Comparison of PD-L1 assays in head and neck carcinoma.

Programmed cell death-ligand 1 (PD-L1) expression is a predictive biomarker for response to immune checkpoint inhibitor in head and neck squamous cell carcinoma. Given the range of antibodies and platforms for PD-L1 testing, it is essential to understand the performance of different staining and scoring methods. PD-L1 expression in 156 head and neck mucosal squamous cell carcinoma (HNmSCC) cases at Asan Medical Center was assessed using 106 tissue microarray (TMA) cores and 50 whole slides. Three standardised PD-L1 assays (22C3 pharmDx, SP263, and 28-8 pharmDx) and one laboratory-developed test (22C3 LDT) were evaluated: the combined positive score (CPS) with ≥1, ≥20, and ≥50 cut-offs, and the tumour positive score (TPS) with ≥1%, ≥20%, ≥50% cut-offs. Concordance on a continuous scale among the assays was good to excellent for CPS [intraclass correlation coefficient (ICC) range 0.73-0.94] and TPS (ICC range 0.70-0.94) and in both TMA and whole slides cohorts. Stratification by variable cut-offs demonstrated moderate to good agreement among most assays, as analysed by Gwet's AC1. PD-L1 expression was significantly correlated with tumour location using the 22C3 pharmDx assay (CPS, p=0.014; TPS, p=0.033). Notable concordance was found among PD-L1 assays, suggesting their potential interchangeability in HNmSCC.

Identification of Proteomic Biomarkers of Acetaminophen-Induced Hepatotoxicity Using Stable Isotope Labeling.

Quantitative proteomics approaches based on stable isotopic labeling and mass spectrometry have been widely applied to disease research, drug target discovery, biomarker identification, and systems biology. One of the notable stable isotopic labeling approaches is trypsin-catalyzed 18O/16O labeling, which has its own advantages of low sample consumption, simple labeling procedure, cost-effectiveness, and absence of chemical reactions that potentially generate by-products. In this chapter, a protocol for 18O/16O labeling-based quantitative proteomics approach is described with an application to the identification of proteomic biomarkers of acetaminophen (APAP)-induced hepatotoxicity in rats. The protocol involves first the extraction of proteins from liver tissues of control and APAP-treated rats and digestion into peptides by trypsin. After cleaning of the peptides by solid-phase extraction, equal amounts of peptides from the APAP treatment and the control groups are then subject to trypsin-catalyzed 18O/16O labeling. The labeled peptides are combined and fractionated by off-line strong cation exchange liquid chromatography (SCXLC), and each fraction is then analyzed by nanoflow reversed-phase LC coupled online with tandem mass spectrometry (RPLC-MS/MS) for identification and quantification of differential protein expression between APAP-treated rats and controls. The protocol is applicable to quantitative proteomic analysis for a variety of biological samples.

Digestive Profiles of Human Milk, Recombinant Human and Bovine Lactoferrin: Comparing the Retained Intact Protein and Peptide Release.

Lactoferrin (LF) is a major component of human milk. LF supplementation (currently bovine) supports the immune system and helps maintain iron homeostasis in adults. No recombinant human lactoferrin (rhLF) is available for commercial food use. To determine the extent to which rhLF (Effera™) produced by Komagataella phaffii digests similarly to hmLF, a validated in vitro digestion protocol was carried out. Bovine LF (bLF) was used as an additional control, as it is approved for use in various food categories. This study compared the extent of intact protein retention and the profile of peptides released in hmLF, bLF and rhLF (each with low and high iron saturation) across simulated adult gastric and intestinal digestion using gel electrophoresis, ELISA and LC-MS. Intact LF retention across digestion was similar across LF types, but the highest iron-saturated hmLF had greater retention in the simulated gastric fluid than all other sample types. Peptides identified in digested hmLF samples strongly correlated with digested rhLF samples (0.86 < r < 0.92 in the gastric phase and 0.63 < r < 0.70 in the intestinal phase), whereas digested bLF samples were significantly different. These findings support the potential for rhLF as a food ingredient for human consumption.

One-Dimensional Acrylamide Gel Electrophoresis for Analysis of Plant Samples.

Polyacrylamide gel electrophoresis (PAGE) is a widely used technique for separating proteins from complex plant samples. Prior to the analysis, proteins must be extracted from plant tissues, which are rather complex than other types of biological material. Different protocols have been applied depending on the protein source, such as seeds, pollen, leaves, roots, and flowers. Total protein amounts must also be determined before conducting gel electrophoresis. The most common methodologies include PAGE under native or denaturing conditions. Both procedures are used consequently for protein identification and characterization via mass spectrometry. Additionally, various staining procedures are available to visualize protein bands in the gel, facilitating the software-based digital evaluation of the gel through image acquisition.

