ArticleUrologic oncology2014
Differentiating progressive from nonprogressive T1 bladder cancer by gene expression profiling: applying RNA-sequencing analysis on archived specimens.
Article in Urologic oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 27 citations in OpenAlex.
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- MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples.Clinical epigenetics · 2021Article
- Regularized Weighted Nonparametric Likelihood Approach for High-Dimension Sparse Subdistribution Hazards Model for Competing Risk Data.Computational and mathematical methods in medicine · 2021Article
- MIXnorm: normalizing RNA-seq data from formalin-fixed paraffin-embedded samples.Bioinformatics (Oxford, England) · 2020Article
- Transcription levels and prognostic significance of the NFI family members in human cancers.PeerJ · 2020Article
- RNA-seq from archival FFPE breast cancer samples: molecular pathway fidelity and novel discovery.BMC medical genomics · 2019Article
- Biological Validation of RNA Sequencing Data from Formalin-Fixed Paraffin-Embedded Primary Melanomas.JCO precision oncology · 2018Article
- The Utilization of Formalin Fixed-Paraffin-Embedded Specimens in High Throughput Genomic Studies.International journal of genomics · 2017Review
- Competing risks data analysis with high-dimensional covariates: an application in bladder cancer.Genomics, proteomics & bioinformatics · 2015Article
- The analytical landscape of static and temporal dynamics in transcriptome data.Frontiers in genetics · 2014Review
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesTo identify gene signatures in transitional cell carcinoma that can differentiate high-grade T1 nonprogressive (T1NP) bladder cancer (BCa) from those T1 progressive (T1P) tumors that progress to muscularis propria-invasive T2 tumors. MATERIALS AND
methodsWe performed a high-throughput RNA sequencing (RNA-Seq) on formalin-fixed and paraffin-embedded BCa specimens with clinical pathologic characteristics best representing the general clinical development of the disease. For the T1NP group, only patients with long-term follow-up (6-17y) and periodic examinations (average of 4 resections and 9 cytology tests) were selected. For the T1P group, only patients in whom a complete resection was performed after a minimum of 8 months after the initial T1 diagnosis were selected, therefore eliminating the possibility of underdiagnosis. Only samples in which muscularis propria was present and uninvolved were included, further assuring a correct diagnosis. The RNA-Seq reads were mapped to the human genome build NCBI 36 (hg18) using TopHat with no mismatch. After alignment to the transcriptome and expression quantification, a linear statistical model was built using Limma between T1NP and T1P samples to identify differentially expressed genes.
resultsOverall, 5,561 genes were mapped to all samples and used for RNA-Seq analysis to identify a gene signature that was significantly and differentially expressed between patients with T1NP BCa and patients with T1P BCa. Signature-based stratification indicated the gene signature correlated notably with the time of T1 development to T2 tumor, suggesting that the molecular signature might be used as an independent predictor for the pace of high-grade T1 BCa progression.
conclusionsThis is the first demonstration that RNA-Seq can be applied as a powerful tool to study BCa using formalin-fixed and paraffin-embedded specimens. We identified a gene signature that can distinguish patients diagnosed with high-grade T1 BCas that remain as non-muscle invasive tumors from those patients with cancers progressing to muscle-invasive tumors. Our findings will make future large-scale clinical cohort studies and clinical trial-based studies possible and help the development of prognostic tools for accurate prediction of T1 BCa progression that may considerably influence the clinical decision-making process, treatment regimen, and patient survival.
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