Radiological evaluation of response to treatment: Application to metastatic renal cancers receiving anti-angiogenic treatment

Prognostic Utility of Parameters Derived From Pretreatment Dual-Layer Spectral-Detector CT in Patients With Metastatic Renal Cell Carcinoma

Background: New therapies have emerged for metastatic renal cell carcinoma (mRCC), though corresponding imaging markers are lacking. Dual-layer spectral-detector CT (DLCT) can quantify iodine concentration (IC) and effective atomic number (Zeffective), providing information beyond attenuation that may indicate mRCC prognosis. Objective: To assess the utility of the DLCT-derived parameters IC and Zeffective for predicting mRCC treatment response and survival. Methods: This prospective study (ClinicalTrials.gov identifier: NCT03616951) enrolled 120 participants with mRCC from January 2018 to January 2020 who underwent DLCT before treatment initiation, with reconstruction of IC and Zeffective maps. Final analysis included 115 participants (86 men, 29 women; median age, 65.1 years), incorporating 313 target lesions that were clinically selected using RECIST version 1.1 on arterial-phase acquisitions of the chest and abdomen. Semiautomatic volumetric segmentation was performed of the target lesions. Pixels from all lesions were combined to a single histogram per patient. Median IC and Zeffective of the combined histograms were recorded. Measurements above and below the cohort median values were considered high and low, respectively. Univariable associations were explored between IC and Zeffective, with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Multivariable associations were explored between IC and ORR, PFS, and OS, adjusting for treatment (tyrosine kinase inhibitor versus checkpoint immunotherapy) and significant univariable predictors [including tumor histology and International mRCC Database Consortium (IMDC) risk factors]. Results: At baseline, median IC was 2.26 mg/ml, and median Zeffective was 8.49. In univariable analysis, high IC and high Zeffective were associated with better ORR (both OR=4.35, p=.001), better PFS (both HR=0.51, p=.004), and better OS (both HR=0.38, p<.001). In multivariable models, high IC independently predicted better ORR (OR=4.35, p=.001), better PFS (HR=0.51, p=.004), and better OS (HR=0.37, p<.001); neutrophilia independently predicted worse PFS (HR=2.10, p=.004) and worse OS (HR=2.28, p=.003). The estimated c-index for predicting OS using IMDC risk factors was 0.650, versus 0.687 when incorporating high attention and 0.692 when incorporating high IC or high Zeffective. Conclusions: High IC and high Zeffective are significant predictors of better treatment response and survival in mRCC. Clinical impact: Baseline DLCT parameters may improve current mRCC prognostic models.

Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory.

Radiomics Response Signature for Identification of Metastatic Colorectal Cancer Sensitive to Therapies Targeting EGFR Pathway

BACKGROUND

The authors sought to forecast survival and enhance treatment decisions for patients with liver metastatic colorectal cancer by using on-treatment radiomics signature to predict tumor sensitiveness to irinotecan, 5-fluorouracil, and leucovorin (FOLFIRI) alone (F) or in combination with cetuximab (FC).

METHODS

We retrospectively analyzed 667 metastatic colorectal cancer patients treated with F or FC. Computed tomography quality was classified as high (HQ) or standard (SD). Four datasets were created using the nomenclature (treatment) - (quality). Patients were randomly assigned (2:1) to training or validation sets: FCHQ: 78:38, FCSD: 124:62, FHQ: 78:51, FSD: 158:78. Four tumor-imaging biomarkers measured quantitative radiomics changes between standard of care computed tomography scans at baseline and 8 weeks. Using machine learning, the performance of the signature to classify tumors as treatment sensitive or treatment insensitive was trained and validated using receiver operating characteristic (ROC) curves. Hazard ratio and Cox regression models evaluated association with overall survival (OS).

RESULTS

The signature (area under the ROC curve [95% confidence interval (CI)]) used temporal decrease in tumor spatial heterogeneity plus boundary infiltration to successfully predict sensitivity to antiepidermal growth factor receptor therapy (FCHQ: 0.80 [95% CI = 0.69 to 0.94], FCSD: 0.72 [95% CI = 0.59 to 0.83]) but failed with chemotherapy (FHQ: 0.59 [95% CI = 0.44 to 0.72], FSD: 0.55 [95% CI = 0.43 to 0.66]). In cetuximab-containing sets, radiomics signature outperformed existing biomarkers (KRAS-mutational status, and tumor shrinkage by RECIST 1.1) for detection of treatment sensitivity and was strongly associated with OS (two-sided P < .005).

CONCLUSIONS

Radiomics response signature can serve as an intermediate surrogate marker of OS. The signature outperformed known biomarkers in providing an early prediction of treatment sensitivity and could be used to guide cetuximab treatment continuation decisions.

Does perfusion computed tomography correlate to pathology in colorectal liver metastases?

Introduction

Targeted therapy against tumor angiogenesis is widely used in clinical practice for patients with colorectal liver metastases (CRLM). Possible predictive biomarkers for tumor angiogenesis, such as, microvessel density (MVD), hypoxia and cell proliferation, can be determined using immunohistochemical staining. However, patients ineligible for surgical treatment need to undergo invasive diagnostic interventions in order to determine these biomarkers. CT perfusion (CTP) is an emerging functional imaging technique, which can non-invasively determine vascular properties of solid tumors. The purpose of this study was to evaluate CTP with histological biomarkers in CRLM.

Material and methods

Patients with CRLM underwent CTP one day before liver surgery. CTP analysis was performed on the entire volume of the largest metastases in each patient. Dual-input maximum slope analysis was used and data concerning arterial flow (AF), portal flow (PF) and perfusion index (PI) were recorded. Immunohistochemical staining with CD34, M75/CA-IX and MIB-1 was performed on the rim in the midsection of the tumor to determine respectively MVD, hypoxia and cell proliferation.

Results

Twenty CRLM in 20 patients were studied. Mean size of the largest CRLM was 37 mm (95% CI 21–54 mm). Mean AF and PF were respectively 64 ml/min/100ml (95% CI 48–79) and 30 ml/min/100ml (95% CI 22–38). Mean PI was 68% (95% CI 62–73). No significant correlation was found between tumor growth patterns and CTP (p = 0.95). MVD did not significantly correlate to AF (r = 0.05; p = 0.84), PF (r = 0.17; p = 0.47) and PI (r = -0.12; p = 0.63). Cell proliferation also did not significantly correlate to AF (r = 0.07; p = 0.78), PF (r = -0.01; p = 0.95) and PI (r = 0.15; p = 0.52). Hypoxia did not significantly correlate to AF (r = -0.05; p = 0.83), however, significantly to PF (r = 0.51; p = 0.02) and a trend to negative correlation with PF (r = -0.43; p = 0.06). However, after controlling the false discovery rate, no significant correlation between CTP and used immunohistochemical biomarkers was found.

Conclusion

In conclusion, this feasibility study found a trend to negative correlation between PI and hypoxia, CTP might therefore possibly evaluate this prognostic marker in CRLM non-invasively. However, CTP is not an appropriate technique for the assessment of microvessels or cell proliferation in CRLM.

Automated Identification of Optimal Portal Venous Phase Timing with Convolutional Neural Networks

OBJECTIVES

To develop a deep learning-based algorithm to automatically identify optimal portal venous phase timing (PVP-timing) so that image analysis techniques can be accurately performed on post contrast studies.

METHODS

681 CT-scans (training: 479 CT-scans; validation: 202 CT-scans) from a multicenter clinical trial in patients with liver metastases from colorectal cancer were retrospectively analyzed for algorithm development and validation. An additional external validation was performed on a cohort of 228 CT-scans from gastroenteropancreatic neuroendocrine cancer patients. Image acquisition was performed according to each centers' standard CT protocol for single portal venous phase, portal venous acquisition. The reference gold standard for the classification of PVP-timing as either optimal or nonoptimal was based on experienced radiologists' consensus opinion. The algorithm performed automated localization (on axial slices) of the portal vein and aorta upon which a novel dual input Convolutional Neural Network calculated a probability of the optimal PVP-timing.

RESULTS

The algorithm automatically computed a PVP-timing score in 3 seconds and reached area under the curve of 0.837 (95% CI: 0.765, 0.890) in validation set and 0.844 (95% CI: 0.786, 0.889) in external validation set.