Comparative study of the commonly used protein quantitation assays on different Hymenoptera venoms: A fundamental aspect of Hymenoptera venom proteome analysis.

Determination of protein concentration in Hymenoptera venoms requires an accurate and reproducible assay as the results will be used to support subsequent proteomic techniques employed in their analyses. However, all protein assay techniques have inherent strengths and weaknesses, demanding their assessment before selecting the most suitable platform for sample analysis. In this study, protein profiles of ant, honeybee, and wasp venoms, and bovine serum albumin (BSA) and hyaluronidase standards were qualitatively assessed using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Their amino acid and protein concentration were quantitatively determined via Amino Acid Analysis (AAA). Amino acid concentration was determined via hydrolysis, derivatization, and chromatographic quantification. Protein concentration was estimated using four different protein concentration assays. The ratios of protein concentration in venom samples to protein standards were calculated, and the accuracy of the protein concentration assays was analysed relative to the concentration determined from AAA. SDS-PAGE analysis showed that BSA contained several protein bands, while hyaluronidase contained a mixture of peptide and protein bands. Ant and honeybee venoms contained a higher proportion of peptide bands, while wasp venom contained more protein bands. As determined by AAA, the ratio of protein concentration in Hymenoptera venoms varied between 1.01 and 1.11 to BSA, and between 0.96 and 1.06 to hyaluronidase. Overall, the Bradford assay was found to be the least accurate and the BCA assay was the most accurate in estimating protein concentration in Hymenoptera venoms. There was no significant advantage in using hyaluronidase as a standard or increasing incubation temperature of BCA assay when analysing Hymenoptera venoms. Diluent solutions containing phenol and human serum albumin interfered with Lowry-based assays.

Absolute quantitation of human wild-type DNAI1 protein in lung tissue using a nanoLC-PRM-MS-based targeted proteomics approach coupled with immunoprecipitation.

BACKGROUND: Dynein axonemal intermediate chain 1 protein (DNAI1) plays an essential role in cilia structure and function, while its mutations lead to primary ciliary dyskinesia (PCD). Accurate quantitation of DNAI1 in lung tissue is crucial for comprehensive understanding of its involvement in PCD, as well as for developing the potential PCD therapies. However, the current protein quantitation method is not sensitive enough to detect the endogenous level of DNAI1 in complex biological matrix such as lung tissue. METHODS: In this study, a quantitative method combining immunoprecipitation with nanoLC-MS/MS was developed to measure the expression level of human wild-type (WT) DNAI1 protein in lung tissue. To our understanding, it is the first immunoprecipitation (IP)-MS based method for absolute quantitation of DNAI1 protein in lung tissue. The DNAI1 quantitation was achieved through constructing a standard curve with recombinant human WT DNAI1 protein spiked into lung tissue matrix. RESULTS: This method was qualified with high sensitivity and accuracy. The lower limit of quantitation of human DNAI1 was 4 pg/mg tissue. This assay was successfully applied to determine the endogenous level of WT DNAI1 in human lung tissue. CONCLUSIONS: The results clearly demonstrate that the developed assay can accurately quantitate low-abundance WT DNAI1 protein in human lung tissue with high sensitivity, indicating its high potential use in the drug development for DNAI1 mutation-caused PCD therapy.

Deciphering a proteomic signature for the early detection of breast cancer from breast milk: the role of quantitative proteomics.

INTRODUCTION: Breast cancer is one of the most prevalent cancers among women in the United States. Current research regarding breast milk has been focused on the composition and its role in infant growth and development. There is little information about the proteins, immune cells, and epithelial cells present in breast milk which can be indicative of the emergence of BC cells and tumors. AREAS COVERED: We summarize all breast milk studies previously done in our group using proteomics. These studies include 1D-PAGE and 2D-PAGE analysis of breast milk samples, which include within woman and across woman comparisons to identify dysregulated proteins in breast milk and the roles of these proteins in both the development of BC and its diagnosis. Our projected outlook for the use of milk for cancer detection is also discussed. EXPERT OPINION: Analyzing the samples by multiple methods allows one to interrogate a set of samples with various biochemical methods that complement each other, thus providing a more comprehensive proteome. Complementing methods like 1D-PAGE, 2D-PAGE, in-solution digestion and proteomics analysis with PTM-omics, peptidomics, degradomics, or interactomics will provide a better understanding of the dysregulated proteins, but also the modifications or interactions between these proteins.

