Quantitative Profiling of Single Formalin Fixed Tumour Sections: proteomics for translational research

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

Protein Expression in Metastatic Melanoma and the Link to Disease Presentation in a Range of Tumor Phenotypes

Malignant melanoma is among the most aggressive skin cancers and it has among the highest metastatic potentials. Although surgery to remove the primary tumor is the gold standard treatment, once melanoma progresses and metastasizes to the lymph nodes and distal organs, i.e., metastatic melanoma (MM), the usual outcome is decreased survival. To improve survival rates and life span, advanced treatments have focused on the success of targeted therapies in the MAPK pathway that are based on BRAF (BRAF V600E) and MEK. The majority of patients with tumors that have higher expression of BRAF V600E show poorer prognosis than patients with a lower level of the mutated protein. Based on the molecular basis of melanoma, these findings are supported by distinct tumor phenotypes determined from differences in tumor heterogeneity and protein expression profiles. With these aspects in mind, continued challenges are to: (1) deconvolute the complexity and heterogeneity of MM; (2) identify the signaling pathways involved; and (3) determine protein expression to develop targeted therapies. Here, we provide an overview of the results from protein expression in MM and the link to disease presentation in a variety of tumor phenotypes and how these will overcome the challenges of clinical problems and suggest new promising approaches in metastatic melanoma and cancer therapy.

Automated sample preparation with SP3 for low-input clinical proteomics

High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format. AutoSP3 performs unbiased protein purification and digestion, and delivers peptides that can be directly analyzed by LCMS, thereby significantly reducing hands-on time, reducing variability in protein quantification, and improving longitudinal reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1,000 proteins from 100 to 1,000 cells. Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples and recapitulated their separation into known histological growth patterns. Finally, we integrated autoSP3 with AFA ultrasonication for the automated end-to-end sample preparation and LCMS analysis of 96 intact tissue samples. Collectively, this constitutes a generic, scalable, and cost-effective workflow with minimal manual intervention, enabling reproducible tissue proteomics in a broad range of clinical and non-clinical applications.

Miniaturized sample preparation on a digital microfluidics device for sensitive bottom-up microproteomics of mammalian cells using magnetic beads and mass spectrometry-compatible surfactants

While LC-MS-based proteomics with high nanograms to micrograms of total protein has become routine, the analysis of samples derived from low cell numbers is challenged by factors such as sample losses, or difficulties encountered with the manual manipulation of small liquid volumes. Digital microfluidics (DMF) is an emerging technique for miniaturized and automated droplet manipulation, which has been proposed as a promising tool for proteomic sample preparation. However, proteome analysis of samples prepared on-chip by DMF has previously been unfeasible, due to incompatibility with down-stream LC-MS instrumentation. To overcome these limitations, we here developed protocols for bottom-up LC-MS based proteomics sample preparation of as little as 100 mammalian cells on a commercially available digital microfluidics device. To this end, we developed effective cell lysis conditions optimized for DMF, as well as detergent-buffer systems compatible with downstream proteolytic digestion on DMF chips and subsequent LC-MS analysis. A major step was the introduction of the single-pot, solid-phase-enhanced sample preparation (SP3) approach on-chip, which allowed the removal of salts and anti-fouling polymeric detergents, thus rendering sample preparation by DMF compatible with LC-MS-based proteome analysis. Application of DMF-SP3 to the proteome analysis of Jurkat T cells led to the identification of up to 2500 proteins from approximately 500 cells, and up to 1200 proteins from approximately 100 cells on an Orbitrap mass spectrometer, emphasizing the high compatibility of DMF-SP3 with low protein input and minute volumes handled by DMF. Taken together, we demonstrate the first sample preparation workflow for proteomics on a DMF chip device reported so far, allowing the sensitive analysis of limited biological material.

High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification

Formalin‐fixed, paraffin‐embedded (FFPE), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here, we developed a pressure cycling technology (PCT)‐SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PCa) and diffuse large B‐cell lymphoma (DLBCL) samples. We show that the proteome patterns of FFPE PCa tissue samples and their analogous fresh‐frozen (FF) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PCa tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between 1 and 15 years in a biobank and show a high degree of the proteome pattern similarity between two types of histological regions in small FFPE samples, that is, punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of a certain degree of biological variations. Applying the method to two independent DLBCL cohorts, we identified myeloperoxidase, a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PCa and DLBCL have been discovered.

Fibrinogen alpha amyloidosis: insights from proteomics

Introduction: Systemic amyloidosis is a diverse group of diseases that, although rare, pose a serious health issue and can lead to organ failure and death. Amyloid typing is essential in determining the causative protein and initiating proper treatment. Mass spectrometry-based proteomics is currently the most sensitive and accurate means of typing amyloid. Areas covered: Amyloidosis can be systemic or localized, acquired or hereditary, and can affect any organ or tissue. Diagnosis requires biopsy, histological analysis, and typing of the causative protein to determine treatment. The kidneys are the most commonly affected organ in systemic disease. Fibrinogen alpha chain amyloidosis (AFib) is the most prevalent form of hereditary renal amyloidosis. Select mutations in the fibrinogen Aα (FGA) gene lead to AFib. Expert commentary: Mass spectrometry is currently the most specific and sensitive method for amyloid typing. Identification of the mutated fibrinogen alpha chain can be difficult in the case of 'private' frameshift mutations, which dramatically change the sequences of the expressed fibrinogen alpha chain. A combination of expert pathologist review, mass spectrometry, and gene sequencing can allow for confident diagnosis and determination of the fibrinogen alpha chain mutated sequence.

