Renal cell cancer

Disulfidptosis-Related LncRNA Signatures for Prognostic Prediction in Kidney Renal Clear Cell Carcinoma

INTRODUCTION BACKGROUND

Disulfidptosis is a prevalent apoptotic mechanism, intrinsically linked to cancer prognosis. However, the specific involvement of disulfidptosis-related long non-coding RNA (DRLncRNAs) in Kidney renal clear cell carcinoma (KIRC) remains incompletely understood. This study aims to elucidate the potential prognostic significance of disulfidptosis-related LncRNAs in KIRC.

MATERIALS AND METHODS

Expression profiles and clinical data of KIRC patients were retrieved from the TCGA database to discern differentially expressed DRLncRNAs correlated with overall survival. Cox univariate analysis, Lasso Regression, and Cox multivariate analysis were used to construct a clinical prediction model.

RESULTS

Six signatures, namely FAM83C.AS1, AC136475.2, AC121338.2, AC026401.3, AC254562.3, and AC000050.2, were established to evaluate overall survival (OS) in the context of Kidney renal clear cell carcinoma (KIRC) in this study. Survival analysis and ROC curves demonstrated the strong predictive performance of the associated signature. The nomogram exhibited accurate prognostic predictions for overall patient survival, offering substantial clinical utility. Gene set enrichment analysis revealed that risk signals were enriched in various immune-related pathways. Furthermore, the risk features exhibited significant correlations with immune cells, immune function, immune cell infiltration, and immune checkpoints.

CONCLUSION

This study has unveiled, for the first time, six disulfdptosis-related LncRNA signatures, laying a solid foundation for enhanced and precise prognostic predictions in KIRC.

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients.

METHODS

Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples.

RESULTS

By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints.

CONCLUSION

In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

Bioinformatics Prediction and Experimental Verification Identify CAB39L as a Diagnostic and Prognostic Biomarker of Kidney Renal Clear Cell Carcinoma

Background and Objectives: Calcium-binding protein 39-like (CAB39L) has been reported to be downregulated and possessed diagnostic and prognostic values in several types of cancer. However, the clinical value and mechanism of CAB39L in kidney renal clear cell carcinoma (KIRC) remain unclear. Materials and Methods: Bioinformatics analysis was conducted using different databases including TCGA, UALCAN, GEPIA, LinkedOmics, STRING, and TIMER. One-way variance analysis and t-test were chosen to investigate the statistical differences of CAB39L expression in KIRC tissues with different clinical characteristics. The receiver operating characteristic (ROC) curve was chosen to assess the discriminatory capacity of CAB39L. Kaplan-Meier curves were employed for assessing the influence of CAB39L on the progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS) of KIRC patients. The independent prognostic significance of clinical parameters for OS such as CAB39L expression in KIRC patients was estimated by Cox analysis. A series of in vitro functional experiments and Western blot (WB) and immunohistochemistry (IHC) were used to validate the relative protein expression and function of CAB39L. Results: The mRNA and protein levels of CAB39L were relatively downregulated in KIRC samples. Meanwhile, hypermethylation of the CAB39L promoter region was possibly associated with its low expression in KIRC. The ROC curve showed that the mRNA expression of CAB39L had a strong diagnostic value for both early and late KIRC. Kaplan-Meier survival curves indicated that a higher mRNA level of CAB39L predicted good PFS, DSS, and OS. The mRNA expression of CAB39L was an independent prognostic factor (hazard ratio = 0.6, p = 0.034) identified by multivariate Cox regression analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis exhibited that CAB39L was mainly associated with substance and energy metabolism. Finally, overexpression of CAB39L impaired the proliferation and metastasis of KIRC cells in vitro. Conclusions: CAB39L possesses prognostic and diagnostic capacity in KIRC.

Dissecting order amidst chaos of programmed cell deaths: construction of a diagnostic model for KIRC using transcriptomic information in blood-derived exosomes and single-cell multi-omics data in tumor microenvironment

Background

Kidney renal clear cell carcinoma (KIRC) is the most frequently diagnosed subtype of renal cell carcinoma (RCC); however, the pathogenesis and diagnostic approaches for KIRC remain elusive. Using single-cell transcriptomic information of KIRC, we constructed a diagnostic model depicting the landscape of programmed cell death (PCD)-associated genes, namely cell death-related genes (CDRGs).

