Comprehensive micro-scaled proteome and phosphoproteome characterization of archived retrospective cancer repositories

Inferring kinase activity from phosphoproteomic data: Tool comparison and recent applications

Aberrant cellular signaling pathways are a hallmark of cancer and other diseases. One of the most important signaling mechanisms involves protein phosphorylation/dephosphorylation. Protein phosphorylation is catalyzed by protein kinases, and over 530 protein kinases have been identified in the human genome. Aberrant kinase activity is one of the drivers of tumorigenesis and cancer progression and results in altered phosphorylation abundance of downstream substrates. Upstream kinase activity can be inferred from the global collection of phosphorylated substrates. Mass spectrometry-based phosphoproteomic experiments nowadays routinely allow identification and quantitation of >10k phosphosites per biological sample. This substrate phosphorylation footprint can be used to infer upstream kinase activities using tools like Kinase Substrate Enrichment Analysis (KSEA), Posttranslational Modification Substrate Enrichment Analysis (PTM-SEA), and Integrative Inferred Kinase Activity Analysis (INKA). Since the topic of kinase activity inference is very active with many new approaches reported in the past 3 years, we would like to give an overview of the field. In this review, an inventory of kinase activity inference tools, their underlying algorithms, statistical frameworks, kinase-substrate databases, and user-friendliness is presented. The most widely-used tools are compared in-depth. Subsequently, recent applications of the tools are described focusing on clinical tissues and hematological samples. Two main application areas for kinase activity inference tools can be discerned. (1) Maximal biological insights can be obtained from large data sets with group comparisons using multiple complementary tools (e.g., PTM-SEA and KSEA or INKA). (2) In the oncology context where personalized treatment requires analysis of single samples, INKA for example, has emerged as tool that can prioritize actionable kinases for targeted inhibition.

Novel FFPE proteomics method suggests prolactin induced protein as hormone induced cytoskeleton remodeling spatial biomarker

Robotically assisted proteomics provides insights into the regulation of multiple proteins achieving excellent spatial resolution. However, developing an effective method for spatially resolved quantitative proteomics of formalin fixed paraffin embedded tissue (FFPE) in an accessible and economical manner remains challenging. We introduce non-robotic In-insert FFPE proteomics approach, combining glass insert FFPE tissue processing with spatial quantitative data-independent mass spectrometry (DIA). In-insert approach identifies 450 proteins from a 5 µm thick breast FFPE tissue voxel with 50 µm lateral dimensions covering several tens of cells. Furthermore, In-insert approach associated a keratin series and moesin (MOES) with prolactin-induced protein (PIP) indicating their prolactin and/or estrogen regulation. Our data suggest that PIP is a spatial biomarker for hormonally triggered cytoskeletal remodeling, potentially useful for screening hormonally affected hotspots in breast tissue. In-insert proteomics represents an alternative FFPE processing method, requiring minimal laboratory equipment and skills to generate spatial proteotype repositories from FFPE tissue.

Proteomic Profiles of Human Arterioles Isolated From Fresh Adipose Tissue or Following Overnight Storage

Arterioles are key determinants of the total peripheral vascular resistance, which, in turn, is a key determinant of arterial blood pressure. However, the amount of protein available from one isolated human arteriole may be less than 5 μg, making proteomic analysis challenging. In addition, obtaining human arterioles requires manual dissection of unfrozen clinical specimens. This limits its feasibility, especially for powerful multicenter clinical studies in which clinical specimens need to be shipped overnight to a research laboratory for arteriole isolation. We performed a study to address low-input, test overnight tissue storage and develop a reference human arteriolar proteomic profile. In tandem mass tag proteomics, use of a booster channel consisting of human induced pluripotent stem cell-derived endothelial and vascular smooth muscle cells (1:5 ratio) increased the number of proteins detected in a human arteriole segment with a false discovery rate of <0.01 from 1051 to more than 3000. The correlation coefficient of proteomic profile was similar between replicate arterioles isolated freshly, following cold storage, or before and after the cold storage (1-way analysis of variance; P = .60). We built a human arteriolar proteomic profile consisting of 3832 proteins based on the analysis of 12 arteriole samples from 3 subjects. Of 1945 blood pressure-relevant proteins that we curated, 476 (12.5%) were detected in the arteriolar proteome, which was a significant overrepresentation (χ2 test; P < .05). These findings demonstrate that proteomic analysis is feasible with arterioles isolated from human adipose tissue following cold overnight storage and provide a reference human arteriolar proteome profile highly valuable for studies of arteriole-related traits.

