Single cell proteomics for personalised medicine

Single-Cell Proteomics with Spatial Attributes: Tools and Techniques

Now-a-days, the single-cell proteomics (SCP) concept is attracting interest, especially in clinical research, because it can identify the proteomic signature specific to diseased cells. This information is very essential when dealing with the progression of certain diseases, such as cancer, diabetes, Alzheimer's, etc. One of the major drawbacks of conventional destructive proteomics is that it gives an average idea about the protein expression profile in the disease condition. During the extraction of the protein from a biopsy or blood sample, proteins may come from both diseased cells and adjacent normal cells or any other cells from the disease environment. Again, SCP along with spatial attributes is utilized to learn about the heterogeneous function of a single protein. Before performing SCP, it is necessary to isolate single cells. This can be done by various techniques, including fluorescence-activated cell sorting (FACS), magnetic-activated cell sorting (MACS), laser capture microdissection (LCM), microfluidics, manual cell picking/micromanipulation, etc. Among the different approaches for proteomics, mass spectrometry-based proteomics tools are widely used for their high resolution as well as sensitivity. This Review mainly focuses on the mass spectrometry-based approaches for the study of single-cell proteomics.

Phosphoproteome profiling reveals critical role of JAK-STAT signaling in maintaining chemoresistance in breast cancer

Breast cancer is responsible for 25% of cancer cases and 15% of cancer death among women. Treatment is usually prolonged and hampered by the development of chemoresistance. The molecular mechanisms maintaining the chemoresistant phenotype remains, however, largely obscure. As kinase signaling in general is highly drugable, identification of kinases essential for maintaining chemoresistance could prove therapeutically useful. Hence we compared cellular kinase activity in chemotherapy resistant MCF7Res cells to chemotherapy-sensitive MCF cells using a peptide array approach that provides an atlas of cellular kinase activities and consequently, predominant pathways can be identified. We observed that peptides phosphorylated by elements of JAK-STAT signaling pathway and PKC signaling pathways are subject to extensive kinase activity in MCF7Res cells as compared to chemotherapy-sensitive MCF cells; and Western blotting confirmed relatively strong activation of these signaling pathways in chemoresistant cells. Importantly, treatment of cells with Tofacitinib, a FDA-approved JAK inhibitor, converted chemoresistant cells to chemosensitive cells, inducing apoptosis when used in conjunction with doxorubicin. Thus our results reveal that chemoresistance in breast cancer is associated with activation of JAK/STAT signaling and suggest that JAK2 may be useful for combating chemoresistance in breast cancer.

Proteomic profiling of breast cancer metabolism identifies SHMT2 and ASCT2 as prognostic factors

Background

Breast cancer tumors are known to be highly heterogeneous and differences in their metabolic phenotypes, especially at protein level, are less well-understood. Profiling of metabolism-related proteins harbors the potential to establish new patient stratification regimes and biomarkers promoting individualized therapy. In our study, we aimed to examine the relationship between metabolism-associated protein expression profiles and clinicopathological characteristics in a large cohort of breast cancer patients.

Methods

Breast cancer specimens from 801 consecutive patients, diagnosed between 2009 and 2011, were investigated using reverse phase protein arrays (RPPA). Patients were treated in accordance with national guidelines in five certified German breast centers. To obtain quantitative expression data, 37 antibodies detecting proteins relevant to cancer metabolism, were applied. Hierarchical cluster analysis and individual target characterization were performed. Clustering results and individual protein expression patterns were associated with clinical data. The Kaplan-Meier method was used to estimate survival functions. Univariate and multivariate Cox regression models were applied to assess the impact of protein expression and other clinicopathological features on survival.

