Recent advances and opportunities in proteomic analyses of tumour heterogeneity

Single-Cell Proteomics Using the One-Step Droplet-in-Oil Digestion Method Reveals Proteins Important for Male Meiotic Progression

Different from DNA or RNA, proteins cannot be amplified. The performance of single-cell proteomics is limited by sample loss during sample preparation. Here, we present a one-step droplet-in-oil digestion (OSDO) method that involves one-step water-in-oil processing using cyclohexane or n-heptane, which can reduce the sample adsorption loss and sample volume change due to evaporation and increase the sensitivity and stability of single-cell proteomics. The OSDO is demonstrated to be compatible with tandem mass tag (TMT) labeling to improve the throughput. The OSDO, followed by data-independent acquisition (DIA), quantified more than 3700 proteins per cell during meiotic progression from pachytene to metaphase I, with no correlation between protein and mRNA levels. Inhibition of VPS34 and DNMT1, two proteins up-regulated in metaphase I, both affected metaphase I formation. The OSDO is an easy-to-operate method compatible with both subsequent labeled and unlabeled quantification to expand the depth, throughput, and applicability in single-cell proteomics.

How Have Massively Parallel Sequencing Technologies Furthered Our Understanding of Oncogenesis and Cancer Progression?

Massively parallel sequencing technologies have been a boon to many fields of biological science, including oncology. Cancer is an umbrella term for many diseases featuring abnormal cellular growth due to genetic and epigenetic aberrations. Advances in sequencing technology allow for interrogation of the DNA and RNA of cancer cells and other cells in the tumor microenvironment down to a single-base resolution. However, these strides come after a rich history of ground-breaking biological assays, like the discovery of the Philadelphia chromosome in the context of leukemia. Many specific genetic and epigenetic modifications have been implicated in oncogenesis, cancer progression, and response to treatment. Sequencing technologies have also helped to associate populations of bacteria in the microbiome to cancer development and prognosis. However, all this new information, especially when procured via high-throughput methods, comes at the cost of being more computationally and staff-resource intensive. There is also more risk to the privacy of the individuals with sequenced genomes. Notwithstanding, the overall benefit of sequencing technologies can greatly outweigh the risks with careful advancements and continued focus on the goal: helping those affected by cancer via precision medicine. Cancer biology has been and will continue to be elucidated by sequencing innovations in ways unimaginable without it.

Glucosinolates and Indole-3-carbinol from Brassica oleracea L. as inhibitors of E. coli CdtB: insights from molecular docking, dynamics, DFT and in vitro assay

Escherichia coli (E. coli), a common human gut bacterium, is generally harmless but capable of causing infections and contributing to diseases like urinary tract infections, sepsis/meningitis, or diarrheal diseases. Notably, E. coli is implicated in developing gallbladder cancer (GBC) either through ascending infection from the gastrointestinal tract or via hematogenous spread. Certain E. coli strains are known to produce toxins, such as cytolethal distending toxins (CDTs), that directly contribute to the genetic mutations and cellular abnormalities observed in GBC. Broccoli (Brassica oleracea) is known for its health-promoting properties, including antimicrobial, antioxidant, and immunomodulatory effects, and is rich in essential compounds. Our study investigates the potential of the phytochemicals of B. oleracea to inhibit the CdtB (PDB ID: 2F1N) protein of E. coli which plays a significant role in the pathogenesis of GBC. By employing in silico molecular docking, Glucosinolates and Indole-3-carbinol emerged as promising inhibitors, demonstrating strong bonding affinities of -8.95 and - 8.5 Kcal/mol, respectively. The molecular dynamic simulation showed that both compounds maintained stable interaction with CdtB with minimal conformational changes observed in the protein-ligand complexes. Additionally, the ADMET analysis provided evidence for the drug-likeness properties of the lead compounds. Furthermore, the DFT (Density Functional Theory) revealed that Indole-3-carbinol is more chemically stable but less reactive than Glucosinolates, with HOMO-LUMO gaps of 5.14 eV and 4.50 eV, respectively. Finally, the in vitro antibacterial assessment confirmed the inhibitory effect of Glucosinolates and Indole-3-carbinol against E. coli through disc diffusion assay with the zone of inhibition 34.25 ± 0.541 and 28.67 ± 0.376 mm compared to the control ciprofloxacin. Our study provides crucial data for developing novel therapeutic agents targeting E. coli-associated GBC from the phytochemicals of B. oleracea.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00276-3.