Methods

In this study, six CDRG categories, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA sequencing (RNA-seq) data of blood-derived exosomes from the exoRBase database, RNA-seq data of tissues from The Cancer Genome Atlas (TCGA) combined with control samples from the GTEx databases, and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were downloaded. Next, we intersected the differentially expressed genes (DEGs) of the KIRC cohort from exoRBase and the TCGA databases with CDRGs and DEGs obtained from single-cell datasets, further screening out the candidate biomarker genes using clinical indicators and machine learning methods and thus constructing a diagnostic model for KIRC. Finally, we investigated the underlying mechanisms of key genes and their roles in the tumor microenvironment using scRNA-seq, single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq), and the spatial transcriptomics sequencing (stRNA-seq) data of KIRC provided by the GEO database.

Result

We obtained 1,428 samples and 216,155 single cells. After the rational screening, we constructed a 13-gene diagnostic model for KIRC, which had high diagnostic efficacy in the exoRBase KIRC cohort (training set: AUC = 1; testing set: AUC = 0.965) and TCGA KIRC cohort (training set: AUC = 1; testing set: AUC = 0.982), with an additional validation cohort from GEO databases presenting an AUC value of 0.914. The results of a subsequent analysis revealed a specific tumor epithelial cell of TRIB3^high subset. Moreover, the results of a mechanical analysis showed the relatively elevated chromatin accessibility of TRIB3 in tumor epithelial cells in the scATAC data, while stRNA-seq verified that TRIB3 was predominantly expressed in cancer tissues.

Conclusions

The 13-gene diagnostic model yielded high accuracy in KIRC screening, and TRIB3^high tumor epithelial cells could be a promising therapeutic target for KIRC.

miR-21-5p/PRKCE axis implicated in immune infiltration and poor prognosis of kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC or ccRCC) is the most notorious subtype of renal cell carcinoma for its poor prognosis. Mounting evidence has highlighted the key role of PRKCE in the initiation and development of several types of human cancer, including kidney renal clear cell carcinoma (KIRC). However, the mechanism of PRKCE aberrant expression and the specific clinical correlation of PRKCE expression with immune cell infiltration in KIRC remains elusive. Therefore, we analyzed the relationship between PRKCE and KIRC using many databases, including Oncomine, TCGA, GTEx, TIMER, and GEO. We found that PRKCE decreased in KIRC tumor tissue compared to normal tissue. The Kaplan-Meier Plotter analysis and Univariate and Multivariate Cox analyses were used to evaluate the association between PRKCE and clinicopathological variables and prognosis. Low PRKCE expression was associated with poor survival and histologic grade, T stage, pathologic stage, and M stage. Besides, the C-indexes and calibration plots of the nomogram based on multivariate analysis showed an effective predictive performance for KIRC patients. In addition, PRKCE may be positively correlated with inflammation and negatively correlated with proliferation, metastasis, and invasion as identified by CancerSEA. Moreover, overexpression of PRKCE suppressed ACHN and Caki-1 cell proliferation, migration, and invasion in vitro. Additionally, methylation level data acquired from UALCAN, DiseaseMeth, CCLE, LinkedOmics, and MEXPRESS was used to investigate the relationship between PRKCE expression and PRKCE methylation level. Furthermore, upstream potential miRNA predictions were further performed to explore the mechanism of PRKCE decreased expression in KIRC using multiple online databases available on publicly assessable bioinformatics platforms. High PRKCE methylation levels and hsa-miR-21-5p may contribute to PRKCE low expression in KIRC. Finally, an analysis of immune infiltration indicated that PRKCE was associated with immune cell infiltration. Importantly, PRKCE may affect prognosis partially by regulating immune infiltration in KIRC. In summary, PRKCE may serve as a novel prognostic biomarker reflecting immune infiltration level and a novel therapeutic target in KIRC.

Comprehensive Analysis of Ferroptosis- and Immune-Related Signatures to Improve the Prognosis and Diagnosis of Kidney Renal Clear Cell Carcinoma

Background

Almost 40% of patients with kidney renal clear cell carcinoma (KIRC) with advanced cancers eventually develop to metastases, and their 5-year survival rates are approximately 10%. Aberrant DNA methylations are significantly associated with the development of KIRC. The aim of our present study was to identify suitable ferroptosis- and immune-related (FI) biomarkers correlated with aberrant methylations to improve the prognosis and diagnosis of KIRC.