Results

We identified three metabolic clusters of breast cancer, which do not reflect the receptor-defined subtypes, but are significantly correlated with overall survival (OS, p ≤ 0.03) and recurrence-free survival (RFS, p ≤ 0.01). Furthermore, univariate and multivariate analysis of individual protein expression profiles demonstrated the central role of serine hydroxymethyltransferase 2 (SHMT2) and amino acid transporter ASCT2 (SLC1A5) as independent prognostic factors in breast cancer patients. High SHMT2 protein expression was significantly correlated with poor OS (hazard ratio (HR) = 1.53, 95% confidence interval (CI) = 1.10–2.12, p ≤ 0.01) and RFS (HR = 1.54, 95% CI = 1.16–2.04, p ≤ 0.01). High protein expression of ASCT2 was significantly correlated with poor RFS (HR = 1.31, 95% CI = 1.01–1.71, p ≤ 0.05).

Conclusions

Our data confirm the heterogeneity of breast tumors at a functional proteomic level and dissects the relationship between metabolism-related proteins, pathological features and patient survival. These observations highlight the importance of SHMT2 and ASCT2 as valuable individual prognostic markers and potential targets for personalized breast cancer therapy.

Trial registration

ClinicalTrials.gov, NCT01592825. Registered on 3 May 2012.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0905-7) contains supplementary material, which is available to authorized users.

Pollen proteomics: from stress physiology to developmental priming

Pollen development and stress. In angiosperms, pollen or pollen grain (male gametophyte) is a highly reduced two- or three-cell structure which plays a decisive role in plant reproduction. Male gametophyte development takes place in anther locules where diploid sporophytic cells undergo meiotic division followed by two consecutive mitotic processes. A desiccated and metabolically quiescent form of mature pollen is released from the anther which lands on the stigma. Pollen tube growth takes place followed by double fertilization. Apart from its importance in sexual reproduction, pollen is also an interesting model system which integrates fundamental cellular processes like cell division, differentiation, fate determination, polar establishment, cell to cell recognition and communication. Recently, pollen functionality has been studied by multidisciplinary approaches which also include OMICS analyses like transcriptomics, proteomics and metabolomics. Here, we review recent advances in proteomics of pollen development and propose the process of developmental priming playing a key role to guard highly sensitive developmental processes.

Improved intra-array and interarray normalization of peptide microarray phosphorylation for phosphorylome and kinome profiling by rational selection of relevant spots

Massive parallel analysis using array technology has become the mainstay for analysis of genomes and transcriptomes. Analogously, the predominance of phosphorylation as a regulator of cellular metabolism has fostered the development of peptide arrays of kinase consensus substrates that allow the charting of cellular phosphorylation events (often called kinome profiling). However, whereas the bioinformatical framework for expression array analysis is well-developed, no advanced analysis tools are yet available for kinome profiling. Especially intra-array and interarray normalization of peptide array phosphorylation remain problematic, due to the absence of “housekeeping” kinases and the obvious fallacy of the assumption that different experimental conditions should exhibit equal amounts of kinase activity. Here we describe the development of analysis tools that reliably quantify phosphorylation of peptide arrays and that allow normalization of the signals obtained. We provide a method for intraslide gradient correction and spot quality control. We describe a novel interarray normalization procedure, named repetitive signal enhancement, RSE, which provides a mathematical approach to limit the false negative results occuring with the use of other normalization procedures. Using in silico and biological experiments we show that employing such protocols yields superior insight into cellular physiology as compared to classical analysis tools for kinome profiling.

Single-cell chemical proteomics with an activity-based probe: identification of low-copy membrane proteins on primary neurons

We propose a novel single-cell chemical proteomics (SCCP) strategy to profile low-abundance membrane proteins in single cells. In this approach, the membrane protein GB1 and its splicing variants were targeted on cultured cell lines and primary neurons using a specifically designed activity-based probe. The functionally labeled single cells were encapsulated in individual buffer droplets on a PDMS microwell array, and were further picked up one at a time and loaded into a capillary electrophoresis system for cell lysis, separation, and laser-induced fluorescence detection of the targeted proteins. The results revealed the expression of GB1 splicing variants in HEK and MEF cells, which was previously only suggested at the transcriptional level. We further applied this method to investigate single primary cells and observed significant heterogeneity among individual mouse cerebellar granule neurons. Interference experiments with GB1 antagonist and agonist validated this observation.

