A streamlined mass spectrometry-based proteomics workflow for large-scale FFPE tissue analysis

Repurposing a drug to punish carbapenem-resistant Acinetobacter baumannii

The OXA β-lactamases in Acinetobacter baumannii represent a primary mechanism for resistance to the carbapenems, a class of antibiotics that represent a last line for treatment. In a screen of an U.S. Food and Drug Administration (FDA)-approved drug library, we identified fendiline, a calcium channel blocker, had significantly more antimicrobial activity against OXA-23 expressing cells. Genetic and proteomic studies revealed that fendiline inhibited the essential lipoprotein trafficking pathway (Lol) in both A. baumannii (LolFD) and Escherichia coli (LolCDE). We demonstrate that OXA-23 is an outer membrane lipoprotein and its overexpression resulted in increased lethality in lolFD-depleted A. baumannii. Our results indicate that overexpression of the OXA-23 β-lactamase in A. baumannii stresses normal lipoprotein trafficking, which makes these cells more susceptible to fendiline. Overall, our data reveal a link between carbapenem resistance and the Lol pathway, which can be leveraged for new drug development.

Deep Visual Proteomics maps proteotoxicity in a genetic liver disease

Protein misfolding diseases, including α1-antitrypsin deficiency (AATD), pose substantial health challenges, with their cellular progression still poorly understood1-3. We use spatial proteomics by mass spectrometry and machine learning to map AATD in human liver tissue. Combining Deep Visual Proteomics (DVP) with single-cell analysis4,5, we probe intact patient biopsies to resolve molecular events during hepatocyte stress in pseudotime across fibrosis stages. We achieve proteome depth of up to 4,300 proteins from one-third of a single cell in formalin-fixed, paraffin-embedded tissue. This dataset reveals a potentially clinically actionable peroxisomal upregulation that precedes the canonical unfolded protein response. Our single-cell proteomics data show α1-antitrypsin accumulation is largely cell-intrinsic, with minimal stress propagation between hepatocytes. We integrated proteomic data with artificial intelligence-guided image-based phenotyping across several disease stages, revealing a late-stage hepatocyte phenotype characterized by globular protein aggregates and distinct proteomic signatures, notably including elevated TNFSF10 (also known as TRAIL) amounts. This phenotype may represent a critical disease progression stage. Our study offers new insights into AATD pathogenesis and introduces a powerful methodology for high-resolution, in situ proteomic analysis of complex tissues. This approach holds potential to unravel molecular mechanisms in various protein misfolding disorders, setting a new standard for understanding disease progression at the single-cell level in human tissue.

Optimization of Extraction Methods for the Quantification of Proteins in Mammalian Tissues

With the development of new vaccine technologies, such as mRNA vaccines, tissue studies are becoming increasingly important. Knowledge of the antigen expression amounts and where the antigen accumulates in the body is essential for designing safe and effective vaccines. Mammalian tissues present challenges in the detection and accurate quantification of target proteins because of their complexity and the lack of protocols that efficiently extract proteins with minimal sample loss. Here, we describe a protocol for the detection and accurate quantification of protein targets in commercially available snap-frozen lung, liver, kidney, and spleen of European domestic ferrets (Mustela putorius furo) by isotope dilution mass spectrometry (IDMS). Housekeeping proteins were chosen that range in abundance to account for different masses of tissue slices of the same organ. Target peptides used for IDMS quantification were conserved across several of the common animal model systems, including baby hamster kidney, mouse, and ferret. Hemagglutinin, the primary antigen of an influenza vaccine, was added at various concentrations to demonstrate the recovery of low-abundance proteins from the complex tissue homogenate. By using housekeeping proteins and a preparation protocol that minimizes sample loss, this study shows that IDMS can accurately quantify proteins in mammalian tissues with unmatched sensitivity and specificity.

In-Depth Cell-Type-Specific Proteome Landscape of the Brain from Human Amyloid-β Overexpression Mouse Model

Amyloid-β (Aβ) plays a crucial role in Alzheimer's disease pathogenesis. Understanding how Aβ overexpression alters the proteome of individual brain cell types is essential but challenging due to the nature of brain tissue, which contains intermingled various cell types. The current methods for cell-type-specific proteomics either require genetic modifications or complex cell isolation, limiting their use. This study introduces a novel method, in situ cell-type-specific proteome analysis using antibody-mediated biotinylation (iCAB), which applies immunohistochemistry with biotin-tyramide to target cell-specific proteins directly in tissue. Applied to 5xFAD mice, iCAB enables us to identify ≈8000 cell-type-specific proteomes with significantly more differentially expressed proteins than traditional bulk proteome methods, pinpointing unique pathways such as mRNA processing, calcium regulation, and phagocytosis for neurons, astrocytes, and microglia, respectively. This study reports in-depth the cell-type-specific brain proteome landscape of the human Aβ overexpression mouse model for the first time using an innovative tool that is powerful, straightforward, and applicable to both animal models and human tissues, without the need for prior genetic alterations.

Mass Spectrometry-Based Proteomics for Next-Generation Precision Oncology

Cancer is the leading cause of death worldwide characterized by patient heterogeneity and complex tumor microenvironment. While the genomics-based testing has transformed modern medicine, the challenge of diverse clinical outcomes highlights unmet needs for precision oncology. As functional molecules regulating cellular processes, proteins hold great promise as biomarkers and drug targets. Mass spectrometry (MS)-based clinical proteomics has illuminated the molecular features of cancers and facilitated discovery of biomarkers or therapeutic targets, paving the way for innovative strategies that enhance the precision of personalized treatment. In this article, we introduced the tools and current achievements of MS-based proteomics, choice of discovery and targeted MS from discovery to validation phases, profiling sensitivity from bulk samples to single-cell level and tissue to liquid biopsy specimens, current regulatory landscape of MS-based protein laboratory-developed tests (LDTs). The challenges, success and future perspectives in translating research MS assay into clinical applications are also discussed. With well-designed validation studies to demonstrate clinical benefits and meet the regulatory requirements for both analytical and clinical performance, the future of MS-based assays is promising with numerous opportunities to improve cancer diagnosis, treatment, and monitoring.

Proteogenomic characterization of non-functional pancreatic neuroendocrine tumors unravels clinically relevant subgroups

The majority of neuroendocrine neoplasms in pancreas are non-functional pancreatic neuroendocrine tumors (NF-PanNETs), which exhibit a high occurrence of distant metastases with limited therapeutic options. Here, we perform a comprehensive molecular characterization of 108 NF-PanNETs through integrative analysis of genomic, transcriptomic, proteomic, and phosphoproteomic profiles. Proteogenomic analysis provides functional insights into the genomic driver alterations of NF-PanNETs, revealing a potential mediator of MEN1 alterations using Men1-conditional knockout mice. Machine-learning-based modeling uncovers a three-protein signature as an independent prognostic factor, which is validated by an independent external cohort. Proteomic and phosphoproteomic-based stratification identifies four subtypes with distinct molecular characteristics, immune microenvironments, and clinicopathological features. Drug screening using patient-derived tumor organoids identifies cyclin-dependent kinase (CDK) 5 and Calcium Voltage-Gated Channel Subunit Alpha1 D (CACNA1D) as ubiquitous and subtype-specific targets, respectively, with in vivo validation using xenograft models. Together, our proteogenomic analyses illustrate a comprehensive molecular landscape of NF-PanNETs, revealing biological insights and therapeutic vulnerabilities.