Proteome analysis of tissues by mass spectrometry

Tissues and biofluids are important sources of information used for the detection of diseases and decisions on patient therapies. There are several accepted methods for preservation of tissues, among which the most popular are fresh-frozen and formalin-fixed paraffin embedded methods. Depending on the preservation method and the amount of sample available, various specific protocols are available for tissue processing for subsequent proteomic analysis. Protocols are tailored to answer various biological questions, and as such vary in lysis and digestion conditions, as well as duration. The existence of diverse tissue-sample protocols has led to confusion in how to choose the best protocol for a given tissue and made it difficult to compare results across sample types. Here, we summarize procedures used for tissue processing for subsequent bottom-up proteomic analysis. Furthermore, we compare protocols for their variations in the composition of lysis buffers, digestion procedures, and purification steps. For example, reports have shown that lysis buffer composition plays an important role in the profile of extracted proteins: the most common are tris(hydroxymethyl)aminomethane, radioimmunoprecipitation assay, and ammonium bicarbonate buffers. Although, trypsin is the most commonly used enzyme for proteolysis, in some protocols it is supplemented with Lys-C and/or chymotrypsin, which will often lead to an increase in proteome coverage. Data show that the selection of the lysis procedure might need to be tissue-specific to produce distinct protocols for individual tissue types. Finally, selection of the procedures is also influenced by the amount of sample available, which range from biopsies or the size of a few dozen of mm² obtained with laser capture microdissection to much larger amounts that weight several milligrams.

A Standardized and Reproducible Proteomics Protocol for Bottom-Up Quantitative Analysis of Protein Samples Using SP3 and Mass Spectrometry

The broad utility of mass spectrometry (MS) for investigating the proteomes of a diverse array of sample types has significantly expanded the use of this technology in biological studies. This widespread use has resulted in a substantial collection of protocols and acquisition approaches designed to obtain the highest-quality data for each experiment. As a result, distilling this information to develop a standard operating protocol for essential workflows, such as bottom-up quantitative shotgun whole proteome analysis, can be complex for users new to MS technology. Further complicating this matter, in-depth description of the methodological choices is seldom given in the literature. In this work, we describe a workflow for quantitative whole proteome analysis that is suitable for biomarker discovery, giving detailed consideration to important stages, including (1) cell lysis and protein cleanup using SP3 paramagnetic beads, (2) quantitative labeling, (3) offline peptide fractionation, (4) MS analysis, and (5) data analysis and interpretation. Special attention is paid to providing comprehensive details for all stages of this proteomics workflow to enhance transferability to external labs. The standardized protocol described here will provide a simplified resource to the proteomics community toward efficient adaptation of MS technology in proteomics studies.

Single-pot, solid-phase-enhanced sample preparation for proteomics experiments

A critical step in proteomics analysis is the optimal extraction and processing of protein material to ensure the highest sensitivity in downstream detection. Achieving this requires a sample-handling technology that exhibits unbiased protein manipulation, flexibility in reagent use, and virtually lossless processing. Addressing these needs, the single-pot, solid-phase-enhanced sample-preparation (SP3) technology is a paramagnetic bead-based approach for rapid, robust, and efficient processing of protein samples for proteomic analysis. SP3 uses a hydrophilic interaction mechanism for exchange or removal of components that are commonly used to facilitate cell or tissue lysis, protein solubilization, and enzymatic digestion (e.g., detergents, chaotropes, salts, buffers, acids, and solvents) before downstream proteomic analysis. The SP3 protocol consists of nonselective protein binding and rinsing steps that are enabled through the use of ethanol-driven solvation capture on the surface of hydrophilic beads, and elution of purified material in aqueous conditions. In contrast to alternative approaches, SP3 combines compatibility with a substantial collection of solution additives with virtually lossless and unbiased recovery of proteins independent of input quantity, all in a simplified single-tube protocol. The SP3 protocol is simple and efficient, and can be easily completed by a standard user in ~30 min, including reagent preparation. As a result of these properties, SP3 has successfully been used to facilitate examination of a broad range of sample types spanning simple and complex protein mixtures in large and very small amounts, across numerous organisms. This work describes the steps and extensive considerations involved in performing SP3 in bottom-up proteomics, using a simplified protein cleanup scenario for illustration.

Proteomics-Derived Biomarker Panel Improves Diagnostic Precision to Classify Endometrioid and High-grade Serous Ovarian Carcinoma

PURPOSE

Ovarian carcinomas are a group of distinct diseases classified by histotypes. As histotype-specific treatment evolves, accurate classification will become critical for optimal precision medicine approaches.

EXPERIMENTAL DESIGN

To uncover differences between the two most common histotypes, high-grade serous (HGSC) and endometrioid carcinoma, we performed label-free quantitative proteomics on freshly frozen tumor tissues (HGSC, n = 10; endometrioid carcinoma, n = 10). Eight candidate protein biomarkers specific to endometrioid carcinoma were validated by IHC using tissue microarrays representing 361 cases of either endometrioid carcinoma or HGSC.

RESULTS

More than 500 proteins were differentially expressed (P < 0.05) between endometrioid carcinoma and HGSC tumor proteomes. A ranked set of 106 proteins was sufficient to correctly discriminate 90% of samples. IHC validated KIAA1324 as the most discriminatory novel biomarker for endometrioid carcinoma. An 8-marker panel was found to exhibit superior performance for discriminating endometrioid carcinoma from HGSC compared with the current standard of WT1 plus TP53 alone, improving the classification rate for HGSC from 90.7% to 99.2%. Endometrioid carcinoma-specific diagnostic markers such as PLCB1, KIAA1324, and SCGB2A1 were also significantly associated with favorable prognosis within endometrioid carcinoma suggesting biological heterogeneity within this histotype. Pathway analysis of proteomic data revealed differences between endometrioid carcinoma and HGSC pertaining to estrogen and interferon signalling.

CONCLUSIONS

In summary, these findings support the use of multi-marker panels for the differential diagnosis of difficult cases resembling endometrioid carcinoma and HGSC.

BAP1 haploinsufficiency predicts a distinct immunogenic class of malignant peritoneal mesothelioma

Background

Malignant peritoneal mesothelioma (PeM) is a rare and fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no effective targeted therapies for PeM exist. Some immune checkpoint inhibitor studies of mesothelioma have found positivity to be associated with a worse prognosis.

Methods

To search for novel therapeutic targets for PeM, we performed a comprehensive integrative multi-omics analysis of the genome, transcriptome, and proteome of 19 treatment-naïve PeM, and in particular, we examined BAP1 mutation and copy number status and its relationship to immune checkpoint inhibitor activation.

Results

We found that PeM could be divided into tumors with an inflammatory tumor microenvironment and those without and that this distinction correlated with haploinsufficiency of BAP1. To further investigate the role of BAP1, we used our recently developed cancer driver gene prioritization algorithm, HIT’nDRIVE, and observed that PeM with BAP1 haploinsufficiency form a distinct molecular subtype characterized by distinct gene expression patterns of chromatin remodeling, DNA repair pathways, and immune checkpoint receptor activation. We demonstrate that this subtype is correlated with an inflammatory tumor microenvironment and thus is a candidate for immune checkpoint blockade therapies.

Conclusions

Our findings reveal BAP1 to be a potential, easily trackable prognostic and predictive biomarker for PeM immunotherapy that refines PeM disease classification. BAP1 stratification may improve drug response rates in ongoing phases I and II clinical trials exploring the use of immune checkpoint blockade therapies in PeM in which BAP1 status is not considered. This integrated molecular characterization provides a comprehensive foundation for improved management of a subset of PeM patients.

Electronic supplementary material

The online version of this article (10.1186/s13073-019-0620-3) contains supplementary material, which is available to authorized users.

Histone Deacetylase Inhibitors Synergize with Catalytic Inhibitors of EZH2 to Exhibit Antitumor Activity in Small Cell Carcinoma of the Ovary, Hypercalcemic Type

Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare but extremely lethal malignancy that mainly impacts young women. SCCOHT is characterized by a diploid genome with loss of SMARCA4 and lack of SMARCA2 expression, two mutually exclusive ATPases of the SWI/SNF chromatin-remodeling complex. We and others have identified the histone methyltransferase EZH2 as a promising therapeutic target for SCCOHT, suggesting that SCCOHT cells depend on the alternation of epigenetic pathways for survival. In this study, we found that SCCOHT cells were more sensitive to pan-HDAC inhibitors compared with other ovarian cancer lines or immortalized cell lines tested. Pan-HDAC inhibitors, such as quisinostat, reversed the expression of a group of proteins that were deregulated in SCCOHT cells due to SMARCA4 loss, leading to growth arrest, apoptosis, and differentiation in vitro and suppressed tumor growth of xenografted tumors of SCCOHT cells. Moreover, combined treatment of HDAC inhibitors and EZH2 inhibitors at sublethal doses synergistically induced histone H3K27 acetylation and target gene expression, leading to rapid induction of apoptosis and growth suppression of SCCOHT cells and xenografted tumors. Therefore, our preclinical study highlighted the therapeutic potential of combined treatment of HDAC inhibitors with EZH2 catalytic inhibitors to treat SCCOHT.

Factors that drive the increasing use of FFPE tissue in basic and translational cancer research

The decision to use 10% neutral buffered formalin fixed, paraffin embedded (FFPE) archival pathology material may be dictated by the cancer research question or analytical technique, or may be governed by national ethical, legal and social implications (ELSI), biobank, and sample availability and access policy. Biobanked samples of common tumors are likely to be available, but not all samples will be annotated with treatment and outcomes data and this may limit their application. Tumors that are rare or very small exist mostly in FFPE pathology archives. Pathology departments worldwide contain millions of FFPE archival samples, but there are challenges to availability. Pathology departments lack resources for retrieving materials for research or for having pathologists select precise areas in paraffin blocks, a critical quality control step. When samples must be sourced from several pathology departments, different fixation and tissue processing approaches create variability in quality. Researchers must decide what sample quality and quality tolerance fit their specific purpose and whether sample enrichment is required. Recent publications report variable success with techniques modified to examine all common species of molecular targets in FFPE samples. Rigorous quality management may be particularly important in sample preparation for next generation sequencing and for optimizing the quality of extracted proteins for proteomics studies. Unpredictable failures, including unpublished ones, likely are related to pre-analytical factors, unstable molecular targets, biological and clinical sampling factors associated with specific tissue types or suboptimal quality management of pathology archives. Reproducible results depend on adherence to pre-analytical phase standards for molecular in vitro diagnostic analyses for DNA, RNA and in particular, extracted proteins. With continuing adaptations of techniques for application to FFPE, the potential to acquire much larger numbers of FFPE samples and the greater convenience of using FFPE in assays for precision medicine, the choice of material in the future will become increasingly biased toward FFPE samples from pathology archives. Recognition that FFPE samples may harbor greater variation in quality than frozen samples for several reasons, including variations in fixation and tissue processing, requires that FFPE results be validated provided a cohort of frozen tissue samples is available.

