Highly Accurate and Robust Absolute Quantification of Target Proteins in Formalin-Fixed Paraffin-Embedded (FFPE) Tissues by LC-MS.

Accurate, absolute liquid chromatography-mass spectrometry (LC-MS)-based quantification of target proteins in formalin-fixed paraffin-embedded (FFPE) tissues would greatly expand sample availability for pharmaceutical/clinical investigations but remains challenging owing to the following issues: (i) efficient/quantitative recovery of target signature peptides from FFPE tissues is essential but an optimal procedure for targeted, absolute quantification is lacking; (ii) most FFPE samples are long-term-stored; severe immunohistochemistry (IHC) signal losses of target proteins during storage were widely reported, while the effect of storage on LC-MS-based methods was unknown; and (iii) the proper strategy to prepare calibration/quality-control samples to ensure accurate targeted protein analysis in FFPE tissues remained elusive. Using targeted quantification of monoclonal antibody (mAb), antigen, and 40 tissue markers in FFPE tissues as a model system, we extensively investigate those issues and develope an LC-MS-based strategy enabling accurate and precise targeted protein quantification in FFPE samples. First, we demonstrated a surfactant cocktail-based procedure (f-SEPOD), providing high/reproducible recovery of target signature peptides from FFPE tissues. Second, a heat-accelerated degradation study within a roughly estimated 5 year storage period recapitulated the loss of protein IHC signals while LC-MS signals of all targets remained constant. This indicates that the storage of FFPE tissues mainly causes decreased immunoreactivity but unlikely chemical degradation of proteins, which strongly suggests that the storage of FFPE tissues does not cause significant quantitative bias for LC-MS-based methods. Third, while a conventional spike-and-extract approach for calibration caused substantial negative biases, a novel approach, using FFPE-treated calibration standards, enabled accurate and precise quantification. With the pipeline, we conducted the first-ever pharmacokinetics measurement of mAb and its target in FFPE tissues, where time courses by FFPE vs fresh tissues showed excellent correlation.

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.

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.

Current LC-MS-based strategies for characterization and quantification of antibody-drug conjugates.

The past few years have witnessed enormous progresses in the development of antibody-drug conjugates (ADCs). Consequently, comprehensive analysis of ADCs in biological systems is critical in supporting discovery, development and evaluation of these agents. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a promising and versatile tool for ADC analysis across a wide range of scenarios, owing to its multiplexing ability, rapid method development, as well as the capability of analyzing a variety of targets ranging from small-molecule payloads to the intact protein with a high, molecular resolution. However, despite this tremendous potential, challenges persist due to the high complexity in both the ADC molecules and the related biological systems. This review summarizes the up-to-date LC-MS-based strategies in ADC analysis and discusses the challenges and opportunities in this rapidly-evolving field.

High-Throughput, Sensitive LC-MS Quantification of Biotherapeutics and Biomarkers Using Antibody-Free, Peptide-Level, Multiple-Mechanism Enrichment via Strategic Regulation of pH and Ionic and Solvent Strengths.

Sensitive and high-throughput measurement of biotherapeutics and biomarkers in plasma and tissues is critical for protein-drug development. Enrichment of target signature peptide (SP) after sample digestion permits sensitive LC-MS-based protein quantification and carries several prominent advantages over protein-level enrichment; however, developing high-quality antipeptide antibodies is challenging. Here we describe a novel, antibody-free, peptide-level-enrichment technique enabling high-throughput, sensitive, and robust quantification of proteins in biomatrices, by highly selective removal of matrix peptides and components via cation-exchange (CX) reversed-phase (RP) SPE with strategically regulated pH and ionic and organic strengths. Multiple-mechanism washing and elution achieved highly selective separation despite the low plate number of the SPE cartridge. We first investigated the adsorption-desorption behaviors of peptides on CX-RP sorbent and the coexisting, perplexing effects of pH, and ionic and organic strengths on the selectivity for SP enrichment, which has not been previously characterized. We demonstrated that the selectivity for separating target SPs from matrix peptides was closely associated with buffer pH relative to the pI of the SP, and pH values of pI - 2, pI, and pI + 2 respectively provided exceptional specificity for the ionic wash, the hydrophobic wash, and selective elution. Furthermore, desorption of peptides from the mixed-mode sorbent showed exponential and linear dependence, respectively, on organic-solvent percentage and salt percentage. On the basis of these findings, we established a streamlined procedure for rapid and robust method development. Quantification of biotherapeutics, targets, and biomarkers in plasma and tissues was used as the model system. Selective enrichment of target SPs was achieved along with elimination of 87-95% of matrix peptides, which improved the LOQ by 20-fold (e.g., 2 ng per gram of tissue). Application was demonstrated by sensitive quantification of time courses of mAb (T84.66) and target (CEA) in plasma and tumor tissues from a low-dose mouse PK study. For the first time, down-regulation of membrane-associated antigen following mAb treatment was observed. The CX-RP enrichment is robust, high-throughput, and universally applicable and thus is highly valuable for ultrasensitive, large-scale measurement of target protein in plasma and tissues.