Biopsy Proteome Score Performs Well as an Effect Measure in a Gluten Challenge Trial of Celiac Disease

BACKGROUND AND AIMS

Development of novel treatments for celiac disease is dependent on precise tools to monitor changes in gluten-induced mucosal damage. Current histology measures are subjective and difficult to standardize. Biopsy proteome scoring is an objective alternative to histology which is based on robust changes in biological pathways that directly reflect gluten-induced mucosal damage. In this study, we aimed to evaluate biopsy proteome scoring as an effect measure in a clinical trial setting by measuring intestinal remodeling in response to oral gluten challenge.

METHODS

We analyzed biopsies from a 14-day gluten challenge trial of treated celiac disease patients that consumed 3 g (n = 6) or 10 g (n = 7) gluten per day. Sections from individually embedded biopsies collected before and after challenge were processed for proteome scoring (n = 109) and measurement of villus height-to-crypt depth ratio (n = 58). Proteome scores were compared with histology, intraepithelial lymphocyte frequency and plasma interleukin-2.

RESULTS

Change in proteome scores were significant for the group of patients who consumed 10 g gluten, but not for the group who consumed 3 g gluten. Altogether, 8 of 13 patients had changes in delta proteome scores above the cutoff. Proteome scores correlated with villus height-to-crypt depth ratios both at run-in and at day 15. Proteome scores at day 15 correlated with intraepithelial lymphocyte frequency and with plasma interleukin-2 levels measured 4 hours post-gluten intake.

CONCLUSION

Biopsy proteome scoring is a simple and reliable measure of gluten-induced mucosal remodeling in response to 14-day oral gluten challenge.

CLINICALTRIALS

gov, Number: NCT03409796.

Recent implementations of data-independent acquisition for cancer biomarker discovery in biological fluids

INTRODUCTION

Cancer is the second-leading cause of death worldwide and accurate biomarkers for early detection and disease monitoring are needed to improve outcomes. Biological fluids, such as blood and urine, are ideal samples for biomarker measurements as they can be routinely collected with relatively minimally invasive methods. However, proteomics analysis of fluids has been a challenge due to the high dynamic range of its protein content. Advances in data-independent acquisition (DIA) mass spectrometry-based proteomics can address some of the technical challenges in the analysis of biofluids, thus enabling the ability for mass spectrometry to propel large-scale biomarker discovery.

AREAS COVERED

We reviewed principles of DIA and its recent applications in cancer biomarker discovery using biofluids. We summarized DIA proteomics studies using biological fluids in the context of cancer research over the past decade, and provided a comprehensive overview of the benefits and challenges of DIA-MS.

EXPERT OPINION

Various studies showed the potential of DIA-MS in identifying putative cancer biomarkers in a high-throughput manner. However, the lack of proper study design and standardization of methods across platforms still needs to be addressed to fully utilize the benefits of DIA-MS to accelerate the biomarker discovery and verification processes.

Proteomic profiling reveals biological processes and biomarkers involved in the pathogenesis of occult breast cancer

BACKGROUND

Occult breast cancer (OBC) is defined as axillary lymph node metastasis without any evidence of a primary tumor in the breast. Because of the limited number of clinical cases, the clinicopathological features and treatment recommendations of OBC are still controversial. In addition, its natural history is poorly understood and its proteomic signature remains unknown.

MATERIALS AND METHODS

We compared the clinicopathological features and prognosis of OBC patients and Non-OBC patients from the Surveillance, Epidemiology, and End Results (SEER) database and analyzed the effects of local treatment on the survival outcomes of OBC patients. Additionally, we performed a quantitative proteomic analysis for tissue samples of metastatic lymph nodes from OBC patients (OBC-LN), and paired tissue samples of metastatic lymph nodes (Non-OBC-LN) and primary tumors (Non-OBC-PT) from Non-OBC patients. We identified differentially expressed proteins in different comparable groups using Student's t test. Functional enrichment and protein-protein interaction network analyses were used to interpret the functions and interactions of the differentially expressed proteins in the comparison of OBC-LN vs Non-OBC-LN. Immunohistochemistry was used for the validation of the hub proteins.

RESULTS

Analysis of data from the SEER database demonstrated that OBC patients had a better prognosis than Non-OBC patients did and that either mastectomy or radiation therapy improved the outcomes of OBC patients. A total of 7208 comparable proteins were successfully quantified. Compared with those of the Non-OBC-LN samples, the OBC-LN protein profiles exhibited an active extracellular matrix and a thoroughly upregulated epithelial-mesenchymal transition phenotype. COL1A1, COL1A2, COL3A1, MMP2 and LUM were overexpressed in the OBC-LN samples and were identified as hub proteins. Immunohistochemical staining demonstrated that the five hub proteins were overexpressed in OBC-LN samples.

CONCLUSION

Our results provide insights for the clinical management of OBC and the proteomic signature of OBC offers molecular basis for further biological research.

The effect of storage time and temperature on the proteomic analysis of FFPE tissue sections

Formalin-fixed paraffin-embedded (FFPE) tissues present an important resource for cancer proteomics. They are more readily available than fresh frozen (FF) tissues and can be stored at ambient temperature for decades. FFPE blocks are largely stable for long-term preservation of tumour histology, but the antigenicity of some proteins in FFPE sections degrades over time resulting in deteriorating performance of immunohistochemistry (IHC). It is not known whether FFPE sections that have previously been cut from blocks and used for liquid chromatography-mass spectrometry (LC-MS) analysis at a later time are affected by storage time or temperature. We determined the stability of FFPE sections stored at room temperature (RT) versus - 80 °C over 48 weeks. The stored sections were processed at different timepoints (n = 11) and compared to sections that were freshly cut from FFPE blocks at each timepoint (controls). A total of 297 sections (rat brain, kidney and liver stored at RT, - 80 °C or freshly cut) were tryptically digested and analysed on TripleTOF 6600 mass spectrometers in data-dependent acquisition (DDA) mode. Kidney and liver digests were also analysed in data-independent acquisition (DIA) mode. The number of proteins and peptides identified by DDA with ProteinPilot and some common post-translational modifications (PTMs) were unaffected by the storage time or temperature. Nine of the most common FFPE-associated modifications were quantified using DIA data and all were unaffected by storage time or temperature. Therefore, FFPE tissue sections are suitable for proteomic studies for at least 48 weeks from the time of sectioning.

Mass Spectrometry-Based Glycomics and Proteomics Profiling of On-Slide Digested Tissue from Complex Biological Samples

Mass spectrometry-based investigation of the heterogeneous glycoproteome from complex biological specimens is a robust approach to mapping the structure, function, and dynamics of the glycome and proteome. Sampling whole wet tissues often provides a large amount of starting material; however, there is a reasonable variability in tissue handling prior to downstream processing steps, and it is difficult to capture all the different biomolecules from a specific region. The on-slide tissue digestion approach, outlined in this protocol chapter, is a simple and cost-effective method that allows comprehensive mapping of the glycoproteome from a single spot of tissue of 1 mm or greater diameter. It provides a selection of target areas on tissue slides appropriate for tissue volumes of 10 nL or greater, corresponding to a 1 μL droplet of enzyme solution applied to a 1-mm diameter target on a 10-μm-thick tissue slice. Sequential enzymatic digestions and desalting of the biomolecules without any prior derivatization from the surface of fresh frozen or formalin-fixed paraffin-embedded tissue slides enable the simultaneous identification of glycosaminoglycan disaccharides such as hyaluronan, chondroitin sulfate and heparan sulfate, asparagine or N-linked glycans, and intact (glyco)peptides using liquid chromatography-tandem mass spectrometry. The in-depth information obtained from this method including the disaccharide compositions, glycan structures, peptide abundances, and site-specific glycan occupancies provides a detailed profiling of a single spot of tissue which has the potential to be disseminated to biomedical laboratories.

