Dataset Information

Prevalence and co-occurrence of actionable genomic alterations in high-grade bladder cancer.

ABSTRACT:

Purpose

We sought to define the prevalence and co-occurrence of actionable genomic alterations in patients with high-grade bladder cancer to serve as a platform for therapeutic drug discovery.

Patients and methods

An integrative analysis of 97 high-grade bladder tumors was conducted to identify actionable drug targets, which are defined as genomic alterations that have been clinically validated in another cancer type (eg, BRAF mutation) or alterations for which a selective inhibitor of the target or pathway is under clinical investigation. DNA copy number alterations (CNAs) were defined by using array comparative genomic hybridization. Mutation profiling was performed by using both mass spectroscopy-based genotyping and Sanger sequencing.

Results

Sixty-one percent of tumors harbored potentially actionable genomic alterations. A core pathway analysis of the integrated data set revealed a nonoverlapping pattern of mutations in the RTK-RAS-RAF and phosphoinositide 3-kinase/AKT/mammalian target of rapamycin pathways and regulators of G1-S cell cycle progression. Unsupervised clustering of CNAs defined two distinct classes of bladder tumors that differed in the degree of their CNA burden. Integration of mutation and copy number analyses revealed that mutations in TP53 and RB1 were significantly more common in tumors with a high CNA burden (P < .001 and P < .003, respectively).

Conclusion

High-grade bladder cancer possesses substantial genomic heterogeneity. The majority of tumors harbor potentially tractable genomic alterations that may predict for response to target-selective agents. Given the genomic diversity of bladder cancers, optimal development of target-specific agents will require pretreatment genomic characterization.

SUBMITTER: Iyer G

PROVIDER: S-EPMC3753703 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prevalence and co-occurrence of actionable genomic alterations in high-grade bladder cancer.

Iyer Gopa G Al-Ahmadie Hikmat H Schultz Nikolaus N Hanrahan Aphrothiti J AJ Ostrovnaya Irina I Balar Arjun V AV Kim Philip H PH Lin Oscar O Weinhold Nils N Sander Chris C Zabor Emily C EC Janakiraman Manickam M Garcia-Grossman Ilana R IR Heguy Adriana A Viale Agnes A Bochner Bernard H BH Reuter Victor E VE Bajorin Dean F DF Milowsky Matthew I MI Taylor Barry S BS Solit David B DB

Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20130729 25

<h4>Purpose</h4>We sought to define the prevalence and co-occurrence of actionable genomic alterations in patients with high-grade bladder cancer to serve as a platform for therapeutic drug discovery.<h4>Patients and methods</h4>An integrative analysis of 97 high-grade bladder tumors was conducted to identify actionable drug targets, which are defined as genomic alterations that have been clinically validated in another cancer type (eg, BRAF mutation) or alterations for which a selective inhibit ...[more]

PMID: 23897969

Similar Datasets

Project description:PurposeWe report our experience with next-generation sequencing to characterize the landscape of actionable genomic alterations in renal cell carcinoma (RCC).Experimental designA query of our institutional clinical sequencing database (MSK-IMPACT) was performed that included tumor samples from 38,468 individuals across all cancer types. Somatic variations were annotated using a precision knowledge database (OncoKB) and the available clinical data stratified by level of evidence. Alterations associated with response to immune-checkpoint blockade (ICB) were analyzed separately; these included DNA mismatch repair (MMR) gene alterations, tumor mutational burden (TMB), and microsatellite instability (MSI). Data from The Cancer Genome Atlas (TCGA) consortium as well as public data from several clinical trials in metastatic RCC were used for validation purposes. Multiregional sequencing data from the TRAcking Cancer Evolution through Therapy (TRACERx) RENAL cohort were used to assess the clonality of somatic mutations.ResultsOf the 753 individuals with RCC identified in the MSK-IMPACT cohort, 115 showed evidence of targetable alterations, which represented a prevalence of 15.3% [95% confidence interval (CI), 12.7%-17.8%). When stratified by levels of evidence, the alterations identified corresponded to levels 2 (11.3%), 3A (5.2%), and 3B (83.5%). A low prevalence was recapitulated in the TCGA cohort at 9.1% (95% CI, 6.9%-11.2%). Copy-number variations predominated in papillary RCC tumors, largely due to amplifications in the MET gene. Notably, higher rates of actionability were found in individuals with metastatic disease (stage IV) compared with those with localized disease (OR, 2.50; 95% CI, 1.16-6.16; Fisher's P = 0.01). On the other hand, the prevalence of alterations associated with response to ICB therapy was found to be approximately 5% in both the MSK-IMPACT and TCGA cohorts and no associations with disease stage were identified (OR, 1.35; 95% CI, 0.46-5.40; P = 0.8). Finally, multiregional sequencing revealed that the vast majority of actionable mutations occurred later during tumor evolution and were only present subclonally in RCC tumors.ConclusionsRCC harbors a low prevalence of clinically actionable alterations compared with other tumors and the evidence supporting their clinical use is limited. These aberrations were found to be more common in advanced disease and seem to occur later during tumor evolution. Our study provides new insights on the role of targeted therapies for RCC and highlights the need for additional research to improve treatment selection using genomic profiling.

Dataset Information

Prevalence and co-occurrence of actionable genomic alterations in high-grade bladder cancer.

Purpose

Patients and methods

Results

Conclusion

Publications

Prevalence and co-occurrence of actionable genomic alterations in high-grade bladder cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets