Differential analysis of MS-data to identify biomarkers or to understand biology is a cornerstone in proteomics. DEqMS is a robust method for analysis of both labelled and label-free MS-data. The ...method takes into account the inherent dependence of protein variance on the number of PSMs or peptides used for quantification, thereby providing a more accurate variance estimation. Compared to current methods, DEqMS achieves better accuracy and statistical power in quantitative proteomics. The tool is available as user-friendly R package.
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Highlights
•DEqMS is a method for statistical analysis of quantitative MS-data.•Variance estimates based on the actual MS-data structure.•Improved statistical power and accuracy in protein differential analysis.•DEqMS is available as a user-friendly R package in Bioconductor.
Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all data sets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several data sets including E. coli proteome spike-in data, using both label-free and TMT-labeled quantification. Compared with previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared with other statistical methods in both label-free and labeled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.
Proteogenomics enable the discovery of novel peptides (from unannotated genomic protein-coding loci) and single amino acid variant peptides (derived from single-nucleotide polymorphisms and ...mutations). Increasing the reliability of these identifications is crucial to ensure their usefulness for genome annotation and potential application as neoantigens in cancer immunotherapy. We here present integrated proteogenomics analysis workflow (IPAW), which combines peptide discovery, curation, and validation. IPAW includes the SpectrumAI tool for automated inspection of MS/MS spectra, eliminating false identifications of single-residue substitution peptides. We employ IPAW to analyze two proteomics data sets acquired from A431 cells and five normal human tissues using extended (pH range, 3-10) high-resolution isoelectric focusing (HiRIEF) pre-fractionation and TMT-based peptide quantitation. The IPAW results provide evidence for the translation of pseudogenes, lncRNAs, short ORFs, alternative ORFs, N-terminal extensions, and intronic sequences. Moreover, our quantitative analysis indicates that protein production from certain pseudogenes and lncRNAs is tissue specific.
Extracellular vesicles (EVs) are increasingly tested as therapeutic vehicles and biomarkers, but still EV subtypes are not fully characterised. To isolate EVs with few co‐isolated entities, a ...combination of methods is needed. However, this is time‐consuming and requires large sample volumes, often not feasible in most clinical studies or in studies where small sample volumes are available. Therefore, we compared EVs rendered by five commonly used methods based on different principles from conditioned cell medium and 250 μl or 3 ml plasma, that is, precipitation (ExoQuick ULTRA), membrane affinity (exoEasy Maxi Kit), size‐exclusion chromatography (qEVoriginal), iodixanol gradient (OptiPrep), and phosphatidylserine affinity (MagCapture). EVs were characterised by electron microscopy, Nanoparticle Tracking Analysis, Bioanalyzer, flow cytometry, and LC‐MS/MS. The different methods yielded samples of different morphology, particle size, and proteomic profile. For the conditioned medium, Izon 35 isolated the highest number of EV proteins followed by exoEasy, which also isolated fewer non‐EV proteins. For the plasma samples, exoEasy isolated a high number of EV proteins and few non‐EV proteins, while Izon 70 isolated the most EV proteins. We conclude that no method is perfect for all studies, rather, different methods are suited depending on sample type and interest in EV subtype, in addition to sample volume and budget.
We present a liquid chromatography-mass spectrometry (LC-MS)-based method permitting unbiased (gene prediction-independent) genome-wide discovery of protein-coding loci in higher eukaryotes. Using ...high-resolution isoelectric focusing (HiRIEF) at the peptide level in the 3.7-5.0 pH range and accurate peptide isoelectric point (pI) prediction, we probed the six-reading-frame translation of the human and mouse genomes and identified 98 and 52 previously undiscovered protein-coding loci, respectively. The method also enabled deep proteome coverage, identifying 13,078 human and 10,637 mouse proteins.
Tartrate-resistant acid phosphatase (TRAP/ACP5), a metalloenzyme that is characteristic for its expression in activated osteoclasts and in macrophages, has recently gained considerable focus as a ...driver of metastasis and was associated with clinically relevant parameters of cancer progression and cancer aggressiveness.
MDA-MB-231 breast cancer cells with different TRAP expression levels (overexpression and knockdown) were generated and characterized for protein expression and activity levels. Functional cell experiments, such as proliferation, migration and invasion assays were performed as well as global phosphoproteomic and proteomic analysis was conducted to connect molecular perturbations to the phenotypic changes.