Towards routine proteome profiling of FFPE tissue: insights from a 1,220-case pan-cancer study

Proteome profiling of formalin-fixed paraffin-embedded (FFPE) specimens has gained traction for the analysis of cancer tissue for the discovery of molecular biomarkers. However, reports so far focused on single cancer entities, comprised relatively few cases and did not assess the long-term performance of experimental workflows. In this study, we analyze 1220 tumors from six cancer entities processed over the course of three years. Key findings include the need for a new normalization method ensuring equal and reproducible sample loading for LC-MS/MS analysis across cohorts, showing that tumors can, on average, be profiled to a depth of >4000 proteins and discovering that current software fails to process such large ion mobility-based online fractionated datasets. We report the first comprehensive pan-cancer proteome expression resource for FFPE material comprising 11,000 proteins which is of immediate utility to the scientific community, and can be explored via a web resource. It enables a range of analyses including quantitative comparisons of proteins between patients and cohorts, the discovery of protein fingerprints representing the tissue of origin or proteins enriched in certain cancer entities.

Protocol for unified metabolomics and proteomics analysis of formalin-fixed paraffin-embedded tissue

The use of archival formalin-fixed paraffin-embedded (FFPE) tissue samples for biochemical analyses is problematic because of the formation of a Schiff base, leading to low protein and metabolite yields during analytical extractions. Here, we overcome this issue using a unified protocol on FFPE tissue for metabolomics and proteomics analyses. Using 20 mg of wet mass tissue, this protocol consistently extracted more than 50 metabolites (across 11 classes of metabolites) and over 900 proteins.

High-throughput proteomic and phosphoproteomic analysis of formalin-fixed paraffin-embedded tissue

Formalin-fixed, paraffin-embedded (FFPE) patient tissues are a valuable resource for proteomic studies with the potential to associate the derived molecular insights with clinical annotations and outcomes. Here we present an optimized, partially automated workflow for FFPE proteomics combining pathology-guided macro-dissection, Adaptive Focused Acoustics (AFA) sonication for lysis and decrosslinking, S-Trap digestion to peptides, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis using Orbitrap, Astral or timsTOF HT instrumentation. The workflow enables analysis of up to 96 dissected FFPE tissue samples or 10 μm scrolls, identifying 8,000-10,000 unique proteins per sample with median CVs <20%. Key optimizations include improved tissue lysis strategies, protein quantification for normalization, and peptide cleanup prior to LC-MS/MS analysis. Application to lung adenocarcinoma (LUAD) FFPE blocks confirms the platform's effectiveness in processing complex, clinically relevant samples, achieving deep proteome coverage and quantitative robustness comparable to TMT-based methods. Using the newly released Orbitrap Astral with short, 24-minute gradients, the workflow identifies up to ~10,000 unique proteins and ~11,000 localized phosphosites in LUAD FFPE tissue. This high-throughput, scalable workflow advances biomarker discovery and proteomic research in archival tissue samples.

Multimodal single cell-resolved spatial proteomics reveal pancreatic tumor heterogeneity

Despite the advances in antibody-guided cell typing and mass spectrometry-based proteomics, their integration is hindered by challenges for processing rare cells in the heterogeneous tissue context. Here, we introduce Spatial and Cell-type Proteomics (SCPro), which combines multiplexed imaging and flow cytometry with ion exchange-based protein aggregation capture technology to characterize spatial proteome heterogeneity with single-cell resolution. The SCPro is employed to explore the pancreatic tumor microenvironment and reveals the spatial alternations of over 5000 proteins by automatically dissecting up to 100 single cells guided by multi-color imaging of centimeter-scale formalin-fixed, paraffin-embedded tissue slide. To enhance cell-type resolution, we characterize the proteome of 14 different cell types by sorting up to 1000 cells from the same tumor, which allows us to deconvolute the spatial distribution of immune cell subtypes and leads to the discovery of subtypes of regulatory T cells. Together, the SCPro provides a multimodal spatial proteomics approach for profiling tissue proteome heterogeneity.

A Photocrosslinking Probe to Capture the Substrates of Caseinolytic Protease P

Protein homeostasis in bacteria is regulated by proteases such as the tetradecameric caseinolytic protease P (ClpP). Although substrates of ClpP have been successfully deciphered in genetically engineered cells, methods which directly trap processed proteins within native cells remain elusive. Here, we introduce an in situ trapping strategy which utilizes trifunctional probes that bind to the active site serine of ClpP and capture adjacent substrates with an attached photocrosslinking moiety. After enrichment using an alkyne handle, substrate deconvolution by mass spectrometry (MS) is performed. We show that our two traps bind substoichiometrically to ClpP, retain protease activity, exhibit unprecedented selectivity for Staphylococcus aureus ClpP in living cells and capture numerous known and novel substrates. The exemplary validation of trapped hits using a targeted proteomics approach confirmed the fidelity of this technology. In conclusion, we provide a novel chemical platform suited for the discovery of serine protease substrates beyond genetic engineering.

Infrared Laser Ablation and Capture of Formalin-Fixed Paraffin-Embedded Tissue

Formalin-fixed paraffin-embedded (FFPE) tissue is a ubiquitous and invaluable resource for biomedical research and clinical applications. However, FFPE tissue proteomics is challenging due to protein cross-linking and chemical modification. Laser ablation sampling allows precise removal of material from tissue sections with high spatial control and reproducibility for offline proteomics by liquid chromatography coupled with tandem mass spectrometry. In this work, we used a pulsed mid-infrared laser for microsampling of rat liver tissue for subsequent identification and quantification of proteins. It was found that more proteins were identified by FFPE tissue laser ablation sampling compared to fresh frozen (FF) tissue laser ablation sampling and that more proteins were identified by laser ablation than by manual dissection of FFPE tissue. In contrast to previous studies, no loss of hydrophilic proteins due to residual cross-linking was observed. The efficient capture of proteins by laser ablation microsampling is attributed to efficient laser breakup of the tissue which facilitates downstream processing of the proteins.

Quantifying Protein Acetylation in Diabetic Nephropathy from Formalin-Fixed Paraffin-Embedded Tissue

PURPOSE

Diabetic kidney disease (DKD) is a serious complication of diabetes mellitus and a leading cause of chronic kidney disease and end-stage renal disease. One potential mechanism underlying cellular dysfunction contributing to kidney disease is aberrant protein post-translational modifications. Lysine acetylation is associated with cellular metabolic flux and is thought to be altered in patients with diabetes and dysfunctional renal metabolism.

EXPERIMENTAL DESIGN

A novel extraction and LC-MS/MS approach was adapted to quantify sites of lysine acetylation from formalin-fixed paraffin-embedded (FFPE) kidney tissue and from patients with DKD and non-diabetic donors (n = 5 and n = 7, respectively).

RESULTS

Analysis of FFPE tissues identified 840 total proteins, with 225 of those significantly changing in patients with DKD. Acetylomic analysis quantified 289 acetylated peptides, with 69 of those significantly changing. Pathways impacted in DKD patients revealed numerous metabolic pathways, specifically mitochondrial function, oxidative phosphorylation, and sirtuin signaling. Differential protein acetylation in DKD patients impacted sirtuin signaling, valine, leucine, and isoleucine degradation, lactate metabolism, oxidative phosphorylation, and ketogenesis.

CONCLUSIONS AND CLINICAL RELEVANCE

A quantitative acetylomics platform was developed for protein biomarker discovery in formalin-fixed and paraffin-embedded biopsies of kidney transplant patients suffering from DKD.