Mimicking and analyzing the tumor microenvironment

The tumor microenvironment (TME) is increasingly appreciated to play a decisive role in cancer development and response to therapy in all solid tumors. Hypoxia, acidosis, high interstitial pressure, nutrient-poor conditions, and high cellular heterogeneity of the TME arise from interactions between cancer cells and their environment. These properties, in turn, play key roles in the aggressiveness and therapy resistance of the disease, through complex reciprocal interactions between the cancer cell genotype and phenotype, and the physicochemical and cellular environment. Understanding this complexity requires the combination of sophisticated cancer models and high-resolution analysis tools. Models must allow both control and analysis of cellular and acellular TME properties, and analyses must be able to capture the complexity at high depth and spatial resolution. Here, we review the advantages and limitations of key models and methods in order to guide further TME research and outline future challenges.

Single-cell proteomics by mass spectrometry: Advances and implications in cancer research

Cancer harbours extensive proteomic heterogeneity. Inspired by the prior success of single-cell RNA sequencing (scRNA-seq) in characterizing minute transcriptomics heterogeneity in cancer, researchers are now actively searching for information regarding the proteomics counterpart. Therefore recently, single-cell proteomics by mass spectrometry (SCP) has rapidly developed into state-of-the-art technology to cater the need. This review aims to summarize application of SCP in cancer research, while revealing current development progress of SCP technology. The review also aims to contribute ideas into research gaps and future directions, ultimately promoting the application of SCP in cancer research.

ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or ConsensusTME. We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.

Deciphering Tumour Heterogeneity: From Tissue to Liquid Biopsy

Simple Summary

Most malignant tumours are highly heterogeneous at molecular and phenotypic levels. Tumour variability poses challenges for the management of patients, as it arises between patients and even evolves in space and time within a single patient. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of tumour diversity in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate tumour heterogeneity.

Abstract

Human solid malignancies harbour a heterogeneous set of cells with distinct genotypes and phenotypes. This heterogeneity is installed at multiple levels. A biological diversity is commonly observed between tumours from different patients (inter-tumour heterogeneity) and cannot be fully captured by the current consensus molecular classifications for specific cancers. To extend the complexity in cancer, there are substantial differences from cell to cell within an individual tumour (intra-tumour heterogeneity, ITH) and the features of cancer cells evolve in space and time. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity with an emphasis on ITH and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of ITH in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate ITH.

Dynamic Cancer Cell Heterogeneity: Diagnostic and Therapeutic Implications

Though heterogeneity of cancers is recognized and has been much discussed in recent years, the concept often remains overlooked in different routine examinations. Indeed, in clinical or biological articles, reviews, and textbooks, cancers and cancer cells are generally presented as evolving distinct entities rather than as an independent heterogeneous cooperative cell population with its self-oriented biology. There are, therefore, conceptual gaps which can mislead the interpretations/diagnostic and therapeutic approaches. In this short review, we wish to summarize and discuss various aspects of this dynamic evolving heterogeneity and its biological, pathological, clinical, diagnostic, and therapeutic implications, using thyroid carcinoma as an illustrative example.

Deep-ultraviolet laser ablation sampling for proteomic analysis of tissue

Deep-ultraviolet laser ablation with a pulsed 193 nm ArF excimer laser was used to remove localized regions from tissue sections from which proteins were extracted for spatially resolved proteomic analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). The ability to capture intact proteins by ablation at 193 nm wavelength was verified by matrix-assisted laser desorption ionization (MALDI) of the protein standard bovine serum albumin (BSA), which showed that BSA was ablated and captured without fragmentation. A Bradford assay of the ablated and captured proteins indicated 90% efficiency for transfer of the intact protein at a laser fluence of 3 kJ/m². Rat brain tissue sections mounted on quartz microscope slides and ablated in transmission mode yielded 2 μg protein per mm² as quantified by the Bradford assay. Tissue areas ranging from 0.06 mm² to 1 mm² were ablated and the ejected material was collected for proteomic analysis. Extracted proteins were digested and the resulting peptides were analyzed by LC-MS/MS. The proteins extracted from the ablated areas were identified and the average number of identified proteins ranged from 85 in the 0.06 mm² area to 2400 in the 1 mm² area of a 50 μm thick tissue. In comparison to infrared laser ablation of equivalent sampled areas, both the protein mass and number of proteins identified using DUV laser ablation sampling were approximately four times larger.