Challenges facing the development and use of protein chips to analyze the phosphoproteome

Recent advances in analytical methods, particularly in the area of protein microarrays, have brought the field of proteomics to the forefront of biological science. Protein arrays have shown to be useful for the multiplexed analysis of several hundreds of proteins in parallel. While much of the effort has focused on developing methods to identify expressed proteins, the identification of post-translational modifications is equally important for comprehensive proteome characterization. Protein phosphorylation constitutes a major type of post-translational modification that mobilizes a high number of genes, is involved in many crucial cell functions and largely contributes to the complexity of the proteome. One of the major challenges to analyze phosphoproteins using arrays is the availability of specific antibodies. Thus far, this has hampered the development of highly complex phosphoprotein arrays. This review discusses some of the recent progress made in the development of techniques and reagents to quantitatively determine sites of protein phosphorylation.

Single-cell-type proteomics: toward a holistic understanding of plant function

Multicellular organisms such as plants contain different types of cells with specialized functions. Analyzing the protein characteristics of each type of cell will not only reveal specific cell functions, but also enhance understanding of how an organism works. Most plant proteomics studies have focused on using tissues and organs containing a mixture of different cells. Recent single-cell-type proteomics efforts on pollen grains, guard cells, mesophyll cells, root hairs, and trichomes have shown utility. We expect that high resolution proteomic analyses will reveal novel functions in single cells. This review provides an overview of recent developments in plant single-cell-type proteomics. We discuss application of the approach for understanding important cell functions, and we consider the technical challenges of extending the approach to all plant cell types. Finally, we consider the integration of single-cell-type proteomics with transcriptomics and metabolomics with the goal of providing a holistic understanding of plant function.

Single cell genomics of the brain: focus on neuronal diversity and neuropsychiatric diseases

Single cell genomics has made increasingly significant contributions to our understanding of the role that somatic genome variations play in human neuronal diversity and brain diseases. Studying intercellular genome and epigenome variations has provided new clues to the delineation of molecular mechanisms that regulate development, function and plasticity of the human central nervous system (CNS). It has been shown that changes of genomic content and epigenetic profiling at single cell level are involved in the pathogenesis of neuropsychiatric diseases (schizophrenia, mental retardation (intellectual/leaning disability), autism, Alzheimer's disease etc.). Additionally, several brain diseases were found to be associated with genome and chromosome instability (copy number variations, aneuploidy) variably affecting cell populations of the human CNS. The present review focuses on the latest advances of single cell genomics, which have led to a better understanding of molecular mechanisms of neuronal diversity and neuropsychiatric diseases, in the light of dynamically developing fields of systems biology and "omics".

Kinome profiling

The use of arrays in genomics has led to a fast and reliable way to screen the transcriptome of an organism. It can be automated and analysis tools have become available and hence the technique has become widely used within the past few years. Signal-transduction routes rely mainly on the phosphorylation status of already available proteins; therefore kinases are central players in signal-transduction routes. The array technology can now also be used for the analysis of the kinome. To enable array analysis, consensus peptides for kinases are spot on a solid support. After incubation with cell lysates and in the presence of radioactive ATP, radioactive peptides can be visualized and the kinases that are active in the cells can be determined. The present paper reviews comprehensively the different kinome array platforms available and results obtained hitherto using such platforms. It will appear that this technology does not disappoint its high expectations and is especially powerful because of its species independence. Nevertheless, improvements are still possible and I shall also sketch future possible directions.

Functional proteomics can define prognosis and predict pathologic complete response in patients with breast cancer

PURPOSE

To determine whether functional proteomics improves breast cancer classification and prognostication and can predict pathological complete response (pCR) in patients receiving neoadjuvant taxane and anthracycline-taxane-based systemic therapy (NST).