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in both normal and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 μm and the largest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in terms of identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables to identify protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Optimized whole-genome sequencing workflow for tumor diagnostics in routine pathology practice

Two decades after the genomics revolution, oncology is rapidly transforming into a genome-driven discipline, yet routine cancer diagnostics is still mainly microscopy based, except for tumor type-specific predictive molecular tests. Pathology laboratories struggle to quickly validate and adopt biomarkers identified by genomics studies of new targeted therapies. Consequently, clinical implementation of newly approved biomarkers suffers substantial delays, leading to unequal patient access to these therapies. Whole-genome sequencing (WGS) can successfully address these challenges by providing a stable molecular diagnostic platform that allows detection of a multitude of genomic alterations in a single cost-efficient assay and facilitating rapid implementation, as well as by the development of new genomic biomarkers. Recently, the Whole-genome sequencing Implementation in standard Diagnostics for Every cancer patient (WIDE) study demonstrated that WGS is a feasible and clinically valid technique in routine clinical practice with a turnaround time of 11 workdays. As a result, WGS was successfully implemented at the Netherlands Cancer Institute as part of routine diagnostics in January 2021. The success of implementing WGS has relied on adhering to a comprehensive protocol including recording patient information, sample collection, shipment and storage logistics, sequencing data interpretation and reporting, integration into clinical decision-making and data usage. This protocol describes the use of fresh-frozen samples that are necessary for WGS but can be challenging to implement in pathology laboratories accustomed to using formalin-fixed paraffin-embedded samples. In addition, the protocol outlines key considerations to guide uptake of WGS in routine clinical care in hospitals worldwide.

Biomarker Identification through Proteomics in Colorectal Cancer

Colorectal cancer (CRC) is a devastating disease that ranks third in diagnosis and as the second leading cause of cancer-related deaths. The early detection of CRC has been shown to be the most effective strategy to improve treatment outcomes and patient survival. Therefore, current lines of research focus on the development of reliable diagnostic tools. Targeted therapies, in combination with standard chemotherapy and immune checkpoint inhibitors, have emerged as promising treatment protocols in CRC. However, their effectiveness is linked to the molecular characteristics of each patient. The importance of discovering biomarkers that help predict response to therapies and assess prognosis is evident as they allow for a fundamental step towards personalized care and successful treatments. Among the ongoing efforts to identify them, mass spectrometry-based translational proteomics presents itself as a unique opportunity as it enables the discovery and application of protein biomarkers that may revolutionize the early detection and treatment of CRC. Our objective is to show the most recent studies focused on the identification of CRC-related protein markers, as well as to provide an updated view of advances in the field of proteomics and cancer.

LC-MS bioanalysis of protein biomarkers and protein therapeutics in formalin-fixed paraffin-embedded tissue specimens

Formalin-fixed paraffin-embedded (FFPE) is a form of preservation and preparation for biopsy specimens. FFPE tissue specimens are readily available as part of oncology studies because they are often collected for disease diagnosis or confirmation. FFPE tissue specimens could be extremely useful for retrospective studies on protein biomarkers because the samples preserved in FFPE blocks could be stable for decades. However, LC-MS bioanalysis of FFPE tissues poses significant challenges. In this Perspective, we review the benefits and recent developments in LC-MS approach for targeted protein biomarker and protein therapeutic analysis using FFPE tissues and their clinical and translational applications. We believe that LC-MS bioanalysis of protein biomarkers in FFPE tissue specimens represents a great potential for its clinical applications.

Accurate Detection of Multiple Tumor Mutations in Formalin-Fixed Paraffin-Embedded Tissues by Coupling Sequence Artifacts Elimination and Mutation Enrichment With MeltArray

Formalin-fixed paraffin-embedded (FFPE) tissues are the primary source of DNA for companion diagnostics (CDx) of cancers. Degradation of FFPE tissue DNA and inherent tumor heterogeneity constitute serious challenges in current CDx assays. To address these limitations, we introduced sequence artifact elimination and mutation enrichment to MeltArray, a highly multiplexed PCR approach, to establish an integrated protocol that provides accuracy, ease of use, and rapidness. Using PIK3CA mutations as a model, we established a MeltArray protocol that could eliminate sequence artifacts completely and enrich mutations from 23.5- to 59.4-fold via a single-reaction pretreatment step comprising uracil-DNA-glycosylase excision and PCR clamping. The entire protocol could identify 13 PIK3CA hotspot mutations of 0.05% to 0.5% mutant allele fractions within 5 hours. Evaluation of 106 breast cancer and 40 matched normal FFPE tissue samples showed that all 47 PIK3CA mutant samples were from the cancer tissue, and no false-positive results were detected in the normal samples. Further evaluation of 105 colorectal and 40 matched normal FFPE tissue samples revealed that 11 PIK3CA mutants were solely from the cancer sample. The detection results of our protocol were consistent with those of the droplet digital PCR assays that underwent sequence artifact elimination. Of the 60 colorectal samples with next-generation sequencing results, the MeltArray protocol detected 2 additional mutant samples with low mutant allele fractions. We conclude that the new protocol provides an improved alternative to current CDx assays for detecting tumor mutations in FFPE tissue DNA.

mROS‑calcium feedback loop promotes lethal ventricular arrhythmias and sudden cardiac death in early myocardial ischemia