Spatial proteomics for understanding the tissue microenvironment

The human body comprises rich populations of cells, which are arranged into tissues and organs with diverse functionalities. These cells exhibit a broad spectrum of phenotypes and are often organized as a heterogeneous but sophisticatedly regulated ecosystem - tissue microenvironment, inside which every cell interacts with and is reciprocally influenced by its surroundings through its life span. Therefore, it is critical to comprehensively explore the cellular machinery and biological processes in the tissue microenvironment, which is best exemplified by the tumor microenvironment (TME). The past decade has seen increasing advances in the field of spatial proteomics, the main purpose of which is to characterize the abundance and spatial distribution of proteins and their post-translational modifications in the microenvironment of diseased tissues. Herein, we outline the achievements and remaining challenges of mass spectrometry-based tissue spatial proteomics. Exciting technology developments along with important biomedical applications of spatial proteomics are highlighted. In detail, we focus on high-quality resources built by scalpel macrodissection-based region-resolved proteomics, method development of sensitive sample preparation for laser microdissection-based spatial proteomics, and antibody recognition-based multiplexed tissue imaging. In the end, critical issues and potential future directions for spatial proteomics are also discussed.

Tumor Profiling at the Service of Cancer Therapy

Cancer treatment options have evolved significantly in the past few years. From the initial surgical procedures, to the latest next-generation technologies, we are now in the position to analyze and understand tumors in a one-by-one basis and use that to our advantage to provide with individualized treatment options that may increase patient survival. In this review, we will focus on how tumor profiling has evolved over the past decades to deliver more efficient and personalized treatment options, and how novel technologies can help us envisage the future of precision oncology toward a better management and, ultimately, increased survival.

The Implementation of Mass Spectrometry-Based Proteomics Workflows in Clinical Routines of Acute Myeloid Leukemia: Applicability and Perspectives

With the current reproducibility of proteome preparation workflows along with the speed and sensitivity of the mass spectrometers, the transition of the mass spectrometry (MS)-based proteomics technology from biomarker discovery to clinical implementation is under appraisal in the biomedicine community. Therefore, this technology might be implemented soon to detect well-known biomarkers in cancers and other diseases. Acute myeloid leukemia (AML) is an aggressive heterogeneous malignancy that requires intensive treatment to cure the patient. Leukemia relapse is still a major challenge even for patients who have favorable genetic abnormalities. MS-based proteomics could be of great help to both describe the proteome changes of individual patients and identify biomarkers that might encourage specific treatments or clinical strategies. Herein, we will review the advances and availability of the MS-based proteomics strategies that could already be used in clinical proteomics. However, the heterogeneity of complex diseases as AML requires consensus to recognize AML biomarkers and to establish MS-based workflows that allow their unbiased identification and quantification. Although our literature review appears promising towards the utilization of MS-based proteomics in clinical AML in a near future, major efforts are required to validate AML biomarkers and agree on clinically approved workflows.

Clinical Application of Multiple Reaction Monitoring-Mass Spectrometry to Human Epidermal Growth Factor Receptor 2 Measurements as a Potential Diagnostic Tool for Breast Cancer Therapy

Background

Human epidermal growth factor receptor 2 (HER2) is often overexpressed in breast cancer and correlates with a worse prognosis. Thus, the accurate detection of HER2 is crucial for providing the appropriate measures for patients. However, the current techniques used to detect HER2 status, immunohistochemistry and fluorescence in situ hybridization (FISH), have limitations. Specifically, FISH, which is mandatory for arbitrating 2+ cases, is time-consuming and costly. To address this shortcoming, we established a multiple reaction monitoring-mass spectrometry (MRM-MS) assay that improves on existing methods for differentiating HER2 status.

Methods

We quantified HER2 expression levels in 210 breast cancer formalin-fixed paraffin-embedded (FFPE) tissue samples by MRM-MS. We aimed to improve the accuracy and precision of HER2 quantification by simplifying the sample preparation through predicting the number of FFPE slides required to ensure an adequate amount of protein and using the expression levels of an epithelial cell-specific protein as a normalization factor when measuring HER2 expression levels.

Results

To assess the correlation between MRM-MS and IHC/FISH data, HER2 quantitative data from MRM-MS were divided by the expression levels of junctional adhesion molecule A, an epithelial cell-specific protein, prior to statistical analysis. The normalized HER2 amounts distinguished between HER2 2+/FISH-negative and 2+/FISH-positive groups (AUROC = 0.908), which could not be differentiated by IHC. In addition, all HER2 status were discriminated by MRM-MS.

