Dataset Information

Targeted genomic landscape of metastases compared to primary tumours in clear cell metastatic renal cell carcinoma.

ABSTRACT: BACKGROUND:The genomic landscape of primary clear cell renal cell carcinoma (ccRCC) has been well described. However, little is known about cohort genomic alterations (GA) landscape in ccRCC metastases, or how it compares to primary tumours in aggregate. The genomic landscape of metastases may have biological, clinical, and therapeutic implications. METHODS:We collected targeted next-generation sequencing mutation calls from two independent cohorts and described the metastases GA landscape and descriptively compared it to the GA landscape in primary tumours. RESULTS:The cohort 1 (n = 578) consisted of 349 primary tumours and 229 metastases. Overall, the most common mutations in the metastases were VHL (66.8%), PBRM1 (41.87%), and SETD2 (24.7%). TP53 was more frequently mutated in metastases compared to primary tumours (14.85% versus 8.9%; p = 0.031). No other gene had significant difference in the cohort frequency of mutations between the metastases and primary tumours. Mutation burden was not significantly different between the metastases and primary tumours or between metastatic sites. The second cohort (n = 257) consisted of 177 primary tumours and 80 metastases. No differences in frequency of mutations or mutational burden were observed between primaries and metastases. CONCLUSIONS:These data support the theory that ccRCC primary tumours and metastases encompass a uniform distribution of common genomic alterations tested by next-generation sequencing targeted panels. This study does not address variability between matched primary tumours and metastases or the change in genomic alterations over time and after sequential systemic therapies.

SUBMITTER: de Velasco G

PROVIDER: S-EPMC5943584 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Targeted genomic landscape of metastases compared to primary tumours in clear cell metastatic renal cell carcinoma.

de Velasco Guillermo G Wankowicz Stephanie A SA Madison Russell R Ali Siraj M SM Norton Craig C Duquette Audrey A Ross Jeffrey S JS Bossé Dominick D Lalani Aly-Khan A AA Miller Vincent A VA Stephens Philip J PJ Young Lauren L Hakimi A Ari AA Signoretti Sabina S Pal Sumanta K SK Choueiri Toni K TK

British journal of cancer 20180420 9

<h4>Background</h4>The genomic landscape of primary clear cell renal cell carcinoma (ccRCC) has been well described. However, little is known about cohort genomic alterations (GA) landscape in ccRCC metastases, or how it compares to primary tumours in aggregate. The genomic landscape of metastases may have biological, clinical, and therapeutic implications.<h4>Methods</h4>We collected targeted next-generation sequencing mutation calls from two independent cohorts and described the metastases GA ...[more]

PMID: 29674707

Similar Datasets

Project description:BackgroundThe genomic background affects the occurrence and metastasis of cancers, including clear cell renal cell carcinoma (ccRCC). However, reports focusing on the prognostic mutational signature of Chinese ccRCC are lacking.MethodsOverall, 929 patients, including a training cohort with Chinese patients (n = 201), a testing cohort with Caucasian patients (n = 274), and a validation cohort (n = 454) were analyzed for the genomic landscape of ccRCC. Then, machine-learning algorithms were used to identify and evaluate the genomic mutational signature (GMS) in ccRCC. Analyses for prognosis, immune microenvironment, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies (ICTs) were performed.ResultsThe DNA variation data of 929 patients with ccRCC suggested markedly differential genomic mutational frequency of the most frequent genes, such as VHL, PBRM1, BAP1, SETD2, and KDM5C between the Chinese and Caucasian populations. PBRM1 showed significant co-occurrence with VHL and SETD2. We then successfully identified a seven-gene mutational signature (GMSMut) that included mutations in FBN1, SHPRH, CELSR1, COL6A6, DST, ABCA13, and BAP1. The GMSMut significantly predicted progressive progression (P < 0.0001, HR = 2.81) and poor prognosis (P < 0.0001, HR = 3.89) in the Chinese training cohort. Moreover, ccRCC patients with the GMSMut had poor survival rates in the testing cohort (P = 0.020) and poor outcomes were predicted for those treated with ICTs in the validation cohort (P = 0.036). Interestingly, a favorable clinical response to ICTs, elevated expression of immune checkpoints, and increased abundance of tumor-infiltrated lymphocytes, specifically CD8+ T cells, Tregs, and macrophages, were observed in the GMSMut cluster.ConclusionsThis study described the pro-tumorigenic GMSMut cluster that improved the prognostic accuracy in Chinese patients with ccRCC. Our discovery of the novel independent prognostic signature highlights the relationship between tumor phenotype and genomic mutational characteristics of ccRCC.

Dataset Information

Targeted genomic landscape of metastases compared to primary tumours in clear cell metastatic renal cell carcinoma.

Publications

Targeted genomic landscape of metastases compared to primary tumours in clear cell metastatic renal cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets