Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multi-omics Study of Single Nucleotide Variants (SNVs) in CRC Cancer Cell Lines

ABSTRACT: We comprehensively investigating mutated peptide detection in CRC cell lines. Transcriptome collected from cell lines, gather the sets of nsSNVs that are express in RNA level to construct customized mutated protein libraries, MaxQuant was used to searched the libraries against shotgun MS data obtain from the same sample. Then, various characteristics of the detected mutated peptides were described, including identification number, identification overlap, and peptide quality.

ORGANISM(S): Homo Sapiens

SUBMITTER: Siqi Liu

PROVIDER: PXD061293 | iProX | Wed Feb 26 00:00:00 GMT 2025

REPOSITORIES: iProX

ACCESS DATA

Json Xml

Similar Datasets

Identification of mutated peptides based on the SNVs dataset derived from translatome

Project description:We comprehensively investigating mutated peptide detection in HCT116 human cell line. We collected transcriptome and translatome data from HCT116, gather the sets of nsSNVs that are express in two different RNA level to construct two customized mutated protein libraries, in addition, a non-customized library was constructed utilizing nsSNVs downloaded from COSMIC database. MaxQuant was used to searched the libraries against shotgun MS data obtain from the same sample. Then, various characteristics of the detected mutated peptides were described, including identification number, identification overlap, and peptide quality.

2022-06-28 | PXD034951 |

Sensitive direct detection of cancer antigens enabled by user-defined peptide libraries

Project description:Data dependent mass spectrometry (MS) is routinely used to identify HLA-bound peptides but it can have limitations in sensitivity and reproducibility. We introduce Pepyrus, a method that uses E. coli to generate large-scale user-defined peptide libraries that can be utilized to improve the confidence in identification of HLA-bound peptides, including lowly abundant neoantigens. Using a Pepyrus peptide library paired with an HLA-specific data independent acquisition (DIA) MS strategy, we recovered >75% of the expected sequences per single injection for libraries of >10,000 peptides. Pepyrus peptide libraries also enabled the identification of 0.1 fmol spiked-in peptides in a complex background. Application of Pepyrus to create personalized peptide libraries facilitated the identification of clinically relevant HLA antigens from melanoma and renal cell carcinoma patient derived cell lines, several of which were previously undetected. Pepyrus customization enables rapid creation of patient- or disease-specific peptide libraries facilitating the confident identification of rare HLA peptides from immunopeptidomics data and the generation of large training datasets to improve spectrum, retention time, and IM prediction tools.

2025-11-20 | GSE309497 | GEO

Homo sapiens

Project description:CD40 and TANK peptide libraries

| PRJNA307051 | ENA

Human CRC cell line baseline phosphoproteomics

Project description:There is a need for robust phosphopeptide enrichment methods to allow signaling network analysis in cancer cell lines and tissues with minimal fractionation. With recent instrument developments thousands of unique phosphopeptides can be detected by single-shot LC-MS/MS. However, successful phosphoproteomics experiments still rely on efficient phosphopeptide enrichment from a tryptic digest prior to LC-MS/MS analysis. Here we describe a performance assessment of HAMMOC (hydroxyl acid modified metal affinity chromatography) (Sugiyama MCP2007, Kyono, JPR 2008) combined with single shot label-free quantitation at 500 µg peptide input level. We apply the method to profile the baseline phosphorylation landscape of a panel of 8 colorectal cancer (CRC) cell lines. These CRC cell lines represent the 3 CRC subtypes (CCS1, CCS2 and CCS3) as reported by large-scale transcriptome analysis. We report an analysis of the phosphoprotein network and processes enriched in the cell lines representing the poor prognosis CCS3 subtype.

2015-04-15 | PXD001550 | Pride

Reproducibility of label-free single-shot phosphoproteomics applied to CRC cell lines

Project description:There is a need for robust phosphopeptide enrichment methods to allow signaling network analysis in cancer cell lines and tissues with minimal fractionation. With recent instrument developments thousands of unique phosphopeptides can be detected by single-shot LC-MS/MS. However, successful phosphoproteomics experiments still rely on efficient phosphopeptide enrichment from a tryptic digest prior to LC-MS/MS analysis. Here we describe a performance assessment of HAMMOC (hydroxyl acid modified metal affinity chromatography) (Sugiyama MCP2007, Kyono, JPR 2008) combined with single shot label-free quantitation at 500 µg peptide input level. In a triplicate analysis we observe good phosphopeptide identification reproducibility (75.8%), depth of identification (6014-6150 phosphopeptides) and reproducibility of label-free quantification (CV 17.8%, Pearson r 0.87-0.98) by single-shot LC-MS/MS.

2015-04-15 | PXD001546 | Pride

Immunogenic epitopes of the meningioma-associated antigen TXNDC16

Project description:We used customized peptide arrays of 163 TXNDC16 peptides to identify immunogenic TXNDC16 epitopes and asked whether discrimination of meningioma and control sera is possible with a specific subset selection of all immunogenic epitopes.

2014-07-01 | GSE58949 | GEO

Saccharomyces cerevisiae BY4741

Project description:Nanopore sequencing improves construction of customized CRISPR-based gene activation libraries

| PRJNA1049995 | ENA

Targeting MDM4/MDM2 binding interface for reactivation of p53 in cancer therapy

Project description:The aim of this experiment has been to investigate the transcriptional profile of HCT116 cells treated with Peptide-3 (Pep3) compared to untreated (NT), treated with solvent (DMSO) or with a mutated peptide (Pep3M) cells. Peptide-3 is a dodecapeptide able to interact with MDM2 at the levels of the interaction region of the MDM4 and MDM2 proteins, thereby interfering with the coopeartivy function of the proteins in the regulation of p53. This peptide is indeed able to specifically activate p53 and to cause apoptotis in different cancer cell lines and tumor growth inhibition in xenograft models.

2017-04-18 | GSE62855 | GEO

Human CRC cell line baseline phosphoproteomics

2017-03-29 | MSV000080788 | MassIVE

Reproducibility, specificity and accuracy of DIA quantification - DIA analysis

Project description:For the complete description see the manuscript. Data dependent acquisition (DDA) is the method of choice for mass spectrometry based proteomics discovery experiments, data-independent acquisition (DIA) is steadily becoming more important. One of the most important requirement to perform a DIA analysis is the availability of spectral libraries for the peptide identification and quantification. Several researches were already conducted regarding the creation of spectral libraries from DDA analyses and obtaining identifications with these in DIA measurements. But so far only few experiments were conducted, to estimate the effect of these libraries on the quantitative level. In this work we created a spike-in gold standard dataset with known contents and ratios of proteins in a complex sample matrix. With this dataset, we first created spectral libraries using different sample preparation approaches with and without sample prefractionation on peptide and protein level. Two different search engines were used for protein identification. In total, five different spike-in states were compared with DIA analyses, comparing eight different spectral libraries generated by varying approaches and one library free method, as well as one default DDA analysis. Not only the number of identifications on peptide and protein level in the spectral libraries and the corresponding analyses was inspected, but also the number of expected and identified significant quantifications and their ratios were thoroughly examined.

2019-11-08 | PXD012988 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data