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Cancers
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Renal Cell Carcinoma: From Pathology to Therapeutic Strategies
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Renal Cell Carcinoma: From Pathology to Therapeutic Strategies

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Molecular Cancer Biology".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 1880

Special Issue Editor

Dr. Jesús García-Donas

E-Mail Website
Guest Editor
Medical Oncology, HM Hospitals—Centro Integral Oncológico HM Clara Campal, 28050 Madrid, Spain
Interests: kidney cancer; genomics; transcriptomics; clinical trial; translational research

Special Issue Information

Dear Colleagues,

Kidney cancer remains one of the best examples of the rational development of therapies based on scientific knowledge. Though antiangiogenics and immunotherapy have largely become standard options, several questions such as ones regarding the selection of the best sequence of treatment or the impact of adjuvant treatment in subpopulations of patients, remain unanswered. Furthermore, new pathological classifications have identified molecularly defined entities with poor response to standard therapies.

In this Special Issue, we would like to present any original article or review regarding pathological/molecular findings, clinical observational studies or clinical trials in this pathology. Works do not need to be limited to clear cell cancer, thus, any other subtypes are welcome.

Additionally, exceptional cases with deep molecular analysis that serve as examples of direct implications of molecular alterations in clinical management are of interest.
We look forward to hearing from your initiatives and projects.

Dr. Jesús García-Donas
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. Cancers 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 2900 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
  • translational research
  • genomics
  • transcriptomics
  • clear cell
  • non-clear cell

Published Papers (3 papers)

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Research

27 pages, 1743 KiB  
Article
Discovery and Validation of Survival-Specific Genes in Papillary Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel
by Jia Hwang, Seokhwan Bang, Moon Hyung Choi, Sung-Hoo Hong, Sae Woong Kim, Hye Eun Lee, Ji Hoon Yang, Un Sang Park and Yeong Jin Choi
Cancers 2024, 16(11), 2006; https://doi.org/10.3390/cancers16112006 (registering DOI) - 25 May 2024
Abstract
Purpose: Papillary renal cell carcinoma (PRCC), the second most common kidney cancer, is morphologically, genetically, and molecularly heterogeneous with diverse clinical manifestations. Genetic variations of PRCC and their association with survival are not yet well-understood. This study aimed to identify and validate survival-specific [...] Read more.
Purpose: Papillary renal cell carcinoma (PRCC), the second most common kidney cancer, is morphologically, genetically, and molecularly heterogeneous with diverse clinical manifestations. Genetic variations of PRCC and their association with survival are not yet well-understood. This study aimed to identify and validate survival-specific genes in PRCC and explore their clinical utility. Materials and Methods: Using machine learning, 293 patients from the Cancer Genome Atlas-Kidney Renal Papillary Cell Carcinoma (TCGA-KIRP) database were analyzed to derive genes associated with survival. To validate these genes, DNAs were extracted from the tissues of 60 Korean PRCC patients. Next generation sequencing was conducted using a customized PRCC gene panel of 202 genes, including 171 survival-specific genes. Kaplan–Meier and Log-rank tests were used for survival analysis. Fisher’s exact test was performed to assess the clinical utility of variant genes. Results: A total of 40 survival-specific genes were identified in the TCGA-KIRP database through machine learning and statistical analysis. Of them, 10 (BAP1, BRAF, CFDP1, EGFR, ITM2B, JAK1, NODAL, PCSK2, SPATA13, and SYT5) were validated in the Korean-KIRP database. Among these survival gene signatures, three genes (BAP1, PCSK2, and SPATA13) showed survival specificity in both overall survival (OS) (p = 0.00004, p = 1.38 × 10−7, and p = 0.026, respectively) and disease-free survival (DFS) (p = 0.00002, p = 1.21 × 10−7, and p = 0.036, respectively). Notably, the PCSK2 mutation demonstrated survival specificity uniquely in both the TCGA-KIRP (OS: p = 0.010 and DFS: p = 0.301) and Korean-KIRP (OS: p = 1.38 × 10−7 and DFS: p = 1.21 × 10−7) databases. Conclusions: We discovered and verified genes specific for the survival of PRCC patients in the TCGA-KIRP and Korean-KIRP databases. The survival gene signature, including PCSK2 commonly obtained from the 40 gene signature of TCGA and the 10 gene signature of the Korean database, is expected to provide insight into predicting the survival of PRCC patients and developing new treatment. Full article
(This article belongs to the Special Issue Renal Cell Carcinoma: From Pathology to Therapeutic Strategies)
15 pages, 3629 KiB  
Article
Characterization of FOLH1 Expression in Renal Cell Carcinoma
by Eric Ovruchesky, Elizabeth Pan, Melis Guer, Andrew Elliott, Shankar Siva, Praful Ravi, Bradley McGregor, Aditya Bagrodia, Ithaar Derweesh, Pedro Barata, Elisabeth I. Heath, Emmanuel S. Antonarakis, Sourat Darabi, Dave S. B. Hoon, Amir Mortazavi, Toni K. Choueiri, Chadi Nabhan, Shuanzeng Wei and Rana R. McKay
Cancers 2024, 16(10), 1855; https://doi.org/10.3390/cancers16101855 - 13 May 2024
Viewed by 545
Abstract
Purpose: Given the emergence of PSMA-targeted diagnostic agents and therapeutics, we sought to investigate patterns of FOLH1 expression in RCC and their impacts on RCC outcomes. Methods: We conducted a pooled multi-institutional analysis of patients with RCC having undergone DNA and RNA next-generation [...] Read more.
Purpose: Given the emergence of PSMA-targeted diagnostic agents and therapeutics, we sought to investigate patterns of FOLH1 expression in RCC and their impacts on RCC outcomes. Methods: We conducted a pooled multi-institutional analysis of patients with RCC having undergone DNA and RNA next-generation sequencing. FOLH1-high/low expression was defined as the ≥75th/<25th percentile of RNA transcripts per million (TPM). Angiogenic, T-effector, and myeloid expression signatures were calculated using previously defined gene sets. Kaplan–Meier estimates were calculated from the time of tissue collection or therapy start. Results: We included 1,724 patients in the analysis. FOLH1 expression was significantly higher in clear cell (71%) compared to non-clear cell RCC tumors (19.0 versus 3.3 TPM, p < 0.001) and varied by specimen site (45% primary kidney/55% metastasis, 13.6 versus 9.9 TPM, p < 0.001). FOLH1 expression was correlated with angiogenic gene expression (Spearman = 0.76, p < 0.001) and endothelial cell abundance (Spearman = 0.76, p < 0.001). While OS was similar in patients with FOLH1-high versus -low ccRCC, patients with FOLH1-high clear cell tumors experienced a longer time on cabozantinib treatment (9.7 versus 4.6 months, respectively, HR 0.57, 95% CI 0.35–0.93, p < 0.05). Conclusions: We observed differential patterns of FOLH1 expression based on histology and tumor site in RCC. FOLH1 was correlated with angiogenic gene expression, increased OS, and a longer duration of cabozantinib treatment. Full article
(This article belongs to the Special Issue Renal Cell Carcinoma: From Pathology to Therapeutic Strategies)
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10 pages, 533 KiB  
Article
Automatic 3D Augmented-Reality Robot-Assisted Partial Nephrectomy Using Machine Learning: Our Pioneer Experience
by Alberto Piana, Daniele Amparore, Michele Sica, Gabriele Volpi, Enrico Checcucci, Federico Piramide, Sabrina De Cillis, Giovanni Busacca, Gianluca Scarpelli, Flavio Sidoti, Stefano Alba, Pietro Piazzolla, Cristian Fiori, Francesco Porpiglia and Michele Di Dio
Cancers 2024, 16(5), 1047; https://doi.org/10.3390/cancers16051047 - 4 Mar 2024
Cited by 1 | Viewed by 920
Abstract
The aim of “Precision Surgery” is to reduce the impact of surgeries on patients’ global health. In this context, over the last years, the use of three-dimensional virtual models (3DVMs) of organs has allowed for intraoperative guidance, showing hidden anatomical targets, thus limiting [...] Read more.
The aim of “Precision Surgery” is to reduce the impact of surgeries on patients’ global health. In this context, over the last years, the use of three-dimensional virtual models (3DVMs) of organs has allowed for intraoperative guidance, showing hidden anatomical targets, thus limiting healthy-tissue dissections and subsequent damage during an operation. In order to provide an automatic 3DVM overlapping in the surgical field, we developed and tested a new software, called “ikidney”, based on convolutional neural networks (CNNs). From January 2022 to April 2023, patients affected by organ-confined renal masses amenable to RAPN were enrolled. A bioengineer, a software developer, and a surgeon collaborated to create hyper-accurate 3D models for automatic 3D AR-guided RAPN, using CNNs. For each patient, demographic and clinical data were collected. A total of 13 patients were included in the present study. The average anchoring time was 11 (6–13) s. Unintended 3D-model automatic co-registration temporary failures happened in a static setting in one patient, while this happened in one patient in a dynamic setting. There was one failure; in this single case, an ultrasound drop-in probe was used to detect the neoplasm, and the surgery was performed under ultrasound guidance instead of AR guidance. No major intraoperative nor postoperative complications (i.e., Clavien Dindo > 2) were recorded. The employment of AI has unveiled several new scenarios in clinical practice, thanks to its ability to perform specific tasks autonomously. We employed CNNs for an automatic 3DVM overlapping during RAPN, thus improving the accuracy of the superimposition process. Full article
(This article belongs to the Special Issue Renal Cell Carcinoma: From Pathology to Therapeutic Strategies)
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