Gene expression of mouse oral cancer cell lines
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ABSTRACT:
PROVIDER: PRJNA579101 | ENA |
REPOSITORIES: ENA
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Project description:A comparative microarray analysis of indolent or aggressive mouse oral cancer cell lines was performed to identify gene expression signatures and specific molecules involved in aggressive tumor growth.
2014-04-13 | GSE50041 | GEO
Project description:A comparative microarray analysis of indolent or aggressive mouse oral cancer cell lines was performed to identify gene expression signatures and specific molecules involved in aggressive tumor growth. We compared 3 indolent cell lines (MOC1, MOC22, MOC23) to 1 aggressive line and it's derivatives (MOC2, MOC2-7 and MOC2-10). We also included a cell line generated from a lymph node metastasis of the MOC2 tumor. The lines were all analyzed in triplicated except for MOC1 which was done in quadruplicate. Finally, we included duplicate samples of primary, normal C57BL/6 oral keratinocytes grown in the same media as the MOC cell lines.
2014-04-13 | E-GEOD-50041 | biostudies-arrayexpress
Project description:To genome-wide screening for the genes whose expression are responsible for the promoter DNA methylation, we performed the cDNA microarray with oral cancer cells before and after a DNA methyltransferase inhibitor, 5-aza-2’-deoxycytidine (AzC), treatment. Total RNA was collected from four oral cancer cell lines before or after AzC treatment.
2015-04-01 | E-GEOD-38823 | biostudies-arrayexpress
Project description:We established two murine OSCC cell lines, named M1-2 and M2-3, from a mouse tumor induced by 4-nitroquinoline 1-oxide (4-NQO)/arecoline. After in vitro selection using sphere culture, NHRI-HN1 and NHRI-HN2 were derived from M1-2 and M2-3 cells, respectively. Only NHRI-HN1 cells are capable of generating orthotopic tumors in syngeneic mice.
2022-09-21 | GSE139282 | GEO
Project description:In Taiwan, oral cancer has been the fourth leading cause of cancer-related deaths in men for at least a decade. Clinical statistics show that approximately 95% of all oral cancer cases are oral cavity squamous cell carcinoma (OSCC). Patients diagnosed with advanced-stage OSCC often present with cervical lymphatic or distant metastasis of cancer cells. The metastasis of OSCC results in a high mortality rate of the disease, indicating that the identification of proteins involved in the progression and/or metastasis of OSCC is important to develop novel strategies for OSCC treatments. To this end, five patient-derived xenograft (PDX) mouse models of OSCC have been established for understanding OSCC microenvironment and progression. Using isobaric tags for relative and absolute quantitation (iTRAQ)-based mass spectrometry, proteins in the tumor tissues of five OSCC patients and five PDX mouse models have been quantitatively profiled. Furthermore, we have determined gene expression profiles of the cancer tissues from four OSCC patients and four PDX mice using the RNA-Seq analyses. Candidate proteins consistently dysregulated in tumor tissues of primary OSCC and PDX mouse models would be selected for further evaluation as potential progression-related proteins and therapeutic targets of OSCC.
2025-05-06 | PXD046930 | Pride
Project description:Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction.
2011-02-01 | E-GEOD-26549 | biostudies-arrayexpress
Project description:Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention.
2011-02-01 | GSE26549 | GEO
Project description:Three types of oral cancer cell lines (HSC3,Sa3 and SAS) and human normal oral keratinocytes(HNOKs) were used to identify a circular RNA specifically. expressed in oral cancer
2020-02-21 | GSE145608 | GEO
Project description:expression of human and mouse breast cancer cell lines
| PRJNA135447 | ENA
Project description:miRNA expression of human cancer and mouse cell lines
| PRJNA116139 | ENA