Lethal ventricular arrhythmia‑sudden cardiac death (LVA‑SCD) occurs frequently during the early stage of myocardial ischemia (MI). However, the mechanism underlying higher LVA‑SCD incidence is still poorly understood. The present study aimed to explore the role of mitochondrial reactive oxygen species (mROS) and Ca2+ crosstalk in promoting LVA‑SCD in early MI. RyR2 S2814A mice and their wild‑type littermates were used. MitoTEMPO was applied to scavenge mitochondrial ROS (mROS). Mice were subjected to severe MI and the occurrence of LVA‑SCD was evaluated. Levels of mitochondrial ROS and calcium (mitoCa2+), cytosolic ROS (cytoROS), and calcium (cytoCa2+), RyR2 Ser‑2814 phosphorylation, CaMKII Met‑282 oxidation, mitochondrial membrane potential (MMP), and glutathione/oxidized glutathione (GSH/GSSG) ratio in the myocardia were detected. Dynamic changes in mROS after hypoxia were investigated using H9c2 cells. Moreover, the myocardial phosphoproteome was analyzed to explore the related mechanisms facilitating mROS‑Ca2+ crosstalk and LVA‑SCD. There was a high incidence (~33.9%) of LVA‑SCD in early MI. Mice who underwent SCD displayed notably elevated levels of myocardial ROS and mROS, and the latter was validated in H9c2 cells. These mice also demonstrated overloads of cytoplasmic and mitochondrial Ca2+, decreased MMP and reduced GSH/GSSG ratio, upregulated RyR2‑S2814 phosphorylation and CaMKII‑M282 oxidation and transient hyperphosphorylation of mitochondrial proteomes in the myocardium. mROS‑specific scavenging by a mitochondria‑targeted antioxidant agent (MitoTEMPO) corrected these SCD‑induced alterations. S2814A mice with a genetically inactivated CaMKII phosphorylation site in RyR2 exhibited decreased overloads in cytoplasmic and mitochondrial Ca2+ and demonstrated similar effects as MitoTEMPO to correct SCD‑induced changes and prevent SCD post‑MI. The data confirmed crosstalk between mROS and Ca2+ in promoting LVA‑SCD. Therefore, we provided evidence that there is a higher incidence of LVA‑SCD in early MI, which may be attributed to a positive feedback loop between mROS and Ca2+ imbalance.

Metastatic cells exploit their stoichiometric niche in the network of cancer ecosystems

Metastasis is a nonrandom process with varying degrees of organotropism-specific source-acceptor seeding. Understanding how patterns between source and acceptor tumors emerge remains a challenge in oncology. We hypothesize that organotropism results from the macronutrient niche of cells in source and acceptor organs. To test this, we constructed and analyzed a metastatic network based on 9303 records across 28 tissue types. We found that the topology of the network is nested and modular with scale-free degree distributions, reflecting organotropism along a specificity/generality continuum. The variation in topology is significantly explained by the matching of metastatic cells to their stoichiometric niche. Specifically, successful metastases are associated with higher phosphorus content in the acceptor compared to the source organ, due to metabolic constraints in proliferation crucial to the invasion of new tissues. We conclude that metastases are codetermined by processes at source and acceptor organs, where phosphorus content is a limiting factor orchestrating tumor ecology.

TMT-Based Proteomics Analysis Revealed the Protein Changes in Perirenal Fat from Obese Rabbits

Obesity has become increasingly prevalent in recent years, and there is a need for a deeper understanding of the complex pathogenesis underlying the obesity condition. Therefore, the objective of this study was to investigate how a high-fat diet (HFD) affects protein expression in a female-rabbit model compared to a standard normal-diet group (SND), to gain comprehensive insights into the molecular mechanisms involved in obesity. To achieve this objective, a tandem mass tag (TMT)-based quantitative proteomics analysis was conducted to examine the molecular changes occurring in the white adipose tissue (WAT) from the HFD and SND groups. The sequencing results identified a total of 4215 proteins, among which 151 proteins exhibited significant differential expression. Specifically, there were 85 upregulated proteins and 66 downregulated proteins in the HFD group compared to the SND group. Further analysis of these differentially expressed proteins (DEPs) revealed their involvement in crucial biological processes, including energy metabolism, hormonal regulation, and inflammatory response. In conclusion, this study sheds light on the impact of HFD on protein expression in a female-rabbit model, providing new insights into the molecular mechanisms underlying obesity and the associated metabolic disorders.

Proteomic analyses identify HK1 and ATP5A to be overexpressed in distant metastases of lung adenocarcinomas compared to matched primary tumors

Lung cancer is the leading cause of cancer-related deaths worldwide with lung adenocarcinoma (LUAD) being the most common type. Genomic studies of LUAD have advanced our understanding of its tumor biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD are still insufficiently explored. The prognosis for lung cancer patients is still mostly determined by the stage of disease at the time of diagnosis. Focusing on late-stage metastatic LUAD with poor prognosis, we compared the proteomic profiles of primary tumors and matched distant metastases to identify relevant and potentially druggable differences. We performed high-performance liquid chromatography (HPLC) and electrospray ionization tandem mass spectrometry (ESI-MS/MS) on a total of 38 FFPE (formalin-fixed and paraffin-embedded) samples. Using differential expression analysis and unsupervised clustering we identified several proteins that were differentially regulated in metastases compared to matched primary tumors. Selected proteins (HK1, ATP5A, SRI and ARHGDIB) were subjected to validation by immunoblotting. Thereby, significant differential expression could be confirmed for HK1 and ATP5A, both upregulated in metastases compared to matched primary tumors. Our findings give a better understanding of tumor progression and metastatic spreads in LUAD but also demonstrate considerable inter-individual heterogeneity on the proteomic level.

