Targeting the Deterministic Evolutionary Trajectories of Clear Cell Renal Cell Carcinoma

Primary and acquired resistance to first-line therapy for clear cell renal cell carcinoma

The introduction of first-line combinations had improved the outcomes for metastatic renal cell carcinoma (mRCC) compared to sunitinib. However, some patients either have inherent resistance or develop resistance as a result of the treatment. Depending on the kind of therapy employed, many factors underlie resistance to systemic therapy. Angiogenesis and the tumor immune microenvironment (TIME), nevertheless, are inextricably linked. Although angiogenesis and the manipulation of the tumor microenvironment are linked to hypoxia, which emerges as a hallmark of renal cell carcinoma (RCC) pathogenesis, it is only one of the potential elements involved in the distinctive intra- and inter-tumor heterogeneity of RCC that is still dynamic. We may be able to more correctly predict therapy response and comprehend the mechanisms underlying primary or acquired resistance by integrating tumor genetic and immunological markers. In order to provide tools for patient selection and to generate hypotheses for the development of new strategies to overcome resistance, we reviewed the most recent research on the mechanisms of primary and acquired resistance to immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs) that target the vascular endothelial growth factor receptor (VEGFR).We can choose patients' treatments and cancer preventive strategies using an evolutionary approach thanks to the few evolutionary trajectories that characterize ccRCC.

Identification of a differentiation-related prognostic nomogram based on single-cell RNA sequencing in clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is a kidney cancer that is originated from the lined proximal convoluted tubule, and its major histological subtype is clear cell RCC (ccRCC). This study aimed to retrospectively analyze single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, to explore the correlation among the evolution of tumor microenvironment (TME), clinical outcomes, and potential immunotherapeutic responses in combination with bulk RNA-seq data from The Cancer Genome Atlas (TCGA) database, and to construct a differentiation-related genes (DRG)-based prognostic risk signature (PRS) and a nomogram to predict the prognosis of ccRCC patients. First, scRNA-seq data of ccRCC samples were systematically analyzed, and three subsets with distinct differentiation trajectories were identified. Then, ccRCC samples from TCGA database were divided into four DRG-based molecular subtypes, and it was revealed that the molecular subtypes were significantly correlated with prognosis, clinicopathological features, TME, and the expression levels of immune checkpoint genes (ICGs). A DRG-based PRS was constructed, and it was an independent prognostic factor, which could well predict the prognosis of ccRCC patients. Finally, we constructed a prognostic nomogram based on the PRS and clinicopathological characteristics, which exhibited a high accuracy and a robust predictive performance. This study highlighted the significance of trajectory differentiation of ccRCC cells and TME evolution in predicting clinical outcomes and potential immunotherapeutic responses of ccRCC patients, and the nomogram provided an intuitive and accurate method for predicting the prognosis of such patients.

ORP5 promotes tumor metastasis via stabilizing c-Met in renal cell carcinoma

ORP5, a lipid transporter, has been reported to increase the metastasis of several cancers. However, the potential mechanisms of ORP5 in renal cell carcinoma (RCC) remain unclear. In this study, we demonstrated that ORP5 was commonly overexpressed in tumor cells and tissues of RCC, and associated with tumor progression. Overexpression of ORP5 could promote RCC cells migration and invasion. In addition, the results suggested that the expression of ORP5 was favorably associated with c-Met expression, and ORP5 promoted RCC cells metastasis by upregulating c-Met in vitro and in vivo. Mechanistically, ORP5 facilitated the ubiquitination and degradation of c-Cbl (the E3 ligase of c-Met), and thus inhibited c-Met lysosomal degradation, which resulted in the stabilization of c-Met. In general, these findings revealed the role of ORP5 in contributing to tumorigenesis via upregulating c-Met in RCC.

Identifying the Potential Role and Prognostic Value of the Platelet-Derived Growth Factor Pathway in Kidney Renal Clear Cell Carcinoma

The platelet-derived growth factor (PDGF) pathway is important in angiogenesis, which can accelerate the formation of vessels in tumor tissues and promote the progression of malignant tumors. To clarify the role of PDGF in the occurrence of renal cell carcinoma and targeted drug resistance, we explored the pathway in kidney renal clear cell carcinoma (KIRC) through bioinformatics analysis with the aim of supporting comprehensive and individualized therapy. First, we found 40 genes related to the PDGF pathway through gene set enrichment analysis and then obtained their expressions and clinical data in 32 different cancers from The Cancer Genome Atlas (TCGA). Mutations in these genes (including copy number and single-nucleotide variation) and mRNA expression were also detected. Next, we conducted a hazard ratio analysis to determine whether the PDGF pathway genes were risk or protective factors in tumors. Although PDGF-related genes acted as traditional oncogenes and were closely related to tumor angiogenesis in many cancers, our results indicated that most genes had a protective role in KIRC. We further analyzed the methylation modification of PDGF pathway genes and found that they were prevalent in 32 different cancers. Furthermore, 539 KIRC samples obtained from TCGA were divided into three clusters based on the mRNA expression of PDGF genes, including normal, inactive, and active PDGF gene expressions. The results from survival curve analysis indicated that the active PDGF cluster of patients had the best survival rate. Using the three clusters, we studied the correlation between the PDGF pathway and 12 common targeted drugs, as well as classical oncogenes and infiltrating immune cells. A prognostic risk model was constructed based on the PDGF score using LASSO-Cox regression analysis to analyze the value of the model in predicting the prognosis of patients with KIRC. Finally, 11 genes were selected for LASSO regression analysis, and the results demonstrated the high predictive value of this risk model and its close relationship with the pathological characteristics of KIRC (metastasis, size, grade, stage, etc.). In addition, we found that the risk score was an independent risk factor correlated with overall survival through univariate and multivariate analyses and a nomogram was built to assess patient prognosis. In conclusion, the occurrence and development of KIRC may be associated with an abnormally activated PDGF pathway, which may be a potential drug target in the treatment of KIRC.

Genomic and Transcriptome Analysis to Identify the Role of the mTOR Pathway in Kidney Renal Clear Cell Carcinoma and Its Potential Therapeutic Significance

The mTOR pathway, a major signaling pathway, regulates cell growth and protein synthesis by activating itself in response to upstream signals. Overactivation of the mTOR pathway may affect the occurrence and development of cancer, but no specific treatment has been proposed for targeting the mTOR pathway. In this study, we explored the expression of mTOR pathway genes in a variety of cancers and the potential compounds that target the mTOR pathway and focused on an abnormal type of cancer, kidney renal clear cell carcinoma (KIRC). Based on the mRNA expression of the mTOR pathway gene, we divided KIRC patient samples into three clusters. We explored possible therapeutic targets of the mTOR pathway in KIRC. We predicted the IC50 of some classical targeted drugs to analyze their correlation with the mTOR pathway. Subsequently, we investigated the correlation of the mTOR pathway with histone modification and immune infiltration, as well as the response to anti-PD-1 and anti-CTLA-4 therapy. Finally, we used a LASSO regression analysis to construct a model to predict the survival of patients with KIRC. This study shows that mTOR scores can be used as tools to study various treatments targeting the mTOR pathway and that we can predict the recovery of KIRC patients through the expression of mTOR pathway genes. These research results can provide a reference for future research on KIRC patient treatment strategies.