Assessing Genomic Copy Number Alterations as Best Practice for Renal Cell Neoplasia: An Evidence-Based Review from the Cancer Genomics Consortium Workgroup

2020 ◽  
Vol 244 ◽  
pp. 40-54 ◽  
Author(s):  
Yajuan J. Liu ◽  
Jane Houldsworth ◽  
Rajyasree Emmadi ◽  
Lisa Dyer ◽  
Daynna J. Wolff
2015 ◽  
Vol 33 (7_suppl) ◽  
pp. 478-478
Author(s):  
Timothy Ito ◽  
Jianming Pei ◽  
Essel Dulaimi ◽  
Craig Menges ◽  
Philip Abbosh ◽  
...  

478 Background: Sarcomatoid differentiation is an uncommon histological finding in renal cell carcinoma (RCC) that may develop from any RCC subtype and is associated with a very poor prognosis. The identification of genetic alterations that drive this aggressive phenotype could aid in the development of more effective targeted therapies. In this study, we aimed to identify unique copy number alterations (CNAs) in patients with sarcomatoid RCC when compared to those with other RCC subtypes. Methods: Genomic copy number analysis was performed using single nucleotide polymorphism (SNP)-based microarrays on tissue extracted from the tumors of 80 patients (9 with sarcomatoid features (sRCC), 39 clear cell (ccRCC), 26 papillary (pRCC) and 6 chromophobe RCC (chRCC)) who underwent renal mass excision between 2010 - 2014. Statistical analysis was performed using Kaplan Meier (KM) survival analysis, t-tests and Fisher exact tests where appropriate. Results: sRCC tumors exhibited significantly higher numbers of CNAs when compared to ccRCC, pRCC and chRCC (mean 20.1 vs. 6.6 vs. 7.0 vs. 6.3, respectively; p <0.0001). The most common copy number losses occurred in chromosome arms 1p, 3p, 9q, 15q, 18q, 21q, and 22q, with losses of 9q (88%), 15q (77%), 18q (66%), and 22 (77%) being unique among sRCC tumors when compared to the other 3 histologies. The most common copy number gains were in chromosome arms 1q, 8q, 17q, and 20p/q, with 1q (55%) and 8q (66%) gains unique when compared to the other 3 histologies. Of the sRCC tumors, 3 arose from ccRCC, 2 from pRCC and 4 from unclassified RCC. sRCC was associated with worse survival compared to ccRCC, pRCC and chRCC on KM analysis (p=0.0006), and higher rates of lymph node positivity (77% vs. 3% vs. 12% vs. 0%, respectively; p<0.0001) and metastases (100% vs. 13% vs. 4% vs. 0%, respectively; p<0.0001) on presentation were observed with sRCC. Conclusions: Sarcomatoid differentiation in RCC is associated with a high rate of chromosomal changes with unique copy number alterations including losses of 9q, 15q, 18q and 22q and gains of 1q and 8q. Identification and validation of candidate driver genes or tumor suppressor loci within these chromosomal regions may help identify targets for future therapies.


2016 ◽  
Vol 195 (4 Part 1) ◽  
pp. 852-858 ◽  
Author(s):  
Timothy Ito ◽  
Jianming Pei ◽  
Essel Dulaimi ◽  
Craig Menges ◽  
Philip H. Abbosh ◽  
...  

2015 ◽  
Vol 193 (4S) ◽  
Author(s):  
Timothy Ito ◽  
Jianming Pei ◽  
Essel Dulaimi ◽  
Craig Menges ◽  
Philip Abbosh ◽  
...  

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 7695-7695
Author(s):  
M. S. Park ◽  
C. Ma ◽  
M. U. Aziz ◽  
S. Rao ◽  
K. Gold ◽  
...  

7695 Background: Lung cancer is the leading cause of cancer death in both men and women with a 5-yr survival rate of 15.5%. Previous studies have begun to characterized genomic copy number alterations of non-small-cell lung CA using array CGH and SNP arrays. We have used aCGH using our 1MB BAC arrays and two algorthims for making copy number alteration (CNA) determinations. We have also pursued the exact copy number gains and losses of several genes using Q-PCR. Methods: Genomic DNA from fresh frozen tumors of 27 patients with NSCLC. We performed aCGH using 1MB Arrays. We used CBS, and MSA to identify regions of CNA. We further pursued several genes of interest (including HRAS, CRK, and CDC42) identified using Q-PCR. Unsupervised hierarchical clustering was performed to look for distinct subgroups. Significant Analysis of Microarrays (SAM) was applied to identify the association between CNAs clinical parameters including tumor subtype, gender, lymph node involvement, tumor stage, and overall survival. Results: 240 regions of amplification and 181 regions of deletions were found, and included all previously published regions implicated in lung cancer. CNAs in > 70% of tumors included amplifications in 1q, 3q, 5p, 6p, 11p, 16q, 20q, and Xq, and deletions in 1p, 8p and 13q. We verified CNAs of HRAS, CRK and CDC42 using Q-PCR. Hierarchical clustering revealed 2 subgroups: one with amplifications in 2q, 4p, 4q, 8q, 21q, 15q, and 16p, and the other with amplifications in 3q, and 5q. These were confirmed by supervised SAM analysis. Using SAM we found that gain of 2q, 4p and 10q, and loss of 16p and 19q were significantly present in adenocarcinomas. (q = 0, FDR = 0%). Gain of 10q, and loss of 6p and 14q were associated with female gender. (q = 0, FDR = 0%). Conclusions: We used aCGH to identify CNAs that characterize non-small cell lung CA tumors with the aim of finding key regions which may harbor important oncogenes and tumor suppressors. Several regions of CNA have been identified, several of which have been associated with clinical parameters. Because much heterogeneity exists in non-small-cell lung tumors, we have demonstrated that clustering analysis is useful in identifying subtypes which may possess prognostic and therapeutic significance. No significant financial relationships to disclose.


2011 ◽  
Vol 185 (4S) ◽  
Author(s):  
Takahiro Narimatsu ◽  
Keiko Matsuura ◽  
Chisato Nakada ◽  
Toru Inoue ◽  
Takeo Nomura ◽  
...  

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