A phase II study of everolimus in combination with imatinib for previously treated advanced renal carcinoma

Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer. Although there is increasing evidence linking ccRCC to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. Though drug therapies are the best choice after the metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving it for almost 2 years. In this case, multi-targeted different variants of therapeutic drugs are essential for effective treatment against ccRCC. To understand molecular mechanisms of ccRCC development and progression, and explore multi-targeted different variants of therapeutic drugs, it is essential to identify ccRCC-causing key genes (KGs). In order to obtain ccRCC-causing KGs, at first, we detected 133 common differentially expressed genes (cDEGs) between ccRCC and control samples based on nine (9) microarray gene-expression datasets with NCBI accession IDs GSE16441, GSE53757, GSE66270, GSE66272, GSE16449, GSE76351, GSE66271, GSE71963, and GSE36895. Then, we filtered these cDEGs through survival analysis with the independent TCGA and GTEx database and obtained 54 scDEGs having significant prognostic power. Next, we used protein-protein interaction (PPI) network analysis with the reduced set of 54 scDEGs to identify ccRCC-causing top-ranked eight KGs (PLG, ENO2, ALDOB, UMOD, ALDH6A1, SLC12A3, SLC12A1, SERPINA5). The pan-cancer analysis with KGs based on TCGA database showed the significant association with different subtypes of kidney cancers including ccRCC. The gene regulatory network (GRN) analysis revealed some crucial transcriptional and post-transcriptional regulators of KGs. The scDEGs-set enrichment analysis significantly identified some crucial ccRCC-causing molecular functions, biological processes, cellular components, and pathways that are linked to the KGs. The results of DNA methylation study indicated the hypomethylation and hyper-methylation of KGs, which may lead the development of ccRCC. The immune infiltrating cell types (CD8+ T and CD4+ T cell, B cell, neutrophil, dendritic cell and macrophage) analysis with KGs indicated their significant association in ccRCC, where KGs are positively correlated with CD4+ T cells, but negatively correlated with the majority of other immune cells, which is supported by the literature review also. Then we detected 10 repurposable drug molecules (Irinotecan, Imatinib, Telaglenastat, Olaparib, RG-4733, Sorafenib, Sitravatinib, Cabozantinib, Abemaciclib, and Dovitinib.) by molecular docking with KGs-mediated receptor proteins. Their ADME/T analysis and cross-validation with the independent receptors, also supported their potent against ccRCC. Therefore, these outputs might be useful inputs/resources to the wet-lab researchers and clinicians for considering an effective treatment strategy against ccRCC.

Bioinformatics analysis to disclose shared molecular mechanisms between type-2 diabetes and clear-cell renal-cell carcinoma, and therapeutic indications

Type 2 diabetes (T2D) and Clear-cell renal cell carcinoma (ccRCC) are both complicated diseases which incidence rates gradually increasing. Population based studies show that severity of ccRCC might be associated with T2D. However, so far, no researcher yet investigated about the molecular mechanisms of their association. This study explored T2D and ccRCC causing shared key genes (sKGs) from multiple transcriptomics profiles to investigate their common pathogenetic processes and associated drug molecules. We identified 259 shared differentially expressed genes (sDEGs) that can separate both T2D and ccRCC patients from control samples. Local correlation analysis based on the expressions of sDEGs indicated significant association between T2D and ccRCC. Then ten sDEGs (CDC42, SCARB1, GOT2, CXCL8, FN1, IL1B, JUN, TLR2, TLR4, and VIM) were selected as the sKGs through the protein-protein interaction (PPI) network analysis. These sKGs were found significantly associated with different CpG sites of DNA methylation that might be the cause of ccRCC. The sKGs-set enrichment analysis with Gene Ontology (GO) terms and KEGG pathways revealed some crucial shared molecular functions, biological process, cellular components and KEGG pathways that might be associated with development of both T2D and ccRCC. The regulatory network analysis of sKGs identified six post-transcriptional regulators (hsa-mir-93-5p, hsa-mir-203a-3p, hsa-mir-204-5p, hsa-mir-335-5p, hsa-mir-26b-5p, and hsa-mir-1-3p) and five transcriptional regulators (YY1, FOXL1, FOXC1, NR2F1 and GATA2) of sKGs. Finally, sKGs-guided top-ranked three repurposable drug molecules (Digoxin, Imatinib, and Dovitinib) were recommended as the common treatment for both T2D and ccRCC by molecular docking and ADME/T analysis. Therefore, the results of this study may be useful for diagnosis and therapies of ccRCC patients who are also suffering from T2D.