Deep quantitative proteomics of North American Pacific coast star tunicate (Botryllus schlosseri).

Botryllus schlosseri, is a model marine invertebrate for studying immunity, regeneration, and stress-induced evolution. Conditions for validating its predicted proteome were optimized using nanoElute® 2 deep-coverage LCMS, revealing up to 4930 protein groups and 20,984 unique peptides per sample. Spectral libraries were generated and filtered to remove interferences, low-quality transitions, and only retain proteins with >3 unique peptides. The resulting DIA assay library enabled label-free quantitation of 3426 protein groups represented by 22,593 unique peptides. Quantitative comparisons of single systems from a laboratory-raised with two field-collected populations revealed (1) a more unique proteome in the laboratory-raised population, and (2) proteins with high/low individual variabilities in each population. DNA repair/replication, ion transport, and intracellular signaling processes were distinct in laboratory-cultured colonies. Spliceosome and Wnt signaling proteins were the least variable (highly functionally constrained) in all populations. In conclusion, we present the first colonial tunicate's deep quantitative proteome analysis, identifying functional protein clusters associated with laboratory conditions, different habitats, and strong versus relaxed abundance constraints. These results empower research on B. schlosseri with proteomics resources and enable quantitative molecular phenotyping of changes associated with transfer from in situ to ex situ and from in vivo to in vitro culture conditions.

IQMMA: Efficient MS1 Intensity Extraction Pipeline Using Multiple Feature Detection Algorithms for DDA Proteomics.

One of the key steps in data dependent acquisition (DDA) proteomics is detection of peptide isotopic clusters, also called "features", in MS1 spectra and matching them to MS/MS-based peptide identifications. A number of peptide feature detection tools became available in recent years, each relying on its own matching algorithm. Here, we provide an integrated solution, the intensity-based Quantitative Mix and Match Approach (IQMMA), which integrates a number of untargeted peptide feature detection algorithms and returns the most probable intensity values for the MS/MS-based identifications. IQMMA was tested using available proteomic data acquired for both well-characterized (ground truth) and real-world biological samples, including a mix of Yeast and E. coli digests spiked at different concentrations into the Human K562 digest used as a background, and a set of glioblastoma cell lines. Three open-source feature detection algorithms were integrated: Dinosaur, biosaur2, and OpenMS FeatureFinder. None of them was found optimal when applied individually to all the data sets employed in this work; however, their combined use in IQMMA improved efficiency of subsequent protein quantitation. The software implementing IQMMA is freely available at https://github.com/PostoenkoVI/IQMMA under Apache 2.0 license.

Immuno-Mass Spectrometry Workflow for Quantification of Serum α-Fetoprotein Using Antibody-Immobilized Magnetic Beads and Modified Eluents.

Immuno-mass spectrometry (MS) is a powerful method for the quantitative analysis of low-abundance proteins in biological specimens. In these procedures, collecting specifically and efficiently the target protein antigens from the antigen-antibody complex generated on the surface of nanocarrier beads is crucial and can be performed by hydrolyzing the proteins directly on the beads or after elution. Herein, we optimized the conditions of the immunoaffinity purification via elution using serum α-fetoprotein (AFP) as a model and its specific antibody immobilized covalently on magnetic beads. Antibody-coated beads were incubated with human serum spiked with standard AFP for antigen-antibody reaction. AFP was then eluted from the beads using various eluents, including organic solvents, to optimize the elution conditions. After proteolytically hydrolyzing the eluted protein, stable isotope-labeled standard peptides were added to the hydrolysate to quantify the eluted AFP via liquid chromatography-tandem MS. Using an optimized workflow for quantitative analysis afforded a correlation between the amount of spiked AFP and heavy to light ratios calculated based on peptide ion peak areas, from which an endogenous AFP concentration of 2.3±0.6 ng/mL was determined in normal serum; this is consistent with previous reports using radioimmunoassay methods. The present immuno-MS workflow could apply to the detection and quantitation of other low-abundance biofluid biomarkers.

EpCAM tumor specificity and proteoform patterns in urothelial cancer.

