In-depth Membrane Proteomic Study of Breast Cancer Tissues for the Generation of a Chromosome-based Protein List

Advances in sample preparation for membrane proteome quantification

Membrane proteins mediate various biological processes. Most drugs commercially available target proteins on the cell surface. Therefore, proteomics of plasma membrane proteins provides useful information for drug discovery. However, membrane proteins are one of the most difficult biological groups to quantify by proteomics because of their hydrophobicity and low protein content. To obtain unbiased quantitative membrane proteomics data, specific strategies should be followed during sample preparation. This review explores the most recent advances in sample preparation for the quantitative analysis of the membrane proteome, including enrichment by subcellular fractionation and trypsin digestion.

Icb-1 expression inhibits growth and fulvestrant response of breast cancer cells and affects survival of breast cancer patients

PURPOSE

Human gene icb-1 recently has been reported to be part of a gene expression score predicting response to antiestrogen fulvestrant in breast cancer patients. In the present study, we examined to what extent icb-1 expression would affect the response of breast cancer cells to this antiestrogen in vitro and investigated underlying molecular mechanisms. Using open access mRNA data, we elucidated the significance of icb-1 expression for survival of breast cancer patients.

METHODS

Icb-1 gene expression was knocked down by RNAi. Breast cancer cell growth after treatment with fulvestrant was assessed using the Cell Titer Blue assay. Gene expression was analyzed by Western blot analysis or RT-qPCR. Survival analyses were performed using bioinformatical online tools and data.

RESULTS

Knockdown of icb-1 in T-47D breast cancer cells significantly increased growth of this cell line and also elevated the growth-stimulatory effect of E2 (p < 0.001). After treatment with different concentrations of fulvestrant, icb-1 knockdown cells exhibited a significantly enhanced response to this drug (p < 0.01). On the molecular level, icb-1 knockdown led to elevated expression of ESR1 and its target gene TFF1 (pS2) and enhanced E2-triggered up-regulation of proliferation genes. Finally, bioinformatical meta-analysis of gene expression data of 3951 breast cancer patients revealed that high icb-1 expression increases their relapse-free survival (HR = 0.87, p < 0.05).

CONCLUSION

The presented data further support a tumor-suppressive role of icb-1 in breast cancer and suggest an inhibitory effect of this gene on fulvestrant action, which both are suggested to be mediated by suppression of cellular E2 response.

Optimization of Data-Independent Acquisition Mass Spectrometry for Deep and Highly Sensitive Proteomic Analysis

Data-independent acquisition (DIA)-mass spectrometry (MS)-based proteomic analysis overtop the existing data-dependent acquisition (DDA)-MS-based proteomic analysis to enable deep proteome coverage and precise relative quantitative analysis in single-shot liquid chromatography (LC)-MS/MS. However, DIA-MS-based proteomic analysis has not yet been optimized in terms of system robustness and throughput, particularly for its practical applications. We established a single-shot LC-MS/MS system with an MS measurement time of 90 min for a highly sensitive and deep proteomic analysis by optimizing the conditions of DIA and nanoLC. We identified 7020 and 4068 proteins from 200 ng and 10 ng, respectively, of tryptic floating human embryonic kidney cells 293 (HEK293F) cell digest by performing the constructed LC-MS method with a protein sequence database search. The numbers of identified proteins from 200 ng and 10 ng of tryptic HEK293F increased to 8509 and 5706, respectively, by searching the chromatogram library created by gas-phase fractionated DIA. Moreover, DIA protein quantification was highly reproducible, with median coefficients of variation of 4.3% in eight replicate analyses. We could demonstrate the power of this system by applying the proteomic analysis to detect subtle changes in protein profiles between cerebrums in germ-free and specific pathogen-free mice, which successfully showed that >40 proteins were differentially produced between the cerebrums in the presence or absence of bacteria.

A three-pronged "Pitchfork" strategy enables an extensive description of the human membrane proteome and the identification of missing proteins

Integral membrane proteins are under-represented in standard proteomic analyses, mostly because of their low expression and absence of trypsin-cleavage sites in their hydrophobic transmembrane segments. Novel and effective strategies for membrane proteomic analysis aim at soluble N-glycosylated segments of integral membrane proteins (CSC, SPEG, N-glyco-FASP) or selectively target the hydrophobic transmembrane alpha-helical segments employing chemical peptide cleavage by CNBr (hpTC). We combined a solid phase enrichment of glycopeptides (SPEG) with a transmembrane segment-oriented hpTC method and a standard "detergent and trypsin" approach into a three-pronged "Pitchfork" strategy to maximize the membrane proteome coverage in human lymphoma cells. This strategy enabled the identification of >1200 integral membrane proteins from all cellular compartments, including 105 CD antigens, 24 G protein-coupled receptors, and 141 solute carrier transporters. The advantage of the combination lies in the complementarity of the methods. SPEG and hpTC target different sets of membrane proteins. HpTC provided identifications of proteins and peptides with significantly higher hydrophobicity compared to SPEG and detergent-trypsin approaches. Among all identified proteins, we observed 32 so-called "missing proteins". The Pitchfork strategy presented here is universally applicable and enables deep and fast description of membrane proteomes in only 3 LC-MS/MS runs per replicate. SIGNIFICANCE: Integral membrane proteins (IMPs) are encoded by roughly a quarter of human coding genes. Their functions and their specific localization makes IMPs highly attractive drug targets. In fact, roughly half of the currently approved drugs in medicine target IMPs. Our knowledge of membrane proteomes is, however, limited. We present a new strategy for the membrane proteome analysis that combines three complementary methods targeting different features of IMPs. Using the combined strategy, we identified over 1200 IMPs in human lymphoma tissue from all sub-cellular compartments in only 3 LC-MS/MS runs per replicate. The three-pronged "Pitchfork" strategy is universally applicable, and offers a fast way toward a reasonably concise description of membrane proteomes in multiple samples.

Gender proteomics II. Which proteins in sexual organs

In continuity with the review dealing with differences by gender in non-sexual organs [1], this review collects data on the proteomes of the sexual organs as involved in human reproduction, under both physiological and pathological conditions. It also collects data on the tissue structures and biological fluids typical of pregnancy, such as placenta and amniotic fluid, as well as what may be tested on preimplantation embryos during medically assisted reproduction. The review includes as well mention to all fluids and secretions connected with sex organs and/or reproduction, including sperm and milk, to exemplify two distinctive items in male and female physiology.

SIGNIFICANCE

The causes of infertility are only incompletely understood; the same holds for the causes, and even the early markers, of the most frequent complications of pregnancy. To these established medical challenges, present day practice adds new issues connected with medically assisted reproduction. Omics approaches, including proteomics, are building the database for basic knowledge to possibly translate into clinical testing and eventually into medical routine in this critical branch of health care.

Progress and pitfalls in finding the 'missing proteins' from the human proteome map

INTRODUCTION

The Human Proteome Project was launched with two main goals: the comprehensive and systematic definition of the human proteome map and the development of ready to use analytical tools to measure relevant proteins in their biological context in health and disease. Despite the great progress in this endeavour, there is still a group of reluctant proteins with no, or scarce, experimental evidence supporting their existence. These are called the 'missing proteins' and represent one of the biggest challenges to complete the human proteome map. Areas covered: This review focuses on the description of the missing proteome based on the HUPO standards, the analysis of the reasons explaining the difficulty of detecting missing proteins and the strategies currently used in the search for missing proteins. The present and future of the quest for the missing proteins is critically revised hereafter. Expert commentary: An overarching multidisciplinary effort is currently being done under the HUPO umbrella to allow completion of the human proteome map. It is expected that the detection of missing proteins will grow in the coming years since the methods and the best tissue/cell type sample for their search are already on the table.

Integral membrane proteins in proteomics. How to break open the black box?

Integral membrane proteins (IMPs) are coded by 20-30% of human genes and execute important functions - transmembrane transport, signal transduction, cell-cell communication, cell adhesion to the extracellular matrix, and many other processes. Due to their hydrophobicity, low expression and lack of trypsin cleavage sites in their transmembrane segments, IMPs have been generally under-represented in routine proteomic analyses. However, the field of membrane proteomics has changed markedly in the past decade, namely due to the introduction of filter assisted sample preparation (FASP), the establishment of cell surface capture (CSC) protocols, and the development of methods that enable analysis of the hydrophobic transmembrane segments. This review will summarize the recent developments in the field and outline the most successful strategies for the analysis of integral membrane proteins.

SIGNIFICANCE

Integral membrane proteins (IMPs) are attractive therapeutic targets mostly due to their many important functions. However, our knowledge of the membrane proteome is severely limited to effectively exploit their potential. This is mostly due to the lack of appropriate techniques or methods compatible with the typical features of IMPs, namely hydrophobicity, low expression and lack of trypsin cleavage sites. This review summarizes the most recent development in membrane proteomics and outlines the most successful strategies for their large-scale analysis.

