1. RNA-sequencing to identify three different molecular grades and immune checkpoint cascades with distinct clinical behaviour in NMIBC
- Author
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Azar Azad, Aidan P. Noon, Girish S. Kulkarni, Neil Fleshner, Thenappan Chandrasekar, A. Erlich, Balram Sukhu, Haiyan Jiang, Morgan Rouprêt, Cynthia Kuk, Thomas Seisen, Jeff Wrana, Kin Chan, Joan Sweet, Jess Shen, Alexandre R. Zlotta, Theodorus van der Kwast, Ruoyu Ni, and Eva Comperat
- Subjects
Oncology ,Cancer Research ,medicine.medical_specialty ,business.industry ,030232 urology & nephrology ,Phenotype ,Immune checkpoint ,Fusion gene ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,TIGIT ,030220 oncology & carcinogenesis ,Internal medicine ,Genotype ,medicine ,business ,Pathological ,Grading (tumors) - Abstract
412 Background: NMIBC has a highly variable clinical behavior not adequately predicted by histological grade or clinical parameters. Some are indolent; others quickly progress to MIBC. Discrepancies between phenotype and genotype is compounded further by interobserver variability in pathological grading. There is an unmet need to improve the prediction of NMIBC. Methods: Whole transcriptomic analysis of 178 bladder tumors (158 NMIBC, 20 MIBC/metastatic) was performed from FFPE tissue incorporating messenger RNA expression, splice variants, gene fusion, mutation detection and immune checkpoint inhibitor cascades. CTLA, PD-1, LAG3, TIM3, TIGIT and B7 were compiled as an index including all major cascade genes. Data were integrated and tested for correlations with pathological grading and clinical outcomes. Conventional pathological grading for WHO 1973 (Grade 1, 2, 3) and 2004 (LG vs HG) classifications was reviewed by 3 expert uro-pathologists. Kappa statistic for interobserver variability was calculated. For validation we used an independent RNA-seq dataset (n = 209, Hedegaard et al. 2016 Cancer Cell). Results: Unsupervised clustering of RNA-Seq data distinguished 3 molecular subtypes of NMIBC; Molecular Grade Related Index (MGRI) 1, MGRI2, MGRI3. MGRI1 comprised of almost exclusively LG tumors. MGRI3 clustered with HG MIBC. Kappa for interobserver variability of expert pathologists was 0.40 and 0.78 in 1973 and 2004 WHO classification, respectively. FGFR3 mutations, FGFR3::TACC3 fusion events and MGRI1 genes were associated with components of xenobiotic metabolism (p = 2.51x10-09) signalling systems, in particular, GTPase regulation (p = 0.002), respiratory cycle genes (p = 0.004), HOX cluster (p = 0.005). MGRI independently predicted progression to MIBC (n = 138, HR = 2.96, 95%CI = 1.70-5.13, p = 1.20x10-04). 5-year PFS in a combined data set (n = 347) differed significantly for MGRI1 (100%) vs MGRI2 (92.2%) vs MGRI3 (73.5%, p = 1.99x10-05, Gray’s test). PD-1 ICC independently predicted progression (OR = 2.85, p < 0.05). Conclusions: RNA-seq delineates 3 molecular classes of NMIBC with different risks of progression to MIBC compared to conventional histologic grading.
- Published
- 2018