Methods

ChAMP and DESeq2 in R (3.6.2) were used to screen the differentially expressed methylation probes and differentially expressed genes, respectively. Univariate and multivariate Cox regression were used to identify the overall survival (OS)-related biomarkers.

Results

We finally identified five FI biomarkers (CCR4, CMTM3, IFITM1, MX2, and NR3C2) that were independently correlated with the OS of KIRC. The area under the curve value of the receiver operating characteristic value of prognosis model was 0.74, 0.68, and 0.72 in the training, validation, and entire cohorts, respectively. The sensitivity and specificity of the diagnosis model were 0.8698 and 0.9722, respectively. In addition, the prognosis model was also significantly correlated with several immune cells and factors.

Conclusion

Our present study suggested that these five FI-DEGs (CCR4, CMTM3, IFITM1, MX2, and NR3C2) could be used as prognosis and diagnosis biomarkers for patients with KIRC, but further cross-validation clinical studies are still needed to confirm them.

AQP9 Is a Prognostic Factor for Kidney Cancer and a Promising Indicator for M2 TAM Polarization and CD8+ T-Cell Recruitment

Background

It is undeniable that the tumor microenvironment (TME) plays an indispensable role in the progression of kidney renal clear cell carcinoma (KIRC). However, the precise mechanism of activities in TME is still unclear.

Methods and Results

Using the CIBERSORT and ESTIMATE calculation methods, the scores of the two main fractions of tumor-infiltrating immune cells (TICs) from The Cancer Genome Atlas (TCGA) database of 537 KIRC patients were calculated. Subsequently, differentially expressed genes (DEGs) were drawn out by performing an overlap between Cox regression analysis and protein–protein interaction (PPI) network. Aquaporin 9 (AQP9) was identified as a latent predictor through the process. Following research revealed that AQP9 expression was positively correlated with the pathological characteristics (TNM stage) and negatively connected with survival time. Then, by performing gene set enrichment analysis (GSEA), it can be inferred that genes with high expression level of AQP9 were mainly enriched in immune-related activities, while low AQP9 group was associated with functions of cellular metabolism. Further studies have shown that regulatory T cells (Tregs), macrophages M2, macrophages M0, CD4+ T cells, and neutrophils were positively correlated with AQP9 expression. While the levels of mast cells, natural killer (NK) cells, and CD8+ T cells are negatively correlated with AQP9. The result of multiple immunohistochemistry (mIHC) suggests a negative relevance between AQP9 and CD8+ T cells and reveals a trend of consistent change on AQP9 and M2 macrophages.

Conclusion

The expression level of AQP9 may be helpful in predicting the prognosis of patients with KIRC, especially to the TME state transition, the mechanism of which is possibly through lipid metabolism and P53, Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathways that affect M2 polarization. AQP9 was associated with the expression levels of M2, tumor-associated macrophages (TAMs), and the recruitment of CD8+ T cells in tumor environment. The research result indicates that AQP9 may be an obstacle to maintain the immune activity of TME.

NFIB promotes the migration and progression of kidney renal clear cell carcinoma by regulating PINK1 transcription

Kidney renal clear cell carcinoma (KIRC) is the most common and aggressive type of renal cell carcinoma. Due to high mortality rate, high metastasis rate and chemical resistance, the prognosis of KIRC patients is poor. Therefore, it is necessary to study the mechanisms of KIRC development and to develop more effective prognostic molecular biomarkers to help clinical patients. In our study, we used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to investigate that the expression of nuclear factor I B (NFIB) is significantly higher in KIRC than in adjacent tissues. Moreover, NFIB expression levels are associated with multiple clinical pathological parameters of KIRC, and KIRC patients with high NFIB expression have poor prognosis, suggesting that NFIB may play vital roles in the malignant development of KIRC. Further studies demonstrated that NFIB could promote the progression and metastasis of KIRC and participate in the regulation of PTEN induced kinase 1 (PINK1). Furthermore, we used chromatin immunoprecipitation (ChIP) experiments to confirm that NFIB binds to the PINK1 promoter and regulates its expression at the transcriptional level. Further experiments also confirmed the important roles of PINK1 in promoting the development of tumors by NFIB. Hence, our data provide a new NFIB-mediated regulatory mechanism for the tumor progression of KIRC and suggest that NFIB can be applied as a new predictor and therapeutic target for KIRC.