Searching Missing Proteins Based on the Optimization of Membrane Protein Enrichment and Digestion Process

A membrane protein enrichment method composed of ultracentrifugation and detergent-based extraction was first developed based on MCF7 cell line. Then, in-solution digestion with detergents and eFASP (enhanced filter-aided sample preparation) with detergents were compared with the time-consuming in-gel digestion method. Among the in-solution digestion strategies, the eFASP combined with RapiGest identified 1125 membrane proteins. Similarly, the eFASP combined with sodium deoxycholate identified 1069 membrane proteins; however, the in-gel digestion characterized 1091 membrane proteins. Totally, with the five digestion methods, 1390 membrane proteins were identified with ≥1 unique peptides, among which 1345 membrane proteins contain unique peptides ≥2. This is the biggest membrane protein data set for MCF7 cell line and even breast cancer tissue samples. Interestingly, we identified 13 unique peptides belonging to 8 missing proteins (MPs). Finally, eight unique peptides were validated by synthesized peptides. Two proteins were confirmed as MPs, and another two proteins were candidate detections.

Appraisal of the Missing Proteins Based on the mRNAs Bound to Ribosomes

Considering the technical limitations of mass spectrometry in protein identification, the mRNAs bound to ribosomes (RNC-mRNA) are assumed to reflect the mRNAs participating in the translational process. The RNC-mRNA data are reasoned to be useful for appraising the missing proteins. A set of the multiomics data including free-mRNAs, RNC-mRNAs, and proteomes was acquired from three liver cancer cell lines. On the basis of the missing proteins in neXtProt (release 2014-09-19), the bioinformatics analysis was carried out in three phases: (1) finding how many neXtProt missing proteins have or do not have RNA-seq and/or MS/MS evidence, (2) analyzing specific physicochemical and biological properties of the missing proteins that lack both RNA-seq and MS/MS evidence, and (3) analyzing the combined properties of these missing proteins. Total of 1501 missing proteins were found by neither RNC-mRNA nor MS/MS in the three liver cancer cell lines. For these missing proteins, some are expected higher hydrophobicity, unsuitable detection, or sensory functions as properties at the protein level, while some are predicted to have nonexpressing chromatin structures on the corresponding gene level. With further integrated analysis, we could attribute 93% of them (1391/1501) to these causal factors, which result in the expression products scarcely detected by RNA-seq or MS/MS.

Mining Missing Membrane Proteins by High-pH Reverse-Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry

Despite significant efforts in the past decade toward complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still "missing proteins". Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using nonsmall cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip prefractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue was incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet, and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring using synthetic peptides, we provided additional evidence of eight missing proteins including seven with transmembrane helix domains. This study demonstrates that mining missing proteins focused on cancer membrane subproteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224.

IQuant: an automated pipeline for quantitative proteomics based upon isobaric tags

Quantitative proteomics technology based on isobaric tags is playing an important role in proteomic investigation. In this paper, we present an automated software, named IQuant, which integrates a postprocessing tool of protein identification and advanced statistical algorithms to process the MS/MS signals generated from the peptides labeled by isobaric tags and aims at proteomics quantification. The software of IQuant, which is freely downloaded at http://sourceforge.net/projects/iquant/, can run from a graphical user interface and a command-line interface, and can work on both Windows and Linux systems.

Discovery of colorectal cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851.

Metrics for the Human Proteome Project 2013-2014 and strategies for finding missing proteins

One year ago the Human Proteome Project (HPP) leadership designated the baseline metrics for the Human Proteome Project to be based on neXtProt with a total of 13,664 proteins validated at protein evidence level 1 (PE1) by mass spectrometry, antibody-capture, Edman sequencing, or 3D structures. Corresponding chromosome-specific data were provided from PeptideAtlas, GPMdb, and Human Protein Atlas. This year, the neXtProt total is 15,646 and the other resources, which are inputs to neXtProt, have high-quality identifications and additional annotations for 14,012 in PeptideAtlas, 14,869 in GPMdb, and 10,976 in HPA. We propose to remove 638 genes from the denominator that are "uncertain" or "dubious" in Ensembl, UniProt/SwissProt, and neXtProt. That leaves 3844 "missing proteins", currently having no or inadequate documentation, to be found from a new denominator of 19,490 protein-coding genes. We present those tabulations and web links and discuss current strategies to find the missing proteins.