We identified an association between metastasis-related properties of TRAP-overexpressing MDA-MB-231 breast cancer cells and a TRAP-dependent regulation of Transforming growth factor (TGFβ) pathway proteins and Cluster of differentiation 44 (CD44). Overexpression of TRAP increased anchorage-independent and anchorage-dependent cell growth and proliferation, induced a more elongated cellular morphology and promoted cell migration and invasion. Migration was increased in the presence of the extracellular matrix (ECM) proteins osteopontin and fibronectin and the basement membrane proteins collagen IV and laminin I. TRAP-induced properties were reverted upon shRNA-mediated knockdown of TRAP or treatment with the small molecule TRAP inhibitor 5-PNA. Global phosphoproteomics and proteomics analyses identified possible substrates of TRAP phosphatase activity or signaling intermediates and outlined a TRAP-dependent regulation of proteins involved in cell adhesion and ECM organization. Upregulation of TGFβ isoform 2 (TGFβ2), TGFβ receptor type 1 (TβR1) and Mothers against decapentaplegic homolog 2 (SMAD2), as well as increased intracellular phosphorylation of CD44 were identified upon TRAP perturbation. Functional antibody-mediated blocking and chemical inhibition demonstrated that TRAP-dependent migration and proliferation is regulated via TGFβ2/TβR, whereas proliferation beyond basal levels is regulated through CD44.
Altogether, TRAP promotes metastasis-related cell properties in MDA-MB-231 breast cancer cells via TGFβ2/TβR and CD44, thereby identifying a potential signaling mechanism associated to TRAP action in breast cancer cells.
In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, ...inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.
Protein phosphorylation is involved in the regulation of most eukaryotic cells functions and mass spectrometry-based analysis has made major contributions to our understanding of this regulation. ...However, low abundance of phosphorylated species presents a major challenge in achieving comprehensive phosphoproteome coverage and robust quantification. In this study, we developed a workflow employing titanium dioxide phospho-enrichment coupled with isobaric labeling by Tandem Mass Tags (TMT) and high-resolution isoelectric focusing (HiRIEF) fractionation to perform in-depth quantitative phosphoproteomics starting with a low sample quantity. To benchmark the workflow, we analyzed HeLa cells upon pervanadate treatment or cell cycle arrest in mitosis. Analyzing 300 µg of peptides per sample, we identified 22,712 phosphorylation sites, of which 19,075 were localized with high confidence and 1,203 are phosphorylated tyrosine residues, representing 6.3% of all detected phospho-sites. HiRIEF fractions with the most acidic isoelectric points are enriched in multiply phosphorylated peptides, which represent 18% of all the phospho-peptides detected in the pH range 2.5-3.7. Cross-referencing with the PhosphoSitePlus database reveals 1,264 phosphorylation sites that have not been previously reported and kinase association analysis suggests that a subset of these may be functional during the mitotic phase.
Fanconi anemia (FA) signaling, a key genomic maintenance pathway, is activated in response to replication stress. Here, we report that phosphorylation of the pivotal pathway protein FANCD2 by CHK1 ...triggers its FBXL12-dependent proteasomal degradation, facilitating FANCD2 clearance at stalled replication forks. This promotes efficient DNA replication under conditions of CYCLIN E- and drug-induced replication stress. Reconstituting FANCD2-deficient fibroblasts with phosphodegron mutants failed to re-establish fork progression. In the absence of FBXL12, FANCD2 becomes trapped on chromatin, leading to replication stress and excessive DNA damage. In human cancers, FBXL12, CYCLIN E, and FA signaling are positively correlated, and FBXL12 upregulation is linked to reduced survival in patients with high CYCLIN E-expressing breast tumors. Finally, depletion of FBXL12 exacerbated oncogene-induced replication stress and sensitized cancer cells to drug-induced replication stress by WEE1 inhibition. Collectively, our results indicate that FBXL12 constitutes a vulnerability and a potential therapeutic target in CYCLIN E-overexpressing cancers.
Synaptic dysfunction is an early pathogenic event in Alzheimer disease (AD). Hence the maintenance of healthy neurotransmission becomes crucial to slow or halt cognitive decline. In search of ...identifying proteins that could play a role in synaptic dysfunction, we studied the proteome of a highly vulnerable hippocampal region that is enriched in excitatory synapses. Our in-depth proteomic analysis suggests an impaired presynaptic signaling in AD. Using immunohistochemistry, we verified significantly reduced levels of complexin-1, complexin-2, and synaptogyrin-1 in AD.