In-Depth Proteomic Analysis of Paraffin-Embedded Tissue Samples from Colorectal Cancer Patients Revealed TXNDC17 and SLC8A1 as Key Proteins Associated with the Disease

A deeper understanding of colorectal cancer (CRC) biology would help to identify specific early diagnostic markers. Here, we conducted quantitative proteomics on FFPE healthy, adenoma, and adenocarcinoma tissue samples from six stage I sporadic CRC patients to identify dysregulated proteins during early CRC development. Two independent quantitative 10-plex TMT experiments were separately performed. After protein extraction, trypsin digestion, and labeling, proteins were identified and quantified by using a Q Exactive mass spectrometer. A total of 2681 proteins were identified and quantified after data analysis and bioinformatics with MaxQuant and the R program. Among them, 284 and 280 proteins showed significant upregulation and downregulation (expression ratio ≥1.5 or ≤0.67, p-value ≤0.05), respectively, in adenoma and/or adenocarcinoma compared to healthy tissue. Ten dysregulated proteins were selected to study their role in CRC by WB, IHC, TMA, and ELISA using tissue and plasma samples from CRC patients, individuals with premalignant colorectal lesions (adenomas), and healthy individuals. In vitro loss-of-function cell-based assays and in vivo experiments using three CRC cell lines with different metastatic properties assessed the important roles of SLC8A1 and TXNDC17 in CRC and liver metastasis. Additionally, SLC8A1 and TXNDC17 protein levels in plasma possessed the diagnostic ability of early CRC stages.

Brain-wide alterations revealed by spatial transcriptomics and proteomics in COVID-19 infection

Understanding the pathophysiology of neurological symptoms observed after severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection is essential to optimizing outcomes and therapeutics. To date, small sample sizes and narrow molecular profiling have limited the generalizability of findings. In this study, we profiled multiple cortical and subcortical regions in postmortem brains of patients with coronavirus disease 2019 (COVID-19) and controls with matched pulmonary pathology (total n = 42) using spatial transcriptomics, bulk gene expression and proteomics. We observed a multi-regional antiviral response without direct active SARS-CoV2 infection. We identified dysregulation of mitochondrial and synaptic pathways in deep-layer excitatory neurons and upregulation of neuroinflammation in glia, consistent across both mRNA and protein. Remarkably, these alterations overlapped substantially with changes in age-related neurodegenerative diseases, including Parkinson's disease and Alzheimer's disease. Our work, combining multiple experimental and analytical methods, demonstrates the brain-wide impact of severe acute/subacute COVID-19, involving both cortical and subcortical regions, shedding light on potential therapeutic targets within pathways typically associated with pathological aging and neurodegeneration.

ZASP: A Highly Compatible and Sensitive ZnCl2 Precipitation-Assisted Sample Preparation Method for Proteomic Analysis

Universal sample preparation for proteomic analysis that enables unbiased protein manipulation, flexible reagent use, and low protein loss is required to ensure the highest sensitivity of downstream liquid chromatography-mass spectrometry (LC-MS) analysis. To address these needs, we developed a ZnCl2 precipitation-assisted sample preparation method (ZASP) that depletes harsh detergents and impurities in protein solutions prior to trypsin digestion via 10 min of ZnCl2 and methanol-induced protein precipitation at room temperature (RT). ZASP can remove trypsin digestion and LC-MS incompatible detergents such as SDS, Triton X-100, and urea at high concentrations in solution and unbiasedly recover proteins independent of the amount of protein input. We demonstrated the sensitivity and reproducibility of ZASP in an analysis of samples with 1 μg to 1000 μg of proteins. Compared to commonly used sample preparation methods such as SDC-based in-solution digestion, acetone precipitation, FASP, and SP3, ZASP has proven to be an efficient approach. Here, we present ZASP, a practical, robust, and cost-effective proteomic sample preparation method that can be applied to profile different types of samples.

Integrated multi-omics assessment of lineage plasticity in a prostate cancer patient with brain and dural metastases

Metastases to the brain are rare in prostate cancer. Here, we describe a patient with two treatment-emergent metastatic lesions, one to the brain with neuroendocrine prostate cancer (NEPC) histology and one to the dural membrane of adenocarcinoma histology. We performed genomic, transcriptomic, and proteomic characterization of these lesions and the primary tumor to investigate molecular features promoting these metastases. The two metastatic lesions had high genomic similarity, including TP53 mutation and PTEN deletion, with the most striking difference being the additional loss of RB1 in the NEPC lesion. Interestingly, the dural lesion expressed both androgen receptor and neuroendocrine markers, suggesting amphicrine carcinoma (AMPC). When analyzing pioneer transcription factors, the AMPC lesion exhibited elevated FOXA1 activity while the brain NEPC lesion showed elevated HOXC10, NFYB, and OTX2 expression suggesting novel roles in NEPC formation or brain tropism. Our results highlight the utility of performing multi-omic characterization, especially in rare cancer subtypes.

Spatial characterization and stratification of colorectal adenomas by deep visual proteomics

Colorectal adenomas (CRAs) are potential precursor lesions to adenocarcinomas, currently classified by morphological features. We aimed to establish a molecular feature-based risk allocation framework toward improved patient stratification. Deep visual proteomics (DVP) is an approach that combines image-based artificial intelligence with automated microdissection and ultra-high sensitive mass spectrometry. Here, we used DVP on formalin-fixed, paraffin-embedded (FFPE) CRA tissues from nine male patients, immunohistologically stained for caudal-type homeobox 2 (CDX2), a protein implicated in colorectal cancer, enabling the characterization of cellular heterogeneity within distinct tissue regions and across patients. DVP identified DMBT1, MARCKS, and CD99 as protein markers linked to recurrence, suggesting their potential for risk assessment. It also detected a metabolic shift to anaerobic glycolysis in cells with high CDX2 expression. Our findings underscore the potential of spatial proteomics to refine early stage detection and contribute to personalized patient management strategies and provided novel insights into metabolic reprogramming.

Comprehensive profiling of the human fecal proteome from IBD patients with DIA-MS enables evaluation of disease-relevant proteins

PURPOSE

Inflammatory bowel disease (IBD), which includes ulcerative colitis (UC) and Crohn's disease (CD), is characterized by chronic gastrointestinal inflammation. A high unmet need exists for noninvasive biomarkers in IBD to monitor changes in disease activity and guide treatment decisions. Stool is an easily accessed, disease proximal matrix in IBD, however the composition of the IBD fecal proteome remains poorly characterized.

EXPERIMENTAL DESIGN

A data-independent acquisition LC-MS/MS approach was used to profile the human fecal proteome in two independent cohorts (Cohort 1: healthy n = 5, UC n = 5, CD n = 5, Cohort 2: healthy n = 20, UC n = 10, and CD n = 10) to identify noninvasive biomarkers reflective of disease activity.

RESULTS

688 human proteins were quantified, with 523 measured in both cohorts. In UC stool 96 proteins were differentially abundant and in CD stool 126 proteins were differentially abundant compared to healthy stool (absolute log2 fold change > 1, p-value < 0.05). Many of these fecal proteins are associated with infiltrating immune cells and ulceration/rectal bleeding, which are hallmarks of IBD pathobiology. Mapping the identified fecal proteins to a whole blood single-cell RNA sequencing data set revealed the involvement of various immune cell subsets to the IBD fecal proteome.

CONCLUSIONS AND CLINICAL RELEVANCE

Findings from this study not only confirmed the presence of established fecal biomarkers for IBD, such as calprotectin and lactoferrin, but also revealed new fecal proteins from multiple pathways known to be dysregulated in IBD. These novel proteins could serve as potential noninvasive biomarkers to monitor specific aspects of IBD disease activity which could expedite clinical development of novel therapeutic targets.