BACKGROUND: The role of the epithelial cell adhesion molecule (EpCAM) in cancer is still unclear. EpCAM cleavage through regulated intramembrane proteolysis results in fragments which interact with both oncogenic and tumor suppressive pathways. Additionally, the EpCAM molecule itself is used as a descriptive therapeutic target in urothelial cancer (UC), while data on its actual tumor specificity remain limited. METHODS: Samples from diagnostic formalin-fixed paraffin-embedded (FFPE) UC tissue and fresh-frozen UC cells were immunoblotted and used for qualitative characterization of five different EpCAM fragments. These expression patterns were quantified across a cohort of 76 samples with 52 UC and 24 normal urothelial samples. Cell viability effects of the extracellular EpEX fragment were assessed in the UC cell lines T24 and HT1376. RESULTS: The proteolytic EpCAM fragments could be identified in clinical FFPE tissue specimens too. Neither overall nor fragment-specific EpCAM expression showed relevant tumor specificity. EpEX and its deglycosylated variant showed an inverse relationship across healthy and tumor tissue with a decrease of deglycosylated EpEX in tumors. However, extracellular EpEX did not show a relevant effect in vitro. CONCLUSIONS: EpCAM should not be regarded as tumor-specific in UC without patient-specific predictive testing. EpCAM fragment patterns indicate cancer-specific changes and could be involved in its complex tumor-biological role.

Bioconjugation of Meldrum's acid activated furan: A detergent compatible assay for protein quantitation.

A simple yet efficient assay for the quantitation of proteins ranging from plasma proteins to purified proteins from whole cell lysate, based on the bioconjugation reaction between protein and Meldrum's acid Activated Furan (MAF) is described. This easy to use, sensitive method is based on the conjugation of amine functionalities present on the protein with MAF to form the corresponding Donor Acceptor Stenhouse Adducts (DASAs) with characteristic absorption in the visible region. The reaction is rapid as well as reproducible and shows a proportionate increase in color change over a broad range of protein concentration. The assay was found to be sensitive up to 0.125 mg/mL concentration of the protein and was compatible with most of the commonly employed detergents and isolation protocols which makes it ideal for the estimation of protein samples containing detergents. Another striking feature of this protocol is its tolerance towards other major interference contributors such as chelating agents, reducing agents, carbohydrates and protease inhibitors.

Tear Samples for Protein Extraction: Comparative Analysis of Schirmer's Test Strip and Microcapillary Tube Methods.

INTRODUCTION: Tear sampling is an attractive option for collecting biological samples in ophthalmology clinics, as it offers a non-invasive alternative to other invasive techniques. However, there are many tear sampling methods still in consideration. This study explores the suitability of Schirmer's test strip and microcapillary tube as reliable and satisfactory methods for tear sampling. METHODS: Tear samples were collected from eight healthy volunteers using the standard Schirmer's test strip method with or without anesthesia and microcapillary tubes. The total tear protein concentrations were analyzed via spectrophotometry and bicinchoninic acid (BCA) protein assay. The protein profile was determined by sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). The optimal wetting length of Schirmer's strip and suitable buffer solutions were compared. Discomfort levels reported by participants and the ease of execution for ophthalmologists were also evaluated. RESULTS: Tear samples exhibited typical protein profiles as shown by SDS-PAGE. The mean total protein obtained from an optimum wetting length of 20 mm using Schirmer's strip without anesthesia in phosphate-buffered saline (PBS) yielded substantial quantities of protein as measured by nanophotometer (220.20 ± 67.43 µg) and the BCA protein assay (210.34 ± 59.46 µg). This method collected a significantly higher quantity of protein compared to the microcapillary tube method (p=0.004) which was much more difficult to standardize. The clinician found it harder to utilize microcapillary tubes, while participants experienced higher insecurity and less discomfort with the microcapillary tube method. PBS used during the tear protein extraction process eluted higher tear protein concentration than ammonium bicarbonate, although the difference was not statistically significant. Using anaesthesia did not ease the sampling procedure substantially and protein quantity was maintained. CONCLUSION: Good quality and quantity of protein from tear samples were extracted with the optimized procedure. Schirmer's strip test in the absence of local anesthesia provided a standard, convenient, and non-invasive method for tear collection.

Chromatographic behaviour of peptides modified with amine-reacting tags for relative protein quantitation in proteomic applications.

Reversed-phase (RP) HPLC separation of peptides labeled with amine-reacting tags for relative protein quantitation (iTRAQ4, iTRAQ8 - isobaric tag for relative and absolute quantitation, TMT - tandem mass tag) has been investigated using large-scale proteomics derived retention datasets. These tags have similar chemistry but use linkers of different length and hydrophobicity, moving the positively charged functional groups further from peptide backbone. Peptide hydrophobicity (RP HPLC retention), on average, increases in the following order: non-labeled < iTRAQ4 < iTRAQ8 < TMT under both low pH (0.1% formic acid) and pH 10 eluent conditions. At the same time, the interplay between hydrophobicity and length of the labeling group drives the deviations from this order. Thus, longer and less hydrophobic iTRAQ8 moiety results in greater retention increase for peptides carrying amphipathic helical structures at the N-terminus. Development of a peptide retention prediction models for these modifications was achieved by predicting correspondent retention shifts ΔHI (hydrophobicity index,% acetonitrile) between unmodified and labelled peptide pairs.

