcium binding protein A4 was the most downregulated protein, as were proteins associated with glycolytic and oxidative energy production. Both responses would reduce tumor proliferation. Upregulation of mesenchymal markers was prominent, and cellular invasiveness increased. Key enzymes in Gem metabolism pathways were altered such that intracellular utilization of Gem would decrease. Ribonucleoside-diphosphate reductase large subunit was the most elevated Gem metabolizing protein, supporting its critical role in GemR. Lower Ribonucleoside-diphosphate reductase large subunit expression is associated with better clinical outcomes in PDAC, and its downregulation paralleled reduced MIAPaCa-2 proliferation and migration and increased Gem sensitivity. Temporal protein-level Gem responses of MIAPaCa-2 versus GemR cell lines (intrinsically GemR PANC-1 and acquired GemR MIA-GR8) implicate adaptive changes in cellular response systems for cell proliferation and drug transport and metabolism, which reduce cytotoxic Gem metabolites, in DNA repair, and additional responses, as key contributors to the complexity of GemR in PDAC. These findings additionally suggest targetable therapeutic vulnerabilities for GemR PDAC patients.

Cyclosporine A Modulates LSP1 Protein Levels in Human B Cells to Attenuate B Cell Migration at Low O2 Levels.

Coordinated migration of B cells within and between secondary lymphoid tissues is required for robust antibody responses to infection or vaccination. Secondary lymphoid tissues normally expose B cells to a low O2 (hypoxic) environment. Recently, we have shown that human B cell migration is modulated by an O2-dependent molecular switch, centrally controlled by the hypoxia-induced (transcription) factor-1α (HIF1A), which can be disrupted by the immunosuppressive calcineurin inhibitor, cyclosporine A (CyA). However, the mechanisms by which low O2 environments attenuate B cell migration remain poorly defined. Proteomics analysis has linked CXCR4 chemokine receptor signaling to cytoskeletal rearrangement. We now hypothesize that the pathways linking the O2 sensing molecular switch to chemokine receptor signaling and cytoskeletal rearrangement would likely contain phosphorylation events, which are typically missed in traditional transcriptomic and/or proteomic analyses. Hence, we have performed a comprehensive phosphoproteomics analysis of human B cells treated with CyA after engagement of the chemokine receptor CXCR4 with CXCL12. Statistical analysis of the separate and synergistic effects of CyA and CXCL12 revealed 116 proteins whose abundance is driven by a synergistic interaction between CyA and CXCL12. Further, we used our previously described algorithm BONITA to reveal a critical role for Lymphocyte Specific Protein 1 (LSP1) in cytoskeletal rearrangement. LSP1 is known to modulate neutrophil migration. Validating these modeling results, we show experimentally that LSP1 levels in B cells increase with low O2 exposure, and CyA treatment results in decreased LSP1 protein levels. This correlates with the increased chemotactic activity observed after CyA treatment. Lastly, we directly link LSP1 levels to chemotactic capacity, as shRNA knock-down of LSP1 results in significantly increased B cell chemotaxis at low O2 levels. These results directly link CyA to LSP1-dependent cytoskeletal regulation, demonstrating a previously unrecognized mechanism by which CyA modulates human B cell migration. Data are available via ProteomeXchange with identifier PXD036167.

Parallel, High-Quality Proteomic and Targeted Metabolomic Quantification Using Laser Capture Microdissected Tissues.

Quantitative proteomics/metabolomics investigation of laser-capture-microdissection (LCM) cell populations from clinical cohorts affords precise insights into disease/therapeutic mechanisms, nonetheless high-quality quantification remains a prominent challenge. Here, we devised an LC/MS-based approach allowing parallel, robust global-proteomics and targeted-metabolomics quantification from the same LCM samples, using biopsies from prostate cancer (PCa) patients as the model system. The strategy features: (i) an optimized molecular weight cutoff (MWCO) filter-based separation of proteins and small-molecule fractions with high and consistent recoveries; (ii) microscale derivatization and charge-based enrichment for ultrasensitive quantification of key androgens (LOQ = 5 fg/1k cells) with excellent accuracy/precision; (iii) reproducible/precise proteomics quantification with low-missing-data using a detergent-cocktail-based sample preparation and an IonStar pipeline for reproducible and precise protein quantification with excellent data quality. Key parameters enabling robust/reproducible quantification have been meticulously evaluated and optimized, and the results underscored the importance of surveying quantitative performances against key parameters to facilitate fit-for-purpose method development. As a proof-of-concept, high-quality quantification of the proteome and androgens in LCM samples of PCa patient-matched cancerous and benign epithelial/stromal cells was achieved (N = 16), which suggested distinct androgen distribution patterns across cell types and regions, as well as the dysregulated pathways involved in tumor-stroma crosstalk in PCa pathology. This strategy markedly leverages the scope of quantitative-omics investigations using LCM samples, and combining with IonStar, can be readily adapted to larger-cohort clinical analysis. Moreover, the capacity of parallel proteomics/metabolomics quantification permits precise corroboration of regulatory processes on both protein and small-molecule levels, with decreased batch effect and enhanced utilization of samples.