Quantitative Comparison of Deparaffinization, Rehydration, and Extraction Methods for FFPE Tissue Proteomics and Phosphoproteomics

Formalin-fixed paraffin-embedded (FFPE) tissues are suitable for proteomic and phosphoproteomic biomarker studies by data-independent acquisition mass spectrometry. The choice of the sample preparation method influences the number, intensity, and reproducibility of identifications. By comparing four deparaffinization and rehydration methods, including heptane, histolene, SubX, and xylene, we found that heptane and methanol produced the lowest coefficients of variation (CVs). Using this, five extraction methods from the literature were modified and evaluated for their performance using kidney, leg muscle, lung, and testicular rat organs. All methods performed well, except for SP3 due to insufficient tissue lysis. Heat n' Beat was the fastest and most reproducible method with the highest digestion efficiency and lowest CVs. S-Trap produced the highest peptide yield, while TFE produced the best phosphopeptide enrichment efficiency. The quantitation of FFPE-derived peptides remains an ongoing challenge with bias in UV and fluorescence assays across methods, most notably in SPEED. Functional enrichment analysis demonstrated that each method favored extracting some gene ontology cellular components over others including chromosome, cytoplasmic, cytoskeleton, endoplasmic reticulum, membrane, mitochondrion, and nucleoplasm protein groups. The outcome is a set of recommendations for choosing the most appropriate method for different settings.

Targeted proteomic approach for quantification of collagen type I and type III in formalin-fixed paraffin-embedded tissue

Collagen is the most abundant protein in mammals and a major structural component of the extracellular matrix (ECM). Changes to ECM composition occur as a result of numerous physiological and pathophysiological causes, and a common means to evaluate these changes is the collagen 3 (Col3) to collagen 1 (Col1) ratio. Current methods to measure the Col3/1 ratio suffer from a lack of specificity and often under- or over-estimate collagen composition and quantity. This manuscript presents a targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) method for quantification of Col3 and Col1 in FFPE tissues. Using surrogate peptides to generate calibration curves, Col3 and Col1 are readily quantified in FFPE tissue sections with high accuracy and precision. The method is applied to several tissue types from both human and reindeer sources, demonstrating its generalizability. In addition, the targeted LC-MS/MS method permits quantitation of the hydroxyprolinated form of Col3, which has significant implications for understanding not only the quantity of Col3 in tissue, but also understanding of the pathophysiology underlying many causes of ECM changes. This manuscript presents a straightforward, accurate, precise, and generalizable method for quantifying the Col3/1 ratio in a variety of tissue types and organisms.

Biopsy Proteome Scoring to Determine Mucosal Remodeling in Celiac Disease

BACKGROUND & AIMS

Histologic evaluation of gut biopsies is a cornerstone for diagnosis and management of celiac disease (CeD). Despite its wide use, the method depends on proper biopsy orientation, and it suffers from interobserver variability. Biopsy proteome measurement reporting on the tissue state can be obtained by mass spectrometry analysis of formalin-fixed paraffin-embedded tissue. Here we aimed to transform biopsy proteome data into numerical scores that give observer-independent measures of mucosal remodeling in CeD.

METHODS

A pipeline using glass-mounted formalin-fixed paraffin-embedded sections for mass spectrometry-based proteome analysis was established. Proteome data were converted to numerical scores using 2 complementary approaches: a rank-based enrichment score and a score based on machine learning using logistic regression. The 2 scoring approaches were compared with each other and with histology analyzing 18 patients with CeD with biopsies collected before and after treatment with a gluten-free diet as well as biopsies from patients with CeD with varying degree of remission (n = 22). Biopsies from individuals without CeD (n = 32) were also analyzed.

RESULTS

The method yielded reliable proteome scoring of both unstained and H&E-stained glass-mounted sections. The scores of the 2 approaches were highly correlated, reflecting that both approaches pick up proteome changes in the same biological pathways. The proteome scores correlated with villus height-to-crypt depth ratio. Thus, the method is able to score biopsies with poor orientation.

CONCLUSIONS

Biopsy proteome scores give reliable observer and orientation-independent measures of mucosal remodeling in CeD. The proteomic method can readily be implemented by nonexpert laboratories in parallel to histology assessment and easily scaled for clinical trial settings.

Proteomic Characterization of Undifferentiated Small Round Cell Sarcomas With EWSR1 and CIC::DUX4 Translocations Reveals Diverging Tumor Biology and Distinct Diagnostic Markers

Undifferentiated small round cell sarcomas (USRS) of bone and soft tissue are a group of tumors with heterogenic genomic alterations sharing similar morphology. In the present study, we performed a comparative large-scale proteomic analysis of USRS (n = 42) with diverse genomic translocations including classic Ewing sarcomas with EWSR1::FLI1 fusions (n = 24) or EWSR1::ERG fusions (n = 4), sarcomas with an EWSR1 rearrangement (n = 2), CIC::DUX4 fusion (n = 8), as well as tumors classified as USRS with no genetic data available (n = 4). Proteins extracted from formalin-fixed, paraffin-embedded pretherapeutic biopsies were analyzed qualitatively and quantitatively using shotgun mass spectrometry (MS). More than 8000 protein groups could be quantified using data-independent acquisition. Unsupervised hierarchical cluster analysis based on proteomic data allowed stratification of the 42 cases into distinct groups reflecting the different molecular genotypes. Protein signatures that significantly correlated with the respective genomic translocations were identified and used to generate a heatmap of all 42 sarcomas with assignment of cases with unknown molecular genetic data to either the EWSR1- or CIC-rearranged groups. MS-based prediction of sarcoma subtypes was molecularly confirmed in 2 cases where next-generation sequencing was technically feasible. MS also detected proteins routinely used in the immunohistochemical approach for the differential diagnosis of USRS. BCL11B highly expressed in Ewing sarcomas, and BACH2 as well as ETS-1 highly expressed in CIC::DUX4-associated sarcomas, were among proteins identified by the present proteomic study, and were chosen for immunohistochemical confirmation of MS data in our study cohort. Differential expressions of these 3 markers in the 2 genetic groups were further validated in an independent cohort of n = 34 USRS. Finally, our proteomic results point toward diverging signaling pathways in the different USRS subgroups.

Promises and Challenges of populational Proteomics in Health and Disease

Advances in proteomic assay technologies have significantly increased coverage and throughput, enabling recent increases in the number of large-scale population-based proteomic studies of human plasma and serum. Improvements in multiplexed protein assays have facilitated the quantification of thousands of proteins over a large dynamic range, a key requirement for detecting the lowest-ranging, and potentially the most disease-relevant, blood-circulating proteins. In this perspective, we examine how populational proteomic datasets in conjunction with other concurrent omic measures can be leveraged to better understand the genomic and non-genomic correlates of the soluble proteome, constructing biomarker panels for disease prediction, among others. Mass spectrometry workflows are discussed as they are becoming increasingly competitive with affinity-based array platforms in terms of speed, cost, and proteome coverage due to advances in both instrumentation and workflows. Despite much success, there remain considerable challenges such as orthogonal validation and absolute quantification. We also highlight emergent challenges associated with study design, analytical considerations, and data integration as population-scale studies are run in batches and may involve longitudinal samples collated over many years. Lastly, we take a look at the future of what the nascent next-generation proteomic technologies might provide to the analysis of large sets of blood samples, as well as the difficulties in designing large-scale studies that will likely require participation from multiple and complex funding sources and where data sharing, study designs, and financing must be solved.