A framework for ultra-low-input spatial tissue proteomics

Spatial proteomics combining microscopy-based cell phenotyping with ultrasensitive mass-spectrometry-based proteomics is an emerging and powerful concept to study cell function and heterogeneity in (patho)physiology. However, optimized workflows that preserve morphological information for phenotype discovery and maximize proteome coverage of few or even single cells from laser microdissected tissue are currently lacking. Here, we report a robust and scalable workflow for the proteomic analysis of ultra-low-input archival material. Benchmarking in murine liver resulted in up to 2,000 quantified proteins from single hepatocyte contours and nearly 5,000 proteins from 50-cell regions. Applied to human tonsil, we profiled 146 microregions including T and B lymphocyte niches and quantified cell-type-specific markers, cytokines, and transcription factors. These data also highlighted proteome dynamics within activated germinal centers, illuminating sites undergoing B cell proliferation and somatic hypermutation. This approach has broad implications in biomedicine, including early disease profiling and drug target and biomarker discovery. A record of this paper's transparent peer review process is included in the supplemental information.

Routine Workflow of Spatial Proteomics on Micro-formalin-Fixed Paraffin-Embedded Tissues

In the era of single-cell biology, spatial proteomics has emerged as an important frontier. However, it still faces several challenges in technology. Formalin-fixed paraffin-embedded (FFPE) tissues are an important material in spatial proteomics, in which fixed tissues are excised using laser capture microdissection (LCM), followed by protein identification with mass spectrometry. For a satisfied spatial proteomics upon FFPE tissues, the excision area is expected to be as small as possible, and the identified proteins are countered upon as much as possible. For a general laboratory for spatial proteomics, a routine workflow is required, not relying on any special device, and is easily operating. In view of these challenges in technology, we initiated a technology evaluation throughout the entire procedure of proteomic analysis with micro-FFPE tissues. In contrast to the protocols reported previously, several innovations in technology were proposed and conducted, such as removal of destaining, decross-linking with "hang-down", solution simplification for peptide generation and balancing to excision area, and capture rate of micro-FFPE tissues. After optimization of all the necessary steps, a routine workflow was established, in which the minimized area for protein identification was 0.002 mm2, while the excision area for a consistent proteomic analysis was 0.05 mm2. Using the developed workflow and collecting the micro-FFPE tissues continuously, for the first time, a spatial proteomic atlas of mouse brain was preliminarily constructed, which exhibited the typical characteristics of spatial-dependent protein abundance and functional enrichment.

Unbiased Phosphoproteome Mining Reveals New Functional Sites of Metabolite-Derived PTMs Involved in MASLD Development

Post-translational modifications (PTMs) of proteins are paramount in health and disease. Phosphoproteome analysis by enrichment techniques is becoming increasingly attractive for biomedical research. Recent findings show co-enrichment of other phosphate-containing biologically relevant PTMs, but these results were obtained by closed searches focused on the modifications sought. Open searches are a breakthrough in high-throughput PTM analysis (OS-PTM), identifying practically all PTMs detectable by mass spectrometry, even unknown ones, with their modified sites, in a hypothesis-free and deep manner. Here we reanalyze liver phosphoproteome by OS-PTM, demonstrating its extremely complex nature. We found extensive Lys glycerophosphorylations (pgK), as well as modification with glycerylphosphorylethanolamine on Glu (gpetE) and flavin mononucleotide on His (fmnH). The functionality of these metabolite-derived PTMs is demonstrated during metabolic dysfunction-associated steatotic liver disease (MASLD) development in mice. MASLD elicits specific alterations in pgK, epgE and fmnH in the liver, mainly on glycolytic enzymes and mitochondrial proteins, suggesting an increase in glycolysis and mitochondrial ATP production from the early insulin-resistant stages. Thus, we show new possible mechanisms based on metabolite-derived PTMs leading to intrahepatic lipid accumulation during MASLD development and reinforce phosphoproteome enrichment as a valuable tool with which to study the functional implications of a variety of low-abundant phosphate-containing PTMs in cell physiology.

Frequent ZNF217 mutations lead to transcriptional deregulation of interferon signal transduction via altered chromatin accessibility in B cell lymphoma

Recent exome-wide studies discovered frequent somatic mutations in the epigenetic modifier ZNF217 in primary mediastinal B cell lymphoma (PMBCL) and related disorders. As functional consequences of ZNF217 alterations remain unknown, we comprehensively evaluated their impact in PMBCL. Targeted sequencing identified genetic lesions affecting ZNF217 in 33% of 157 PMBCL patients. Subsequent gene expression profiling (n = 120) revealed changes in cytokine and interferon signal transduction in ZNF217-aberrant PMBCL cases. In vitro, knockout of ZNF217 led to changes in chromatin accessibility interfering with binding motifs for crucial lymphoma-associated transcription factors. This led to disturbed expression of interferon-responsive and inflammation-associated genes, altered cell behavior, and aberrant differentiation. Mass spectrometry demonstrates that ZNF217 acts within a histone modifier complex containing LSD1, CoREST and HDAC and interferes with H3K4 methylation and H3K27 acetylation. Concluding, our data suggest non-catalytic activity of ZNF217, which directs histone modifier complex function and controls B cell differentiation-associated patterns of chromatin structure.