METHODS

Reverse phase protein array (RPPA) using 146 antibodies to proteins relevant to breast cancer was applied to three independent tumor sets. Supervised clustering to identify subgroups and prognosis in surgical excision specimens from a training set (n = 712) was validated on a test set (n = 168) in two cohorts of patients with primary breast cancer. A score was constructed using ordinal logistic regression to quantify the probability of recurrence in the training set and tested in the test set. The score was then evaluated on 132 FNA biopsies of patients treated with NST to determine ability to predict pCR.

RESULTS

Six breast cancer subgroups were identified by a 10-protein biomarker panel in the 712 tumor training set. They were associated with different recurrence-free survival (RFS) (log-rank p = 8.8 E-10). The structure and ability of the six subgroups to predict RFS was confirmed in the test set (log-rank p = 0.0013). A prognosis score constructed using the 10 proteins in the training set was associated with RFS in both training and test sets (p = 3.2E-13, for test set). There was a significant association between the prognostic score and likelihood of pCR to NST in the FNA set (p = 0.0021).

CONCLUSION

We developed a 10-protein biomarker panel that classifies breast cancer into prognostic groups that may have potential utility in the management of patients who receive anthracycline-taxane-based NST.

Towards elucidation of functional molecular signatures of the adhesive-migratory phenotype of malignant cells

Over the years, malignant transformation has been investigated on multiple levels, ranging from clinical pathology to the underlying molecular mechanisms. In "zooming in" on this process, cancer biologists have focused their attention on the molecular and cellular manifestations of the "transformed phenotype", including the genomic instability of cancer cells, their deregulated transcriptional activity, their aberrant morphology and dynamics, and the altered signaling networks activated in them. Attempts to elucidate the mechanisms underlying malignant and metastatic transformation are primarily motivated by the desire to identify specific molecules and signaling pathways that can serve as targets for novel therapies. In recent years, such studies were reinforced by major technological and conceptual developments: novel and powerful tools for genomic and proteomic analysis have been developed, and advanced computational approaches offer "systems-level" integration of rich and complex biological datasets into meaningful functional networks. In this article, we consider the current and potential impact of these new experimental approaches and, in particular, the recent progress made in quantitative proteomics, to elucidate the mechanisms underlying the "transformed phenotype". We will primarily focus on the adhesion and migration of cancer cells, and their relationships to the deregulated growth, metastatic dissemination, and anchorage independence associated with malignant transformation.

Understanding dendritic cell biology and its role in immunological disorders through proteomic profiling

Dendritic cells (DC) have always been present on the bright spot of immune research. They have been extensively studied for the last 35 years, and much is known about their different phenotypes, stimulatory capacity, and role in the immune system. During the last 15 years, great attention has been given to studies on global gene and protein expression profiles during the differentiation and maturation processes of these cells. It is well understood that studying the proteome, together with information on the role of protein post-translational modifications (PTM), will reveal the real dynamics of a living cell. The rapid increase of proteomic studies during the last decade describing the differentiation and maturation process in DCs, as well as modifications brought by the use of different compounds that either increase or decrease their immunogenicity, reflects the importance of understanding the molecular processes behind the functional properties of these cells. In the present review, we will give an overview of proteomic studies focusing on DCs. Thereby we will concentrate on the importance of these studies in understanding DC behavior from a molecular point of view and how these findings have aided in understanding the differences in functional properties of these cells.