Species comparison of liver proteomes reveals links to naked mole-rat longevity and human aging

Background

Mammals display a wide range of variation in their lifespan. Investigating the molecular networks that distinguish long- from short-lived species has proven useful to identify determinants of longevity. Here, we compared the livers of young and old long-lived naked mole-rats (NMRs) and the phylogenetically closely related, shorter-lived, guinea pigs using an integrated omics approach.

Results

We found that NMR livers display a unique expression pattern of mitochondrial proteins that results in distinct metabolic features of their mitochondria. For instance, we observed a generally reduced respiration rate associated with lower protein levels of respiratory chain components, particularly complex I, and increased capacity to utilize fatty acids. Interestingly, we show that the same molecular networks are affected during aging in both NMRs and humans, supporting a direct link to the extraordinary longevity of both species. Finally, we identified a novel detoxification pathway linked to longevity and validated it experimentally in the nematode Caenorhabditis elegans.

Conclusions

Our work demonstrates the benefits of integrating proteomic and transcriptomic data to perform cross-species comparisons of longevity-associated networks. Using a multispecies approach, we show at the molecular level that livers of NMRs display progressive age-dependent changes that recapitulate typical signatures of aging despite the negligible senescence and extraordinary longevity of these rodents.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0547-y) contains supplementary material, which is available to authorized users.

Quantitative Proteomic Analysis Identifies AHNAK (Neuroblast Differentiation-associated Protein AHNAK) as a Novel Candidate Biomarker for Bladder Urothelial Carcinoma Diagnosis by Liquid-based Cytology

Cytological examination of urine is the most widely used noninvasive pathologic screen for bladder urothelial carcinoma (BLCA); however, inadequate diagnostic accuracy remains a major challenge. We performed mass spectrometry-based proteomic analysis of urine samples of ten patients with BLCA and ten paired patients with benign urothelial lesion (BUL) to identify ancillary proteomic markers for use in liquid-based cytology (LBC). A total of 4,839 proteins were identified and 112 proteins were confirmed as expressed at significantly different levels between the two groups. We also performed an independent proteomic profiling of tumor tissue samples where we identified 7,916 proteins of which 758 were differentially expressed. Cross-platform comparisons of these data with comparative mRNA expression profiles from The Cancer Genome Atlas identified four putative candidate proteins, AHNAK, EPPK1, MYH14 and OLFM4. To determine their immunocytochemical expression levels in LBC, we examined protein expression data from The Human Protein Atlas and in-house FFPE samples. We further investigated the expression of the four candidate proteins in urine cytology samples from two independent validation cohorts. These analyses revealed AHNAK as a unique intracellular protein differing in immunohistochemical expression and subcellular localization between tumor and non-tumor cells. In conclusion, this study identified a new biomarker, AHNAK, applicable to discrimination between BLCA and BUL by LBC. To our knowledge, the present study provides the first identification of a clinical biomarker for LBC based on in-depth proteomics.

Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology

Increasing attention has been focused on cell type proteome profiling for understanding the heterogeneous multicellular microenvironment in tissue samples. However, current cell type proteome profiling methods need large amounts of starting materials which preclude their application to clinical tumor specimens with limited access. Here, by seamlessly combining laser capture microdissection and integrated proteomics sample preparation technology SISPROT, specific cell types in tumor samples could be precisely dissected with single cell resolution and processed for high-sensitivity proteome profiling. Sample loss and contamination due to the multiple transfer steps are significantly reduced by the full integration and noncontact design. H&E staining dyes which are necessary for cell type investigation could be selectively removed by the unique two-stage design of the spintip device. This easy-to-use proteome profiling technology achieved high sensitivity with the identification of more than 500 proteins from only 0.1 mm² and 10 μm thickness colon cancer tissue section. The first cell type proteome profiling of four cell types from one colon tumor and surrounding normal tissue, including cancer cells, enterocytes, lymphocytes, and smooth muscle cells, was obtained. 5271, 4691, 4876, and 2140 protein groups were identified, respectively, from tissue section of only 5 mm² and 10 μm thickness. Furthermore, spatially resolved proteome distribution profiles of enterocytes, lymphocytes, and smooth muscle cells on the same tissue slices and across four consecutive sections with micrometer distance were successfully achieved. This fully integrated proteomics technology, termed LCM-SISPROT, is therefore promising for spatial-resolution cell type proteome profiling of tumor microenvironment with a minute amount of clinical starting materials.

