774 Analysis of site specific miRNA expression in distant metastases of clear cell renal cell carcinoma

375 Background: MicroRNAs (miRNA) are short, non-coding RNAs involved in post-transcriptional gene regulation. Several reports have assessed their role as blood based biomarkers given their tissue and cancer-specific expression. Using an integrative approach we sequenced the miRNA transcriptome of the plasma of several clear cell renal cell carcinoma (ccRCC) patients both before and after surgery as well as several controls. Methods: We performed next generation miRNA sequencing (miRNAseq) on eight pairs (pre- and post-operative plasma samples) and four non-cancer controls to identify potential biomarker candidates. We further integrated our data with the miRNAseq tumor data from the Cancer Genome Atlas (TCGA) study to determine whether plasma miRNA levels are representative of tumor miRNA expression in ccRCC. Results: Overall, 930 unique miRNAs were detected, including 272 at greater than or equal to 10 read counts. There was a global shift of miRNA expression toward the non-cancer controls in the postoperative samples compared to preoperative. We further identified several stably expressed miRNAs across all samples and controls including miR-16, miR-191, and miR-103. We also identified several potential biomarker candidates by looking at differential expression both in terms of preoperative and postoperative status, as well as tumor vs. control including miR-378 and miR-660. Intriguingly, the plasma miRNA expression patterns showed no relationship to the tumor expression patterns using the TCGA samples. Conclusions: Plasma miRNA expression patterns are consistently altered in ccRCC and, following surgery, globally revert to the non-cancerous levels of the controls. Several biomarker candidates have been identified and a panel is undergoing validation in larger cohorts. Plasma miRNA levels do not appear to reflect tumor levels in ccRCC.

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Patterns of distant metastases in patients with clear cell renal cell carcinoma––A population‐based analysis

Cancer Medicine ◽

10.1002/cam4.3596 ◽

2020 ◽

Author(s):

Jianxin Xue ◽

Wensun Chen ◽

Wenbo Xu ◽

Zicheng Xu ◽

Xiao Li ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Distant Metastases ◽

Population Based ◽

Cell Renal Cell Carcinoma

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Circulating microRNAs from the Molecular Mechanisms to Clinical Biomarkers: A Focus on the Clear Cell Renal Cell Carcinoma

Genes ◽

10.3390/genes12081154 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1154

Author(s):

Claudia Tito ◽

Elena De Falco ◽

Paolo Rosa ◽

Alessia Iaiza ◽

Francesco Fazi ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Mirna Expression ◽

Renal Cell ◽

Molecular Mechanisms ◽

Clear Cell ◽

Transcriptional Level ◽

Cell Renal Cell Carcinoma ◽

Post Surgery ◽

Clinical Biomarkers

microRNAs (miRNAs) are emerging as relevant molecules in cancer development and progression. MiRNAs add a post-transcriptional level of control to the regulation of gene expression. The deregulation of miRNA expression results in changing the molecular circuitry in which miRNAs are involved, leading to alterations of cell fate determination. In this review, we describe the miRNAs that are emerging as innovative molecular biomarkers from liquid biopsies, not only for diagnosis, but also for post-surgery management in cancer. We focus our attention on renal cell carcinoma, in particular highlighting the crucial role of circulating miRNAs in clear cell renal cell carcinoma (ccRCC) management. In addition, the functional deregulation of miRNA expression in ccRCC is also discussed, to underline the contribution of miRNAs to ccRCC development and progression, which may be relevant for the identification and design of innovative clinical strategies against this tumor.

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Global and Targeted miRNA Expression Profiling in Clear Cell Renal Cell Carcinoma Tissues Potentially Links miR-155-5p and miR-210-3p to both Tumorigenesis and Recurrence

American Journal Of Pathology ◽

10.1016/j.ajpath.2018.07.026 ◽

2018 ◽

Vol 188 (11) ◽

pp. 2487-2496 ◽

Cited By ~ 12

Author(s):

Jinhua Zhang ◽

Yuanqing Ye ◽

David W. Chang ◽

Shu-Hong Lin ◽

Maosheng Huang ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Mirna Expression ◽

Expression Profiling ◽

Renal Cell ◽

Clear Cell ◽

Cell Renal Cell Carcinoma ◽

Mirna Expression Profiling

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Renal Sinus Fat Invasion in pT3a Clear Cell Renal Cell Carcinoma Affects Outcomes of Patients Without Nodal Involvement or Distant Metastases

The Journal of Urology ◽

10.1016/j.juro.2009.01.048 ◽

2009 ◽

Vol 181 (5) ◽

pp. 2027-2032 ◽

Cited By ~ 33

Author(s):

Roberto Bertini ◽

Marco Roscigno ◽

Massimo Freschi ◽

Elena Strada ◽

Giovanni Petralia ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Distant Metastases ◽

Nodal Involvement ◽

Cell Renal Cell Carcinoma ◽

Renal Sinus ◽

Renal Sinus Fat

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AGAP2-AS1 as a potential marker for development of distant metastases in surgically treated low-risk clear cell renal cell carcinoma.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.6_suppl.732 ◽

2020 ◽

Vol 38 (6_suppl) ◽

pp. 732-732

Author(s):

Sigrid Nakken ◽

Øystein Eikrem ◽

Hans-Peter Marti ◽

Christian Beisland ◽

Leif Bostad ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Distant Metastases ◽

Low Risk ◽

Rna Seq ◽

Cell Renal Cell Carcinoma ◽

Fixed Tissue ◽

Fuhrman Grade

732 Background: Historically, 30 % of patients with localized kidney cancer develop distant metastases during follow-up. There is an urgent need to improve the individual risk assessment for clear cell renal cell carcinoma (ccRCC) patients. We therefore aim to characterize the gene expression profile of low-risk patients both with and without progressive disease to define predictive outcome candidate markers. Methods: Formalin-fixed tissue blocks from ccRCC patients (n=24, eight progressors and 16 non-progressors) with a low Leibovich score were collected. Patients had a mean age of 65 years (5 females and 19 males). The non-progressors were matched 2:1 to the progressors for gender, age, pT tumor stage, size, Fuhrman grade, and eGFR. Total RNA was extracted(miRNeasy FFPE Kit, Qiagen) and sequenced (TruSeq RNA Access Library Kit, Illumina). RNA-seq results were analyzed by ingenuity pathway analysis, K Nearest Neighbors algorithm, and survival analysis. Results: 1167 differentially expressed genes (abs.FC≥2, p≤0.05) were detected. Progressors overexpressed genes related to cancer, B-cell infiltration and other immune-system related pathways. Principal component analyses and hierarchical clustering depicted a systematic transcriptomic difference between progressors and non-progressors. Combinations of up to 10 genes were evaluated as classifiers. The AGAP2-AS1 mRNA classified 23 out of 24 samples correctly, without the need for a larger gene panel. The trend of expression was confirmed with RT-PCR.The correlation between sample status as either progressor or non-progressor and AGAP2-AS1 level was R2 =0.69, p <0.01. Patients were split into groups based on AGAP2-AS1 expression (cut-off log2cpm>1), where higher expression correlated with shorter survival; Wilcoxon (p<0.0001),Log-rank test (p<0.0001), Hazard ratio; 9.24E-11. Immunohistochemistry of AGAP2, USP10 and KI-67 confirmed results from the mRNA level. Conclusions: RNA-seq results show a transcriptomic difference between low-risk ccRCC progressors and low-risk non-progressors. AGAP2-AS1 may serve as a potential classifier for the identification of low-risk progressors.

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