Normics: Proteomic Normalization by Variance and Data-Inherent Correlation Structure.

Several algorithms for the normalization of proteomic data are currently available, each based on a priori assumptions. Among these is the extent to which differential expression (DE) can be present in the dataset. This factor is usually unknown in explorative biomarker screens. Simultaneously, the increasing depth of proteomic analyses often requires the selection of subsets with a high probability of being DE to obtain meaningful results in downstream bioinformatical analyses. Based on the relationship of technical variation and (true) biological DE of an unknown share of proteins, we propose the "Normics" algorithm: Proteins are ranked based on their expression level-corrected variance and the mean correlation with all other proteins. The latter serves as a novel indicator of the non-DE likelihood of a protein in a given dataset. Subsequent normalization is based on a subset of non-DE proteins only. No a priori information such as batch, clinical, or replicate group is necessary. Simulation data demonstrated robust and superior performance across a wide range of stochastically chosen parameters. Five publicly available spike-in and biologically variant datasets were reliably and quantitively accurately normalized by Normics with improved performance compared to standard variance stabilization as well as median, quantile, and LOESS normalizations. In complex biological datasets Normics correctly determined proteins as being DE that had been cross-validated by an independent transcriptome analysis of the same samples. In both complex datasets Normics identified the most DE proteins. We demonstrate that combining variance analysis and data-inherent correlation structure to identify non-DE proteins improves data normalization. Standard normalization algorithms can be consolidated against high shares of (one-sided) biological regulation. The statistical power of downstream analyses can be increased by focusing on Normics-selected subsets of high DE likelihood.

Immuno-MALDI-MS for Accurate Quantitation of Targeted Peptides from Volume-Restricted Samples.

The immuno-MALDI-MS method can be used to quantify low-abundance proteins from clinical samples that offer only a limited amount of material for analysis. An internal standard, in the form of a stable isotope-labeled peptide, is used to ensure reproducible and absolute quantitation. The protocol described here was optimized for the quantitation of AKT1 and AKT2, but we offer instructions on how to adapt the method to target other proteins. The described workflow is compatible with automation via a liquid handling robot for high-throughput applications.

Multiplex LC-MS/MS Testing for Early Detection of Kidney Injury: A Next-Generation Alternative to Conventional Immunoassays?

BACKGROUND: LC-MS/MS has enabled the translation of many novel biomarkers to the clinical laboratory, but its potential for measurement of urinary proteins is still unexplored. In this study we examined the correlation and agreement between immunoassay and LC-MS/MS in the quantitation of kidney injury biomarkers and evaluated the application of technical LC-MS/MS meta-data assessment to ensure test result validity. METHODS: NGAL, IGFBP7, TIMP2, and KIM-1 were quantified in 345 urine samples with one multiplex lab-developed test that combines immunocapture with mass spectrometry read-out and 4 singleplex sandwich-type immunoassays. Assay performance and imprecision were monitored by 2 urine-based quality controls. Ion ratios, signal intensity, and retention time were monitored over all study samples. RESULTS: The LC-MS/MS retention time drift was ≤1.2%, ion ratios were within 20% of the target values at concentrations of >100 pmol/L, and peptides originating from the same protein were in agreement (slopes between 1.03 and 1.41). The interassay CV was between 9.3% and 19.1% for LC-MS/MS analysis and between 4.2% and 10.9% for immunoassay. Direct LC-MS/MS analysis was correlated with immunoassay in the quantitation of NGAL (r = 0.93; range: 0.01-37 nmol/L), IGFBP7 (r = 0.80; range: 0.01-2.6 nmol/L), TIMP2 (r = 0.85; range: 0.01-6.3 nmol/L), and KIM-1 (r = 0.70; range 0.01-0.4 nmol/L), but the analytical methodologies differed in measurands and calibration strategies. CONCLUSIONS: LC-MS/MS is explored as a next-generation technology for multiplex urinary protein measurement. It has great potential to overcome nonselectivity and lack of standardization because of its capability of directly measuring well-defined molecular proteins.

Recent advances in isobaric labeling and applications in quantitative proteomics.

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.