Functional proteomics of Arabidopsis thaliana guard cells uncovers new stomatal signaling pathways

We isolated a total of 3 x 10(8) guard cell protoplasts from 22,000 Arabidopsis thaliana plants and identified 1734 unique proteins using three complementary proteomic methods: protein spot identification from broad and narrow pH range two-dimensional (2D) gels, and 2D liquid chromatography-matrix assisted laser desorption/ionization multidimensional protein identification technology. This extensive single-cell-type proteome includes 336 proteins not previously represented in transcriptome analyses of guard cells and 52 proteins classified as signaling proteins by Gene Ontology analysis, of which only two have been previously assessed in the context of guard cell function. THIOGLUCOSIDE GLUCOHYDROLASE1 (TGG1), a myrosinase that catalyzes the production of toxic isothiocyanates from glucosinolates, showed striking abundance in the guard cell proteome. tgg1 mutants were hyposensitive to abscisic acid (ABA) inhibition of guard cell inward K(+) channels and stomatal opening, revealing that the glucosinolate-myrosinase system, previously identified as a defense against biotic invaders, is required for key ABA responses of guard cells. Our results also suggest a mechanism whereby exposure to abiotic stresses may enhance plant defense against subsequent biotic stressors and exemplify how enhanced knowledge of the signaling networks of a specific cell type can be gained by proteomics approaches.

Cellular physiology of rat cardiac myocytes in cardiac fibrosis: in vitro simulation using the cardiac myocyte/cardiac non-myocyte co-culture system

An understanding of the cellular physiology of cardiac myocytes (MCs) and non-myocytes (NMCs) may help to explain the mechanisms underlying cardiac hypertrophy. Despite numerous studies using MC/NMC co-culture systems, it is difficult to precisely evaluate the influence of each cell type because of the inherent cellular heterogeneity of such a system. Here we developed a co-culture system using Wistar rat neonatal MCs and NMCs isolated by discontinuous Percoll gradient and adhesion separation methods and cultured on either side of insert well membranes. Co-culture of MCs and NMCs resulted in significant increases in [3H]-leucine incorporation by MCs, in the amount of protein synthesized by MCs, and in the secretion of natriuretic peptides, while the addition of MCs to NMC cultures significantly reduced [3H]-thymidine incorporation by NMCs. Interestingly, the percentage of the brain natriuretic peptide (BNP) component of total natriuretic peptide secreted (atrial natriuretic peptide+BNP) increased as the number of NMCs placed in the MC/NMC co-culture system increased. However, MCs did not affect production of angiotensin II (Ang II) by NMCs or secretion of endothelin-1 and transforming growth factor-beta1 into the MC/NMC co-culture system. This finding was supported by the anti-hypertrophic and anti-fibrotic actions of RNH6270, an active form of olmesartan, on MCs in the MC/NMC co-culture system and on NMCs that may synthesize Ang II in the heart. The present data indicate that cardiac fibrosis may not only facilitate MC hypertrophy (possibly through the local angiotensin system) but may also change particular pathophysiological properties of MCs, such as the secretory pattern of natriuretic peptides.

Mass spectrometry-based "omics" technologies in cancer diagnostics

Many "omics" techniques have been developed for one goal: biomarker discovery and early diagnosis of human cancers. A comprehensive review of mass spectrometry-based "omics" approaches performed on various biological samples for molecular diagnosis of human cancers is presented in this article. Furthermore, the existing and potential problems/solutions (both de facto experimental and bioinformatic challenges), and future prospects have been extensively discussed. Although the use of present omic methods as diagnostic tools are still in their infant stage and consequently not ready for immediate clinical use, it can be envisaged that the "omics"-based cancer diagnostics will gradually enter into the clinic in next 10 years as an important supplement to current clinical diagnostics.

