Browse
Submit Data
Databases
API
Help

Dataset Information

9 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Proteogenomic Analysis Identifies a Novel Human SHANK3 Isoform.

ABSTRACT: Mutations of the SHANK3 gene have been associated with autism spectrum disorder. Individuals harboring different SHANK3 mutations display considerable heterogeneity in their cognitive impairment, likely due to the high SHANK3 transcriptional diversity. In this study, we report a novel interaction between the Mutated in colorectal cancer (MCC) protein and a newly identified SHANK3 protein isoform in human colon cancer cells and mouse brain tissue. Hence, our proteogenomic analysis identifies a new human long isoform of the key synaptic protein SHANK3 that was not predicted by the human reference genome. Taken together, our findings describe a potential new role for MCC in neurons, a new human SHANK3 long isoform and, importantly, highlight the use of proteomic data towards the re-annotation of GC-rich genomic regions.

SUBMITTER: Benthani F

PROVIDER: S-EPMC4463715 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Proteogenomic Analysis Identifies a Novel Human SHANK3 Isoform.

Benthani Fahad F Tran Phuong N PN Currey Nicola N Ng Irvin I Giry-Laterriere Marc M Carey Louise L Kohonen-Corish Maija R J MR Pangon Laurent L

International journal of molecular sciences 20150519 5

Mutations of the SHANK3 gene have been associated with autism spectrum disorder. Individuals harboring different SHANK3 mutations display considerable heterogeneity in their cognitive impairment, likely due to the high SHANK3 transcriptional diversity. In this study, we report a novel interaction between the Mutated in colorectal cancer (MCC) protein and a newly identified SHANK3 protein isoform in human colon cancer cells and mouse brain tissue. Hence, our proteogenomic analysis identifies a ne ...[more]

PMID: 25997006

Similar Datasets

Proteomics analysis and proteogenomic characterization of different physiopathological human lenses.

Project description:The aim of the present study was to identify the proteomic differences among human lenses in different physiopathological states and to screen for susceptibility genes/proteins via proteogenomic characterization.The total proteomes identified across the regenerative lens with secondary cataract (RLSC), congenital cataract (CC) and age-related cataract (ARC) groups were compared to those of normal lenses using isobaric tagging for relative and absolute protein quantification (iTRAQ). The up-regulated proteins between the groups were subjected to biological analysis. Whole exome sequencing (WES) was performed to detect genetic variations.The most complete human lens proteome to date, which consisted of 1251 proteins, including 55.2% previously unreported proteins, was identified across the experimental groups. Bioinformatics functional annotation revealed the common involvement of cellular metabolic processes, immune responses and protein folding disturbances among the groups. RLSC-over-expressed proteins were characteristically enriched in the intracellular immunological signal transduction pathways. The CC groups featured biological processes relating to gene expression and vascular endothelial growth factor (VEGF) signaling transduction, whereas the molecular functions corresponding to external stress were specific to the ARC groups. Combined with WES, the proteogenomic characterization narrowed the list to 16 candidate causal molecules.These findings revealed common final pathways with diverse upstream regulation of cataractogenesis in different physiopathological states. This proteogenomic characterization shows translational potential for detecting susceptibility genes/proteins in precision medicine.

| S-EPMC5735820 | biostudies-other

Multiomics analysis identifies novel facilitators of human dopaminergic neuron differentiation

Project description:Midbrain dopaminergic neurons (mDANs) control voluntary movement, cognition, and reward behavior under physiological conditions and are implicated in human diseases such as Parkinson's disease (PD). Many transcription factors (TFs) controlling human mDAN differentiation during development have been described, but much of the regulatory landscape remains undefined. Using a tyrosine hydroxylase (TH) human iPSC reporter line, we here generate time series transcriptomic and epigenomic profiles of purified mDANs during differentiation. Integrative analysis predicts novel regulators of mDAN differentiation and super-enhancers are used to identify key TFs. We find LBX1, NHLH1 and NR2F1/2 to promote mDAN differentiation and show that overexpression of either LBX1 or NHLH1 can also improve mDAN specification. A more detailed investigation of TF targets reveals that NHLH1 promotes the induction of neuronal miR-124, LBX1 regulates cholesterol biosynthesis, and NR2F1/2 controls neuronal activity.

| S-SCDT-10_1038-S44319-023-00024-2 | biostudies-other

Proteogenomic Analysis of Salivary Adenoid Cystic Carcinomas Defines Molecular Subtypes and Identifies Therapeutic Targets.

