Genomic and transcriptomic landscape of a mouse model for immunotherapy in oral squamous cell carcinoma
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ABSTRACT:
PROVIDER: PRJEB60258 | ENA |
REPOSITORIES: ENA
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Project description:We examined the 4-nitroquinoline-1-oxide (4NQO)-induced oral squamous cell carcinoma (OSCC) model for genetic aberrations, transcriptomic profile, and immune cell compositions at different pathological stages.
2023-08-01 | GSE229289 | GEO
Project description:To investigate the anti-tumor effect of agonistic anti-CD40, 4NQO-indued OSCC mice with agonistic anti-CD40.
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Project description:Oral squamous cell carcinoma (OSCC) is the most common malignancy of the oral cavity and despite therapeutic advances, late-stage diagnoses continue to negatively affect survival, presenting a continuing challenge for clinicians. Detailed molecular characterization by recent bulk and single-cell RNA-sequencing datasets from OSCC suggest that identification of prognostic biomarkers may lead to more targeted therapies, improving patient outcomes. Development of OSCC is associated with exposure to tobacco, alcohol consumption, and infection with human papillomavirus. The mouse model of 4-Nitroquinoline 1-oxide (4NQO) carcinogenesis produces a spectrum of neoplastic lesions that are a robust model of tobacco-induced OSCC. Specifically, studies have shown that similar to human OSCC, mouse OSCC shows upregulation of the oncogenic master transcription factor p63. We performed complementary loss- and gain-of-function experiments of p63 in mouse 4NQO-transformed OSCC cell lines and utilized RNA-sequencing and ChIP-sequencing to uncover the p63 oncogenic network. By combining our signature with publicly available bulk and scRNA-seq data, we generated a murine p63 signature that we have utilized to better understand the role of p63 in mOSCC. Our analyses have identified several potential biomarkers and conserved pathways that are relevant to hOSCC, as well as highlighted the dynamic role of p63 in migration and invasion.
2023-01-10 | GSE217668 | GEO
Project description:Oral squamous cell carcinoma (OSCC) is the most common malignancy of the oral cavity and despite therapeutic advances, late-stage diagnoses continue to negatively affect survival, presenting a continuing challenge for clinicians. Detailed molecular characterization by recent bulk and single-cell RNA-sequencing datasets from OSCC suggest that identification of prognostic biomarkers may lead to more targeted therapies, improving patient outcomes. Development of OSCC is associated with exposure to tobacco, alcohol consumption, and infection with human papillomavirus. The mouse model of 4-Nitroquinoline 1-oxide (4NQO) carcinogenesis produces a spectrum of neoplastic lesions that are a robust model of tobacco-induced OSCC. Specifically, studies have shown that similar to human OSCC, mouse OSCC shows upregulation of the oncogenic master transcription factor p63. We performed complementary loss- and gain-of-function experiments of p63 in mouse 4NQO-transformed OSCC cell lines and utilized RNA-sequencing and ChIP-sequencing to uncover the p63 oncogenic network. By combining our signature with publicly available bulk and scRNA-seq data, we generated a murine p63 signature that we have utilized to better understand the role of p63 in mOSCC. Our analyses have identified several potential biomarkers and conserved pathways that are relevant to hOSCC, as well as highlighted the dynamic role of p63 in migration and invasion.
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Project 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.
2022-04-04 | PXD025701 | Pride
Project description:Oral cavity squamous cell carcinoma (OSCC) is a disease with extensive morbidity and mortality and few useful molecular targets. Multiplatform integrated genomic analysis was performed in order to identify genomic drivers and molecularly discernible tumor subtypes. mRNA, miRNA and methylation data are all submitted to GEO We measured microRNA expression of 43 OSCC cases with Agilent Human miRNA microarray rel12.0
2013-01-01 | E-GEOD-41115 | biostudies-arrayexpress
Project description:Oral cavity squamous cell carcinoma (OSCC) is a disease with extensive morbidity and mortality and few useful molecular targets. Multiplatform integrated genomic analysis was performed in order to identify genomic drivers and molecularly discernible tumor subtypes. mRNA, miRNA and methylation data are all submitted to GEO We measured gene expression of 43 OSCC cases with the Affymetrix Human Exon 1.0 ST Array
2013-01-01 | E-GEOD-41116 | biostudies-arrayexpress
Project description:Oral cavity squamous cell carcinoma (OSCC) is a disease with extensive morbidity and mortality and few useful molecular targets. Multiplatform integrated genomic analysis was performed in order to identify genomic drivers and molecularly discernible tumor subtypes. mRNA, miRNA and methylation data are all submitted to GEO We measured methylation of 42 OSCC tumors, 2 normal oral epithelial tissues, and 2 normal blood samples with Illumina HumanMethylation450 arrays
2013-01-01 | E-GEOD-41114 | biostudies-arrayexpress
Project description:OSCC is associated with substantial mortality and morbidity. To identify potential biomarkers for the early detection of invasive OSCC, we compared the gene expressions of OSCC, oral dysplasia, and normal oral tissue from patients without oral cancer or preneoplastic oral lesions (controls). Results provided models of gene expression to distinguish OSCC from controls. RNA from 167 OSCC, 17 dysplasia and 45 normal oral tissues were extracted and hybridized to Affymetrix U133 2.0 Plus GeneChip arrays. The differentially expressed genes were identified using GenePlus software and the validation was done using RT-PCR, using independent internal and external datasets.
2011-07-21 | E-GEOD-30784 | biostudies-arrayexpress
Project description:In order to identify biomarkers that contribute to genetic causes of OSCC, we attempt to identify copy number variation regions (CNV) in patients with OSCC. We identified and confirmed the clinical significance of amplification regions scattered from 8q22.2 to 8q24.3. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from normal oral tissues and OSCC specimens. Copy number analysis of Affymetrix SNP 6.0 arrays was performed for 112 OSCC specimens and 10 non-cancerous samples.
2011-08-31 | E-GEOD-25103 | biostudies-arrayexpress