CONCLUSION

A fully automated, deep-learning derived PVP-timing algorithm was developed to classify scans' contrast-enhancement timing and identify scans with optimal PVP-timing. The rapid identification of such scans will aid in the analysis of quantitative (radiomics) features used to characterize tumors and changes in enhancement with treatment in a multitude of settings including quantitative response criteria such as Choi and MASS which rely on reproducible measurement of enhancement.

High expression of apoptosis protein (Api-5) in chemoresistant triple-negative breast cancers: an innovative target

Anti-apoptotic protein-5 (API-5) is a survival protein interacting with the protein acinus, preventing its cleavage by caspase-3 and thus inhibiting apoptosis. We studied the effect of targeting API-5 in chemoresistant triple negative breast cancers (TNBCs), to reverse chemoresistance.

78 TNBC biopsies from patients with different responses to chemotherapy were analysed for API-5 expression before any treatment. Further studies on API-5 expression and inhibition were performed on patient-derived TNBC xenografts, one highly sensitive to chemotherapies (XBC-S) and the other resistant to most tested drugs (XBC-R). In situ assessments of necrosis, cell proliferation, angiogenesis, and apoptosis in response to anti-API-5 peptide were performed on the TNBC xenografts.

Clinical analyses of the 78 TNBC biopsies revealed that API-5 was more markedly expressed in endothelial cells before any treatment among patients with chemoresistant TNBC, and this was associated with greater micro-vessel density. A transcriptomic analysis of xenografted tumors showed an involvement of anti-apoptotic genes in the XBC-R model, and API-5 expression was higher in XBC-R endothelial cells. API-5 expression was also correlated with hypoxic stress conditions both in vitro and in vivo. 28 days of anti-API-5 peptide efficiently inhibited the XBC-R xenograft via caspase-3 apoptosis. This inhibition was associated with major inhibition of angiogenesis associated with necrosis and apoptosis.

API-5 protein could be a valid therapeutic target in chemoresistant metastatic TNBC.

Weight-loss with activation of brown fat: Suspect pheochromocytoma

INTRODUCTION

Excess catecholamine stimulates heat production in brown adipose tissue (BAT). Activation of BAT can be detected in patients presenting pheochromocytoma.

CASE STUDY

A 58-year-old female patient sought medical advice due to 13 kg weight loss over 2 years accompanied by sweating and high blood pressure. Thoracic-abdominal-pelvic CT-scan revealed a solid 40 mm mass in the left adrenal compartment with peri-adrenal nodules and a solid 80 mm mass at the lower end of the right kidney. ¹⁸FDG-PET scan exhibited intense uptake in the supraclavicular, intercostal, mediastinal, peri-renal, mesenteric, iliac and inguinal spaces. Renal tumor with locoregional infiltration and remote metastases was initially considered. Diagnosis of pheochromocytoma was subsequently confirmed by a 10-fold increase in urinary catecholamine, metanephrine and normetanephrine levels. Left adrenalectomy confirmed the diagnosis of pheochromocytoma, with 3 lymph-node metastases in the adjacent adipose tissue surrounded by brown fat. The patient was clinically asymptomatic with normal blood pressure at 3 months post-surgery. A weight gain of 6 kg was recorded, with normalisation of catecholamines/metanephrine/normetanephrine levels. Bilateral peri-renal infiltration (including the right renal mass) disappeared on CT-scan, and TEP-18-FDG no longer showed hypermetabolism. Recurrent mediastinal metastases were diagnosed 6 months after surgery.

CONCLUSION

Brown fat activation may mislead diagnosis of pheochromocytoma, suggesting multi-metastatic extra-adrenal tumor, if clinicians are not aware of it.

Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm

PURPOSE

New response patterns to anticancer drugs have led tumor size-based response criteria to shift to also include density measurements. Choi criteria, for instance, categorize antiangiogenic therapy response as a decrease in tumor density > 15% at the portal venous phase (PVP). We studied the effect that PVP timing has on measurement of the density of liver metastases (LM) from colorectal cancer (CRC).

