Constitutional genetic variants as predictors of antiangiogenic therapy outcome in renal cell carcinoma

Influence of genetic polymorphisms in vascular endothelial-related genes on the clinical outcome of axitinib in patients with metastatic renal cell carcinoma

OBJECTIVE

Axitinib is an oral multi-target tyrosine kinase inhibitor used for the treatment of renal cell carcinoma (RCC). Because of the severe adverse events (AEs) associated with axitinib, patients often need dose reductions or discontinue its use, highlighting the need for effective biomarkers to assess efficacy and/or AEs. The aim of this study was to investigate the relationship between single nucleotide polymorphisms (SNPs) in genes involved in the pharmacodynamic action of axitinib and clinical prognosis and AEs in metastatic RCC (mRCC) patients.

METHODS

This study included 80 mRCC patients treated with first-, second-, or third-line axitinib (5 mg orally twice daily). Clinical parameters and genetic polymorphisms were examined in 75 cases (53 males and 22 females). We assessed three SNPs in each of three candidate genes namely, angiotensin-converting enzyme (ACE), nitric oxide synthase 3 (NOS3), and angiotensin II receptor type 1 (AT1R), all of which are involved in axitinib effects on vascular endothelial function.

RESULTS

Axitinib-treated patients carrying the ACE deletion allele suffered more frequently from hand-foot syndrome and a deterioration in kidney function (p  = .045 and p =  0.005, respectively) whereas those carrying the NOS3 G allele suffered more frequently from proteinuria and multiple AEs (p  = .025 and p =  0.036, respectively).

CONCLUSIONS

Our study found that the ACE deletion allele and the NOS3 G allele are associated with increased AEs.

Severe hyperglycaemia following pazopanib treatment: The role of drug-drug-gene interactions in a patient with metastatic renal cell carcinoma-A case report

WHAT IS KNOWN AND OBJECTIVE

Pazopanib is a tyrosine kinase inhibitor with hyperglycaemia as a known adverse event, but case reports of severe hyperglycaemia are exceptional. We report a case of severe hyperglycaemia following pazopanib administration in a patient with metastatic renal cell carcinoma.

CASE SUMMARY

Severe hyperglycaemia developed in a patient one month following initiation of pazopanib therapy. As drug-drug-gene interactions may lead to hyperglycaemia, pharmacogenetic assessment was requested. The obtained findings indicated intermediate function of both OATP1B1 and P-glycoprotein transporters, which may cause prolonged pazopanib bioavailability and increased toxicity. Pazopanib was discontinued and, following patient recovery, was reintroduced at a lower dose.

WHAT IS NEW AND CONCLUSION

The pharmacogenetic profiling of the patient on polypharmacy enabled better management of pazopanib therapy.

Deep sequencing reveals microRNAs predictive of antiangiogenic drug response

The majority of metastatic renal cell carcinoma (RCC) patients are treated with tyrosine kinase inhibitors (TKI) in first-line treatment; however, a fraction are refractory to these antiangiogenic drugs. MicroRNAs (miRNAs) are regulatory molecules proven to be accurate biomarkers in cancer. Here, we identified miRNAs predictive of progressive disease under TKI treatment through deep sequencing of 74 metastatic clear cell RCC cases uniformly treated with these drugs. Twenty-nine miRNAs were differentially expressed in the tumors of patients who progressed under TKI therapy (P values from 6 × 10^-9 to 3 × 10^-3). Among 6 miRNAs selected for validation in an independent series, the most relevant associations corresponded to miR-1307-3p, miR-155-5p, and miR-221-3p (P = 4.6 × 10^-3, 6.5 × 10^-3, and 3.4 × 10^-2, respectively). Furthermore, a 2 miRNA-based classifier discriminated individuals with progressive disease upon TKI treatment (AUC = 0.75, 95% CI, 0.64-0.85; P = 1.3 × 10^-4) with better predictive value than clinicopathological risk factors commonly used. We also identified miRNAs significantly associated with progression-free survival and overall survival (P = 6.8 × 10^-8 and 7.8 × 10^-7 for top hits, respectively), and 7 overlapped with early progressive disease. In conclusion, this is the first miRNome comprehensive study, to our knowledge, that demonstrates a predictive value of miRNAs for TKI response and provides a new set of relevant markers that can help rationalize metastatic RCC treatment.

Axitinib in the treatment of renal cell carcinoma: patient selection and perspectives

BACKGROUND

Axitinib is a next-generation, selective tyrosine kinase inhibitor targeting the vascular endothelial growth factor receptors. It is approved for the treatment of metastatic renal cell carcinoma (mRCC) based on a demonstrated progression-free survival advantage over sorafenib in the second-line treatment setting. However, given the variety of available targeted therapies for mRCC, appropriate patient selection for the available therapies remains a significant clinical challenge.

PURPOSE

This review summarizes the available evidence on the clinical, toxicity, and pharmacologic considerations for determining appropriate patient selection for axitinib therapy. In addition, it describes recent data on the use of predictive biomarkers to guide clinical management. This paper consists of material obtained via PubMed and Medline literature searches through October 2015.

CONCLUSION

Axitinib has a well-established role in the management of mRCC. Consistent clinical efficacy has been demonstrated across prognostic risk groups and prior therapeutic exposures. Although axitinib is generally well tolerated, appropriate toxicity management is critical to maximizing drug delivery and optimizing treatment outcomes. Although incident hypertension has been associated with improved clinical outcomes on axitinib, there are currently no validated clinical or genetic predictive biomarkers to guide patient selection.