Benefits of FAIMS to Improve the Proteome Coverage of Deteriorated and/or Cross-Linked TMT 10-Plex FFPE Tissue and Plasma-Derived Exosomes Samples

The proteome characterization of complex, deteriorated, or cross-linked protein mixtures as paired clinical FFPE or exosome samples isolated from low plasma volumes (250 µL) might be a challenge. In this work, we aimed at investigating the benefits of FAIMS technology coupled to the Orbitrap Exploris 480 mass spectrometer for the TMT quantitative proteomics analyses of these complex samples in comparison to the analysis of protein extracts from cells, frozen tissue, and exosomes isolated from large volume plasma samples (3 mL). TMT experiments were performed using a two-hour gradient LC-MS/MS with or without FAIMS and two compensation voltages (CV = -45 and CV = -60). In the TMT experiments of cells, frozen tissue, or exosomes isolated from large plasma volumes (3 mL) with FAIMS, a limited increase in the number of identified and quantified proteins accompanied by a decrease in the number of peptides identified and quantified was observed. However, we demonstrated here a noticeable improvement (>100%) in the number of peptide and protein identifications and quantifications for the plasma exosomes isolated from low plasma volumes (250 µL) and FFPE tissue samples in TMT experiments with FAIMS in comparison to the LC-MS/MS analysis without FAIMS. Our results highlight the potential of mass spectrometry analyses with FAIMS to increase the depth into the proteome of complex samples derived from deteriorated, cross-linked samples and/or those where the material was scarce, such as FFPE and plasma-derived exosomes from low plasma volumes (250 µL), which might aid in the characterization of their proteome and proteoforms and in the identification of dysregulated proteins that could be used as biomarkers.

Oncogenic Proteomics Approaches for Translational Research and HIV-Associated Malignancy Mechanisms

Recent advances in the field of proteomics have allowed extensive insights into the molecular regulations of the cell proteome. Specifically, this allows researchers to dissect a multitude of signaling arrays while targeting for the discovery of novel protein signatures. These approaches based on data mining are becoming increasingly powerful for identifying both potential disease mechanisms as well as indicators for disease progression and overall survival predictive and prognostic molecular markers for cancer. Furthermore, mass spectrometry (MS) integrations satisfy the ongoing demand for in-depth biomarker validation. For the purpose of this review, we will highlight the current developments based on MS sensitivity, to place quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data for future applications in cancer precision medicine. We will also discuss malignancies associated with oncogenic viruses such as Acquire Immunodeficiency Syndrome (AIDS) and suggest novel mechanisms behind this phenomenon. Human Immunodeficiency Virus type-1 (HIV-1) proteins are known to be oncogenic per se, to induce oxidative and endoplasmic reticulum stresses, and to be released from the infected or expressing cells. HIV-1 proteins can act alone or in collaboration with other known oncoproteins, which cause the bulk of malignancies in people living with HIV-1 on ART.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.

Hybrid-DIA: intelligent data acquisition integrates targeted and discovery proteomics to analyze phospho-signaling in single spheroids

Achieving sufficient coverage of regulatory phosphorylation sites by mass spectrometry (MS)-based phosphoproteomics for signaling pathway reconstitution is challenging, especially when analyzing tiny sample amounts. To address this, we present a hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) that combines targeted and discovery proteomics through an Application Programming Interface (API) to dynamically intercalate DIA scans with accurate triggering of multiplexed tandem mass spectrometry (MSx) scans of predefined (phospho)peptide targets. By spiking-in heavy stable isotope labeled phosphopeptide standards covering seven major signaling pathways, we benchmark hybrid-DIA against state-of-the-art targeted MS methods (i.e., SureQuant) using EGF-stimulated HeLa cells and find the quantitative accuracy and sensitivity to be comparable while hybrid-DIA also profiles the global phosphoproteome. To demonstrate the robustness, sensitivity, and biomedical potential of hybrid-DIA, we profile chemotherapeutic agents in single colon carcinoma multicellular spheroids and evaluate the phospho-signaling difference of cancer cells in 2D vs 3D culture.

MS-based proteomics of body fluids: The end of the beginning

Accurate biomarkers are a crucial and necessary precondition for precision medicine, yet existing ones are often unspecific and new ones have been very slow to enter the clinic. Mass spectrometry (MS)-based proteomics excels by its untargeted nature, specificity of identification and quantification making it an ideal technology for biomarker discovery and routine measurement. It has unique attributes compared to affinity binder technologies, such as OLINK Proximity Extension Assay and SOMAscan. In a previous review we described technological and conceptual limitations that had held back success (Geyer et al., 2017). We proposed a 'rectangular strategy' to better separate true biomarkers by minimizing cohort-specific effects. Today, this has converged with advances in MS-based proteomics technology, such as increased sample throughput, depth of identification and quantification. As a result, biomarker discovery studies have become more successful, producing biomarker candidates that withstand independent verification and, in some cases, already outperform state-of-the-art clinical assays. We summarize developments over the last years, including the benefits of large and independent cohorts, which are necessary for clinical acceptance. They are also required for machine learning or deep learning. Shorter gradients, new scan modes and multiplexing are about to drastically increase throughput, cross-study integration, and quantification, including proxies for absolute levels. We have found that multi-protein panels are inherently more robust than current single analyte tests and better capture the complexity of human phenotypes. Routine MS measurement in the clinic is fast becoming a viable option. The full set of proteins in a body fluid (global proteome) is the most important reference and the best process control. Additionally, it increasingly has all the information that could be obtained from targeted analysis although the latter may be the most straightforward way to enter into regular use. Many challenges remain, not least of a regulatory and ethical nature, but the outlook for MS-based clinical applications has never been brighter.