METHODS

Pretreatment PVP computed tomography images from 291 patients with LM-CRC from the CRYSTAL trial (Cetuximab Combined With Irinotecan in First-Line Therapy for Metastatic Colorectal Cancer; ClinicalTrials.gov identifier: NCT00154102) were included. Four radiologists independently scored the scans' timing according to a three-point scoring system: early, optimal, late PVP. Using this, we developed, by machine learning, a proprietary computer-aided quality-control algorithm to grade PVP timing. The reference standard was a computer-refined consensus. For each patient, we contoured target liver lesions and calculated their mean density.

RESULTS

Contrast-product administration data were not recorded in the digital imaging and communications in medicine headers for injection volume (94%), type (93%), and route (76%). The PVP timing was early, optimal, and late in 52, 194, and 45 patients, respectively. The mean (95% CI) accuracy of the radiologists for detection of optimal PVP timing was 81.7% (78.3 to 85.2) and was outperformed by the 88.6% (84.8 to 92.4) computer accuracy. The mean ± standard deviation of LM-CRC density was 68 ± 15 Hounsfield units (HU) overall and 59.5 ± 14.9 HU, 71.4 ± 14.1 HU, 62.4 ± 12.5 HU at early, optimal, and late PVP timing, respectively. LM-CRC density was thus decreased at nonoptimal PVP timing by 14.8%: 16.7% at early PVP ( P < .001) and 12.6% at late PVP ( P < .001).

CONCLUSION

Nonoptimal PVP timing should be identified because it significantly decreased tumor density by 14.8%. Our computer-aided quality-control system outperformed the accuracy, reproducibility, and speed of radiologists' visual scoring. PVP-timing scoring could improve the extraction of tumor quantitative imaging biomarkers and the monitoring of anticancer therapy efficacy at the patient and clinical trial levels.

Response Detection of Castrate-Resistant Prostate Cancer to Clinically Utilised and Novel Treatments by Monitoring Phospholipid Metabolism

Androgen receptor (AR) activation is the primary driving factor in prostate cancer which is initially responsive to castration but then becomes resistant (castration-resistant prostate cancer (CRPC)). CRPC cells still retain the functioning AR which can be targeted by other therapies. A recent promising development is the use of inhibitors (Epi-1) of protein-protein interaction to inhibit AR-activated signalling. Translating novel therapies into the clinic requires sensitive early response indicators. Here potential response markers are explored. Growth inhibition of prostate cancer cells with flutamide, paclitaxel, and Epi-1 was measured using the MTT assay. To simulate choline-PET scans, pulse-chase experiments were carried out with [³H-methyl]choline and proportion of phosphorylated activity was determined after treatment with growth inhibitory concentrations of each drug. Extracts from treated cells were also subject to ³¹P-NMR spectroscopy. Cells treated with flutamide demonstrated decreased [³H-methyl]choline phosphorylation, whilst the proportion of phosphorylated [³H-methyl]choline that was present in the lipid fraction was increased in Epi-1-treated cells. Phospholipid breakdown products, glycerophosphorylcholine and glycerophosphoethanolamine levels, were shown by 31P-NMR spectroscopy to be decreased to undetectable levels in cells treated with Epi-1. LNCaP cells responding to treatment with novel protein-protein interaction inhibitors suggest that ³¹P-NMR spectroscopy may be useful in detecting response to this promising therapy.

Principles of Kinase Inhibitor Therapy for Solid Tumors

OBJECTIVE

We aimed to identify key principles of targeted therapy of protein kinases and their application to the management of solid tumors.

BACKGROUND

Concurrent advances in tumor genomic analysis and molecular inhibitor development have dramatically impacted the diagnosis and treatment of solid tumors, and common themes regarding the use of kinase inhibitors are developing.

METHODS

The list of kinase inhibitors that have been approved by the US Food and Drug Administration was reviewed and articles related to the agents were searched in the PubMed database up until December 2015. We included pivotal, randomized controlled phase 2 and 3 trials, and also pertinent preclinical studies.

RESULTS

Small molecule inhibitors targeted against driver kinases, overactive in selected subsets of solid tumors, elicit improved response rates and survival compared with standard chemotherapy. Disease control has been proven in the metastatic and, to a limited extent, the adjuvant setting. However, tumor eradication is rare, and duration of treatment response is limited by the development of drug resistance.