Conclusions

This MRM-MS assay yields more accurate HER2 expression levels relative to immunohistochemistry and should help to guide clinicians toward the proper treatment for breast cancer patients, based on their HER2 expression.

Addressing Cellular Heterogeneity in Cancer through Precision Proteomics

Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.

An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

The impact of ultraviolet- and infrared-based laser microdissection technology on phosphoprotein detection in the laser microdissection-reverse phase protein array workflow

Reversible protein phosphorylation represents a key mechanism by which signals are transduced in eukaryotic cells. Dysregulated phosphorylation is also a hallmark of carcinogenesis and represents key drug targets in the precision medicine space. Thus, methods that preserve phosphoprotein integrity in the context of clinical tissue analyses are crucially important in cancer research. Here we investigated the impact of UV laser microdissection (UV LMD) and IR laser capture microdissection (IR LCM) on phosphoprotein abundance of key cancer signaling protein targets assessed by reverse-phase protein microarray (RPPA). Tumor epithelial cells from consecutive thin sections obtained from four high-grade serous ovarian cancers were harvested using either UV LMD or IR LCM methods. Phosphoprotein abundances for ten phosphoproteins that represent important drug targets were assessed by RPPA and revealed no significant differences in phosphoprotein integrity from those obtained using higher-energy UV versus the lower-energy IR laser methods.

Intratumour heterogeneity of p53 expression; causes and consequences

Genomic alterations in different types of cancer have been identified by comprehensive sequencing methodologies, revealing TP53 as the most frequently mutated gene across the majority of human cancer types. Cytotoxic treatments are still major cancer therapy strategies but cancer recurrence due to therapy resistance is a major challenge. Resistant cell populations may be associated with TP53 mutant clones exhibiting abnormal p53 expression patterns in tumours. Given data that levels of mutant p53 influence cancer cell growth and survival, understanding the mechanisms underlying intratumour heterogeneity of p53 can be exploited to design strategies that improve patient survival. The patterns of p53 protein examined by immunohistochemistry of both premalignant and malignant tissues are complex, ranging from intense staining of all tumour cell nuclei to complete absence of staining and with many intermediate phenotypes. Animal models that express only mutant proteins and adoption of international standards for terminology have brought greater clarity to understanding the causes of variation and are at the same time demonstrating the utility of p53 in oncology. In addition to p53 mutation, MDM2 and chaperone activities, gene copy number and TP53 mRNA levels linked to proliferative activity and differentiation are all now established as causes of variation in p53 staining, with clinical implications. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The molecular pathology of cancer: from pan-genomics to post-genomics

As the cancer genomics of most major cancer types have been comprehensively catalogued over the past decade through a variety of national and international efforts, the delineation of cancer subtypes has been refined, and our understanding of critical cancer drivers and of the potentially targetable vulnerabilities that they create has grown tremendously. The 2018 Annual Review Issue of the Journal of Pathology provides in-depth assessments of how these pan-genomic approaches have enabled advances in cancer classification, targeted therapy selection, and assessment of cancer progression, all of which are now genomically informed, using several cancer types as examples. Beyond these areas of by now conventional pan-genomic tumour analysis, there are also reviews of diverse 'post-genomic' areas, such as the analysis of circulating free tumour DNA in plasma, concurrent germline cancer predisposition profiling in the setting of apparently sporadic cancer, genetic alterations in epigenetic control and DNA repair, proteomics of tumour heterogeneity, computational pathology, and the roles of the cellular stress response and the microbiome in human cancers. As we are able to derive more and more biologically useful information from diverse human biospecimens, these many advances are informing and transforming the practice of cancer pathology. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Recent advances in single-cell analysis by mass spectrometry

Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail.