The clinical significance of <em>UBE2C</em> gene in progression of renal cell carcinoma

Renal cell carcinoma (RCC), with high morbidity and mortality, is one of the top ten serious cancers. Due to limited therapies and little knowledge about the mechanism underlying RCC, overall survival of RCC patients is poor. UBE2C is a member of ubiquitin modification system and promotes carcinogenesis in cancer, but its role in RCC is unknown. Based on the TCGA (The Cancer Genome Atlas) data, UBE2C was over-expressed in a total of 525 RCC tissues and displayed higher expression in advanced tissues (stage IV vs stage I, p<0.05). RT-qPCR and IHC analysis confirmed over-expression of UBE2C in 90 of clinical RCC tissues. Further, UBE2C was associated with clinical factors including TNM stage, gender, and pathological stage. And higher UBE2C expression predicted shorter overall survival and progression-free survival. Both univariate and multivariate COX analysis suggested UBE2C as a critical gene in RCC. Then GO and KEGG analysis showed that cell cycle and DNA replication pathways were two top signaling pathways affected by UBE2C. In vitro assay showed that knockdown of UBE2C in 786-O cells inhibited proliferation and migration significantly. Therefore, this study proves that UBE2C is an important gene in RCC and is essential to proliferation and migration of RCC.

Identification of RNA Transcript Makers Associated With Prognosis of Kidney Renal Clear Cell Carcinoma by a Competing Endogenous RNA Network Analysis

Objective

This study aims to identify several RNA transcripts associated with the prognosis of kidney renal clear cell carcinoma (KIRC).

Methods

The differentially expressed mRNAs, lncRNAs, and miRNAs (DEmRNAs, DElncRNAs, and DEmiRNAs) between KIRC cases and controls were screened based on an RNA-seq dataset from The Cancer Genome Atlas (TCGA) database. Subsequently, miRcode, miRDB, and TargetScan database were used to predict interactions between lncRNAs, miRNAs and target mRNAs. Then, a ceRNA network was built using miRNAs-mRNAs and lncRNAs-miRNAs pairs. Functional analysis of mRNAs in ceRNA was performed. Finally, the survival analysis of RNA transcripts in ceRNA network and correlation analysis for key RNA regulators were carried out.

Results

There were 1527 DElncRNAs, 54 DEmiRNAs, and 2321 DEmRNAs. A ceRNA network was constructed among 81 lncRNAs, 9 miRNAs, and 197 mRNAs. Functional analysis showed that numerous mRNAs were significantly associated with regulation of cellular glucuronidation. In addition, 35 lncRNAs, 84 mRNAs and two miRNAs were significantly corelated to the survival of patients with KIRC (P < 0.05). Among them, miRNA-21 and miRNA-155 were negatively related to three lncRNAs (LINC00472, SLC25A5.AS1, and TCL6). Seven mRNA targets of miRNA-21 (FASLG, FGF1, TGFBI, ALX1, SLC30A10, ADCY2, and ABAT) and 12 mRNAs targets of miRNA-155 (STXBP5L, SCG2, SPI1, C12orf40, TYRP1, CTHRC1, TDO2, PTPRQ, TRPM8, ERMP1, CD36, and ST9SIA4) also acted as prognostic biomarkers for KIRC patients.

Conclusion

We screened numerous novel prognosis-related RNA markers for KIRC patients by a ceRNA network analysis, providing deeper understandings of prognostic values of RNA transcripts for KIRC.

NR1B2 suppress kidney renal clear cell carcinoma (KIRC) progression by regulation of LATS 1/2-YAP signaling

BACKGROUND

Kidney Renal Clear Cell Carcinoma (KIRC) accounts for 75% of all renal cancers. Previous study had conflict evidences regarding NR1B2 role in cancer, and its expression and biological role in KIRC remained unclear. Our aims were to characterize the role of NR1B2 in KIRC.