Project description:PurposeSalivary gland adenoid cystic carcinoma (ACC) has heterogeneous clinical behavior. Currently, all patients are treated uniformly, and no standard-of-care systemic therapy exists for metastatic ACC. We conducted an integrated proteogenomic analyses of ACC tumors to identify dysregulated pathways and propose a classification with therapeutic implications.Experimental designRNA/DNA sequencing of 54 flash-frozen salivary ACCs and reverse phase protein array (RPPA) in 38 specimens were performed, with validation by Western blotting and/or IHC. Three independent ACC cohorts were used for validation.ResultsBoth unbiased RNA sequencing (RNA-seq) and RPPA analysis revealed two molecular subtypes: ACC-I (37%) and ACC-II (63%). ACC-I had strong upregulation of MYC, MYC target genes, and mRNA splicing, enrichment of NOTCH-activating mutations, and dramatically worse prognosis. ACC-II exhibited upregulation of TP63 and receptor tyrosine kinases (AXL, MET, and EGFR) and less aggressive clinical course. TP63 and MYC were sufficient to assign tumors to ACC subtypes, which was validated in one independent cohort by IHC and two additional independent cohorts by RNA-seq. Furthermore, IHC staining for MYC and P63 protein levels can be used to identify ACC subtypes, enabling rapid clinical deployment to guide therapeutic decisions. Our data suggest a model in which ACC-I is driven by MYC signaling through either NOTCH mutations or direct amplification, which in turn suppress P63 signaling observed in ACC-II, producing unique therapeutic vulnerabilities for each subtype.ConclusionsCooccurrence of multiple actionable protein/pathways alterations in each subtype indicates unique therapeutic vulnerabilities and opportunities for optimal combination therapy for this understudied and heterogeneous disease.

| S-EPMC7854509 | biostudies-literature

Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities.

Project description:We performed the first proteogenomic study on a prospectively collected colon cancer cohort. Comparative proteomic and phosphoproteomic analysis of paired tumor and normal adjacent tissues produced a catalog of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers, drug targets, and cancer/testis antigens. Proteogenomic integration not only prioritized genomically inferred targets, such as copy-number drivers and mutation-derived neoantigens, but also yielded novel findings. Phosphoproteomics data associated Rb phosphorylation with increased proliferation and decreased apoptosis in colon cancer, which explains why this classical tumor suppressor is amplified in colon tumors and suggests a rationale for targeting Rb phosphorylation in colon cancer. Proteomics identified an association between decreased CD8 T cell infiltration and increased glycolysis in microsatellite instability-high (MSI-H) tumors, suggesting glycolysis as a potential target to overcome the resistance of MSI-H tumors to immune checkpoint blockade. Proteogenomics presents new avenues for biological discoveries and therapeutic development.

| S-EPMC6768830 | biostudies-literature

Proteogenomic analysis of melanoma brain metastases from distinct anatomical sites identifies pathways of metastatic progression.

