A Curated Resource for Phosphosite-specific Signature Analysis

Krug, Karsten; Mertins, Philipp; Zhang, Bin; Hornbeck, Peter; Raju, Rajesh; Ahmad, Rushdy; Szucs, Matthew J.; Mundt, Filip; Forestier, Dominique; Jané‐Valbuena, Judit; Keshishian, Hasmik; Gillette, Michael A.; Tamayo, Pablo; Mesirov, Jill P.; Jaffe, Jacob D.; Carr, Steven A.; Mani, D. R.

doi:10.1074/mcp.tir118.000943

Cited by 219 publications

(331 citation statements)

References 45 publications

(42 reference statements)

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“…Furthermore, phosphosite-specific signature analysis showed to be able to identify dysregulation of phosphorylation-regulated pathways in cancer (18).…”

Section: Introductionmentioning

confidence: 99%

Mass spectrometry based immunopeptidomics leads to robust predictions of phosphorylated HLA class I ligands

Solleder

Guillaume

Racle

et al. 2019

Preprint

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Declaration of Interest:The authors declare no potential conflicts of interest. AbstractThe presentation of peptides on class I human leukocyte antigen (HLA-I) molecules plays a central role in immune recognition of infected or malignant cells. In cancer, non-self HLA-I ligands can arise from many different alterations, including non-synonymous mutations, gene fusion, cancer-specific alternative mRNA splicing or aberrant post-translational modifications. Identifying HLA-I ligands remains a challenging task that requires either heavy experimental work for in-vivo identification or optimized bioinformatics tools for accurate predictions. To date, no HLA-I ligand predictor includes post-translational modifications. To fill this gap, we curated phosphorylated HLA-I ligands from several immunopeptidomics studies (including six newly measured samples) covering 72 HLA-I alleles, and retrieved a total of 2,066 unique phosphorylated peptides. We then expanded our motif deconvolution tool to identify precise binding motifs of phosphorylated HLA-I ligands.Our results reveal a clear enrichment of phosphorylated peptides among HLA-C ligands and demonstrate a prevalent role of both HLA-I motifs and kinase motifs on the presentation of phosphorylated peptides. This data further enabled us to develop and validate the first predictor of interactions between HLA-I molecules and phosphorylated peptides.

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“…Furthermore, phosphosite-specific signature analysis showed to be able to identify dysregulation of phosphorylation-regulated pathways in cancer (18).…”

Section: Introductionmentioning

confidence: 99%

Mass spectrometry based immunopeptidomics leads to robust predictions of phosphorylated HLA class I ligands

Solleder

Guillaume

Racle

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…In this regard, we would like to comment that the LINCS data generation effort is on-going and we expect the number of signatures available as part of this step of analysis to grow over time. We also aim to further integrate piNET and its visualization engine with the recently published PTMsigDB that enables PTM-Signature Enrichment Analysis (PTM-SEA) of phospho signature data (32), and thus should alleviate some of the above mentioned limitations as well. Table 1.…”

Section: Discussionmentioning

confidence: 99%

piNET: a versatile web platform for downstream analysis and visualization of proteomics data

Shamsaei

Chojnacki

Pilarczyk

et al. 2019

Preprint

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Large proteomics data, including those generated by mass spectrometry, are being generated to characterize biological systems at the protein level. Computational methods and tools to identify and quantify peptides, proteins and post-translational modifications (PTMs) that are captured in modern mass spectrometers have matured over the years. On the other hand, tools for downstream analysis, interpretation and visualization of proteomics data sets, in particular those involving PTMs, require further improvement and integration to accelerate scientific discovery and maximize the impact of proteomics studies by connecting them better with biological knowledge across not only proteomics, but also other Omics domains. With the goal of addressing these challenges, the piNET server has been developed as a versatile web platform to facilitate mapping, annotation, analysis and visualization of peptide, PTM, and protein level quantitative data generated by either targeted, shotgun or other proteomics approaches. Building on our experience with large scale analysis of gene and protein expression profiles as part of the Library of Integrated Network Cellular Signatures (LINCS) project, piNET has been designed as a fast, versatile and easy to use web-based tool with three modules that provide mapping from peptides (with PTMs) to proteins, from PTM sites to modifying enzymes that target those sites, and finally from proteins (with PTMs) to pathways, and for further mechanistic insights to LINCS signatures of chemical and genetic perturbations. piNET is freely available at http://www.pinet-server.org.

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“…Functional Annotation Tool v6.8 (https://david.ncifcrf.gov/summary.jsp) with all detected proteins in this study as background (Fig 5e). The compound responses were enriched by phosphorylation sitespecific functional enrichment through ssGSEA2.0/PTM-SEA 59 . Sequence analysis (Figs 5f and 6d) was conducted and visualized by IceLogo (https://iomics.ugent.be/icelogoserver/) 60 .…”

Section: Functional Annotation Was Carried Out In Davidmentioning

confidence: 99%

Global impact of phosphorylation on protein endurance

et al. 2020

Preprint

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Post-translational modifications such as phosphorylation can have profound effects on the physicochemical and biological properties of proteins. However, high-throughput and systematic approaches have not yet been developed to assess the effects of specific modification types and sites on protein lifetime, which represents a key parameter for understanding signaling rewiring and drug development. Here we describe a proteomic method, DeltaSILAC, to quantify the impact of site-specific phosphorylation on the endurance of thousands of proteins in live cells. Being configured on the reproducible data-independent acquisition mass spectrometry (DIA-MS), the pulse labeling approach using stable isotope-labeled amino acids in cells (SILAC), together with a novel peptide-level matching strategy, this multiplexed assay revealed the global delaying effect of phosphorylation on protein turnover in growing cancer cells. Further, we identified local sequence and structural features in proximity to the phosphorylated sites that could be associated with protein endurance alterations. We found that phosphorylated sites accelerating protein turnover are functionally selected for cell fitness and evolutionarily conserved. DeltaSILAC provides a generalizable approach for prioritizing the effects of phosphorylation sites on protein lifetime in the context of cell signaling and disease biology, which is highly complementary to existing methods. Finally, DeltaSILAC is widely applicable to diverse posttranslational modification types and different cell systems.

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A Curated Resource for Phosphosite-specific Signature Analysis

Cited by 219 publications

References 45 publications

Mass spectrometry based immunopeptidomics leads to robust predictions of phosphorylated HLA class I ligands

Mass spectrometry based immunopeptidomics leads to robust predictions of phosphorylated HLA class I ligands

piNET: a versatile web platform for downstream analysis and visualization of proteomics data

Global impact of phosphorylation on protein endurance

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