Potential Neuroprotective Mechanisms of Methamphetamine Treatment in Traumatic Brain Injury Defined by Large-Scale IonStar-Based Quantitative Proteomics.

Although traumatic brain injury (TBI) causes hospitalizations and mortality worldwide, there are no approved neuroprotective treatments, partly due to a poor understanding of the molecular mechanisms underlying TBI neuropathology and neuroprotection. We previously reported that the administration of low-dose methamphetamine (MA) induced significant functional/cognitive improvements following severe TBI in rats. We further demonstrated that MA mediates neuroprotection in part, via dopamine-dependent activation of the PI3K-AKT pathway. Here, we further investigated the proteomic changes within the rat cortex and hippocampus following mild TBI (TM), severe TBI (TS), or severe TBI plus MA treatment (TSm) compared to sham operated controls. We identified 402 and 801 altered proteins (APs) with high confidence in cortical and hippocampal tissues, respectively. The overall profile of APs observed in TSm rats more closely resembled those seen in TM rather than TS rats. Pathway analysis suggested beneficial roles for acute signaling through IL-6, TGFß, and IL-1ß. Moreover, changes in fibrinogen levels observed in TSm rats suggested a potential role for these proteins in reducing/preventing TBI-induced coagulopathies. These data facilitate further investigations to identify specific pathways and proteins that may serve as key targets for the development of neuroprotective therapies.

Mutant Kras as a Biomarker Plays a Favorable Role in FL118-Induced Apoptosis, Reactive Oxygen Species (ROS) Production and Modulation of Survivin, Mcl-1 and XIAP in Human Bladder Cancer.

Tumor heterogeneity in key gene mutations in bladder cancer (BC) is a major hurdle for the development of effective treatments. Using molecular, cellular, proteomics and animal models, we demonstrated that FL118, an innovative small molecule, is highly effective at killing T24 and UMUC3 high-grade BC cells, which have Hras and Kras mutations, respectively. In contrast, HT1376 BC cells with wild-type Ras are insensitive to FL118. This concept was further demonstrated in additional BC and colorectal cancer cells with mutant Kras versus those with wild-type Kras. FL118 strongly induced PARP cleavage (apoptosis hallmark) and inhibited survivin, XIAP and/or Mcl-1 in both T24 and UMUC3 cells, but not in the HT1376 cells. Silencing mutant Kras reduced both FL118-induced PARP cleavage and downregulation of survivin, XIAP and Mcl-1 in UMUC3 cells, suggesting mutant Kras is required for FL118 to exhibit higher anticancer efficacy. FL118 increased reactive oxygen species (ROS) production in T24 and UMUC3 cells, but not in HT1376 cells. Silencing mutant Kras in UMUC3 cells reduced FL118-mediated ROS generation. Proteomics analysis revealed that a profound and opposing Kras-relevant signaling protein is changed in UMUC3 cells and not in HT1376 cells. Consistently, in vivo studies indicated that UMUC3 tumors are highly sensitive to FL118 treatment, while HT1376 tumors are highly resistant to this agent. Silencing mutant Kras in UMUC3 cell-derived tumors decreases UMUC3 tumor sensitivity to FL118 treatment. Together, our studies revealed that mutant Kras is a favorable biomarker for FL118 targeted treatment.

MS1 ion current-based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts.

The rapidly-advancing field of pharmaceutical and clinical research calls for systematic, molecular-level characterization of complex biological systems. To this end, quantitative proteomics represents a powerful tool but an optimal solution for reliable large-cohort proteomics analysis, as frequently involved in pharmaceutical/clinical investigations, is urgently needed. Large-cohort analysis remains challenging owing to the deteriorating quantitative quality and snowballing missing data and false-positive discovery of altered proteins when sample size increases. MS1 ion current-based methods, which have become an important class of label-free quantification techniques during the past decade, show considerable potential to achieve reproducible protein measurements in large cohorts with high quantitative accuracy/precision. Nonetheless, in order to fully unleash this potential, several critical prerequisites should be met. Here we provide an overview of the rationale of MS1-based strategies and then important considerations for experimental and data processing techniques, with the emphasis on (i) efficient and reproducible sample preparation and LC separation; (ii) sensitive, selective and high-resolution MS detection; iii)accurate chromatographic alignment; (iv) sensitive and selective generation of quantitative features; and (v) optimal post-feature-generation data quality control. Prominent technical developments in these aspects are discussed. Finally, we reviewed applications of MS1-based strategy in disease mechanism studies, biomarker discovery, and pharmaceutical investigations.