Project description:Melanoma brain metastases (MBM) portend a grim prognosis and can occur in up to 40% of melanoma patients. Genomic characterization of brain metastases has been previously carried out to identify potential mutational drivers. However, to date a comprehensive multi-omics approach has yet to be used to analyze brain metastases. In this case report, we present an unbiased proteogenomics analyses of a patient's primary skin cancer and three brain metastases from distinct anatomic locations. We performed molecular profiling comprised of a targeted DNA panel and full transcriptome as well as proteomics using mass spectrometry. Phylogeny demonstrated that all MBMs shared a SMARCA4 mutation and deletion of 12q. Proteogenomics identified multiple pathways upregulated in the MBMs compared to the primary tumor. The protein, PIK3CG, was present in many of these pathways and had increased gene expression in metastatic melanoma tissue from the cancer genome atlas data. Proteomics demonstrated PIK3CG levels were significantly increased in all 3 MBMs and this finding was further validated by immunohistochemistry. In summary, this case report highlights the potential role of proteogenomics in identifying pathways involved in metastatic tumor progression. Furthermore, our multi-omics approach can be considered to aid in precision oncology efforts and provide avenues for therapeutic innovation.

| S-EPMC7487560 | biostudies-literature

Comprehensive proteogenomic analysis of human embryonic and induced pluripotent stem cells.

Project description:Although the concepts of somatic cell reprogramming and human-induced pluripotent stem cells (hiPSCs) generation have undergone several analyses to validate the usefulness of these cells in research and clinic, it remains still controversial whether the hiPSCs are equivalent to human embryonic stem cells (hESCs), pointing to the need of further characterization for a more comprehensive understanding of pluripotency. Most of the experimental evidence comes from the transcriptome analysis, while a little is available on protein data, and even less is known about the post-translational modifications. Here, we report a combined strategy of mass spectrometry and gene expression profiling for proteogenomic analysis of reprogrammed and embryonic stem cells. The data obtained through this integrated, multi-"omics" approach indicate that a small, but still significant, number of distinct pathways is enriched in reprogrammed versus embryonic stem cells, supporting the view that pluripotency is an extremely complex, multifaceted phenomenon, with peculiarities that are characteristic of each cell type.

| S-EPMC6653499 | biostudies-literature

Proteogenomic integration of single-cell RNA and protein analysis identifies novel tumour-infiltrating lymphocyte phenotypes in breast cancer

Project description:High-throughput single-cell RNA sequencing (scRNA-Seq) has become a routine platform for the dissection of solid tumours into their cellular components. The development of methods to incorporate detection of cellular protein epitopes via barcoded antibodies has enabled advances in immunophenotyping, but its application to investigating tissue immunology has been limited. We applied joint single cell RNA and epitope analysis to a cohort of 6 breast cancer samples to improve resolution of the tumour microenvironment (TME). We detect cell types unidentifiable by analysis of RNA or protein alone, and reveal novel markers for resting and activated tissue infiltrating lymphocytes (TILs). We further identify two distinct states of activated CD4+ T follicular helper (Tfh) cells in breast cancers – one associated with markers of tissue residency and exhaustion (CD103+ Tfh), and a previously-undescribed phenotype marked by the expression of IGFL2 and NMB (IGFL2+ Tfh). The two Tfh cell subsets occupy distinct TME niches, with CD103+ Tfh cells uniquely co-localizing with and signalling to macrophages. This Tfh cell stratification is clinically important, as the increased ratio of CD103 Tfh to IGFL2+ Tfh cells associates with improved disease outcome and response to checkpoint immunotherapy. Collectively, we provide a framework for improved phenotyping of TILs and showcase how proteogenomics more robustly catalogues the emergence of novel cellular states with clinical significance in tissue contexts such as the TME.

2024-06-30 | GSE199219 | GEO

Integrative proteogenomic analyses of human tumours identifies ADNP as a novel oncogenic mediator of cell cycle progression in high-grade serous ovarian cancer with poor prognosis.