An overview of glioblastoma multiforme and temozolomide resistance: can LC-MS-based proteomics reveal the fundamental mechanism of temozolomide resistance?

Glioblastoma multiforme (GBM) is a primary type of lethal brain tumor. Over the last two decades, temozolomide (TMZ) has remained the primary chemotherapy for GBM. However, TMZ resistance in GBM constitutes an underlying factor contributing to high rates of mortality. Despite intense efforts to understand the mechanisms of therapeutic resistance, there is currently a poor understanding of the molecular processes of drug resistance. For TMZ, several mechanisms linked to therapeutic resistance have been proposed. In the past decade, significant progress in the field of mass spectrometry-based proteomics has been made. This review article discusses the molecular drivers of GBM, within the context of TMZ resistance with a particular emphasis on the potential benefits and insights of using global proteomic techniques.

The Cytidine N-Acetyltransferase NAT10 Participates in Peripheral Nerve Injury-Induced Neuropathic Pain by Stabilizing SYT9 Expression in Primary Sensory Neurons

RNA N4-acetylcytidine (ac4C) modification is increasingly recognized as an important layer of gene regulation; however, the involvement of ac4C in pain regulation has not been studied. Here, we report that N-acetyltransferase 10 protein (NAT10; the only known ac4C "writer") contributes to the induction and development of neuropathic pain in an ac4C-dependent manner. Peripheral nerve injury increases the levels of NAT10 expression and overall ac4C in injured dorsal root ganglia (DRGs). This upregulation is triggered by the activation of upstream transcription factor 1 (USF1), a transcription factor that binds to the Nat10 promoter. Knock-down or genetic deletion of NAT10 in the DRG abolishes the gain of ac4C sites in Syt9 mRNA and the augmentation of SYT9 protein, resulting in a marked antinociceptive effect in nerve-injured male mice. Conversely, mimicking NAT10 upregulation in the absence of injury evokes the elevation of Syt9 ac4C and SYT9 protein and induces the genesis of neuropathic-pain-like behaviors. These findings demonstrate that USF1-governed NAT10 regulates neuropathic pain by targeting Syt9 ac4C in peripheral nociceptive sensory neurons. Our findings establish NAT10 as a critical endogenous initiator of nociceptive behavior and a promising new target for treating neuropathic pain.SIGNIFICANCE STATEMENT The cytidine N4-acetylcytidine (ac4C), a new epigenetic RNA modification, is crucial for the translation and stability of mRNA, but its role for chronic pain remains unclear. Here, we demonstrate that N-acetyltransferase 10 (NAT10) acts as ac4C N-acetyltransferase and plays an important role in the development and maintenance of neuropathic pain. NAT10 was upregulated via the activation of the transcription factor upstream transcription factor 1 (USF1) in the injured dorsal root ganglion (DRG) after peripheral nerve injury. Since pharmacological or genetic deleting NAT10 in the DRG attenuated the nerve injury-induced nociceptive hypersensitivities partially through suppressing Syt9 mRNA ac4C and stabilizing SYT9 protein level, NAT10 may serve as an effective and novel therapeutic target for neuropathic pain.

ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues

Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for retrospective studies, but protein extraction and subsequent sample processing steps have been shown to be challenging for mass spectrometry (MS) analysis. Streamlined high-throughput sample preparation workflows are essential for efficient peptide extraction from complex clinical specimens such as fresh frozen tissues or FFPE. Overall, proteome analysis has gained significant improvements in the instrumentation, acquisition methods, sample preparation workflows, and analysis pipelines, yet even the most recent FFPE workflows remain complex and are not readily scalable. Here, we present an optimized workflow for automated sonication-free acid-assisted proteome (ASAP) extraction from FFPE sections. ASAP enables efficient protein extraction from FFPE specimens, achieving similar proteome coverage as established methods using expensive sonicators, resulting in reduced sample processing time. The broad applicability of ASAP on archived pediatric tumor FFPE specimens resulted in high-quality data with increased proteome coverage and quantitative reproducibility. Our study demonstrates the practicality and superiority of the ASAP workflow as a streamlined, time- and cost-effective pipeline for high-throughput FFPE proteomics of clinical specimens.

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.

Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps

The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography-mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them.

Biomarker Analysis of Formalin-Fixed Paraffin-Embedded Clinical Tissues Using Proteomics

The relatively recent developments in mass spectrometry (MS) have provided novel opportunities for this technology to impact modern medicine. One of those opportunities is in biomarker discovery and diagnostics. Key developments in sample preparation have enabled a greater range of clinical samples to be characterized at a deeper level using MS. While most of these developments have focused on blood, tissues have also been an important resource. Fresh tissues, however, are difficult to obtain for research purposes and require significant resources for long-term storage. There are millions of archived formalin-fixed paraffin-embedded (FFPE) tissues within pathology departments worldwide representing every possible tissue type including tumors that are rare or very small. Owing to the chemical technique used to preserve FFPE tissues, they were considered intractable to many newer proteomics techniques and primarily only useful for immunohistochemistry. In the past couple of decades, however, researchers have been able to develop methods to extract proteins from FFPE tissues in a form making them analyzable using state-of-the-art technologies such as MS and protein arrays. This review will discuss the history of these developments and provide examples of how they are currently being used to identify biomarkers and diagnose diseases such as cancer.