METHODS

NR1B2 expression in TCGA database were analyzed. Clinical KIRC samples were examined by RT-PCR, western blot and tissue microarray (TMA). The relationship between NR1B2 expression and the clinical characteristics were evaluated. KIRC cell line were stably overexpressed NR1B2 or with an NR1B2 knocked down using lentivirus system. The cells were analyzed by migration and invasion assay, then injected into nude mice to assess tumor growth and metastasis. EMT marker expression and LATS 1/2-YAP pathway demonstration were detected by the TCGA database and western blot.

RESULTS

The expression of NR1B2 in KIRC was significantly down-regulated in the TCGA database and our clinical samples. Moreover, NR1B2 expression negatively correlated with tumor stage and positively correlated with overall and disease-free survival rate. Univariate and multivariate analyses indicated the expression level of NR1B2 could be used as an independent factor for predicting the prognosis of KIRC. Overexpression NR1B2 significantly inhibited and knockdown NR1B2 markedly promoted KIRC cell invasion and metastasis both in vitro and in vivo. Mechanistic investigations revealed that NR1B2 might be a tumor suppressor to inhibit EMT through the LATS1/2-YAP pathway.

CONCLUSIONS

our results defined NR1B2 as a tumor suppressor in KIRC that restricted EMT by the LATS1/2-YAP pathway.

Downregulation of microRNA-206 suppresses clear cell renal carcinoma proliferation and invasion by targeting vascular endothelial growth factor A

MicroRNA-206 (miR-206) has been discovered to have anticancer properties in different tissues. However, the role of miR-206 on renal carcinoma is still ambiguous. In the present study, we investigated the role of miR-206 on the development of renal carcinoma. The results indicated that miR-206 was significantly downregulated in 69 clear cell renal carcinoma (ccRCC) tissues and low-level of miR-206 related to shorter metastasis-free survival time for patients with ccRCC. The results indicated that vascular endothelial growth factor A (VEGFA) was a direct target of miR-206 in renal cancer cells. Further studies revealed that upregulation of miR-206 inhibited renal cancer cell proliferation, invasion and migration, suggesting that miR-206 functioned as a tumor suppressor. RNA interference targeting VEGFA mRNA could mimic the upregulation of miR-206 functions, and also suppressed tumor formation in vivo in nude mice. These results suggest that miR-206 plays an important role in ccRCC tumorigenesis by targeting VEGFA.

Downregulated miR-646 in clear cell renal carcinoma correlated with tumour metastasis by targeting the nin one binding protein (NOB1)

Background:

Nin one binding protein (NOB1) was identified as a potential oncogene in human glioma and miR-646 plays an important role in human growth and development. However, the underlying molecular mechanisms of NOB1 in tumorigenicity and its correlation with miR-646 in renal cell carcinoma (RCC) have not been investigated.

Methods:

We performed bioinformatic analysis to explore miRNA targeting NOB1. The expression of NOB1 and miR-646 from 100 cases of clear cell RCC (ccRCC) and 30 cases of adjacent non-tumour tissues were detected by quantitative real-time PCR. The expression of miR-646 was correlated with NOB1 expression, tumour features and patient metastasis-free survival. The effect of overexpression of mir-646 on renal cancer cell proliferation was detected by colony formation in soft agar. Using a xenograft tumour model, we observed the in vivo tumorigenesis effect of miR-646 and NOB1.

Results:

miR-646 negatively regulated NOB1 and inhibited the proliferation and migration of renal cancer cells. There was a significant upregulation of NOB1 in ccRCC and it was further increased in metastatic cases, while miR-646 was downregulated in tumour tissues and further decreased in metastatic ccRCC. Additionally, expression of miR-646 was inversely correlated with the expression of NOB1. The downregulation of miR-646 also indicated a higher probability of developing metastasis. Most importantly, miR-646 expression was an independent predictor of ccRCC metastasis by the univariate analysis and binary logistic regression model (both P<0.05). Colony formation in soft agar and xenograft tumour model suggested that miR-646 and NOB1 are required for tumorigenesis in vitro and in vivo. Furthermore, suppression of NOB1 increased the phosphorylation of several proteins in MAPK pathway.

