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Osca-Verdegal R, Beltrán-García J, Górriz JL, Martínez Jabaloyas JM, Pallardó FV, García-Giménez JL. Use of Circular RNAs in Diagnosis, Prognosis and Therapeutics of Renal Cell Carcinoma. Front Cell Dev Biol 2022; 10:879814. [PMID: 35813211 PMCID: PMC9257016 DOI: 10.3389/fcell.2022.879814] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 05/31/2022] [Indexed: 12/12/2022] Open
Abstract
Renal cell carcinoma is the most common type of kidney cancer, representing 90% of kidney cancer diagnoses, and the deadliest urological cancer. While the incidence and mortality rates by renal cell carcinoma are higher in men compared to women, in both sexes the clinical characteristics are the same, and usually unspecific, thereby hindering and delaying the diagnostic process and increasing the metastatic potential. Regarding treatment, surgical resection remains the main therapeutic strategy. However, even after radical nephrectomy, metastasis may still occur in some patients, with most metastatic renal cell carcinomas being resistant to chemotherapy and radiotherapy. Therefore, the identification of new biomarkers to help clinicians in the early detection, and treatment of renal cell carcinoma is essential. In this review, we describe circRNAs related to renal cell carcinoma processes reported to date and propose the use of some in therapeutic strategies for renal cell carcinoma treatment.
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Affiliation(s)
- Rebeca Osca-Verdegal
- Center for Biomedical Network Research on Rare Diseases (CIBERER), Institute of Health Carlos III, Valencia, Spain
- Department of Physiology, Faculty of Medicine and Dentistry, University of Valencia, Valencia, Spain
| | - Jesús Beltrán-García
- Center for Biomedical Network Research on Rare Diseases (CIBERER), Institute of Health Carlos III, Valencia, Spain
- Department of Physiology, Faculty of Medicine and Dentistry, University of Valencia, Valencia, Spain
- INCLIVA Biomedical Research Institute, Valencia, Spain
| | - José Luis Górriz
- Department of Nephrology, University Clinic Hospital, INCLIVA, University of Valencia, Valencia, Spain
| | | | - Federico V. Pallardó
- Center for Biomedical Network Research on Rare Diseases (CIBERER), Institute of Health Carlos III, Valencia, Spain
- Department of Physiology, Faculty of Medicine and Dentistry, University of Valencia, Valencia, Spain
- INCLIVA Biomedical Research Institute, Valencia, Spain
| | - José Luis García-Giménez
- Center for Biomedical Network Research on Rare Diseases (CIBERER), Institute of Health Carlos III, Valencia, Spain
- Department of Physiology, Faculty of Medicine and Dentistry, University of Valencia, Valencia, Spain
- INCLIVA Biomedical Research Institute, Valencia, Spain
- EpiDisease S.L. (Spin-Off CIBER-ISCIII), Parc Científic de la Universitat de València, Valencia, Spain
- *Correspondence: José Luis García-Giménez,
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Development and validation of a vascularity-based architectural classification for clear cell renal cell carcinoma: correlation with conventional pathological prognostic factors, gene expression patterns, and clinical outcomes. Mod Pathol 2022; 35:816-824. [PMID: 34848832 DOI: 10.1038/s41379-021-00982-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 11/18/2021] [Accepted: 11/19/2021] [Indexed: 11/08/2022]
Abstract
The prognostic significance of an architectural grading system for clear cell renal cell carcinoma (ccRCC) has recently been demonstrated. The present study aimed to establish a vascularity-based architectural classification using the cohort of 436 patients with localized ccRCC who underwent extirpative surgery and correlated the findings with conventional pathologic factors, gene expression, and prognosis. First, we assessed architectural patterns in the highest-grade area on hematoxylin and eosin-stained slides, then separately evaluated our surrogate score for vascularity. We grouped nine architectural patterns into three categories based on the vascular network score. "Vascularity-based architectural classification" was defined: category 1: characterized by enrichment of the vascular network, including compact/small nested, macrocyst/microcystic, and tubular/acinar patterns; category 2: characterized by a widely spaced-out vascular network, including alveolar/large nested, thick trabecular/insular, papillary/pseudopapillary patterns; category 3: characterized by scattered vascularity without a vascular network, including solid sheets, rhabdoid and sarcomatoid patterns. Adverse pathological prognostic factors such as TNM stage, WHO/ISUP grade, and necrosis were significantly associated with category 3, followed by category 2 (all p < 0.001). We successfully validated the classification using The Cancer Genome Atlas (TCGA) cohort (n = 162), and RNA-sequencing data available from TCGA showed that the angiogenesis gene signature was significantly enriched in category 1 compared to categories 2 and 3, whereas the immune gene signature was significantly enriched in category 3 compared to categories 1 and 2. In univariate analysis, vascularity-based architectural classification showed the best accuracy in pathological prognostic factors for predicting recurrence-free survival (c-index = 0.786). The predictive accuracy of our model which integrated WHO/ISUP grade, necrosis, TNM stage, and vascularity-based architectural classification was greater than conventional risk models (c-index = 0.871 vs. 0.755-0.843). Our findings suggest that the vascularity-based architectural classification is prognostically useful and may help stratify patients appropriately for management based on their likelihood of post-surgical recurrence.
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Maughan BL. Start of a New Era: Management of Non-Clear Cell Renal Cell Carcinoma in 2022. Curr Oncol Rep 2022; 24:1201-1208. [PMID: 35438388 PMCID: PMC9468090 DOI: 10.1007/s11912-022-01269-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/08/2022] [Indexed: 11/28/2022]
Abstract
Purpose of Review Historically, kidney cancer was diagnosed as either clear cell renal carcinoma (ccRCC) or non-clear cell renal carcinoma (nccRCC). With further research into the pathophysiology of nccRCC, multiple distinct subtypes have emerged creating distinct diagnosis, such as papillary renal cell carcinoma (PRCC), chromophobe renal cell carcinoma (crRCC), or unclassified carcinoma (cRCC). Many other kidney cancer subtypes are now included in the WHO classification system. Recent Findings The prognosis for each of the more frequently diagnosed types is discussed here along with treatment recommendations. The available clinical trial results and salient retrospective studies of each subtype are reviewed here to guide clinicians on the optimal treatment selection for patients with these rare histologic types or RCC. Summary Many nccRCC types are now recognized and each has unique molecular drivers which are different than ccRCC. The optimal treatment strategy is different for each subtype. The prognosis also differs based on the histology.
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Affiliation(s)
- Benjamin L Maughan
- Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope Drive, Room HCI S 5617, Salt Lake City, UT, 84112, USA.
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