Reverse phase protein array: validation of a novel proteomic technology and utility for analysis of primary leukemia specimens and hematopoietic stem cells

Proteomics has the potential to provide answers in cancer pathogenesis and to direct targeted therapy through the comprehensive analysis of protein expression levels and activation status. The realization of this potential requires the development of new, rapid, high-throughput technologies for performing protein arrays on patient samples, as well as novel analytic techniques to interpret them. Herein, we describe the validation and robustness of using reverse phase protein arrays (RPPA) for the analysis of primary acute myelogenous leukemia samples as well as leukemic and normal stem cells. In this report, we show that array printing, detection, amplification, and staining precision are very high, reproducible, and that they correlate with traditional Western blotting. Using replicates of the same sample on the same and/or separate arrays, or using separate protein samples prepared from the same starting sample, the intra- and interarray reproducibility was extremely high. No statistically significant difference in protein signal intensities could be detected within the array setups. The activation status (phosphorylation) was maintained in experiments testing delayed processing and preparation from multiple freeze-thawed samples. Differences in protein expression could reliably be detected in as few as three cell protein equivalents. RPPA prepared from rare populations of normal and leukemic stem cells were successfully done and showed differences from bulk populations of cells. Examples show how RPPAs are ideally suited for the large-scale analysis of target identification, validation, and drug discovery. In summary, RPPA is a highly reliable, reproducible, high-throughput system that allows for the rapid large-scale proteomic analysis of protein expression and phosphorylation state in primary acute myelogenous leukemia cells, cell lines, and in human stem cells.

The use of proteomic techniques to explore the holistic effects of nutrients in vivo

The availability of ‘omics’ technologies is transforming scientific approaches to physiological problems from a reductionist viewpoint to that of a holistic viewpoint. This is of profound importance in nutrition, since the integration of multiple systems at the level of gene expression on the synthetic side through to metabolic enzyme activity on the degradative side combine to govern nutrient availability to tissues. Protein activity is central to the process of nutrition from the initial absorption of nutrients via uptake carriers in the gut, through to distribution and transport in the blood, metabolism by degradative enzymes in tissues and excretion through renal tubule exchange proteins. Therefore, the global profiling of the proteome, defined as the entire protein complement of the genome expressed in a particular cell or organ, or in plasma or serum at a particular time, offers the potential for identification of important biomarkers of nutritional state that respond to alterations in diet. The present review considers the published evidence of nutritional modulation of the proteome in vivo which has expanded exponentially over the last 3 years. It highlights some of the challenges faced by researchers using proteomic approaches to understand the interactions of diet with genomic and metabolic–phenotypic variables in normal populations.

Multiplexed phosphoprotein analysis in immune cells

Analyzing signaling networks in immune cells is of particular interests in diseases where treatment choices are preferentially immunomodulatory. By combining phospho-specific antibodies with multicolor flow cytometry it is possible to perform quantitative multiparameter analysis of signaling pathways within complex cell populations. Multiplexed phosphoprotein analysis will potentially incorporate environmental factors such as toxins or pathogens and genetic variability of individual patients in a step towards personalized medicine.

Circulating tumor cells: the 'leukemic phase' of solid cancers

It is well known that malignant cells circulate in the bloodstream of patients with solid tumors. However, the biological significance of circulating tumor cells (CTCs) and the clinical relevance of their detection are still debated. Besides technical issues regarding CTC-detection methods, discontinuous shedding of CTCs from established cancer deposits, genomic instability and metastatic inefficiency might underlie the conflicting results currently available. Nevertheless, technological advances and recent clinical findings are prompting researchers to dissect CTC biology further. Here, we review these recent findings, and discuss the prospects for the identification and molecular characterization of the CTC subset that is responsible for metastasis development. This would provide a formidable tool for prognosis evaluation, anticancer-drug development and, ultimately, cancer-therapy personalization.

Single-cell genomics

The evolution of higher plants depended on the ability of cells to express hereditary information in many different ways and led to the development of specialized cell types, reflecting an elaborate system of control over gene expression in the individual component cells of various tissues. Bulk tissue sampling results in the loss of spatial resolution, and recent efforts have been directed toward improving access to specialized cell types in plants. Access to the contents of individual cells followed by analyses using post-genomic technologies promise to revolutionize our understanding of the differentiation of specialized cell types, and to enable downstream applications aimed at harnessing their unique biochemical properties.