High-Throughput Proteomics and Phosphoproteomics of Rat Tissues Using Microflow Zeno SWATH.

High-throughput tissue proteomics has great potential in the advancement of precision medicine. Here, we investigated the combined sensitivity of trap-elute microflow liquid chromatography with a ZenoTOF for DIA proteomics and phosphoproteomics. Method optimization was conducted on HEK293T cell lines to determine the optimal variable window size, MS2 accumulation time and gradient length. The ZenoTOF 7600 was then compared to the previous generation TripleTOF 6600 using eight rat organs, finding up to 23% more proteins using a fifth of the sample load and a third of the instrument time. Spectral reference libraries generated from Zeno SWATH data in FragPipe (MSFragger-DIA/DIA-NN) contained 4 times more fragment ions than the DIA-NN only library and quantified more proteins. Replicate single-shot phosphopeptide enrichments of 50-100 µg of rat tryptic peptide were analyzed by microflow HPLC using Zeno SWATH without fractionation. Using Spectronaut we quantified a shallow phosphoproteome containing 1000-3000 phosphoprecursors per organ. Promisingly, clear hierarchical clustering of organs was observed with high Pearson correlation coefficients >0.95 between replicate enrichments and median CV of 20%. The combined sensitivity of microflow HPLC with Zeno SWATH allows for the high-throughput quantitation of an extensive proteome and shallow phosphoproteome from small tissue samples.

Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities.

Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.

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

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

Proteomic-based stratification of intermediate-risk prostate cancer patients.

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

Pan-cancer proteomic map of 949 human cell lines.

The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.

Proteomic profiling of idiopathic Parkinson's disease primary patient cells by SWATH-MS.

PURPOSE: Parkinson's disease (PD) is the second most prevalent neurodegenerative disease. It is generally diagnosed clinically after the irreversible loss of dopaminergic neurons and no general biomarkers currently exist. To gain insight into the underlying cellular causes of PD we aimed to quantify the proteomic differences between healthy control and PD patient cells. EXPERIMENTAL DESIGN: Sequential Window Acquisition of all THeoretical Mass Spectra was performed on primary cells from healthy controls and PD patients. RESULTS: In total, 1948 proteins were quantified and 228 proteins were significantly differentially expressed in PD patient cells. In PD patient cells, we identified seven significantly increased proteins involved in the unfolded protein response (UPR) and focused on cells with high and low amounts of PDIA6 and HYOU1. We discovered that PD patients with high amounts of PDIA6 and HYOU1 proteins were more sensitive to endoplasmic reticulum stress, in particular to tunicamycin. Data is available via ProteomeXchange with identifier PXD030723. CONCLUSIONS AND CLINICAL RELEVANCE: This data from primary patient cells has uncovered a critical role of the UPR in patients with PD and may provide insight to the underlying cellular dysfunctions in these patients.

Improved identification and quantification of peptides in mass spectrometry data via chemical and random additive noise elimination (CRANE).

MOTIVATION: The output of electrospray ionization-liquid chromatography mass spectrometry (ESI-LC-MS) is influenced by multiple sources of noise and major contributors can be broadly categorized as baseline, random and chemical noise. Noise has a negative impact on the identification and quantification of peptides, which influences the reliability and reproducibility of MS-based proteomics data. Most attempts at denoising have been made on either spectra or chromatograms independently, thus, important 2D information is lost because the mass-to-charge ratio and retention time dimensions are not considered jointly. RESULTS: This article presents a novel technique for denoising raw ESI-LC-MS data via 2D undecimated wavelet transform, which is applied to proteomics data acquired by data-independent acquisition MS (DIA-MS). We demonstrate that denoising DIA-MS data results in the improvement of peptide identification and quantification in complex biological samples. AVAILABILITY AND IMPLEMENTATION: The software is available on Github (https://github.com/CMRI-ProCan/CRANE). The datasets were obtained from ProteomeXchange (Identifiers-PXD002952 and PXD008651). Preliminary data and intermediate files are available via ProteomeXchange (Identifiers-PXD020529 and PXD025103). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PIONEER: Pipeline for Generating High-Quality Spectral Libraries for DIA-MS Data.