Adverse renal outcomes following targeted therapies in renal cell carcinoma: a systematic review and meta-analysis

Introduction: To clarify the prevalence of adverse renal outcomes following targeted therapies in renal cell carcinoma (RCC). Methods: A systematic search was performed in MEDLINE, EMBASE, and Cochrane Central Library. Studies that had reported adverse renal outcomes following targeted therapies in RCC were eligible. Outcomes included adverse renal outcomes defined as either renal dysfunction as evidenced by elevated serum creatinine levels or the diagnosis of acute kidney injury, or proteinuria as indicated by abnormal urine findings. The risk of bias was assessed according to Cochrane handbook guidelines. Publication bias was assessed using Funnel plot analysis and Egger Test. Results: The occurrences of the examined outcomes, along with their corresponding 95% confidence intervals (CIs), were combined using a random-effects model. In all, 23 studies including 10 RCTs and 13 observational cohort studies were included. The pooled incidence of renal dysfunction and proteinuria following targeted therapies in RCC were 17% (95% CI: 12%-22%; I2 = 88.5%, p < 0.01) and 29% (95% CI: 21%-38%; I2 = 93.2%, p < 0.01), respectively. The pooled incidence of both types of adverse events varied substantially across different regimens. Occurrence is more often in polytherapy compared to monotherapy. The majority of adverse events were rated as CTCAE grades 1 or 2 events. Four studies were assessed as having low risk of bias. Conclusion: Adverse renal outcomes reflected by renal dysfunction and proteinuria following targeted therapies in RCC are not uncommon and are more often observed in polytherapy compared to monotherapy. The majority of the adverse events were of mild severity. Systematic Review Registration: Identifier CRD42023441979.

RAPTOR up-regulation contributes to resistance of renal cancer cells to PI3K-mTOR inhibition

The outlook for patients with advanced renal cell cancer (RCC) has been improved by targeted agents including inhibitors of the PI3 kinase (PI3K)-AKT-mTOR axis, although treatment resistance is a major problem. Here, we aimed to understand how RCC cells acquire resistance to PI3K-mTOR inhibition. We used the RCC4 cell line to generate a model of in vitro resistance by continuous culture in PI3K-mTOR kinase inhibitor NVP-BEZ235 (BEZ235, Dactolisib). Resistant cells were cross-resistant to mTOR inhibitor AZD2014. Sensitivity was regained after 4 months drug withdrawal, and resistance was partially suppressed by HDAC inhibition, supporting an epigenetic mechanism. BEZ235-resistant cells up-regulated and/or activated numerous proteins including MET, ABL, Notch, IGF-1R, INSR and MEK/ERK. However, resistance was not reversed by inhibiting or depleting these pathways, suggesting that many induced changes were passengers not drivers of resistance. BEZ235 blocked phosphorylation of mTOR targets S6 and 4E-BP1 in parental cells, but 4E-BP1 remained phosphorylated in resistant cells, suggesting BEZ235-refractory mTORC1 activity. Consistent with this, resistant cells over-expressed mTORC1 component RAPTOR at the mRNA and protein level. Furthermore, BEZ235 resistance was suppressed by RAPTOR depletion, or allosteric mTORC1 inhibitor rapamycin. These data reveal that RAPTOR up-regulation contributes to PI3K-mTOR inhibitor resistance, and suggest that RAPTOR expression should be included in the pharmacodynamic assessment of mTOR kinase inhibitor trials.