Increasing the throughput of sensitive proteomics by plexDIA

Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completeness, reducing missing data more than twofold across samples. Applied to single human cells, plexDIA quantified ~1,000 proteins per cell and achieved 98% data completeness within a plexDIA set while using ~5 minutes of active chromatography per cell. These results establish a general framework for increasing the throughput of sensitive and quantitative protein analysis.

Proteomics separates adult-type diffuse high-grade gliomas in metabolic subgroups independent of 1p/19q codeletion and across IDH mutational status

High-grade adult-type diffuse gliomas are malignant neuroepithelial tumors with poor survival rates in combined chemoradiotherapy. The current WHO classification is based on IDH1/2 mutational and 1p/19q codeletion status. Glioma proteome alterations remain undercharacterized despite their promise for a better molecular patient stratification and therapeutic target identification. Here, we use mass spectrometry to characterize 42 formalin-fixed, paraffin-embedded (FFPE) samples from IDH-wild-type (IDHwt) gliomas, IDH-mutant (IDHmut) gliomas with and without 1p/19q codeletion, and non-neoplastic controls. Based on more than 5,500 quantified proteins and 5,000 phosphosites, gliomas separate by IDH1/2 mutational status but not by 1p/19q status. Instead, IDHmut gliomas split into two proteomic subtypes with widespread perturbations, including aerobic/anaerobic energy metabolism. Validations with three independent glioma proteome datasets confirm these subgroups and link the IDHmut subtypes to the established proneural and classic/mesenchymal subtypes in IDHwt glioma. This demonstrates common phenotypic subtypes across the IDH status with potential therapeutic implications for patients with IDHmut gliomas.

DNA methylation-based classification of sinonasal tumors

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs.

From Bowen disease to cutaneous squamous cell carcinoma: eight markers were verified from transcriptomic and proteomic analyses

Background

Bowen's disease is a cutaneous squamous cell carcinoma (CSCC) in situ. If left untreated, BD may progress to invasive CSCC. CSCC is one of the most common cutaneous carcinoma in the elderly and the advanced, metastasis CSCC usually have a poor outcomes. However, the mechanisms of invasion and metastasis from Bowen’s disease to CSCC is complicated and still unclear.

Objectives

The aim of this study was to explore the biomarkers and molecular alterations in Bowen’s disease development process via analyzing the proteomics changes in tissues of CSCC, Bowen disease and healthy skin.

Methods

A total of 7 individuals with CSCC (5 for proteomics study and 2 for validation), 7 individuals with Bowen disease (5 for proteomics study and 2 for validation) and 7 healthy controls (5 for proteomics study and 2 for validation) presented to the Department of Dermatology, Yijishan Hospital, the First Affiliated Hospital of Wannan Medical College between January 2021 and December 2021 were enrolled. The proteomics analysis was performed to screen differentially expressed proteins/gens (DEPs/DEGs) in the lesions of CSCC, Bowen disease and healthy skin tissues. The transcriptomic data (GSE32628) of CSCC was selected and downloaded from the GEO database. The common DEGs in our proteomics results and GSE32628 between CSCC and healthy skin tissues were selected. And then, the common DEGs which significantly up or down-regulated between CSCC and Bowen disease in our proteomics results were further screened to identify using Western blot methods in the validation group. CSCC A431 cells were transfected with SERPINB1 small interfering RNA (si-SERPINB1) or small interfering RNA negative control (si-NC). To explore the effect of SERPINB1 silencing on migration and invasion ability of A431 cells.

Results

A total of 501 proteins were differentially expressed between the CSCC and healthy skin tissues, with 332 up-regulated and 169 down-regulated at least 1.5-fold with a P value < 0.05. These DEPs involved multiple biological functions such as protein binding process, immune, inflammation, ribosome, protein digestion and absorption, ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway and others. A total of 20 common DEGs (COL3A1, LUM, TNC, COL1A1, ALDH3A2, FSCN1, SERPINB4, SERPINB1, CD36, COL4A1, CSTB, GPX3, S100A7, ACTN1, SERPINB3, S100A8, RAB31, STAT1, SPRR1B, S100A9) between CSCC and healthy skin tissues in GSE32628 and our proteomics results were found. Besides, the proteins of TNC, FSCN1, SERPINB1, ACTN1 and RAB31 in CSCC were significantly up-regulated, while COL3A1, COL1A1 and CD36 were significantly down-regulated relative to Bowen disease in proteomics results. These proteins were mainly involved in multiple pathways, including Focal adhesion, ECM-receptor interaction, Human papillomavirus infection, PI3K-Akt signaling pathway, PPAR signaling pathway, AMPK signaling pathway and others. These eight proteins were selected for further validation. According to the Western blotting analysis, when compared with the Bowen disease and healthy skin tissues, we found that the relative expression levels of TNC, FSCN1, SERPINB1, ACTN1 and RAB31 in the CSCC were significantly increased, while COL1A1 and CD36 were significantly decreased, and the differences were statistically significant (P < 0.05). Furthermore, the relative expression levels of TNC, FSCN1, SERPINB1 in the Bowen disease were also significantly increased, while the COL3A1 were also significantly decreased relative to the healthy control. SERPINB1 siRNA inhibited the expression of SERPINB1 at mRNA and protein levels in the A431 cells. After interfering with the expression of SERPINB1, the migration and invasion ability in the A431 cells were significantly decreased (P < 0.05).

