MassIVE MSV000099414

Imported Reanalysis Dataset Public PXD025701

Protein markers in Oral Squamous Cell Carcinoma (OSCC)

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Description

Oral squamous cell carcinoma (OSCC) is a main reason of oral cancer mortality and morbidity. Cancer of oral cavity in central south Asia, ranks among third most common kinds of cancer. The discovery of candidate markers to differentiate normal from malignant cells in clinical diagnosis of OSCC would be of critical importance because this malignancy has poor prognosis. To improve the clinical outcome in OSCC patients, the present study was aimed at identifying robust candidate biomarkers for early OSCC diagnosis and to enhance understanding of the mechanisms of disease progression and pathogenesis. Of particular interest are proteins that can be found in tissue lysates of OSCC tumor vs normal adjacent mucosa samples and secreted in cell line Secretomes of HNSCC for non-invasive detection. We analysed 17 paired human malignant OSCC tissues and normal adjacent tissue in addition to secretomes of 9 HNSCC cell lines. The proteome dataset of OSCC and normal tissues consisted of 5,123 protein groups, including 299 proteins with strong differential expression (p-value <0.01, fold change barrier to ?+2 and <-2, 205 upregulated and 94 down regulated) and 134 common proteins were also found out of total dataset of 4473 identified proteins of HNSCC cell line secretomes. Functional data analysis revealed that these differential proteins were significantly associated with multiple biological processes. Myogenesis, Fatty Acid Metabolism and KRAS Signaling DN were associated with the proteins downregulated in cancer tissues, while Protein Secretion, Unfolded Protein Response, Spliceosomal complex assembly, Protein localization to endosome and Interferon Gamma Response were enriched in the set of upregulated proteins and these regulated proteins may be classically or non-classically secreted. Furthermore, we found differential enrichment of Creb3L1, ESRRA, YY, ELF2, STAT1 and XBP transcription factors potentially regulating these major pathways. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Head and neck carcinoma ; Biomarkers. ; Label-free ; Secretome ; Oral squamous cell carcinoma ; DatasetType:Proteomics

Contact

Principal Investigators:
(in alphabetical order) 		Connie Jimenez, Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands, N/A
Submitting User: ccms
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Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.