Dosing de novo combinations of two targeted drugs: Towards a customized precision medicine approach to advanced cancers

Metastatic cancers harbor complex genomic alterations. Thus, monotherapies are often suboptimal. Individualized combinations are needed in order to attenuate resistance. To help inform selection of safe starting doses for novel, two-agent, targeted drug combinations, we identified clinical trials in adult oncology patients who received targeted drug doublets (PubMed, January 1, 2010 through December 31, 2013). The dose percentage was calculated for each drug: (safe dose in combination divided by single agent full dose) X 100. Additive dose percentage represented the sum of the dose percentage for each drug. A total of 144 studies (N = 8568 patients; 95 combinations) were analyzed. In 51% of trials, each of the two drugs could be administered at 100% of their full dose. The lowest safe additive dose percentage was 60% if targets and/or class of drugs overlapped, or in the presence of mTor inhibitors, which sometimes compromised the combination dose. If neither class nor target overlapped and if mTor inhibitors were absent, the lowest safe additive dose percentage was 143%. The current observations contribute to the knowledge base that informs safe starting doses for new combinations of targeted drugs in the context of clinical trials or practice, hence facilitating customized combination therapies.

Targeting HIF2 in Clear Cell Renal Cell Carcinoma

Inactivation of the von Hippel-Lindau tumor-suppressor protein (pVHL) is the signature "truncal" event in clear cell renal cell carcinoma, which is the most common form of kidney cancer. pVHL is part of a ubiquitin ligase the targets the α subunit of the hypoxia-inducible factor (HIF) transcription factor for destruction when oxygen is available. Preclinical studies strongly suggest that deregulation of HIF, and particularly HIF2, drives pVHL-defective renal carcinogenesis. Although HIF2α was classically considered undruggable, structural and chemical work by Rick Bruick and Kevin Gardner at University of Texas Southwestern laid the foundation for the development of small molecule direct HIF2α antagonists (PT2385 and the related tool compound PT2399) by Peloton Therapeutics that block the dimerization of HIF2α with its partner protein ARNT1. These compounds inhibit clear cell renal cell carcinoma growth in preclinical models, and PT2385 has now entered the clinic. Nonetheless, the availability of such compounds, together with clustered regularly interspaced short palindromic repeat (CRISPR)-based gene editing approaches, has revealed a previously unappreciated heterogeneity among clear cell renal carcinomas and patient-derived xenografts with respect to HIF2 dependence, suggesting that predictive biomarkers will be needed to optimize the use of such agents in the clinic.

Future perspectives for mTOR inhibitors in renal cell cancer treatment

ABSTRACT 

Everolimus is a mTOR inhibitor that demonstrates antitumor and antiangiogenic activities. In a randomized Phase III trial, patients with metastatic renal cell carcinoma who progressed on sunitinib/sorafenib were treated with everolimus and showed significant improvement in progression-free survival compared with best supportive care. Novel approaches in treatment are expected to ensure less toxic therapies and increase efficacy of everolimus. To provide a new perspective for mTOR inhibitor research and therapy, we discuss renal cell carcinoma cancer stem cells as a potential target for mTOR inhibitors and present new concepts on emerging antiangiogenic therapies. Finally, we point why systems biology approach with reverse molecular engineering may also contribute to the field of drug discovery in renal cell carcinoma.

PI3Ks-drug targets in inflammation and cancer

Phosphoinositide 3-kinases (PI3Ks) control cell growth, proliferation, cell survival, metabolic activity, vesicular trafficking, degranulation, and migration. Through these processes, PI3Ks modulate vital physiology. When over-activated in disease, PI3K promotes tumor growth, angiogenesis, metastasis or excessive immune cell activation in inflammation, allergy and autoimmunity. This chapter will introduce molecular activation and signaling of PI3Ks, and connections to target of rapamycin (TOR) and PI3K-related protein kinases (PIKKs). The focus will be on class I PI3Ks, and extend into current developments to exploit mechanistic knowledge for therapy.