Clinical and molecular prognostic and predictive biomarkers in clear cell renal cell cancer

ABSTRACT 

The natural history of clear cell renal cell cancer is highly unpredictable with various progressors and with populations where small renal masses may be accompanied by metastatic disease. Currently, there is a critical need to determine patient risk and optimize treatment regimes. For these patients, molecular markers may offer significant information in terms of prognostic and predictive values, as well as determination of valid therapeutic targets. Until now, only a few of the many identified clear cell renal cell cancer biomarkers have been clinically validated in large cohorts. And only several biomarkers are integrated in predictive or prognostic models. Therefore, a large cohesive effort is required to advance the field of clear cell renal cell cancer prognostic biomarkers through systematic discovery, verification, validation and clinical implementation.

Treating advanced hepatocellular carcinoma: How to get out of first gear

Hepatocellular carcinoma is a common malignancy with a poor prognosis. Sorafenib is the only systemic therapy known to improve the overall survival of patients with advanced disease. The clinical benefit of sorafenib is modest and the mechanistic basis for its activity is unknown. Four phase 3 clinical trials have failed to improve on sorafenib in the frontline setting and no agent has been shown to impact outcomes after sorafenib failure. Several factors have contributed to this recent stall in drug development but new approaches hold promise and currently are being investigated. This review will focus on the current pipeline of experimental therapeutics for patients with advanced hepatocellular carcinoma and shed a light on scientific limitations that hamper the advancement of new therapies for this disease, and ways around it.

The urinary proteome and peptidome of renal cell carcinoma patients: a comparison of different techniques

Renal cell carcinomas, originating from the renal cortex, account for about 80% of kidney primary malignancies. Small localized tumors rarely produce symptoms and diagnosis is often delayed until the disease is advanced. In contrast to other urological cancers, renal cell carcinomas are associated with a high degree of metastases and a low 5-year survival rate. The identification of diagnostic and prognostic markers, especially in the urine, remains an area of intense investigation. Different proteomic strategies have been applied so far to biomarker discovery in urine at the proteome or the peptidome level. Gel-based and gel-free strategies combined with mass spectrometry are the most-used strategies, have different success rates, and will be depicted here. We also prefigure a scenario in which the limitations of a single approach are overcome by applying new and complementary research strategies, relying on the excellent availability coupled to the intrinsic richness typical of urine samples.

Sunitinib resistance in renal cell carcinoma

Of the many targeted therapies introduced since 2006, sunitinib has carved its way to become the most commonly used first-line therapy for the treatment of metastatic renal cell carcinoma (RCC). Despite significant improvements in progression-free survival, 30% of the patients are intrinsically resistant to sunitinib and the remaining 70% who respond initially will eventually become resistant in 6-15 months. While the molecular mechanisms of acquired resistance to sunitinib have been unravelling at a rapid rate, the mechanisms of intrinsic resistance remain elusive. Combination therapy, sunitinib rechallenge and sequential therapy have been investigated as means to overcome resistance to sunitinib. Of these, sequential therapy appears to be the most promising strategy. This mini review summarises our emerging understanding of the molecular mechanisms, and the strategies employed to overcome sunitinib resistance.

Renal carcinoma pharmacogenomics and predictors of response: Steps toward treatment individualization

Molecular knowledge has deeply affected the treatment and outcome of kidney cancer in recent years, and several therapeutic options have become available. However, there are no validated biomarkers to select the best drug for each patient. Already published studies and ongoing investigations could change this scenario in the near future. Regarding antiangiogenic drugs, several works on single nucleotide polymorphisms have achieved promising results, with some SNPs predicting resistance to sunitinib and pazopanib being validated. If more evidence is gained, it could prompt prospective studies exploring a molecularly driven selection of treatment. Another relevant line of investigation for antiangiogenic drugs is the cytokines and antiangiogenic factors. Different studies have found that cytokines and antiangiogenic factors are able to predict the outcome of patients treated with sunitinib, pazopanib, or sorafenib. Issues regarding the thresholds of normality and the best time for assessment are pending, but the communicated results are encouraging. Less evidence is available for mammalian target of rapamycin inhibitors but recent data support a key role of the phosphoinositide 3-kinase/Akt pathway in clear cell renal cell carcinoma and points toward poor response to angiogenic drugs when the pathway is activated. Whether modern phosphoinositide 3-kinase inhibitors could be the best option for these patients is a question that should be addressed. Additionally, a new class of immunomodulators, like anti-programmed death 1 drugs, has demonstrated to achieve long-lasting stabilizations even in some patients with no radiological response or early progression. This is a singular situation where the identification of reliable predictors of efficacy will be key in the development of these drugs in renal cell carcinoma. Finally, germline mutations of the c-Met gene have been proposed as the first predictor of response to targeted therapies in papillary renal cell carcinoma. As a conclusion, translational research will be a cornerstone to move a next step forward in kidney cancer.

Molecular markers to predict response to therapy

Currently approved treatments for metastatic renal cell carcinoma (RCC) include vascular endothelial growth factor (VEGF)-blocking agents, mammalian target of rapamycin (mTOR) inhibitors, and cytokine therapy. In the near future, we are likely to add immune checkpoint blocking agents to this list. As we develop treatment platforms around each therapeutic class, determining which drug is best for a particular patient becomes increasingly important. At this point, we do not have validated predictive biomarkers for patients with RCC. Here, we discuss the logistical challenges surrounding biomarker development, summarize the current crop of biomarker candidates, and explore potential avenues for the development of more effective predictive tools for patients with advanced RCC.