Conclusions

This study highlights that eight proteins, TNC, FSCN1, SERPINB1, ACTN1, RAB31, COL3A1, COL1A1, CD36, were significantly associated with the mechanisms of invasion and metastasis in Bowen’s disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03622-1.

Unbiased spatial proteomics with single-cell resolution in tissues

Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges and recent advances in the LC-MS-based analysis of minute protein amounts, down to the level of single cells. Application of this technology revealed that single-cell transcriptomes are dominated by stochastic noise due to the very low number of transcripts per cell, whereas the single-cell proteome appears to be complete. The spatial organization of cells in tissues can be studied by emerging technologies, including multiplexed imaging and spatial transcriptomics, which can now be combined with ultra-sensitive proteomics. Combined with high-content imaging, artificial intelligence and single-cell laser microdissection, MS-based proteomics provides an unbiased molecular readout close to the functional level. Potential applications range from basic biological questions to precision medicine.

Mapping the O-GlcNAc Modified Proteome: Applications for Health and Disease

O-GlcNAc is a pleotropic, enigmatic post-translational modification (PTM). This PTM modifies thousands of proteins differentially across tissue types and regulates diverse cellular signaling processes. O-GlcNAc is implicated in numerous diseases, and the advent of O-GlcNAc perturbation as a novel class of therapeutic underscores the importance of identifying and quantifying the O-GlcNAc modified proteome. Here, we review recent advances in mass spectrometry-based proteomics that will be critical in elucidating the role of this unique glycosylation system in health and disease.

Scaling Up Single-Cell Proteomics

Single-cell tandem MS has enabled analyzing hundreds of single cells per day and quantifying thousands of proteins across the cells. The broad dissemination of these capabilities can empower the dissection of pathophysiological mechanisms in heterogeneous tissues. Key requirements for achieving this goal include robust protocols performed on widely accessible hardware, robust quality controls, community standards, and automated data analysis pipelines that can pinpoint analytical problems and facilitate their timely resolution. Toward meeting these requirements, this perspective outlines both existing resources and outstanding opportunities, such as parallelization, for catalyzing the wide dissemination of quantitative single-cell proteomics analysis that can be scaled up to tens of thousands of single cells. Indeed, simultaneous parallelization of the analysis of peptides and single cells is a promising approach for multiplicative increase in the speed of performing deep and quantitative single-cell proteomics. The community is ready to begin a virtuous cycle of increased adoption fueling the development of more technology and resources for single-cell proteomics that in turn drive broader adoption, scientific discoveries, and clinical applications.

Evaluation of Disposable Trap Column nanoLC-FAIMS-MS/MS for the Proteomic Analysis of FFPE Tissue

Proteomic biomarker discovery using formalin-fixed paraffin-embedded (FFPE) tissue requires robust workflows to support the analysis of large cohorts of patient samples. It also requires finding a reasonable balance between achieving a high proteomic depth and limiting the overall analysis time. To this end, we evaluated the merits of online coupling of single-use disposable trap column nanoflow liquid chromatography, high-field asymmetric-waveform ion-mobility spectrometry (FAIMS), and tandem mass spectrometry (nLC-FAIMS-MS/MS). The data show that ≤600 ng of peptide digest should be loaded onto the chromatographic part of the system. Careful characterization of the FAIMS settings enabled the choice of optimal combinations of compensation voltages (CVs) as a function of the employed LC gradient time. We found nLC-FAIMS-MS/MS to be on par with StageTip-based off-line basic pH reversed-phase fractionation in terms of proteomic depth and reproducibility of protein quantification (coefficient of variation ≤15% for 90% of all proteins) but requiring 50% less sample and substantially reducing sample handling. Using FFPE materials from the lymph node, lung, and prostate tissue as examples, we show that nLC-FAIMS-MS/MS can identify 5000-6000 proteins from the respective tissue within a total of 3 h of analysis time.

Precision medicine and phosphoproteomics for the identification of novel targeted therapeutic avenues in sarcomas

Rapid advances in genomic technologies have enabled in-depth interrogation of cancer genomes, revealing novel and unexpected therapeutic targets in many cancer types. Identifying actionable dependencies in the diverse and heterogeneous group of sarcomas, particularly those that occur in children or adolescents and young adults (AYAs), remains especially challenging. These patients rarely harbor actionable genomic aberrations, no targeted agent is approved, and outcomes have remained poor for the past decades. This underlines a clear need to refine our methods for target identification. Phosphoproteomics studies in sarcoma showed the power of such analyses to capture novel actionable drivers that are not accompanied by mutational events or gene amplifications. This Review makes the case that incorporating phosphoproteomic molecular profiling alongside (functional) genomics technologies can significantly expand therapeutic target identification, and pinpoint drug mechanisms of action, in pediatric and AYA sarcoma patients. We explore the utility and prospects of phosphoproteomics in personalized medicine.