Quantitative label-free mass spectrometry using contralateral and adjacent breast tissues reveal differentially expressed proteins and their predicted impacts on pathways and cellular functions in breast cancer

Proteins play an essential role in the biological processes associated with cancer. Their altered expression levels can deregulate critical cellular pathways and interactive networks. In this study, the mass spectrometry-based label-free quantification followed by functional annotation was performed to investigate the most significant deregulated proteins among tissues of primary breast tumor (PT) and axillary metastatic lymph node (LN) and corresponding non-tumor tissues contralateral (NCT) and adjacent (ANT) from patients diagnosed with invasive ductal carcinoma. A total of 462 proteins was observed as differentially expressed (DEPs) among the groups analyzed. A high level of similarity was observed in the proteome profile of both non-tumor breast tissues and DEPs (n = 12) were mainly predicted in the RNA metabolism. The DEPs among the malignant and non-tumor breast tissues [n = 396 (PTxNCT) and n = 410 (LNxNCT)] were related to pathways of the LXR/RXR, NO, eNOS, eIF2 and sirtuins, tumor-related functions, fatty acid metabolism and oxidative stress. Remarkable similarity was observed between both malignant tissues, which the DEPs were related to metastatic capabilities. Altogether, our findings revealed differential proteomic profiles that affected cancer associated and interconnected signaling processes. Validation studies are recommended to demonstrate the potential of individual proteins and/or pathways as biological markers in breast cancer. SIGNIFICANCE: The proteomic analysis of this study revealed high similarity in the proteomic profile of the contralateral and adjacent non-tumor breast tissues. Significant differences were identified among the proteome of the malignant and non-tumor tissue groups of the same patients, providing relevant insights into the hallmarks, signaling pathways, biological functions, and interactive protein networks that act during tumorigenesis and breast cancer progression. These proteins are suggested as targets of relevant interest to be explored as potential biological markers related to tumor development and metastatic progression in the breast cancer disease.

Carrier-Assisted Single-Tube Processing Approach for Targeted Proteomics Analysis of Low Numbers of Mammalian Cells

Heterogeneity in composition is inherent in all cell populations, even those containing a single cell type. Single-cell proteomics characterization of cell heterogeneity is currently achieved by antibody-based technologies, which are limited by the availability of high-quality antibodies. Herein we report a simple, easily implemented, mass spectrometry (MS)-based targeted proteomics approach, termed cLC-SRM (carrier-assisted liquid chromatography coupled to selected reaction monitoring), for reliable multiplexed quantification of proteins in low numbers of mammalian cells. We combine a new single-tube digestion protocol to process low numbers of cells with minimal loss together with sensitive LC-SRM for protein quantification. This single-tube protocol builds upon trifluoroethanol digestion and further minimizes sample losses by tube pretreatment and the addition of carrier proteins. We also optimized the denaturing temperature and trypsin concentration to significantly improve digestion efficiency. cLC-SRM was demonstrated to have sufficient sensitivity for reproducible detection of most epidermal growth factor receptor (EGFR) pathway proteins expressed at levels ≥30 000 and ≥3000 copies per cell for 10 and 100 mammalian cells, respectively. Thus, cLC-SRM enables reliable quantification of low to moderately abundant proteins in less than 100 cells and could be broadly useful for multiplexed quantification of important proteins in small subpopulations of cells or in size-limited clinical samples. Further improvements of this method could eventually enable targeted single-cell proteomics when combined with either SRM or other emerging ultrasensitive MS detection.

MALDI Imaging for Proteomic Painting of Heterogeneous Tissue Structures

PURPOSE

To present matrix-assisted laser desorption/ionization (MALDI) imaging as a powerful method to highlight various tissue compartments.

EXPERIMENTAL DESIGN

Formalin-fixed paraffin-embedded (FFPE) tissue of a uterine cervix, a pancreas, a duodenum, a teratoma, and a breast cancer tissue microarray (TMA) are analyzed by MALDI imaging and by immunohistochemistry (IHC). Peptide images are visualized and analyzed using FlexImaging and SCiLS Lab software. Different histological compartments are compared by hierarchical cluster analysis.

RESULTS

MALDI imaging highlights tissue compartments comparable to IHC. In cervical tissue, normal epithelium can be discerned from intraepithelial neoplasia. In pancreatic and duodenal tissues, m/z signals from lymph follicles, vessels, duodenal mucosa, normal pancreas, and smooth muscle structures can be visualized. In teratoma, specific m/z signals to discriminate squamous epithelium, sebaceous glands, and soft tissue are detected. Additionally, tumor tissue can be discerned from the surrounding stroma in small tissue cores of TMAs. Proteomic data acquisition of complex tissue compartments in FFPE tissue requires less than 1 h with recent mass spectrometers.

CONCLUSION AND CLINICAL RELEVANCE

The simultaneous characterization of morphological and proteomic features in the same tissue section adds proteomic information for histopathological diagnostics, which relies at present on conventional hematoxylin and eosin staining, histochemical, IHC and molecular methods.