Data-independent-acquisition mass spectrometry (DIA-MS) is a state-of-the-art proteomic technique for high-throughput identification and quantification of peptides and proteins. Interpretation of DIA-MS data relies on the use of a spectral library, which is optimally created from data acquired from the same samples in data-dependent acquisition (DDA) mode. As DIA-MS quantification relies on the spectral libraries, having a high-quality, non-redundant, and comprehensive spectral library is essential. This article describes the major steps for creating a high-quality spectral library using a combination of multiple complementary search engines. We discuss appropriate strategies to control the false discovery rate for the final spectral library as a result of merging multiple searches. © 2021 The Authors Current Protocols © 2021 Wiley Periodicals LLC. Basic Protocol 1: Searching DDA-MS files with multiple search engines Basic Protocol 2: Merging results from multiple search engines Basic Protocol 3: Creating spectral libraries from merged results Alternate Protocol: Using CLI for automating tasks Support Protocol: Creating concatenated FASTA files.

Strategies to enable large-scale proteomics for reproducible research.

Reproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy. We perform 1560 data independent acquisition (DIA)-MS runs of eight samples containing known proportions of ovarian and prostate cancer tissue and yeast, or control HEK293T cells. Replicates are run on six mass spectrometers operating continuously with varying maintenance schedules over four months, interspersed with ~5000 other runs. We utilise negative controls and replicates to remove unwanted variation and enhance biological signal, outperforming existing methods. We also design a method for reducing missing values. Integrating these computational modules into a pipeline (ProNorM), we mitigate variation among instruments over time and accurately predict tissue proportions. We demonstrate how to improve the quantitative analysis of large-scale DIA-MS data, providing a pathway toward clinical proteomics.

Barocycler-Based Concurrent Multiomics Method To Assess Molecular Changes Associated with Atherosclerosis Using Small Amounts of Arterial Tissue from a Single Mouse.

Atherosclerosis is a complex, multifactorial disease characterized by the buildup of plaque in the arterial wall. Apolipoprotein E gene deficient (Apoe-/-) mice serve as a commonly used tool to elucidate the pathophysiology of atherosclerosis because of their propensity to spontaneously develop arterial lesions. To date, however, an integrated omics assessment of atherosclerotic lesions in individual Apoe-/- mice has been challenging because of the small amount of diseased and nondiseased tissue available. To address this current limitation, we developed a multiomics method (Multi-ABLE) based on the proteomic method called accelerated Barocycler lysis and extraction (ABLE) to assess the depth of information that can be obtained from arterial tissue derived from a single mouse by splitting ABLE to allow for a combined proteomics-metabolomics-lipidomics analysis (Multi-ABLE). The new method includes tissue lysis via pressure cycling technology (PCT) in a Barocycler, followed by proteomic analysis of half the sample by nanoLC-MS and sequential extraction of lipids (organic extract) and metabolites (aqueous extract) combined with HILIC and reversed phase chromatography and time-of-flight mass spectrometry on the other half. Proteomic analysis identified 845 proteins, 93 of which were significantly altered in lesion-containing arteries. Lipidomic and metabolomic analyses detected 851 lipid and 362 metabolite features, which included 215 and 65 identified lipids and metabolites, respectively. The Multi-ABLE method is the first to apply a concurrent multiomics pipeline to cardiovascular disease using small (<5 mg) tissue samples, and it is applicable to other diseases where limited size samples are available at specific points during disease progression.

Addressing the Challenges of High-Throughput Cancer Tissue Proteomics for Clinical Application: ProCan.

The cancer tissue proteome has enormous potential as a source of novel predictive biomarkers in oncology. Progress in the development of mass spectrometry (MS)-based tissue proteomics now presents an opportunity to exploit this by applying the strategies of comprehensive molecular profiling and big-data analytics that are refined in other fields of 'omics research. ProCan (ProCan is a registered trademark) is a program aiming to generate high-quality tissue proteomic data across a broad spectrum of cancer types. It is based on data-independent acquisition-MS proteomic analysis of annotated tissue samples sourced through collaboration with expert clinical and cancer research groups. The practical requirements of a high-throughput translational research program have shaped the approach that ProCan is taking to address challenges in study design, sample preparation, raw data acquisition, and data analysis. The ultimate goal is to establish a large proteomics knowledge-base that, in combination with other cancer 'omics data, will accelerate cancer research.

A Case Study and Methodology for OpenSWATH Parameter Optimization Using the ProCan90 Data Set and 45 810 Computational Analysis Runs.