Molecular characterization of ERBB2-amplified colorectal cancer identifies potential mechanisms of resistance to targeted therapies: a report of two instructive cases

ERBB2 amplification has been identified in ∼5% of KRAS wild-type colorectal cancers (CRCs). A recent clinical trial showed response to HER2-directed therapy in a subset of ERBB2-amplified metastatic CRCs resistant to chemotherapy and EGFR-directed therapy. With the aim of better understanding mechanisms of resistance to HER2-directed and EGFR-directed therapies, we report the complete molecular characterization of two cases of ERBB2-amplified CRC. PCR-free whole-genome sequencing was used to identify mutations, copy-number alterations, structural variations, and losses of heterozygosity. ERBB2 copy number was also measured by fluorescence in situ hybridization. Single-stranded mRNA sequencing was used for gene expression profiling. Immunohistochemistry and protein mass spectrometry were used to quantify HER2 protein expression. The cases showed ERBB2 copy number of 86 and 92, respectively. Both cases were immunohistochemically positive for HER2 according to CRC-specific scoring criteria. Fluorescence in situ hybridization and protein mass spectrometry corroborated significantly elevated ERBB2 copy number and abundance of HER2 protein. Both cases were microsatellite stable and without mutation of RAS pathway genes. Additional findings included altered expression of PTEN, MET, and MUC1 and mutation of PIK3CA The potential effects of the molecular alterations on sensitivity to EGFR and HER2-directed therapies were discussed. Identification of ERBB2 amplification in CRC is necessary to select patients who may respond to HER2-directed therapy. An improved understanding of the molecular characteristics of ERBB2-amplified CRCs and their potential mechanisms of resistance will be useful for future research into targeted therapies and may eventually inform therapeutic decision-making.

Extending the Compatibility of the SP3 Paramagnetic Bead Processing Approach for Proteomics

The diversity in protein and peptide biochemistry necessitates robust protocols and reagents for efficiently handling and enriching these molecules prior to analysis with mass spectrometry (MS) or other techniques. Further exploration of the paramagnetic bead-based approach, single-pot solid-phase-enhanced sample preparation (SP3), is carried out toward updating and extending previously described conditions and experimental workflows. The SP3 approach was tested in a wide range of experimental scenarios, including (1) binding solvents (acetonitrile, ethanol, isopropanol, acetone), (2) binding pH (acidic vs neutral), (3) solvent/lysate ratios (50-200%, v/v), (4) mixing and rinsing conditions (on-rack vs off-rack rinsing), (5) Enrichment of nondenatured proteins, and (6) capture of individual proteins from noncomplex mixtures. These results highlight the robust handling of proteins in a broad set of scenarios while also enabling the development of a modified SP3 workflow that offers extended compatibility. The modified SP3 approach is used in quantitative in-depth proteome analyses to compare it with commercial paramagnetic bead-based HILIC methods (MagReSyn) and across multiple binding conditions (e.g., pH and solvent during binding). Together, these data reveal the extensive quantitative coverage of the proteome possible with SP3 independent of the binding approach utilized. The results further establish the utility of SP3 for the unbiased handling of peptides and proteins for proteomic applications.

Clear cell carcinomas of the ovary and kidney: clarity through genomics

Clear cell ovarian carcinoma (CCOC) and clear cell renal cell carcinoma (ccRCC) both feature clear cytoplasm, owing to the accumulation of cytoplasmic glycogen. Genomic studies have demonstrated several mutational similarities between these two diseases, including frequent alterations in the chromatin remodelling SWI-SNF and cellular proliferation phosphoinositide 3-kinase-mammalian target of rapamycin pathways, as well as a shared hypoxia-like mRNA expression signature. Although many targeted treatment options have been approved for advanced-stage ccRCC, CCOC patients are still treated with conventional platinum and taxane chemotherapy, to which they are resistant. To determine the extent of similarity between these malignancies, we performed unsupervised clustering of mRNA expression data from these cancers. This review highlights the similarities and differences between these two clear cell carcinomas to facilitate knowledge translation within future research efforts. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Advancing translational research and precision medicine with targeted proteomics

Remarkable advances in quantitative mass spectrometry have shifted the focus of proteomics from the characterization of protein expression profiles to detailed investigations on the spatial and temporal organization of the proteome. Demands for precision therapy and personalized medicine are challenged by heterogeneity in the larger population, which have led to drawbacks in biomarker performance and therapeutic efficacy. The consistent adaptation of the cellular proteome in response to distinctive signals defines a phenotype. Acquisition of quantitative multi-layered omics data on multiple individuals over defined time scales has made it possible to establish means to probe the extent to which the genome, transcriptome and environment influence the variability of the proteome in given conditions, over time. Comprehensive, reproducible datasets generated with contemporary quantitative, massively parallel, targeted proteomic approaches offer as yet untapped benefits for biomarker discovery, development, and validation. The objective of this review is to recapitulate on advances in targeted proteomics approaches for quantifying the cellular proteome and to address ways to incorporate these data towards improving present day methodologies for biomarker evaluation and precision medicine. SIGNIFICANCE: Advances in quantitative mass spectrometry have shifted the focus of proteomics from the characterization of protein expression profiles to detailed investigations on the spatial and temporal organization of the proteome. This review expounds on avenues through which targeted proteomic methodologies can be constructively implemented in translational research and precision medicine to overcome existing challenges that hinder the success of protein biomarkers in clinics, and to develop precise therapeutics for future applications.

