Characterizing recurrent and lethal small renal masses in clear cell renal cell carcinoma using recurrent somatic mutations

Manley, Brandon; Reznik, Ed; Ghanaat, Mazyar; Kashan, Mahyar; Becerra, Maria F.; Casuscelli, Jozefina; Tennenbaum, Daniel M.; Redzematovic, Almedina; Carlo, Maria I.; Sato, Yusuke; Arcila, Maria E.; Voss, Martin H.; Feldman, Darren R.; Motzer, Robert J.; Russo, Paul; Coleman, Jonathan; Hsieh, James J.; Hakimi, A. Ari

doi:10.1016/j.urolonc.2017.10.012

Cited by 27 publications

(25 citation statements)

References 29 publications

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“…However, this collection method has benefits, including the examination of unique cases of interest to clinicians. Second, because of the retrospective nature of this study, the study sample size was small; this limited our ability to further investigate the ITH of primary tumors, although the ITH in ccRCC tumors, including even small renal masses, may be substantial [1]. In future studies, we plan to overcome this ITH limitation by analyzing the circulating tumor DNA in plasma.…”

Section: Discussionmentioning

confidence: 99%

“…Approximately one-third of patients treated for localized clear cell renal cell carcinoma (ccRCC), the most common subtype of RCC, relapse following surgery; moreover, 15% of these patients exhibit metastatic potential, which can lead to death [1][2][3]. Tumor growth and changes in radiographic images are time-dependent predictors of poor oncological outcomes, whereas tumor grade, tumor necrosis, and patient performance are subject to inter-observer variability [1][2][3][4]. Alternatively, multigene assays may provide prognostic information beyond what is possible with traditional approaches and are now included in standard treatment guidelines for some tumors [4].…”

Section: Introductionmentioning

confidence: 99%

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Gene Expression Analysis of Aggressive Clinical T1 Stage Clear Cell Renal Cell Carcinoma for Identifying Potential Diagnostic and Prognostic Biomarkers

Park

Pierorazio

Lee

et al. 2020

Cancers

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The molecular characteristics of early-stage clear cell renal cell carcinomas (ccRCCs) measuring ≤7 cm associated with poor clinical outcomes remain poorly understood. Here, we sought to validate genes associated with ccRCC progression and identify candidate genes to predict ccRCC aggressiveness. From among 1069 nephrectomies performed on patients, RNA sequencing was performed for 12 ccRCC patients with aggressive characteristics and matched pairs of 12 ccRCC patients without aggressive characteristics. Using a prospective cohort (ClinicalTrials.gov Identifier: NCT03694912), the expression levels of nine genes (PBRM1, BAP1, SETD2, KDM5C, FOXC2, CLIP4, AQP1, DDX11, and BAIAP2L1) were measured by reverse-transcription polymerase chain reaction from frozen tissues, and their relation to Fuhrman grade was investigated in 70 patients with small ccRCC (≤4 cm). In total, 251 genes were differentially expressed and presented fold changes with p-values < 0.05; moreover, 10 genes with the greatest upregulation or downregulation in aggressive ccRCC remained significant even after adjustment. We validated previously identified genes that were associated with ccRCC progression and identified new candidate genes that reflected the aggressiveness of ccRCC. Our study provides new insight into the tumor biology of ccRCC and will help stratify patients with early-stage ccRCC by molecular subtyping.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Gene Expression Analysis of Aggressive Clinical T1 Stage Clear Cell Renal Cell Carcinoma for Identifying Potential Diagnostic and Prognostic Biomarkers

Park

Pierorazio

Lee

et al. 2020

Cancers

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“…These clinical guidelines on the management of renal masses have been accepted by the American Urological Association, European Association of Urology, and National Comprehensive Cancer Network [[6], [7], [8]]. …”

Section: Introductionmentioning

confidence: 99%

Risk Prediction Tool for Aggressive Tumors in Clinical T1 Stage Clear Cell Renal Cell Carcinoma Using Molecular Biomarkers