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Highlights
•Laser microdissection of highly vulnerable hippocampal region.•Proteomic analysis of postmortem human brain tissue of AD and control cases.•Decreased levels of presynaptic proteins, but not postsynaptic proteins, in AD.•Immunohistochemistry verifies decreased levels of selected presynaptic proteins.
Synaptic dysfunction is an early pathogenic event in Alzheimer disease (AD) that contributes to network disturbances and cognitive decline. Some synapses are more vulnerable than others, including the synapses of the perforant path, which provides the main excitatory input to the hippocampus. To elucidate the molecular mechanisms underlying the dysfunction of these synapses, we performed an explorative proteomic study of the dentate terminal zone of the perforant path. The outer two-thirds of the molecular layer of the dentate gyrus, where the perforant path synapses are located, was microdissected from five subjects with AD and five controls. The microdissected tissues were dissolved and digested by trypsin. Peptides from each sample were labeled with different isobaric tags, pooled together and pre-fractionated into 72 fractions by high-resolution isoelectric focusing. Each fraction was then analyzed by liquid chromatography-mass spectrometry. We quantified the relative expression levels of 7322 proteins, whereof 724 showed significantly altered levels in AD. Our comprehensive data analysis using enrichment and pathway analyses strongly indicated that presynaptic signaling, such as exocytosis and synaptic vesicle cycle processes, is severely disturbed in this area in AD, whereas postsynaptic proteins remained unchanged. Among the significantly altered proteins, we selected three of the most downregulated synaptic proteins; complexin-1, complexin-2 and synaptogyrin-1, for further validation, using a new cohort consisting of six AD and eight control cases. Semi-quantitative analysis of immunohistochemical staining confirmed decreased levels of complexin-1, complexin-2 and synaptogyrin-1 in the outer two-thirds of the molecular layer of the dentate gyrus in AD. Our in-depth proteomic analysis provides extensive knowledge on the potential molecular mechanism underlying synaptic dysfunction related to AD and supports that presynaptic alterations are more important than postsynaptic changes in early stages of the disease. The specific synaptic proteins identified could potentially be targeted to halt synaptic dysfunction in AD.
Drug resistance is a major obstacle to targeted cancer therapies. Here we have used in-depth molecular response profiling and drug screening to investigate early adaptive responses after ...EGFR-inhibition and to identify new combination therapy targets. Response profiling at both mRNA and protein level revealed increased signaling in multiple pathways with the potential to blunt efficacy and cause drug resistance. Inhibition of several of these pathways resulted in synergistic effects together with EGFR-inhibitors, suggesting potential new combination therapy strategies.
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Highlights
•EGFR-TKI molecular response profiling covering 10138 proteins and 13486 mRNAs.•EGFR-TKI combination therapy screen using a library of 528 compounds.•Several new candidate EGFR-TKI escape mechanisms and combination therapy targets.•Combined targeting of the oncogene BCL6 and EGFR results in synergy in NSCLC cells.
Drug resistance is a major obstacle to curative cancer therapies, and increased understanding of the molecular events contributing to resistance would enable better prediction of therapy response, as well as contribute to new targets for combination therapy. Here we have analyzed the early molecular response to epidermal growth factor receptor (EGFR) inhibition using RNA sequencing data covering 13,486 genes and mass spectrometry data covering 10,138 proteins. This analysis revealed a massive response to EGFR inhibition already within the first 24 h, including significant regulation of hundreds of genes known to control downstream signaling, such as transcription factors, kinases, phosphatases and ubiquitin E3-ligases. Importantly, this response included upregulation of key genes in multiple oncogenic signaling pathways that promote proliferation and survival, such as ERBB3, FGFR2, JAK3, and BCL6, indicating an early adaptive response to EGFR inhibition. Using a library of more than 500 approved and experimental compounds in a combination therapy screen, we could show that several kinase inhibitors with targets including JAK3 and FGFR2 increased the response to EGFR inhibitors. Further, we investigated the functional impact of BCL6 upregulation in response to EGFR inhibition using siRNA-based silencing of BCL6. Proteomics profiling revealed that BCL6 inhibited transcription of multiple target genes including p53, resulting in reduced apoptosis which implicates BCL6 upregulation as a new EGFR inhibitor treatment escape mechanism. Finally, we demonstrate that combined treatment targeting both EGFR and BCL6 act synergistically in killing lung cancer cells. In conclusion, or data indicates that multiple different adaptive mechanisms may act in concert to blunt the cellular impact of EGFR inhibition, and we suggest BCL6 as a potential target for EGFR inhibitor-based combination therapy.
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