CONCLUSIONS

Kinase inhibitors induce response in diverse types of solid tumors. Although the agents are often effective in defined molecular subsets, cure is rare and resistance is common. This broad review provides rationale for further investigation of multimodality therapy combining kinase inhibitors with additional systemic and local therapies, including surgery.

A Pharmacometric Framework for Axitinib Exposure, Efficacy, and Safety in Metastatic Renal Cell Carcinoma Patients

The relationships between exposure, biomarkers (vascular endothelial growth factor (VEGF), soluble VEGF receptors (sVEGFR)-1, -2, -3, and soluble stem cell factor receptor (sKIT)), tumor sum of longest diameters (SLD), diastolic blood pressure (dBP), and overall survival (OS) were investigated in a modeling framework. The dataset included 64 metastatic renal cell carcinoma patients (mRCC) treated with oral axitinib. Biomarker timecourses were described by indirect response (IDR) models where axitinib inhibits sVEGFR-1, -2, and -3 production, and VEGF degradation. No effect was identified on sKIT. A tumor model using sVEGFR-3 dynamics as driver predicted SLD data well. An IDR model, with axitinib exposure stimulating the response, characterized dBP increase. In a time-to-event model the SLD timecourse predicted OS better than exposure, biomarker- or dBP-related metrics. This type of framework can be used to relate pharmacokinetics, efficacy, and safety to long-term clinical outcome in mRCC patients treated with VEGFR inhibitors. (ClinicalTrial.gov identifier NCT00569946.).

Pharmacometric Modeling of Liver Metastases' Diameter, Volume, and Density and Their Relation to Clinical Outcome in Imatinib-Treated Patients With Gastrointestinal Stromal Tumors

Three‐dimensional and density‐based tumor metrics have been suggested to better discriminate tumor response to treatment than unidimensional metrics, particularly for tumors exhibiting nonuniform size changes. In the developed pharmacometric modeling framework based on data from 77 imatinib‐treated gastrointestinal patients, the time‐courses of liver metastases' maximum transaxial diameters, software‐calculated actual volumes (V_actual) and calculated ellipsoidal volumes were characterized by logistic growth models, in which imatinib induced a linear dose‐dependent size reduction. An indirect response model best described the reduction in density. Substantial interindividual variability in the drug effect of all response assessments and additional interlesion variability in the drug effect on density were identified. The predictive ability of longitudinal tumor unidimensional and three‐dimensional size and density on overall survival (OS) and progression‐free survival (PFS) were compared using parametric time‐to‐event models. Death hazard increased with increasing V_actual. This framework may guide early clinical interventions based on three‐dimensional tumor responses to enhance benefits for patients with gastrointestinal stromal tumors (GIST).

Dynamic Contrast-Enhanced Magnetic Resonance Imaging as a Pharmacodynamic Biomarker for Pazopanib in Metastatic Renal Carcinoma

INTRODUCTION/BACKGROUND

Traditional imaging assessment criteria might not correlate well with clinical benefit from vascular endothelial growth factor pathway-directed therapy in metastatic renal cancer. Preclinical data suggest tumor growth is preceded by a rise in K^trans level, a parameter derived from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) that reflects vascular permeability. We thus hypothesized that K^trans might be a predictive biomarker for pazopanib.

PATIENTS AND METHODS

Patients with metastatic renal cancer were treated with pazopanib at 800 mg oral daily until disease progression. MRI of the abdomen and pelvis with a DCE-MRI sequence was obtained at baseline and every 8 weeks.

RESULTS

Seventy-three DCE-MRI scans were completed and 66 were technically assessable. Of the 17 patients with at least 1 DCE-MRI scan after the baseline scan, 16 (94%) had a decline in K^trans level. Changes in K^trans compared with baseline after 1, 8, 16, and 24 weeks were -49%, -65%, -63%, and -53%, respectively (P = .0052, repeated measures analysis of variance). The median K^trans nadir occurred at 8 weeks. The median progression-free survival (PFS) was 32.1 weeks. PFS was longer in patients with higher baseline K^trans values (P = .036, log rank). Baseline K^trans did not reach significance in a Cox proportional hazard model including clinical prognostic index and previous treatments (P = .083).