Conclusions:

Downregulated miR-646 in ccRCC was associated with tumour metastasis through MAPK pathway by targeting NOB1. miR-646 and NOB1 may play an important role in the development of ccRCC.

Rapamycin pharmacokinetic and pharmacodynamic relationships in osteosarcoma: a comparative oncology study in dogs

Background

Signaling through the mTOR pathway contributes to growth, progression and chemoresistance of several cancers. Accordingly, inhibitors have been developed as potentially valuable therapeutics. Their optimal development requires consideration of dose, regimen, biomarkers and a rationale for their use in combination with other agents. Using the infrastructure of the Comparative Oncology Trials Consortium many of these complex questions were asked within a relevant population of dogs with osteosarcoma to inform the development of mTOR inhibitors for future use in pediatric osteosarcoma patients.

Methodology/Principal Findings

This prospective dose escalation study of a parenteral formulation of rapamycin sought to define a safe, pharmacokinetically relevant, and pharmacodynamically active dose of rapamycin in dogs with appendicular osteosarcoma. Dogs entered into dose cohorts consisting of 3 dogs/cohort. Dogs underwent a pre-treatment tumor biopsy and collection of baseline PBMC. Dogs received a single intramuscular dose of rapamycin and underwent 48-hour whole blood pharmacokinetic sampling. Additionally, daily intramuscular doses of rapamycin were administered for 7 days with blood rapamycin trough levels collected on Day 8, 9 and 15. At Day 8 post-treatment collection of tumor and PBMC were obtained. No maximally tolerated dose of rapamycin was attained through escalation to the maximal planned dose of 0.08 mg/kg (2.5 mg/30kg dog). Pharmacokinetic analysis revealed a dose-dependent exposure. In all cohorts modulation of the mTOR pathway in tumor and PBMC (pS6RP/S6RP) was demonstrated. No change in pAKT/AKT was seen in tumor samples following rapamycin therapy.

Conclusions/Significance

Rapamycin may be safely administered to dogs and can yield therapeutic exposures. Modulation pS6RP/S6RP in tumor tissue and PBMCs was not dependent on dose. Results from this study confirm that the dog may be included in the translational development of rapamycin and potentially other mTOR inhibitors. Ongoing studies of rapamycin in dogs will define optimal schedules for their use in cancer and evaluate the role of rapamycin use in the setting of minimal residual disease.

Systemic therapy of kidney cancer: tyrosine kinase inhibitors, antiangiogenesis or IL-2?

The von Hippel-Lindau (VHL) tumor suppressor gene is mutated in at least 50% of sporadic clear-cell renal cell carcinoma (RCC). This leads to a pseudohypoxic state in which the pVHL complex does not degrade hypoxia-inducible factor. Subsequent intracellular hypoxia-inducible factor accumulation results in increased production of growth factors such as VEGF, responsible for angiogenesis, tumor proliferation and mitogenesis. Recently, a number of strategies have been designed to specifically target these pathways. The VEGF, its related receptor and the mammalian target of rapamycin (mTOR) signal transduction pathway, in particular, have been utilized as therapeutic targets. Clinical trials have demonstrated the survival benefit of these agents, particularly in clear-cell RCC. Today, sunitinib is recommended as first-line therapy for intermediate- or low-risk patients with metastatic RCC. Sorafenib is advised as second-line therapy, whereas temsirolimus is generally recommended as first-line treatment in high-risk patients. Everolimus is the new standard following sunitinib. High-risk patients appeared to benefit less than low-risk patients from bevacizumab plus IFN-alpha therapy. High-dose IL-2 has been proven effective in prolonging progression-free survival or overall survival, depending on risk group selection criteria. Although novel agents show a consistent effect as measured by objective response, no currently available data demonstrate that these agents will cure any patient.

Pazopanib: an antiangiogenic drug in perspective

Pazopanib, a tyrosine kinase inhibitor targeted to angiogenesis, has been tested in preclinical and clinical trials and has shown promising activity against a variety of solid tumors, such as renal cancer, all of which are related to the angiogenic pathway. It has a safety profile related to this mechanism of action. Diarrhea, hypertension, hair depigmentation and nausea are the most common side effects. Pazopanib is currently under evaluation as monotherapy and in combination with some potentially synergistic agents of proven activity.