In the current study, we show how ProCan90, a curated data set of HEK293 technical replicates, can be used to optimize the configuration options for algorithms in the OpenSWATH pipeline. Furthermore, we use this case study as a proof of concept for horizontal scaling of such a pipeline to allow 45 810 computational analysis runs of OpenSWATH to be completed within four and a half days on a budget of US $10 000. Through the use of Amazon Web Services (AWS), we have successfully processed each of the ProCan 90 files with 506 combinations of input parameters. In total, the project consumed more than 340 000 core hours of compute and generated in excess of 26 TB of data. Using the resulting data and a set of quantitative metrics, we show an analysis pathway that allows the calculation of two optimal parameter sets, one for a compute rich environment (where run time is not a constraint), and another for a compute poor environment (where run time is optimized). For the same input files and the compute rich parameter set, we show a 29.8% improvement in the number of quality protein (>2 peptide) identifications found compared to the current OpenSWATH defaults, with negligible adverse effects on quantification reproducibility or drop in identification confidence, and a median run time of 75 min (103% increase). For the compute poor parameter set, we find a 55% improvement in the run time from the default parameter set, at the expense of a 3.4% decrease in the number of quality protein identifications, and an intensity CV decrease from 14.0% to 13.7%.

Accelerated Barocycler Lysis and Extraction Sample Preparation for Clinical Proteomics by Mass Spectrometry.

We have developed a streamlined proteomic sample preparation protocol termed Accelerated Barocycler Lysis and Extraction (ABLE) that substantially reduces the time and cost of tissue sample processing. ABLE is based on pressure cycling technology (PCT) for rapid tissue solubilization and reliable, controlled proteolytic digestion. Here, a previously reported PCT based protocol was optimized using 1-4 mg biopsy punches from rat kidney. The tissue denaturant urea was substituted with a combination of sodium deoxycholate (SDC) and N-propanol. ABLE produced comparable numbers of protein identifications in half the sample preparation time, being ready for MS injection in 3 h compared with 6 h for the conventional urea based method. To validate ABLE, it was applied to a diverse range of rat tissues (kidney, lung, muscle, brain, testis), human HEK 293 cell lines, and human ovarian cancer samples, followed by SWATH-mass spectrometry (SWATH-MS). There were similar numbers of quantified proteins between ABLE-SWATH and the conventional method, with greater than 70% overlap for all sample types, except muscle (58%). The ABLE protocol offers a standardized, high-throughput, efficient, and reproducible proteomic preparation method that when coupled with SWATH-MS has the potential to accelerate proteomics analysis to achieve a clinically relevant turn-around time.

Characterization of inter-crystallite peptides in human enamel rods reveals contribution by the Y allele of amelogenin.

Proteins of the inter-rod sheath and peptides within the narrow inter-crystallite space of the rod structure are considered largely responsible for visco-elastic and visco-plastic properties of enamel. The present study was designed to investigate putative peptides of the inter-crystallite space. Entities of 1-6 kDa extracted from enamel rods of erupted permanent teeth were analysed by mass spectrometry (MS) and shown to comprise N-terminal amelogenin (AMEL) peptides either containing or not containing exon 4 product. Other dominant entities consisted of an N-terminal peptide from ameloblastin (AMBN) and a series of the most hydrophobic peptides from serum albumin (ALBN). Amelogenin peptides encoded by the Y-chromosome allele were strongly detected in Enamel from male teeth. Location of N-terminal AMEL peptides as well as AMBN and ALBN, between apatite crystallites, was disclosed by immunogold scanning electron microscopy (SEM). Density plots confirmed the relative abundance of these products including exon 4+ AMEL peptides that have greater capacity for binding to hydroxyapatite. Hydrophilic X and Y peptides encoded in exon 4 differ only in substitution of non-polar isoleucine in Y for polar threonine in X with reduced disruption of the hydrophobic N-terminal structure in the Y form. Despite similarity of X and Y alleles of AMEL the non-coding region upstream from exon 4 shows significant variation with implications for segregation of processing of transcripts from exon 4. Detection of fragments from multiple additional proteins including keratins (KER), fetuin A (FETUA), proteinases and proteinase inhibitors, likely reflect biochemical events during enamel formation.

The Impact of Commonly Used Alkylating Agents on Artifactual Peptide Modification.

Iodoacetamide is by far the most commonly used agent for alkylation of cysteine during sample preparation for proteomics. An alternative, 2-chloroacetamide, has recently been suggested to reduce the alkylation of residues other than cysteine, such as the N-terminus, Asp, Glu, Lys, Ser, Thr, and Tyr. Here we show that although 2-chloroacetamide reduces the level of off-target alkylation, it exhibits a range of adverse effects. The most significant of these is methionine oxidation, which increases to a maximum of 40% of all Met-containing peptides, compared with 2-5% with iodoacetamide. Increases were also observed for mono- and dioxidized tryptophan. No additional differences between the alkylating reagents were observed for a range of other post-translational modifications and digestion parameters. The deleterious effects were observed for 2-chloroacetamide from three separate suppliers. The adverse impact of 2-chloroacetamide on methionine oxidation suggests that it is not the ideal alkylating reagent for proteomics.

FD5180, a Novel Protein Kinase Affinity Probe, and the Effect of Bead Loading on Protein Kinase Identification.

The effects of compound loading on the identification of protein kinases (PKs) was examined using two previously reported sepharose-supported PK inhibitors (PKIs): bisindolylmaleimide X (S1) and CZC8004 (S2). Compound loadings of 0.1, 0.5, 2.5, 5, 10, 25, and 50% content and an ethanolamine-blocked control bead (no compound) were investigated. A 50% bead loading gave the highest level of PK identification for both S1 and S2, extracting 34 and 55 PKs, respectively, from a single cell lysate. Control beads allowed overall identification of 23 PKs, which we term the kinase beadome, whereas sepharose-supported sunitinib (S7; 50% loading) identified 20, 11 of which were common to the control beads. The reliability of bead pull-downs was examined in duplicate experiments using two independently synthesized batches each of S1 and S2. Bead S1 showed high similarity in the absolute numbers of PKs identified across two experiments, at 40 and 35 PKs, of which 26 were common across the two batches of beads, with 14 and 9 unique PKs identified in each experiment. The S2 beads extracted 61 and 64 PKs with 55 PKs common across the two bead batches examined. We also report on the development and use of a novel promiscuous PKI analogue, 2-[(5-chloro-2{[4-(piperazin-1-yl)phenyl]amino}pyrimidin-4-yl)amino]-N-methylbenzene-sulfonamide (S15), which extracted 12 additional unique PKs over the two parent compounds from which it was designed, the combination of which identifies 160 unique PKs. S15 was based on the common pyrimidine core scaffold of S9 and S10. Thus, S15 expands the utility of kinobeads by broadening the kinome coverage for bead-based pull-down. Combining the data for all beads across 90 and 180 min liquid chromatography-mass spectrometry (LC-MS)/MS analysis identified a total of 160 unique PKs.

IQGAP1 is associated with nuclear envelope reformation and completion of abscission.

The final stage of mitosis is cytokinesis, which results in 2 independent daughter cells. Cytokinesis has 2 phases: membrane ingression followed by membrane abscission. IQGAP1 is a scaffold protein that interacts with proteins implicated in mitosis, including F-actin, myosin and CaM. IQGAP1 in yeast recruits actin and myosin II filaments to the contractile ring for membrane ingression. In contrast, we show that mammalian IQGAP1 is not required for ingression, but coordinates nuclear pore complex (NPC) reassembly and completion of abscission. Depletion of IQGAP1 disrupts Nup98 and mAb414 nuclear envelope localization and delays abscission timing. IQGAP1 phosphorylation increases 15-fold upon mitotic entry at S86, S330 and T1434, with the latter site being targeted by CDK2/Cyclin A and CDK1/Cyclin A/B in vitro. Expressing the phospho-deficient mutant IQGAP1-S330A impairs NPC reassembly in cells undergoing abscission. Thus, mammalian IQGAP1 functions later in mitosis than its yeast counterpart to regulate nuclear pore assembly in a S330 phosphorylation-dependent manner during the abscission phase of cytokinesis.

Characterization of monomeric and multimeric snake neurotoxins and other bioactive proteins from the venom of the lethal Australian common copperhead (Austrelaps superbus).

Envenomation by Australian copperheads results mainly in muscle paralysis largely attributed to the presence of postsynaptic α-neurotoxins. However, poorly reversible neurotoxic effects suggest that these venoms may contain snake presynaptic phospholipase A2 neurotoxins (SPANs) that irreversibly inhibit neurotransmitter release. Using size-exclusion liquid chromatography, the present study isolated the first multimeric SPAN complex from the venom of the Australian common copperhead, Austrelaps superbus. The multimeric SPAN P-elapitoxin-As1a (P-EPTX-As1a) along with two novel monomeric SPANs and a new postsynaptic α-neurotoxin were then pharmacologically characterized using the chick biventer cervicis nerve-muscle preparation. All SPANs inhibited nerve-evoked twitch contractions at the neuromuscular junction without inhibiting contractile responses to cholinergic agonists or KCl. These actions are consistent with a prejunctional action to inhibit neurotransmitter release, without direct myotoxicity. Furthermore, the multimeric P-EPTX-As1a caused tetanic 'fade' in muscle tension under high frequency nerve stimulation, and produced a triphasic alteration to neurotransmitter release. These actions have been previously noted with other multimeric SPAN complexes such as taipoxin. Moreover, the neurotoxic α-subunit of P-EPTX-As1a shows high homology to taipoxin α-chain. Several other coagulopathic and myotoxic high mass proteins including a class PIII snake venom metalloproteinase, C-type lectin, l-amino acid oxidase, acetylcholinesterase and phospholipase B were also identified that may contribute to the overall toxicity of A. superbus venom. In conclusion, clinicians should be aware that early antivenom intervention might be necessary to prevent the onset of irreversible presynaptic neurotoxicity caused by multimeric and monomeric SPANs and that A. superbus venom is potentially capable of producing coagulopathic and myotoxic effects.

Cloning and activity of a novel α-latrotoxin from red-back spider venom.

The venom of the European black widow spider Latrodectus tredecimguttatus (Theridiidae) contains several high molecular mass (110-140 kDa) neurotoxins that induce neurotransmitter exocytosis. These include a vertebrate-specific α-latrotoxin (α-LTX-Lt1a) responsible for the clinical symptoms of latrodectism and numerous insect-specific latroinsectoxins (LITs). In contrast, little is known about the expression of these toxins in other Latrodectus species despite the fact that envenomation by these spiders induces a similar clinical syndrome. Here we report highly conserved α-LTX, α-LIT and δ-LIT sequence tags in Latrodectus mactans, Latrodectus hesperus and Latrodectus hasselti venoms using tandem mass spectrometry, following bioassay-guided separation of venoms by liquid chromatography. Despite this sequence similarity, we show that the anti-α-LTX monoclonal antibody 4C4.1, raised against α-LTX-Lt1a, fails to neutralize the neurotoxicity of all other Latrodectus venoms tested in an isolated chick biventer cervicis nerve-muscle bioassay. This suggests that there are important structural differences between α-LTXs in theridiid spider venoms. We therefore cloned and sequenced the α-LTX from the Australian red-back spider L. hasselti (α-LTX-Lh1a). The deduced amino acid sequence of the mature α-LTX-Lh1a comprises 1180 residues (∼132kDa) with ∼93% sequence identity with α-LTX-Lt1a. α-LTX-Lh1a is composed of an N-terminal domain and a central region containing 22 ankyrin-like repeats. The presence of two furin cleavage sites, conserved with α-LTX-Lt1a, indicates that α-LTX-Lh1a is derived from the proteolytic cleavage of an N-terminal signal peptide and C-terminal propeptide region. However, we show that α-LTX-Lh1a has key substitutions in the 4C4.1 epitope that explains the lack of binding of the monoclonal antibody.

Prognostic association of YB-1 expression in breast cancers: a matter of antibody.

The literature concerning the subcellular location of Y-box binding protein 1 (YB-1), its abundance in normal and cancer tissues, and its prognostic significance is replete with inconsistencies. An explanation for this could be due in part to the use of different antibodies in immunohistochemical and immunofluorescent labeling of cells and tissues. The inconsistencies could also be due to poor resolution of immunohistochemical data. We analyzed two cohorts of breast tumours for both abundance and subcellular location of YB-1 using three different antibodies; two targeting N-terminal epitopes (AB-a and AB-b) and another (AB-c) targeting a C-terminal epitope. We also investigated stress-induced nuclear translocation of YB-1 in cell culture. We report that both AB-a and AB-c detected increased YB-1 in the cytoplasm of high-grade breast cancers, and in those lacking estrogen and progesterone receptors; however the amount of YB-1 detected by AB-a in these cancers is significantly greater than that detected by AB-c. We confirm our previously published findings that AB-b is also detecting hnRNP A1, and cannot therefore be used to reliably detect YB-1 by immunohistochemistry. We also report that AB-a detected nuclear YB-1 in some tumour tissues and stress treated cells, whereas AB-c did not. To understand this, cancer cell lines were analyzed using native gel electrophoresis, which revealed that the antibodies detect different complexes in which YB-1 is a component. Our data suggest that different YB-1 antibodies show different staining patterns that are determined by the accessibility of epitopes, and this depends on the nature of the YB-1 complexes. It is important therefore to standardize the protocols if YB-1 is to be used reproducibly as a prognostic guide for different cancers.