CONCLUSION

We show that K^trans is a pharmacodynamic biomarker for pazopanib therapy in metastatic renal cancer. Because of the small sample size, the predictive capacity of K^trans recovery could not be assessed, but baseline K^trans correlated with PFS.

Optimizing clinical benefit with targeted treatment in mRCC: "Tumor growth rate" as an alternative clinical endpoint

Tumor growth rate (TGR), usually defined as the ratio between the slope of tumor growth before the initiation of treatment and the slope of tumor growth during treatment, between the nadir and disease progression, is a measure of the rate at which tumor volume increases over time. In patients with metastatic renal cell carcinoma (mRCC), TGR has emerged as a reliable alternative parameter to allow a quantitative and dynamic evaluation of tumor response. This review presents evidence on the correlation between TGR and treatment outcomes and discusses the potential role of this tool within the treatment scenario of mRCC. Current evidence, albeit of retrospective nature, suggests that TGR might represent a useful tool to assess whether treatment is altering the course of the disease, and has shown to be significantly associated with progression-free survival and overall survival. Therefore, TGR may represent a valuable endpoint for clinical trials evaluating new molecularly targeted therapies. Most importantly, incorporation of TGR in the assessment of individual patients undergoing targeted therapies may help clinicians decide if a given agent is no longer able to control disease growth and whether continuing therapy beyond RECIST progression may still produce clinical benefit.

[Modern imaging of renal tumors - application in diagnostics and therapy. Characterization, operation planning and therapy monitoring of renal lesions]

This article elucidates the various tools used for the diagnostics and characterization of renal lesions. The advantages and limitations of ultrasound, contrast-enhanced ultrasound (CEUS), computed tomography (CT) and magnetic resonance imaging (MRI) are presented and discussed. In addition, modern imaging features of CT and MRI, such as iodine quantification in CT as well as diffusion-weighted and perfusion imaging in MRI are presented. Lastly, recent developments in standardized reporting of renal tumors regarding the intraoperative surgical risk are presented.

Surgical considerations for patients with metastatic renal cell carcinoma

Among patients with renal cell carcinoma (RCC), 25-30% present with metastatic disease at the time of initial diagnosis. Despite the ever-increasing array of treatment options available for these patients, surgery remains one of the cornerstones of therapy. Proper patient selection for cytoreductive surgery is paramount to its effective use in the management of patients with metastatic RCC despite the decrease in reported morbidity rates. We explore the evolving role cytoreductive surgery in metastatic RCC spanning the immunotherapy era to the targeted therapy era. Despite significant advances in the management of patients with metastatic RCC, further evidence on the definitive role of cytoreductive surgery in the targeted therapy era is awaited through large randomized trials.

Predictive biomarker candidates to delineate efficacy of antiangiogenic treatment in renal cell carcinoma

Antiangiogenic therapy is currently considered as the cornerstone of treatment in metastatic kidney cancer. A monoclonal antibody against the vascular endothelial growth factor (VEGF) and several tyrosine kinase inhibitors targeting the VEGF receptors demonstrated, 7 years ago, to deeply impact the outcome of this tumor and became a model of integration of molecular knowledge into clinical practice. Unfortunately, no further improvement in survival has been made and 20-25 % of cases remain primary refractory to these drugs, with an overall dismal prognosis. Since biomarker predictors of activity are lacking, their development could highly help in the process of making clinical decisions when choosing the best option for every patient or prompting the inclusion in clinical trials. This unmet medical need could become even more relevant if new immunotherapy confirms its initial promising results in this pathology. In this article, we provide an insight of current state of the art regarding the prediction of antiangiogenic efficacy in kidney cancer and propose new strategies for the implementation of such markers in clinical practice.

PET/Computed Tomography in Renal, Bladder, and Testicular Cancer

Imaging plays an important role in the clinical management of cancer patients. Hybrid imaging with PET/computed tomography (CT) is having a broad impact in oncology, and in recent years PET/CT is beginning to have an impact in urooncology. In both bladder and renal cancers, there is a need to study the efficacy of other tracers than F-18 fluorodeoxyglucose (FDG), particularly tracers with limited renal excretion. Thus, new tracers are being introduced. This review focuses on the clinical role of FDG and other PET agents in renal, bladder, and testicular cancers.