Park

Lee

Cho

et al. 2019

Computational and Structural Biotechnology Journal

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Some early-stage clear cell renal cell carcinomas (ccRCCs) of ≤7 cm are associated with a poor clinical outcome. In this study, we investigated molecular biomarkers associated with aggressive clinical T1 stage ccRCCs of ≤7 cm, which were used to develop a risk prediction tool toward guiding the decision of treatment. Among 1069 nephrectomies performed for ccRCC of ≤7 cm conducted between January 2008 and December 2014, 177 cases with available formalin-fixed paraffin-embedded tissue were evaluated. An aggressive tumor was defined as a tumor exhibiting synchronous metastasis, recurrence, or leading to cancer-specific death. Expression levels of six genes (FOXC2, CLIP4, PBRM1, BAP1, SETD2, and KDM5C) were measured by reverse-transcription polymerase chain reaction (qRT-PCR) and their relation to clinical outcomes was investigated. Immunohistochemistry was performed to validate the expression profiles of selected genes significantly associated with clinical outcomes in multivariate analysis. Using these genes, we developed a prediction model of aggressive ccRCC based on logistic regression and deep-learning methods. FOXC2, PBRM1, and BAP1 expression levels were significantly lower in aggressive ccRCC than non-aggressive ccRCC both in univariate and multivariate analysis. The immunohistochemistry result demonstrated the significant downregulation of FOXC2, PBRM1, and BAP1 expression in aggressive ccRCC. Adding immunohistochemical staining results to qRT-PCR, the aggressive ccRCC prediction models had the area under the curve (AUC) of 0.760 and 0.796 and accuracy of 0.759 and 0.852 using the logistic regression method and deep-learning method, respectively. Use of these biomarkers and the developed prediction model can help stratify patients with clinical T1 stage ccRCC.

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“…Furthermore, the fact that PBRM1, SETD2, and BAP1 encode chromatin-and histone-regulating tumor suppressor proteins suggests epigenetic dysregulation as a convergent pathogenic theme in ccRCC [17]. As VHL loss is the truncal event during ccRCC development, its mutation status has no impact on clinical outcome [1], whereas PBRM1 [24], SETD2 [92], BAP1 [22,[92][93][94], KDM5C [95], TP53 [96], and TERT promoter [97] mutations are associated with more aggressive clinical features when all stages of ccRCC are considered, which is consistent with a notion that their loss occurs as a second, third or further downstream driver event [98]. Of note, mouse modeling demonstrated that PBRM1, a key component of the PBAF SWI/SNF chromatin remodeling complex, functions as a tumor suppressor by preventing self-perpetuating, feed-forward amplification of HIF oncogenic signals [51,99,100], and this may explain why its mutation in small renal masses is associated with tumor invasiveness [24].…”

Section: Clear Cell Rccmentioning

confidence: 99%

Genomic classifications of renal cell carcinoma: a critical step towards the future application of personalized kidney cancer care with pan‐omics precision

Hsieh

Cao

et al. 2018

The Journal of Pathology

104

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Over the past 20 years, classifications of kidney cancer have undergone major revisions based on morphological refinements and molecular characterizations. The 2016 WHO classification of renal tumors recognizes more than ten different renal cell carcinoma (RCC) subtypes. Furthermore, the marked inter-and intra-tumor heterogeneity of RCC is now well appreciated. Nevertheless, contemporary multi-omics studies of RCC, encompassing genomics, transcriptomics, proteomics, and metabolomics, not only highlight apparent diversity but also showcase and underline commonality. Here, we wish to provide an integrated perspective concerning the future 'functional' classification of renal cancer by bridging gaps among morphology, biology, multi-omics, and therapeutics. This review focuses on recent progress and elaborates the potential value of contemporary pan-omics approaches with a special emphasis on cancer genomics unveiled through next-generation sequencing technology, and how an integrated multi-omics approach might impact precision-based personalized kidney cancer care in the near future.

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Characterizing recurrent and lethal small renal masses in clear cell renal cell carcinoma using recurrent somatic mutations

Cited by 27 publications

References 29 publications

Gene Expression Analysis of Aggressive Clinical T1 Stage Clear Cell Renal Cell Carcinoma for Identifying Potential Diagnostic and Prognostic Biomarkers

Gene Expression Analysis of Aggressive Clinical T1 Stage Clear Cell Renal Cell Carcinoma for Identifying Potential Diagnostic and Prognostic Biomarkers

Risk Prediction Tool for Aggressive Tumors in Clinical T1 Stage Clear Cell Renal Cell Carcinoma Using Molecular Biomarkers

Genomic classifications of renal cell carcinoma: a critical step towards the future application of personalized kidney cancer care with pan‐omics precision

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