Unraveling endometriosis-associated ovarian carcinomas using integrative proteomics

Background: To elucidate potential markers of endometriosis and endometriosis-associated endometrioid and clear cell ovarian carcinomas using mass spectrometry-based proteomics.

Methods: A total of 21 fresh, frozen tissues from patients diagnosed with clear cell carcinoma, endometrioid carcinoma, endometriosis and benign endometrium were subjected to an in-depth liquid chromatography-tandem mass spectrometry analysis on the Q-Exactive Plus. Protein identification and quantification were performed using MaxQuant, while downstream analyses were performed using Perseus and various bioinformatics databases.

Results: Approximately 9000 proteins were identified in total, representing the first in-depth proteomic investigation of endometriosis and its associated cancers. This proteomic data was shown to be biologically sound, with minimal variation within patient cohorts and recapitulation of known markers. While moderate concordance with genomic data was observed, it was shown that such data are limited in their abilities to represent tumours on the protein level and to distinguish tumours from their benign precursors.

Conclusions: The proteomic data suggests that distinct markers may differentiate endometrioid and clear cell carcinoma from endometriosis. These markers may be indicators of pathobiology but will need to be further investigated. Ultimately, this dataset may serve as a basis to unravel the underlying biology of the endometrioid and clear cell cancers with respect to their endometriotic origins.

Recent advances and opportunities in proteomic analyses of tumour heterogeneity

Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with poor patient prognosis for many cancer types. Indeed, non-malignant cell populations, such as vascular endothelial and immune cells, are known to play key roles supporting and, in some cases, driving aggressive tumour biology, and represent targets of emerging therapeutics, such as antiangiogenesis and immune checkpoint inhibitors. The biochemical interplay between these cellular populations and how they contribute to molecular tumour heterogeneity remains enigmatic, particularly from the perspective of the tumour proteome. This review focuses on recent advances in proteomic methods, namely imaging mass spectrometry, single-cell proteomic techniques, and preanalytical sample processing, that are uniquely positioned to enable detailed analysis of discrete cellular populations within tumours to improve our understanding of tumour proteomic heterogeneity. This review further emphasizes the opportunity afforded by the application of these techniques to the analysis of tumour heterogeneity in formalin-fixed paraffin-embedded archival tumour tissues, as these represent an invaluable resource for retrospective analyses that is now routinely accessible, owing to recent technological and methodological advances in tumour tissue proteomics. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Spatial Tissue Proteomics Quantifies Inter- and Intratumor Heterogeneity in Hepatocellular Carcinoma (HCC)

The interpatient variability of tumor proteomes has been investigated on a large scale but many tumors display also intratumoral heterogeneity regarding morphological and genetic features. It remains largely unknown to what extent the local proteome of tumors intrinsically differs. Here, we used hepatocellular carcinoma as a model system to quantify both inter- and intratumor heterogeneity across human patient specimens with spatial resolution. We defined proteomic features that distinguish neoplastic from the directly adjacent nonneoplastic tissue, such as decreased abundance of NADH dehydrogenase complex I. We then demonstrated the existence of intratumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry-based proteomics to analyze diagnostic tumor specimens with spatial resolution. Data are available via ProteomeXchange with identifier PXD007052.

Molecular and functional signatures in a novel Alzheimer's disease mouse model assessed by quantitative proteomics

Background

Alzheimer’s disease (AD), the most common neurodegenerative disorder, is characterized by the deposition of extracellular amyloid plaques and intracellular neurofibrillary tangles. To understand the pathological mechanisms underlying AD, developing animal models that completely encompass the main features of AD pathologies is indispensable. Although mouse models that display pathological hallmarks of AD (amyloid plaques, neurofibrillary tangles, or both) have been developed and investigated, a systematic approach for understanding the molecular characteristics of AD mouse models is lacking.

Methods

To elucidate the mechanisms underlying the contribution of amyloid beta (Aβ) and tau in AD pathogenesis, we herein generated a novel animal model of AD, namely the AD-like pathology with amyloid and neurofibrillary tangles (ADLP^APT) mice. The ADLP^APT mice carry three human transgenes, including amyloid precursor protein, presenilin-1, and tau, with six mutations. To characterize the molecular and functional signatures of AD in ADLP^APT mice, we analyzed the hippocampal proteome and performed comparisons with individual-pathology transgenic mice (i.e., amyloid or neurofibrillary tangles) and wild-type mice using quantitative proteomics with 10-plex tandem mass tag.

Results

The ADLP^APT mice exhibited accelerated neurofibrillary tangle formation in addition to amyloid plaques, neuronal loss in the CA1 area, and memory deficit at an early age. In addition, our proteomic analysis identified nearly 10,000 protein groups, which enabled the identification of hundreds of differentially expressed proteins (DEPs) in ADLP^APT mice. Bioinformatics analysis of DEPs revealed that ADLP^APT mice experienced age-dependent active immune responses and synaptic dysfunctions.

Conclusions

Our study is the first to compare and describe the proteomic characteristics in amyloid and neurofibrillary tangle pathologies using isobaric label-based quantitative proteomics. Furthermore, we analyzed the hippocampal proteome of the newly developed ADLP^APT model mice to investigate how both Aβ and tau pathologies regulate the hippocampal proteome. Because the ADLP^APT mouse model recapitulates the main features of AD pathogenesis, the proteomic data derived from its hippocampus has significant utility as a novel resource for the research on the Aβ-tau axis and pathophysiological changes in vivo.

Electronic supplementary material

The online version of this article (10.1186/s13024-017-0234-4) contains supplementary material, which is available to authorized users.

Origin of clear cell carcinoma: nature or nurture?

A rare but serious complication of endometriosis is the development of carcinoma, and clear cell and endometrioid carcinomas of the ovary are the two most common malignancies which arise from endometriosis. They are distinct diseases, characterized by unique morphologies, immunohistochemical profiles, and responses to treatment. However, both arise in endometriosis and can share common mutations. The overlapping mutational profiles of clear cell and endometrioid carcinomas suggest that their varied histologies may be due to a different cell of origin which gives rise to each type of cancer. Cochrane and colleagues address this question in a recent article in this journal. They show that a marker of ovarian clear cell carcinoma, cystathionine gamma lyase, is expressed in ciliated cells. Similarly, they show that markers of secretory cells (estrogen receptor and methylenetetrahydrofolate dehydrogenase 1) are expressed in ovarian endometrioid carcinoma. Taken together, they suggest that endometrioid and clear cell carcinomas arise from cells related to secretory and ciliated cells, respectively. We discuss Cochrane et al's work in the context of other efforts to determine the cell of origin of gynecological malignancies, with an emphasis on recent developments and challenges unique to the area. These limitations complicate our interpretation of tumor differentiation; does it reflect nature imposed by a specific cell of origin or nurture, by either mutation(s) or environment? Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Tissue and plasma proteomics for early stage cancer detection

The pursuit of novel and effective biomarkers is essential in the struggle against cancer, which is a leading cause of mortality worldwide. Here we discuss the relative advantages and disadvantages of the most frequently used proteomics techniques, concentrating on the latest advances and application of tissue and plasma proteomics for novel cancer biomarker discovery.

Tumor Microenvironment and Models of Ovarian Cancer: The 11th Biennial Rivkin Center Ovarian Cancer Research Symposium

OBJECTIVE

The aim of this study was to review the latest research advances on the topics of the ovarian cancer tumor microenvironment and models of ovarian cancer.

METHODS

In September 2016, a symposium of the leaders in the field of ovarian cancer research was convened to present and discuss current advances and future directions in ovarian cancer research.

RESULTS

One session was dedicated to Tumor Microenvironment and Models of Ovarian Cancer, and included a keynote presentation from Anil Sood, MD, and an invited oral presentation from David Huntsman, MD. Eight additional oral presentations were selected from abstract submissions. Twenty-nine abstracts were presented in poster format and can be grouped into the categories of stromal cells in the microenvironment, immune cells in the microenvironment, epithelial-mesenchymal transition and metastasis, metabolomics, and model systems including spheroids, murine models, and other animal models.

CONCLUSIONS

Rapid advances continue in our understanding of the influence of the tumor microenvironment on ovarian cancer progression and metastasis. Vascular endothelial cells, stromal cells, and immune cells all modulate epithelial tumor cell biology and therefore serve as potential targets for improved treatment responses either in conjunction with or instead of current treatment modalities. Characterization of the underlying genetic alterations in both the tumor cells and surrounding microenvironment cells enhances our understanding of tumor biology. Model systems including both in vitro and in vivo approaches allow novel advances. Technological advances including sequencing strategies, use of mass spectrometry for metabolomics and other studies, and bioengineering approaches all complement conventional methodologies to push forward our understanding and ultimately the treatment of ovarian cancer.

Recent advances in proteomic profiling of pancreatic ductal adenocarcinoma and the road ahead

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers worldwide. However, there remain many unmet clinical needs, from diagnosis to treatment strategies. The inherent complexity of the molecular characteristics of PDAC has made it difficult to meet these challenges, rendering proteomic profiling of PDAC a critical area of research. Area covered: In this review, we present recent advances in mass spectrometry (MS) and its current application in proteomic studies on PDAC. In addition, we discuss future directions for research that can efficiently incorporate current MS-based technologies that address key issues of PDAC proteomics. Expert commentary: Compared with other cancer studies, little progress has been made in PDAC proteomics, perhaps attributed to the difficulty in performing in-depth and large-scale clinical studies on PDAC. However, recent advances in mass spectrometry can advance PDAC proteomics past the fundamental research stage.

Selective aggregation of the splicing factor Hsh155 suppresses splicing upon genotoxic stress

Upon genotoxic stress, dynamic relocalization events control DNA repair as well as alterations of the transcriptome and proteome, enabling stress recovery. How these events may influence one another is only partly known. Beginning with a cytological screen of genome stability proteins, we find that the splicing factor Hsh155 disassembles from its partners and localizes to both intranuclear and cytoplasmic protein quality control (PQC) aggregates under alkylation stress. Aggregate sequestration of Hsh155 occurs at nuclear and then cytoplasmic sites in a manner that is regulated by molecular chaperones and requires TORC1 activity signaling through the Sfp1 transcription factor. This dynamic behavior is associated with intron retention in ribosomal protein gene transcripts, a decrease in splicing efficiency, and more rapid recovery from stress. Collectively, our analyses suggest a model in which some proteins evicted from chromatin and undergoing transcriptional remodeling during stress are targeted to PQC sites to influence gene expression changes and facilitate stress recovery.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs

PURPOSE

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated.