Project description:BackgroundDespite toxic side effects and limited durable response, the current standard-of-care treatment for high grade serous ovarian cancer (HGSOC) remains platinum/taxane-based chemotherapy. Given that the overall prognosis has not improved drastically over the past several decades, there is a critical need to understand the underlying mechanisms that lead to tumour development and progression.MethodsWe utilized an integrative proteogenomic analysis of HGSOC tumours applying a poor prognosis gene expression signature (PPS) as a conceptual framework to analyse orthogonal genomic and proteomic data from the TCGA (n?=?488) and CPTAC (n?=?169) studies. Genes identified through in silico analyses were assessed in vitro studies to demonstrate their impact on proliferation and cell cycle progression.FindingsThese analyses identified DNA amplification and overexpression of the transcription factor ADNP (Activity Dependent Neuroprotector Homeobox) in poorly prognostic tumours. Validation studies confirmed the prognostic capacity of ADNP and suggested an oncogenic role for this protein given the association between ADNP expression and pro-proliferative signalling. In vitro studies confirmed ADNP as a novel and essential mediator of cell proliferation through dysregulation of cell cycle checkpoints.InterpretationWe identified ADNP as being amplified and overexpressed in poor prognosis HGSOC in silico analyses and demonstrated that ADNP is a novel and essential oncogene in HGSOC which mediates proliferation through dysregulation of cell cycle checkpoints in vitro.FundingThe National Cancer Institute of the National Institutes of Health, the V Foundation for Cancer Research and the New Jersey Commission for Cancer Research.

| S-EPMC6921307 | biostudies-literature

Proteogenomic analysis of human chromosome 9-encoded genes from human samples and lung cancer tissues.

Project description:The Chromosome-centric Human Proteome Project (C-HPP) was recently initiated as an international collaborative effort. Our team adopted chromosome 9 (Chr 9) and performed a bioinformatics and proteogenomic analysis to catalog Chr 9-encoded proteins from normal tissues, lung cancer cell lines, and lung cancer tissues. Approximately 74.7% of the Chr 9 genes of the human genome were identified, which included approximately 28% of missing proteins (46 of 162) on Chr 9 compared with the list of missing proteins from the neXtProt Master Table (2013-09). In addition, we performed a comparative proteomics analysis between normal lung and lung cancer tissues. On the basis of the data analysis, 15 proteins from Chr 9 were detected only in lung cancer tissues. Finally, we conducted a proteogenomic analysis to discover Chr 9-residing single nucleotide polymorphisms (SNP) and mutations described in the COSMIC cancer mutation database. We identified 21 SNPs and four mutations containing peptides on Chr 9 from normal human cells/tissues and lung cancer cell lines, respectively. In summary, this study provides valuable information of the human proteome for the scientific community as part of C-HPP. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000603.

| S-EPMC3918476 | biostudies-literature

Proteogenomic characterization and comprehensive integrative genomic analysis of human colorectal cancer liver metastasis.

Project description:BACKGROUND:Proteogenomic characterization and integrative and comparative genomic analysis provide a functional context to annotate genomic abnormalities with prognostic value. METHODS:Here, we analyzed the proteomes and performed whole exome and transcriptome sequencing and single nucleotide polymorphism array profiling for 2 sets of triplet samples comprised of normal colorectal tissue, primary CRC tissue, and synchronous matched liver metastatic tissue. RESULTS:We identified 112 CNV-mRNA-protein correlated molecules, including up-regulated COL1A2 and BGN associated with prognosis, and four strongest hot spots (chromosomes X, 7, 16 and 1) driving global mRNA abundance variation in CRC liver metastasis. Two sites (DMRTB1R202H and PARP4V458I) were revealed to frequent mutate only in the liver metastatic cohort and displayed dysregulated protein abundance. Moreover, we confirmed that the mutated peptide number has potential prognosis value and somatic variants displayed increased protein abundance, including high MYH9 and CCT6A expression, with clinical significance. CONCLUSIONS:Our proteogenomic characterization and integrative and comparative genomic analysis provides a new paradigm for understanding human colon and rectal cancer liver metastasis. TRIAL REGISTRATION:ClinicalTrials, NCT02917707. Registered 28 September 2016, https://clinicaltrials.gov/ct2/show/NCT02917707 .

| S-EPMC6148962 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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