Comparative Quantitative Proteomic Analysis of Melanoma Subtypes, Nevus-Associated Melanoma, and Corresponding Nevi

A substantial part of cutaneous malignant melanomas develops from benign nevi. However, the precise molecular events driving the transformation from benign to malignant melanoma are not well-understood. We used laser microdissection and mass spectrometry to analyze the proteomes of melanoma subtypes, including superficial spreading melanomas (n = 17), nodular melanomas (n = 17), and acral melanomas (n = 15). Furthermore, we compared the proteomes of nevi cells with those of melanoma cells within the same specimens (nevus-associated melanoma (n = 14)). In total, we quantified 7935 proteins. Despite the genomic and clinical differences of the melanoma subtypes, our analysis revealed relatively similar proteomes, except for the upregulation of proteins involved in immune activation in nodular melanomas versus acral melanomas. Examining nevus-associated melanoma versus nevi, we found 1725 differentially expressed proteins (false discovery rate < 0.05). Among these proteins were 140 that overlapped with cancer hallmarks, tumor suppressors, and regulators of metabolism and cell cycle. Pathway analysis indicated aberrant activation of the phosphoinositide 3-kinase-protein kinase B-mTOR pathways and the Hippo-YAP pathway. Using a classifier, we identified six proteins capable of distinguishing melanoma from nevi samples. Our study represents a comprehensive comparative analysis of the proteome in melanoma subtypes and associated nevi, offering insights into the biological behavior of these distinct entities.

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.

Evaluation of DNAmAge in paired fresh, frozen, and formalin-fixed paraffin-embedded heart tissues

The continued development in methylome analysis has enabled a more precise assessment of DNA methylation, but treatment of target tissue prior to analysis may affect DNA analysis. Prediction of age based on methylation levels in the genome (DNAmAge) has gained much interest in disease predisposition (biological age estimation), but also in chronological donor age estimation in crime case samples. Various epigenetic clocks were designed to predict the age. However, it remains unknown how the storage of the tissues affects the DNAmAge estimation. In this study, we investigated the storage method impact of DNAmAge by the comparing the DNAmAge of the two commonly used storage methods, freezing and formalin-fixation and paraffin-embedding (FFPE) to DNAmAge of fresh tissue. This was carried out by comparing paired heart tissue samples of fresh tissue, samples stored by freezing and FFPE to chronological age and whole blood samples from the same individuals. Illumina EPIC beadchip array was used for methylation analysis and the DNAmAge was evaluated with the following epigenetic clocks: Horvath, Hannum, Levine, Horvath skin+blood clock (Horvath2), PedBE, Wu, BLUP, EN, and TL. We observed differences in DNAmAge among the storage conditions. FFPE samples showed a lower DNAmAge compared to that of frozen and fresh samples. Additionally, the DNAmAge of the heart tissue was lower than that of the whole blood and the chronological age. This highlights caution when evaluating DNAmAge for FFPE samples as the results were underestimated compared with fresh and frozen tissue samples. Furthermore, the study also emphasizes the need for a DNAmAge model based on heart tissue samples for an accurate age estimation.

Mass Spectrometry-Based Proteomics of Poly(methylmethacrylate)-Embedded Bone

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely employed technique in proteomics research for studying the proteome biology of various clinical samples. Hard tissues, such as bone and teeth, are routinely preserved using synthetic poly(methyl methacrylate) (PMMA) embedding resins that enable histological, immunohistochemical, and morphological examination. However, the suitability of PMMA-embedded hard tissues for large-scale proteomic analysis remained unexplored. This study is the first to report on the feasibility of PMMA-embedded bone samples for LC-MS/MS analysis. Conventional workflows yielded merely limited coverage of the bone proteome. Using advanced strategies of prefractionation by high-pH reversed-phase liquid chromatography in combination with isobaric tandem mass tag labeling resulted in proteome coverage exceeding 1000 protein identifications. The quantitative comparison with cryopreserved samples revealed that each sample preparation workflow had a distinct impact on the proteomic profile. However, workflow replicates exhibited a high reproducibility for PMMA-embedded samples. Our findings further demonstrate that decalcification prior to protein extraction, along with the analysis of solubilization fractions, is not preferred for PMMA-embedded bone. The biological applicability of the proposed workflow was demonstrated using samples of human PMMA-embedded alveolar bone and the iliac crest, which revealed anatomical site-specific proteomic profiles. Overall, these results establish a crucial foundation for large-scale proteomics studies contributing to our knowledge of bone biology.

An Automated and Fast Sample Preparation Workflow for Laser Microdissection Guided Ultrasensitive Proteomics

Spatial tissue proteomics integrating whole-slide imaging, laser microdissection, and ultrasensitive mass spectrometry is a powerful approach to link cellular phenotypes to functional proteome states in (patho)physiology. To be applicable to large patient cohorts and low sample input amounts, including single-cell applications, loss-minimized and streamlined end-to-end workflows are key. We here introduce an automated sample preparation protocol for laser microdissected samples utilizing the cellenONE robotic system, which has the capacity to process 192 samples in 3 h. Following laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, our optimized protocol facilitates lysis, formalin de-crosslinking, and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows 'on-the-fly' sample clean-up, particularly pertinent for laser microdissection workflows. We validate our method in human tonsil archival tissue, where we profile proteomes of spatially-defined B-cell, T-cell, and epithelial microregions of 4000 μm2 to a depth of ∼2000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.

Heat 'n Beat: A Universal High-Throughput End-to-End Proteomics Sample Processing Platform in under an Hour

Proteomic analysis by mass spectrometry of small (≤2 mg) solid tissue samples from diverse formats requires high throughput and comprehensive proteome coverage. We developed a nearly universal, rapid, and robust protocol for sample preparation, suitable for high-throughput projects that encompass most cell or tissue types. This end-to-end workflow extends from original sample to loading the mass spectrometer and is centered on a one-tube homogenization and digestion method called Heat 'n Beat (HnB). It is applicable to most tissues, regardless of how they were fixed or embedded. Sample preparation was divided into separate challenges. The initial sample washing and final peptide cleanup steps were adapted to three tissue sources: fresh frozen (FF), optimal cutting temperature (OCT) compound embedded (FF-OCT), and formalin-fixed paraffin embedded (FFPE). Third, for core processing, tissue disruption and lysis were decreased to a 7 min heat and homogenization treatment, and reduction, alkylation, and proteolysis were optimized into a single step. The refinements produced near doubled peptide yield when compared to our earlier method ABLE delivered a consistently high digestion efficiency of 85-90%, reported by ProteinPilot, and required only 38 min for core processing in a single tube, with the total processing time being 53-63 min. The robustness of HnB was demonstrated on six organ types, a cell line, and a cancer biopsy. Its suitability for high-throughput applications was demonstrated on a set of 1171 FF-OCT human cancer biopsies, which were processed for end-to-end completion in 92 h, producing highly consistent peptide yield and quality for over 3513 MS runs.

Investigating the relationship between Epstein-Barr virus infection and gastric cancer: A systematic review and meta-analysis

Background and Aims

Gastric cancer (GC) is a common cancer type worldwide, and various factors can be involved in its occurrence. One of these factors is Epstein-Barr virus (EBV) infection. In this regard, a systematic review and meta-analysis was conducted to achieve a better understanding of the EBV prevalence in GC samples.

Methods

English databases were searched and studies that reported the prevalence and etiological factors of EBV related to GC from July 2007 to November 2022 were retrieved. The reported data were selected based on the inclusion and exclusion criteria. The pooled prevalence of EBV infection with 95% confidence intervals was calculated. Quality assessment, heterogeneity testing, and publication bias assessment were also performed. The literature search showed 953 studies, of which 87 studies met our inclusion criteria and were used for meta-analysis.

