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A five-gene expression signature to predict progression in T1G3 bladder cancer

ABSTRACT: To analyze the gene expression profiles of progressive and non-progressive T1G3 bladder cancer (BCa) patients in order to develop a gene expression signature to predict tumour progression. Multicenter, retrospective study of formalin-fixed paraffin embedded (FFPE) tissue samples from 96 T1G3 BCa patients who underwent a transurethral resection. Patients with concomitant CIS were excluded. Global gene expression patterns were analyzed in 21 selected samples from progressive and non-progressive T1G3 BCa patients using microarrays. Expression levels of 94 key genes selected from microarrays and from the literature were studied by quantitative PCR in an independent cohort of 75 samples from progressive and non-progressive T1G3 BCa patients. Univariate logistic regression was used to identify individual predictors. Progressive and non-progressive T1G3 BCa patients show different gene expression patterns. Identification of new genes associated with a high probability of tumour progression in combination with a robust, easy-to-use and reliable algorithm may contribute to tailor treatment and surveillance strategies in these patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE57813 | GEO | 2016/07/29

SECONDARY ACCESSION(S): PRJNA248142

REPOSITORIES: GEO

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A five-gene expression signature to predict progression in T1G3 bladder cancer

Project description:To analyze the gene expression profiles of progressive and non-progressive T1G3 bladder cancer (BCa) patients in order to develop a gene expression signature to predict tumour progression. Multicenter, retrospective study of formalin-fixed paraffin embedded (FFPE) tissue samples from 96 T1G3 BCa patients who underwent a transurethral resection. Patients with concomitant CIS were excluded. Global gene expression patterns were analyzed in 21 selected samples from progressive and non-progressive T1G3 BCa patients using microarrays. Expression levels of 94 key genes selected from microarrays and from the literature were studied by quantitative PCR in an independent cohort of 75 samples from progressive and non-progressive T1G3 BCa patients. Univariate logistic regression was used to identify individual predictors. Progressive and non-progressive T1G3 BCa patients show different gene expression patterns. Identification of new genes associated with a high probability of tumour progression in combination with a robust, easy-to-use and reliable algorithm may contribute to tailor treatment and surveillance strategies in these patients. Transcriptomic profile from nine non-progressive and twelve progressive T1G3 bladder cancer FFPE samples

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