Predictive Value of MicroRNAs in the Progression of Oral Leukoplakias
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE62809 | GEO | 2015/02/01
SECONDARY ACCESSION(S): PRJNA265196
REPOSITORIES: GEO
Similar Datasets
Project description:Predictive Value of MicroRNAs in the Progression of Oral Leukoplakias Comparison of 10 samples from non-progressive leukoplakias (did not turn into oral squamous cell carcinoma), with 10 samples from progressive leukoplakias (turned into oral squamous cell carcinoma w/in 5 yrs)
2015-02-01 | E-GEOD-62809 | biostudies-arrayexpress
Project description:Predictive Value of MicroRNAs in the Progression of Oral Leukoplakias Comparison of 10 samples from non-progressive leukoplakias (did not turn into oral squamous cell carcinoma), with 10 samples from progressive leukoplakias (turned into oral squamous cell carcinoma w/in 5 yrs)
| S-ECPF-GEOD-62809 | biostudies-other
Project description:Predictive Value of MicroRNAs in the Progression of Oral Leukoplakias
| PRJNA265196 | ENA
Project description:Oral squamous cell carcinoma (OSCC) is the sixth most common cause of cancer mortality worldwide, and the five-year survival rate remains low in patients with advanced OSCC. Many studies indicate that microRNAs (miRNAs) may paly critical roles in OSCC carcinogenesis, but the dynamic composition and functions of miRNAs-mRNAs regulatory networks in OSCC pathogenesis remain largely unknown. Thus, detailed investigations of OSCC-associated miRNAs and their regulated networks may provide insights into mechanistic understanding of OSCC progression and development of new strategies of OSCC management. To this end, we first sought to compile from a systems perspective the miRNA-mRNA networks underlying OSCC pathogenesis. Our targeted, qRT-PCR-based expression profiling of 232 miRNAs in 49 human oral tissue samples (including 19 normal and 30 OSCC specimens) identified 49 differentially expressed miRNAs (p-value < 0.01 and fold change > 2) in OSCC tissues.
2017-09-18 | GSE103931 | GEO
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:Circulating exosomal microRNAs as predictive biomarkers of neoadjuvant chemotherapy response in breast cancer
2021-12-31 | GSE182951 | GEO
Project description:The human cumulus cell transcriptome provides poor predictive value for embryo transfer outcome
| PRJNA1104189 | ENA
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:Our objective was to analyze with microarray the differential expression of microRNAs in oral squamous cell carcinoma compared with healthy control tissue. We have obtained a total of 97 genes desregulated, 36 overexpressed and 61 under expressed, where 81 were microRNAs.
2017-12-03 | GSE98463 | GEO
Project description:Oral cancer causes pain associated with cancer progression. The mechanism(s) underlying the pain is not fully understood. We report here that the function of the Ca2+ channel ORAI1 is an important regulator of oral cancer pain. ORAI1 was highly expressed in tumor samples from oral cancer patients and ORAI1 activation caused sustained Ca2+ influx in human oral cancer cells. RNA-seq analysis showed broad modulation of oral cancer markers such MMPs and pain modulators by ORAI1. Inoculation of oral cancer cells lacking ORAI1 into mouse paws reduced ectopic tumor growth and allodynia, reducing secreted MMP1 levels and the excitation of trigeminal ganglia (TG) neurons. The stimulation of TG neurons with MMP1 evoked an increase in action potentials. These data demonstrate an important role of ORAI1 in oral cancer progression likely by controlling the expression of MMP1 resulting in increased cancer progression and pain
2023-12-27 | GSE236706 | GEO