Resistance to sunitinib in renal cell carcinoma: From molecular mechanisms to predictive markers and future perspectives

Of the many targeted therapies introduced since 2006, sunitinib has carved its way to become the most commonly used first-line therapy for the treatment of metastatic renal cell carcinoma (RCC). Despite significant improvements in progression-free survival, 30% of the patients are intrinsically resistant to sunitinib and the remaining 70% who respond initially will eventually become resistant in 6–15 months. While the molecular mechanisms of acquired resistance to sunitinib have been unravelling at a rapid rate, the mechanisms of intrinsic resistance remain elusive. Combination therapy, sunitinib-rechallenge and sequential therapy have been investigated as means to overcome resistance to sunitinib. Of these, sequential therapy appears to be the most promising strategy. This mini review summarises our emerging understanding of the molecular mechanisms, and the strategies employed to overcome sunitinib resistance.

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Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma

PeerJ ◽

10.7717/peerj.8096 ◽

2019 ◽

Vol 7 ◽

pp. e8096 ◽

Cited By ~ 2

Author(s):

Haiping Zhang ◽

Jian Zou ◽

Ying Yin ◽

Bo Zhang ◽

Yaling Hu ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Differentially Expressed Genes ◽

Renal Cell ◽

Molecular Mechanisms ◽

Clear Cell ◽

Clinical Stage ◽

Stage I ◽

Differentially Expressed ◽

Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.

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Molecular Mechanisms of Immune Dysfunction in Renal Cell Carcinoma

Renal Cell Carcinoma ◽

10.1385/1-59259-229-5:63 ◽

2003 ◽

pp. 63-78 ◽

Cited By ~ 6

Author(s):

Robert G. Uzzo ◽

Patricia Rayman ◽

Andrew C. Novick ◽

Ronald M. Bukowski ◽

James H. Finke

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Molecular Mechanisms ◽

Immune Dysfunction

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Editorial Comment to Systemic therapy in the management of localized and locally advanced renal cell carcinoma: Current state and future perspectives

International Journal of Urology ◽

10.1111/iju.13952 ◽

2019 ◽

Vol 26 (5) ◽

pp. 542-543

Author(s):

Katsunori Tatsugami

Keyword(s):

Renal Cell Carcinoma ◽

Editorial Comment ◽

Cell Carcinoma ◽

Systemic Therapy ◽

Renal Cell ◽

Locally Advanced ◽

Advanced Renal Cell Carcinoma ◽

Future Perspectives ◽

Current State

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Role of the KEAP1-NRF2 Axis in Renal Cell Carcinoma

Cancers ◽

10.3390/cancers12113458 ◽

2020 ◽

Vol 12 (11) ◽

pp. 3458

Author(s):

Sara Clerici ◽

Alessandra Boletta

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Cellular Response ◽

Molecular Mechanisms ◽

Antioxidant Response ◽

Specific Tumor ◽

The Moment ◽

The Many ◽

Direct Inhibitors

NRF2 is a transcription factor that coordinates the antioxidant response in many different tissues, ensuring cytoprotection from endogenous and exogenous stress stimuli. In the kidney, its function is essential in appropriate cellular response to oxidative stress, however its aberrant activation supports progression, metastasis, and resistance to therapies in renal cell carcinoma, similarly to what happens in other nonrenal cancers. While at the moment direct inhibitors of NRF2 are not available, understanding the molecular mechanisms that regulate its hyperactivation in specific tumor types is crucial as it may open new therapeutic perspectives. Here, we focus our attention on renal cell carcinoma, describing how NRF2 hyperactivation can contribute to tumor progression and chemoresistance. Furthermore, we highlight the mechanism whereby the many pathways that are generally altered in these tumors converge to dysregulation of the KEAP1-NRF2 axis.

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MCP-1/MCPIP-1 Signaling Modulates the Effects of IL-1β in Renal Cell Carcinoma through ER Stress-Mediated Apoptosis

International Journal of Molecular Sciences ◽

10.3390/ijms20236101 ◽

2019 ◽

Vol 20 (23) ◽

pp. 6101 ◽

Cited By ~ 1

Author(s):

Chia-Huei Lee ◽

Pin-Feng Hung ◽

Shang-Chieh Lu ◽

Hsuan-Lien Chung ◽

Shang-Lun Chiang ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Er Stress ◽

Cell Carcinoma ◽

Renal Cell ◽

Molecular Mechanisms ◽

Meta Analysis ◽

Terminal Deoxynucleotidyl Transferase ◽

Hek 293 ◽

Homologous Protein ◽

Tumor Stages

In renal cell carcinoma (RCC), interleukin (IL)-1β may be a pro-metastatic cytokine. However, we have not yet noted the clinical association between tumoral expression or serum level of IL-1β and RCC in our patient cohort. Herein, we investigate molecular mechanisms elicited by IL-1β in RCC. We found that IL-1β stimulates substantial monocyte chemoattractant protein (MCP)-1 production in RCC cells by activating NF-kB and AP-1. In our xenograft RCC model, intra-tumoral MCP-1 injection down-regulated Ki67 expression and reduced tumor size. Microarray analysis revealed that MCP-1 treatment altered protein-folding processes in RCC cells. MCP-1-treated RCC cells and xenograft tumors expressed MCP-1-induced protein (MCPIP) and molecules involved in endoplasmic reticulum (ER) stress-mediated apoptosis, namely C/EBP Homologous Protein (CHOP), protein kinase-like ER kinase (PERK), and calnexin (CNX). ER stress-mediated apoptosis in MCP-1-treated RCC cells was confirmed using Terminal deoxynucleotidyl transferase dUTP Nick-End Labeling (TUNEL) assay. Moreover, ectopic MCPIP expression increased PERK expression in Human embryonic kidney (HEK)293 cells. Our meta-analysis revealed that low MCP-1 levels reduce 1-year post-nephrectomy survival in patients with RCC. Immunohistochemistry indicated that in some RCC biopsy samples, the correlation between MCP-1 or MCPIP expression and tumor stages was inverse. Thus, MCP-1 and MCPIP potentially reduce the IL-1β-mediated oncogenic effect in RCC; our findings suggest that ER stress is a potential RCC treatment target.

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