Results

The pooled prevalence of EBV infection related to GC was estimated to be 9.5% (95% confidence interval [CI]: 8.2%-11%) in the general population. The prevalence of EBV infection related to GC by gender was 13.5% (95% CI: 11.1%-16.3%) in males and 7.6% (95% CI: 5.4%-10.6%) in females. No significant differences were observed in terms of geographical region. Out of the 87 studies included in the meta-analysis, the most common diagnostic test was in situ hybridization (58 cases).

Conclusions

Altogether, the results indicated that EBV infection is one of the important factors in the development of GC. However, this does not necessarily mean that EBV infection directly causes GC since other factors may also be involved in the development of GC. Therefore, it is recommended to conduct extensive epidemiological studies on various aspects of the relationship between this virus and GC, which can provide valuable information for understanding the relationship between EBV and GC.

Current updates in sarcoma biomarker discovery: emphasis on next-generation sequencing-based methods

Soft tissue sarcomas comprise a heterogeneous group of neoplasms. Although soft tissue malignancies make up only 2% of adult cancers, classification based on histomorphology presents a diagnostic challenge. Characterisation of soft tissue sarcomas by molecular analysis is rapidly evolving to improve diagnostic accuracy and develop targeted therapies. This review highlights the advances in molecular techniques, including current next-generation sequencing-based assays (fusion detection by RNA sequencing, targeted/whole exome sequencing, microRNA profiling), as well as emerging methods (liquid biopsies, DNA methylation profiling, single-cell molecular profiling and next-generation immunohistochemistry) for future clinical applications.

Magnetic Bead-Based Workflow for Sensitive and Streamlined Cell Surface Proteomics

Cell surface proteins represent an important class of molecules for therapeutic targeting and cellular phenotyping. However, their enrichment and detection via mass spectrometry-based proteomics remains challenging due to low abundance, post-translational modifications, hydrophobic regions, and processing requirements. To improve their identification, we optimized a Cell-Surface Capture (CSC) workflow that incorporates magnetic bead-based processing. Using this approach, we evaluated labeling conditions (biotin tags and catalysts), enrichment specificity (streptavidin beads), missed cleavages (lysis buffers), nonenzymatic deamidation (digestion and deglycosylation buffers), and data acquisition methods (DDA, DIA, and TMT). Our findings support the use of alkoxyamine-PEG4-biotin plus 5-methoxy-anthranilic acid, SDS/urea-based lysis buffers, single-pot solid-phased-enhanced sample-preparation (SP3), and streptavidin magnetic beads for maximal surfaceome coverage. Notably, with semiautomated processing, sample handling was simplified and between ∼600 and 900 cell surface N-glycoproteins were identified from only 25-200 μg of HeLa protein. CSC also revealed significant differences between in vitro monolayer cultures and in vivo tumor xenografts of murine CT26 colon adenocarcinoma samples that may aid in target identification for drug development. Overall, the improved efficiency of the magnetic-based CSC workflow identified both previously reported and novel N-glycosites with less material and high reproducibility that should help advance the field of surfaceomics by providing insight in cellular phenotypes not previously documented.

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.

Proteomic analysis reveals LRPAP1 as a key player in the micropapillary pattern metastasis of lung adenocarcinoma

Objectives

Lung adenocarcinomas have different prognoses depending on their histological growth patterns. Micropapillary growth within lung adenocarcinoma, particularly metastasis, is related to dismal prognostic outcome. Metastasis accounts for a major factor leading to mortality among lung cancer patients. Understanding the mechanisms underlying early stage metastasis can help develop novel treatments for improving patient survival.

Methods

Here, quantitative mass spectrometry was conducted for comparing protein expression profiles among various histological subtypes, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and invasive adenocarcinoma (including acinar and micropapillary [MIP] types). To determine the mechanism of MIP-associated metastasis, we identified a protein that was highly expressed in MIP. The expression of the selected highly expressed MIP protein was verified via immunohistochemical (IHC) analysis and its function was validated by an in vitro migration assay.

Results

Proteomic data revealed that low-density lipoprotein receptor-related protein-associated protein 1 (LRPAP1) was highly expressed in MIP group, which was confirmed by IHC. The co-expressed proteins in this study, PSMD1 and HSP90AB1, have been reported to be highly expressed in different cancers and play an essential role in metastasis. We observed that LRPAP1 promoted lung cancer progression, including metastasis, invasion and proliferation in vitro and in vivo.

Conclusion

LRPAP1 is necessary for MIP-associated metastasis and is the candidate novel anti-metastasis therapeutic target.

Spatial Proteomics of Single Hepatocytes with Multiplexed Data-Independent Acquisition (mDIA)

Spatially resolved mass spectrometry-based proteomics at single-cell resolution promises to provide insights into biological heterogeneity. We describe a protocol based on multiplexed data-independent acquisition (mDIA) with dimethyl labeling to enhance proteome depth, accuracy, and throughput while minimizing costs. It enables high-quality proteome analysis of single isolated hepatocytes and utilizes liver zonation for single-cell proteomics benchmarking. This adaptable, modular protocol will promote the use of single-cell proteomics in spatial biology.

Development of a sample preparation method for micro-proteomics analysis of the formaldehyde-fixed paraffin-embedded liver tissue samples

Liver micro-proteomics based on the routinely used formaldehyde-fixed paraffin-embedded (FFPE) samples is valuable for innovative research, but the technical approach for sample preparation is often challenging. In this study, we aimed to develop a method for sample preparation for micro-proteomics on using the FFPE liver samples. We collected 2000 individual cells per batch from FFPE liver slices with laser capture microdissection and used them as test samples. We used the microscale fresh-frozen liver samples or HepG2 cells as control samples. For the FFPE samples, we first established a procedure for protein extraction. 2 h incubation at 95 °C in alkaline amine buffer supplemented with 4% sodium dodecyl sulfate allows improved production, efficiency, and quality of protein extraction. Then, we developed a dedicated protocol HDMSP for the micro-concentrated (<0.05 μg/μL) protein preparation for mass spectrometry (MS) based analysis, in which 2 μg/μL carboxyl magnetic beads and 70% acetonitrile are used to induce protein precipitation. For the 0.01 μg/μL protein control samples, protein recovery rate (PRR) by HDMSP is 72.1%, while the PRR is 5.9% if using a standard method solid phase-enhanced sample preparation. For the FFPE samples, the HDMSP PRR is 88.8%, and the subsequent MS analysis demonstrates increased depth, robustness, and quantitation accuracy for HDMSP relative to the control of in-gel digestion. Moreover, the physicochemical properties and subcellular location of the FFPE liver micro-proteome are comparable to those of the fresh-frozen control samples processed with filter-aided sample preparation (FASP). HDMSP is also comparable to FASP in terms of reproducibility and physicochemical properties in liver subcellular proteomes, and meanwhile reduces the sample preparation time by 15.9% and the experimental cost by 30.8%. Overall, the new method is simple and highly effective for preparing the microscale FFPE liver protein samples for MS analysis. This study provides a useful solution for FFPE liver micro-proteomics.

A Fast-Tracking Sample Preparation Protocol for Proteomics of Formalin-Fixed Paraffin-Embedded Tumor Tissues

Archived tumor specimens are routinely preserved by formalin fixation and paraffin embedding. Despite the conventional wisdom that proteomics might be ineffective due to the cross-linking and pre-analytical variables, these samples have utility for both discovery and targeted proteomics. Building on this capability, proteomics approaches can be used to maximize our understanding of cancer biology and clinical relevance by studying preserved tumor tissues annotated with the patients' medical histories. Proteomics of formalin-fixed paraffin-embedded (FFPE) tissues also integrates with histological evaluation and molecular pathology strategies, so that additional collection of research biopsies or resected tumor aliquots is not needed. The acquisition of data from the same tumor sample also overcomes concerns about biological variation between samples due to intratumoral heterogeneity. However, the protein extraction and proteomics sample preparation from FFPE samples can be onerous, particularly for small (i.e., limited or precious) samples. Therefore, we provide a protocol for a recently introduced kit-based EasyPep method with benchmarking against a modified version of the well-established filter-aided sample preparation strategy using laser-capture microdissected lung adenocarcinoma tissues from a genetically engineered mouse model. This model system allows control over the tumor preparation and pre-analytical variables while also supporting the development of methods for spatial proteomics to examine intratumoral heterogeneity. Data are posted in ProteomeXchange (PXD045879).

A High-Throughput PIXUL-Matrix-Based Toolbox to Profile Frozen and Formalin-Fixed Paraffin-Embedded Tissues Multiomes

Large-scale high-dimensional multiomics studies are essential to unravel molecular complexity in health and disease. We developed an integrated system for tissue sampling (CryoGrid), analytes preparation (PIXUL), and downstream multiomic analysis in a 96-well plate format (Matrix), MultiomicsTracks96, which we used to interrogate matched frozen and formalin-fixed paraffin-embedded (FFPE) mouse organs. Using this system, we generated 8-dimensional omics data sets encompassing 4 molecular layers of intracellular organization: epigenome (H3K27Ac, H3K4m3, RNA polymerase II, and 5mC levels), transcriptome (messenger RNA levels), epitranscriptome (m6A levels), and proteome (protein levels) in brain, heart, kidney, and liver. There was a high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles confirmed known organ-specific superenhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic profiles, known to be poorly correlated with transcriptomic data, can be more accurately predicted by the full suite of multiomics data, compared with using epigenomic, transcriptomic, or epitranscriptomic measurements individually.

A region-resolved proteomic map of the human brain enabled by high-throughput proteomics

Substantial efforts are underway to deepen our understanding of human brain morphology, structure, and function using high-resolution imaging as well as high-content molecular profiling technologies. The current work adds to these approaches by providing a comprehensive and quantitative protein expression map of 13 anatomically distinct brain regions covering more than 11,000 proteins. This was enabled by the optimization, characterization, and implementation of a high-sensitivity and high-throughput microflow liquid chromatography timsTOF tandem mass spectrometry system (LC-MS/MS) capable of analyzing more than 2,000 consecutive samples prepared from formalin-fixed paraffin embedded (FFPE) material. Analysis of this proteomic resource highlighted brain region-enriched protein expression patterns and functional protein classes, protein localization differences between brain regions and individual markers for specific areas. To facilitate access to and ease further mining of the data by the scientific community, all data can be explored online in a purpose-built R Shiny app (https://brain-region-atlas.proteomics.ls.tum.de).

Transcriptomics and proteomics reveal distinct biology for lymph node metastases and tumour deposits in colorectal cancer

Both lymph node metastases (LNMs) and tumour deposits (TDs) are included in colorectal cancer (CRC) staging, although knowledge regarding their biological background is lacking. This study aimed to compare the biology of these prognostic features, which is essential for a better understanding of their role in CRC spread. Spatially resolved transcriptomic analysis using digital spatial profiling was performed on TDs and LNMs from 10 CRC patients using 1,388 RNA targets, for the tumour cells and tumour microenvironment. Shotgun proteomics identified 5,578 proteins in 12 different patients. Differences in RNA and protein expression were analysed, and spatial deconvolution was performed. Image-based consensus molecular subtype (imCMS) analysis was performed on all TDs and LNMs included in the study. Transcriptome and proteome profiles identified distinct clusters for TDs and LNMs in both the tumour and tumour microenvironment segment, with upregulation of matrix remodelling, cell adhesion/motility, and epithelial-mesenchymal transition (EMT) in TDs (all p < 0.05). Spatial deconvolution showed a significantly increased abundance of fibroblasts, macrophages, and regulatory T-cells (p < 0.05) in TDs. Consistent with a higher fibroblast and EMT component, imCMS classified 62% of TDs as poor prognosis subtype CMS4 compared to 36% of LNMs (p < 0.05). Compared to LNMs, TDs have a more invasive state involving a distinct tumour microenvironment and upregulation of EMT, which are reflected in a more frequent histological classification of TDs as CMS4. These results emphasise the heterogeneity of locoregional spread and the fact that TDs should merit more attention both in future research and during staging. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Proteomics analysis of an individual formalin-fixed paraffin-embedded tissue section using isobaric-tag amplification

RATIONALE

The comprehensive analysis of formalin-fixed paraffin-embedded (FFPE) tissues is essential for retrospective clinical studies. However, detecting low-abundance proteins and obtaining proteome-scale data from FFPE samples pose analytical challenges in mass spectrometry-based proteomics. To overcome this challenge, our study focuses on implementing an isobaric labeling approach to improve the detection of low-abundance target proteins in FFPE tissues, thereby enhancing the qualitative and quantitative analysis.

METHODS

We employed an isobaric labeling approach utilizing synthetic peptides or proteins to enable the qualitative and quantitative measurement of target proteins in FFPE tissue samples. To achieve this, we incorporated tandem mass tag (TMT)-labeled recombinant proteins or synthetic peptides into TMT-labeled metastatic breast cancer FFPE tissues. Through this strategy, we successfully detect coexisting CD276 (B7-H3) and CD147 proteins while identifying over 6000 proteins using targeted analysis of individual FFPE tissue sections.

RESULTS

Our findings provide compelling evidence that the incorporation of isobaric labeling, along with the inclusion of TMT-labeled peptides or proteins, greatly enhances the detection of target proteins in FFPE tissue samples. By employing this approach, we were able to obtain robust qualitative measurements of CD276 and CD147 proteins, showcasing its effectiveness in identifying more than 6000 proteins in FFPE samples.

CONCLUSIONS

The integration of an isobaric labeling approach, in conjunction with synthetic peptides or proteins, presents a valuable strategy for enhancing the detection and validation of target proteins in FFPE tissue analysis. This technique holds immense potential in retrospective clinical studies, as it enables comprehensive analysis of low-abundance proteins and facilitating proteome-scale investigations in FFPE samples. By leveraging this methodology, researchers can unlock new insights into disease mechanisms and advance our understanding of complex biological processes.

Deep topographic proteomics of a human brain tumour

The spatial organisation of cellular protein expression profiles within tissue determines cellular function and is key to understanding disease pathology. To define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping proteomes within tissue structures. Here, we present a workflow for spatially-resolved, quantitative proteomics of tissue that generates maps of protein abundance across tissue slices derived from a human atypical teratoid-rhabdoid tumour at three spatial resolutions, the highest being 40 µm, to reveal distinct abundance patterns of thousands of proteins. We employ spatially-aware algorithms that do not require prior knowledge of the fine tissue structure to detect proteins and pathways with spatial abundance patterns and correlate proteins in the context of tissue heterogeneity and cellular features such as extracellular matrix or proximity to blood vessels. We identify PYGL, ASPH and CD45 as spatial markers for tumour boundary and reveal immune response-driven, spatially-organised protein networks of the extracellular tumour matrix. Overall, we demonstrate spatially-aware deep proteo-phenotyping of tissue heterogeneity, to re-define understanding tissue biology and pathology at the molecular 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.