EXPERIMENTAL DESIGN

To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized.

RESULTS

In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator.

CONCLUSION AND CLINICAL RELEVANCE

Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications.

Clear cell and endometrioid carcinomas: are their differences attributable to distinct cells of origin?

Endometrial epithelium is the presumed tissue of origin for both eutopic and endometriosis-derived clear cell and endometrioid carcinomas. We had previously hypothesized that the morphological, biological and clinical differences between these carcinomas are due to histotype-specific mutations. Although some mutations and genomic landscape features are more likely to be found in one of these histotypes, we were not able to identify a single class of mutations that was exclusively present in one histotype and not the other. This lack of genomic differences led us to an alternative hypothesis that these cancers could arise from distinct cells of origin within endometrial tissue, and that it is the cellular context that accounts for their differences. In a proteomic screen, we identified cystathionine γ-lyase (CTH) as a marker for clear cell carcinoma, as it is expressed at high levels in clear cell carcinomas of the ovary and endometrium. In the current study, we analysed normal Müllerian tissues, and found that CTH is expressed in ciliated cells of endometrium (both eutopic endometrium and endometriosis) and fallopian tubes. We then demonstrated that other ciliated cell markers are expressed in clear cell carcinomas, whereas endometrial secretory cell markers are expressed in endometrioid carcinomas. The same differential staining of secretory and ciliated cells was demonstrable in a three-dimensional organoid culture system, in which stem cells were stimulated to differentiate into an admixture of secretory and ciliated cells. These data suggest that endometrioid carcinomas are derived from cells of the secretory cell lineage, whereas clear cell carcinomas are derived from, or have similarities to, cells of the ciliated cell lineage. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Identification of LEFTY as a molecular marker for ovarian clear cell carcinoma

To identify proteins involved in ovarian clear cell carcinoma (OCCCa), shotgun proteomics analysis was applied using formalin-fixed and paraffin-embedded samples of ovarian carcinoma. Analysis of 1521 proteins revealed that 52 were differentially expressed between four OCCCa and 12 non-OCCCa samples. Of the highly expressed proteins in OCCCa, we focused on left-right determination factor (LEFTY), a novel member of the transforming growth factor-β superfamily. In 143 cases of ovarian epithelial carcinoma including 99 OCCCas and 44 non-OCCCas, LEFTY expression at both mRNA and protein levels was significantly higher in OCCCas compared with non-OCCCas, with the mRNA expression of LEFTY1 being predominant compared to that of LEFTY2. OCCCa cells stably overexpressing LEFTY1 showed reduced cell proliferation, along with decreased pSmad2 expression, and also either displayed an activated p53/p21^waf1 pathway or increased p27^kip1 expression, directly or indirectly. Moreover, the treatment of stable cell lines with cisplatin led to increased apoptotic cells, together with the inhibition of protein expression of a pSmad2-mediated X-linked inhibitor of apoptosis and a decreased bcl2/bax ratio. Blocking LEFTY1 expression with a specific short hairpin RNA inhibited cisplatin-induced apoptosis, probably through the increased expression of both XIAP and bcl2, but not bax. In clinical samples, a significantly higher number of apoptotic cells and lower Ki-67 labeling indices were observed in OCCCas with a high LEFTY score relative to those with a low score. These findings suggest that LEFTY may be an excellent OCCCa-specific molecular marker, which has anti-tumor effects in altering cell proliferation and cellular susceptibility to apoptosis.

The histone methyltransferase EZH2 is a therapeutic target in small cell carcinoma of the ovary, hypercalcaemic type

Small cell carcinoma of the ovary, hypercalcaemic type (SCCOHT) is a rare but aggressive and untreatable malignancy affecting young women. We and others recently discovered that SMARCA4, a gene encoding the ATPase of the SWI/SNF chromatin-remodelling complex, is the only gene recurrently mutated in the majority of SCCOHT. The low somatic complexity of SCCOHT genomes and the prominent role of the SWI/SNF chromatin-remodelling complex in transcriptional control of genes suggest that SCCOHT cells may rely on epigenetic rewiring for oncogenic transformation. Herein, we report that approximately 80% (19/24) of SCCOHT tumour samples have strong expression of the histone methyltransferase EZH2 by immunohistochemistry, with the rest expressing variable amounts of EZH2. Re-expression of SMARCA4 suppressed the expression of EZH2 in SCCOHT cells. In comparison to other ovarian cell lines, SCCOHT cells displayed hypersensitivity to EZH2 shRNAs and two selective EZH2 inhibitors, GSK126 and EPZ-6438. EZH2 inhibitors induced cell cycle arrest, apoptosis, and cell differentiation in SCCOHT cells, along with the induction of genes involved in cell cycle regulation, apoptosis, and neuron-like differentiation. EZH2 inhibitors suppressed tumour growth and improved the survival of mice bearing SCCOHT xenografts. Therefore, our data suggest that loss of SMARCA4 creates a dependency on the catalytic activity of EZH2 in SCCOHT cells and that pharmacological inhibition of EZH2 is a promising therapeutic strategy for treating this disease. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.