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Cells
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New Insights into Kidney Cancer
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New Insights into Kidney Cancer

A special issue of Cells (ISSN 2073-4409). This special issue belongs to the section "Cellular Pathology".

Deadline for manuscript submissions: closed (15 July 2022) | Viewed by 13392

Special Issue Editor

Dr. Anna Julie Peired

E-Mail Website
Guest Editor
Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence, Viale Morgagni 50, 50134 Florence, Italy
Interests: kidney cancer; acute kidney injury; chronic kidney injury; renal progenitors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Kidney cancer is the 13th most common malignancy worldwide, and its incidence is increasing every year. Renal cell carcinomas (RCC) are a heterogeneous group of kidney tumors, composed of a number of histologically and genetically distinct diseases. Clear cell, papillary, and chromophobe are the most common histological subtypes of RCC. RCC originates principally from the proximal convoluted tubule of the nephron, and recent evidence points toward a population of endogenous progenitor cells that would undergo oncogenic transformation and give rise to tumors. Surgery remains the most effective treatment for RCC, but patients often experience metastatic spread and recurrence. Although a variety of risk factors has been described, some kidney cancers develop in the apparent absence of a clear cause, suggesting the existence of still undetermined risk factors.

In this Special Issue, we aim to tackle the conundrums that challenge kidney cancer understanding and treatment, focusing on cutting-edge technologies and pioneering ideas. The introduction of novel technologies such as single cell RNA sequencing, microfluidic platforms, and 3D tumor models, but also novel treatment approaches, such as personalized mRNA cancer vaccines and checkpoint inhibitors, warrants fast progress in kidney cancer research. In recent years, several groundbreaking studies have shined light on mostly unexplored fields.

We hope that this Special Issue will allow scientists from different horizons, nephrologists and urologists, as well as basic researchers, to develop a network and share their ideas on original approaches to improving our knowledge of kidney cancer biology and to developing novel therapies. Both original research articles and reviews are welcome.

Dr. Anna Julie Peired
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cells is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • kidney cancer
  • renal cell carcinoma
  • risk factors
  • gender
  • renal progenitors
  • 3D modeling
  • single cell RNA sequencing
  • organoids
  • gender medicine

Published Papers (4 papers)

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Research

17 pages, 2770 KiB  
Article
In Silico, In Vitro, and Clinical Investigations of Cathepsin B and Stefin A mRNA Expression and a Correlation Analysis in Kidney Cancer
by Magdalena Rudzinska-Radecka, Anastasia S. Frolova, Anastasia V. Balakireva, Neonila V. Gorokhovets, Vadim S. Pokrovsky, Darina V. Sokolova, Dmitry O. Korolev, Natalia V. Potoldykova, Andrey Z. Vinarov, Alessandro Parodi and Andrey A. Zamyatnin, Jr.
Cells 2022, 11(9), 1455; https://doi.org/10.3390/cells11091455 - 25 Apr 2022
Cited by 9 | Viewed by 2817
Abstract
The cysteine protease Cathepsin B (CtsB) plays a critical role in multiple signaling pathways, intracellular protein degradation, and processing. Endogenous inhibitors regulate its enzymatic activity, including stefins and other cystatins. Recent data proved that CtsB is implicated in tumor extracellular matrix remodeling, cell [...] Read more.
The cysteine protease Cathepsin B (CtsB) plays a critical role in multiple signaling pathways, intracellular protein degradation, and processing. Endogenous inhibitors regulate its enzymatic activity, including stefins and other cystatins. Recent data proved that CtsB is implicated in tumor extracellular matrix remodeling, cell invasion, and metastasis: a misbalance between cathepsins and their natural inhibitors is often considered a sign of disease progression. In the present study, we investigated CtsB and stefin A (StfA) expression in renal cell carcinoma (RCC). mRNA analysis unveiled a significant CTSB and STFA increase in RCC tissues compared to adjacent non-cancerogenic tissues and a higher CtsB expression in malignant tumors than in benign renal neoplasms. Further analysis highlighted a positive correlation between CtsB and StfA expression as a function of patient sex, age, tumor size, grade, lymph node invasion, metastasis occurrence, and survival. Alternative overexpression and silencing of CtsB and StfA confirmed the correlation expression between these proteins in human RCC-derived cells through protein analysis and fluorescent microscopy. Finally, the ectopic expression of CtsB and StfA increased RCC cell proliferation. Our data strongly indicated that CtsB and StfA expression play an important role in RCC development by mutually stimulating their expression in RCC progression. Full article
(This article belongs to the Special Issue New Insights into Kidney Cancer)
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13 pages, 1962 KiB  
Article
B7-H4 Immune Checkpoint Protein Affects Viability and Targeted Therapy of Renal Cancer Cells
by Maite Emaldi and Caroline E. Nunes-Xavier
Cells 2022, 11(9), 1448; https://doi.org/10.3390/cells11091448 - 25 Apr 2022
Cited by 6 | Viewed by 3211
Abstract
Targeted therapy in combination with immune checkpoint inhibitors has been recently implemented in advanced or metastatic renal cancer treatment. However, many treated patients either do not respond or develop resistance to therapy, making alternative immune checkpoint-based immunotherapies of potential clinical benefit for specific [...] Read more.
Targeted therapy in combination with immune checkpoint inhibitors has been recently implemented in advanced or metastatic renal cancer treatment. However, many treated patients either do not respond or develop resistance to therapy, making alternative immune checkpoint-based immunotherapies of potential clinical benefit for specific groups of patients. In this study, we analyzed the global expression of B7 immune checkpoint family members (PD-L1, PD-L2, B7-H2, B7-H3, B7-H4, B7-H5, B7-H6, and B7-H7) in human renal cancer cells (Caki-1, A-498, and 786-O cell lines) upon treatment with clinically relevant targeted drugs, including tyrosine kinase inhibitors (Axitinib, Cabozantinib, and Lenvatinib) and mTOR inhibitors (Everolimus and Temsirolimus). Gene expression analysis by quantitative PCR revealed differential expression patterns of the B7 family members in renal cancer cell lines upon targeted drug treatments. B7-H4 gene expression was upregulated after treatment with various targeted drugs in Caki-1 and 786-O renal cancer cells. Knocking down the expression of B7-H4 by RNA interference (RNAi) using small interfering RNA (siRNA) decreased renal cancer cell viability and increased drug sensitivity. Our results suggest that B7-H4 expression is induced upon targeted therapy in renal cancer cells and highlight B7-H4 as an actionable immune checkpoint protein in combination with targeted therapy in advanced renal cancer cases resistant to current treatments. Full article
(This article belongs to the Special Issue New Insights into Kidney Cancer)
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22 pages, 2876 KiB  
Article
Multi-Omics Profiling to Assess Signaling Changes upon VHL Restoration and Identify Putative VHL Substrates in Clear Cell Renal Cell Carcinoma Cell Lines
by Xuechun Wang, Jin Hu, Yihao Fang, Yanbin Fu, Bing Liu, Chao Zhang, Shan Feng and Xin Lu
Cells 2022, 11(3), 472; https://doi.org/10.3390/cells11030472 - 29 Jan 2022
Cited by 8 | Viewed by 4072
Abstract
The inactivation of von Hippel–Lindau (VHL) is critical for clear cell renal cell carcinoma (ccRCC) and VHL syndrome. VHL loss leads to the stabilization of hypoxia-inducible factor α (HIFα) and other substrate proteins, which, together, drive various tumor-promoting pathways. There is inadequate molecular [...] Read more.
The inactivation of von Hippel–Lindau (VHL) is critical for clear cell renal cell carcinoma (ccRCC) and VHL syndrome. VHL loss leads to the stabilization of hypoxia-inducible factor α (HIFα) and other substrate proteins, which, together, drive various tumor-promoting pathways. There is inadequate molecular characterization of VHL restoration in VHL-defective ccRCC cells. The identities of HIF-independent VHL substrates remain elusive. We reinstalled VHL expression in 786-O and performed transcriptome, proteome and ubiquitome profiling to assess the molecular impact. The transcriptome and proteome analysis revealed that VHL restoration caused the downregulation of hypoxia signaling, glycolysis, E2F targets, and mTORC1 signaling, and the upregulation of fatty acid metabolism. Proteome and ubiquitome co-analysis, together with the ccRCC CPTAC data, enlisted 57 proteins that were ubiquitinated and downregulated by VHL restoration and upregulated in human ccRCC. Among them, we confirmed the reduction of TGFBI (ubiquitinated at K676) and NFKB2 (ubiquitinated at K72 and K741) by VHL re-expression in 786-O. Immunoprecipitation assay showed the physical interaction between VHL and NFKB2. K72 of NFKB2 affected NFKB2 stability in a VHL-dependent manner. Taken together, our study generates a comprehensive molecular catalog of a VHL-restored 786-O model and provides a list of putative VHL-dependent ubiquitination substrates, including TGFBI and NFKB2, for future investigation. Full article
(This article belongs to the Special Issue New Insights into Kidney Cancer)
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13 pages, 3200 KiB  
Article
Oncocytoma-Related Gene Signature to Differentiate Chromophobe Renal Cancer and Oncocytoma Using Machine Learning
by Khaled Bin Satter, Paul Minh Huy Tran, Lynn Kim Hoang Tran, Zach Ramsey, Katheine Pinkerton, Shan Bai, Natasha M. Savage, Sravan Kavuri, Martha K. Terris, Jin-Xiong She and Sharad Purohit
Cells 2022, 11(2), 287; https://doi.org/10.3390/cells11020287 - 15 Jan 2022
Cited by 4 | Viewed by 2310
Abstract
Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discovery dataset. The transcriptomic differences were identified with unsupervised [...] Read more.
Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discovery dataset. The transcriptomic differences were identified with unsupervised learning in the discovery dataset (97.8% accuracy) with density based UMAP (DBU). The top 30 genes were identified by univariate gene expression analysis and ROC analysis, to create a gene signature called COGS. COGS, combined with DBU, was able to differentiate chRCC from RO in the discovery dataset with an accuracy of 97.8%. The classification accuracy of COGS was validated in an independent meta-dataset consisting of TCGA-KICH and GSE12090, where COGS could differentiate chRCC from RO with 100% accuracy. The differentially expressed genes were involved in carbohydrate metabolism, transcriptomic regulation by TP53, beta-catenin-dependent Wnt signaling, and cytokine (IL-4 and IL-13) signaling highly active in cancer cells. Using multiple datasets and machine learning, we constructed and validated COGS as a tool that can differentiate chRCC from RO and complement histology in routine clinical practice to distinguish these two tumors. Full article
(This article belongs to the Special Issue New Insights into Kidney Cancer)
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