Vascular endothelial growth factor-targeted therapy in patients with renal cell carcinoma pretreated with immune checkpoint inhibitors: A systematic literature review.

INTRODUCTION: We conducted a systematic literature review to identify evidence for use of vascular endothelial growth factor (VEGF)-targeted (anti-VEGF) treatment in patients with renal cell carcinoma (RCC) following prior checkpoint inhibitor (CPI)-based therapy. METHODS: This was a PRISMA-standard systematic literature review; registered with PROSPERO (CRD42021255568). Literature searches were conducted in MEDLINE®, Embase, and the Cochrane Library (January 28, 2021; updated September 13, 2022) to identify publications reporting efficacy/effectiveness and safety/tolerability evidence for anti-VEGF treatment in patients with RCC who had received prior CPI therapy. RESULTS: Of 2,639 publications screened, 48 were eligible and featured 2,759 patients treated in trials and 2,209 in real-world studies (RWS). Most patients with available data were treated with anti-VEGF tyrosine kinase inhibitor-based regimens (trials: 93 %; RWS: 100 %), most commonly cabozantinib, which accounted for 46 % of trial and 62 % of RWS patients in publications with available data. Collectively, there was consistent evidence of anti-VEGF treatment activity after prior CPI therapy. Activity was reported for all anti-VEGF regimens and regardless of prior CPI-based regimen. No new safety signals were detected for subsequent anti-VEGF therapy; no studies suggested increased immune-related adverse events associated with prior CPI therapy. The results were limited by data quality; study heterogeneity prohibited meta-analyses. CONCLUSION: Based on the available data (most commonly for cabozantinib), anti-VEGF therapy appears to be a rational treatment choice in patients with RCC who have progressed despite prior CPI-based therapy. Results from ongoing trials of combination anti-VEGF plus CPI regimen post prior CPI therapy trials will contribute more definitive evidence. PLAIN LANGUAGE SUMMARY: Anticancer treatments that work by reducing levels of a substance in the body called Vascular Endothelial Growth Factor are known as anti-VEGF drugs. Reducing VEGF levels helps to reduce blood supply to tumors, which can slow the speed at which the cancer grows. Some other types of anticancer drugs that help the immune system to fight cancer cells are called checkpoint inhibitors. Here, we looked at published studies that investigated how anti-VEGF drugs work, and what side effects they cause, in people who have already been treated with checkpoint inhibitors for a type of kidney cancer called renal cell carcinoma. We aimed to summarize the available evidence to help doctors decide how best to use anti-VEGF drugs in these patients. We found 48 studies that included almost 5,000 patients. The results of the studies showed that anti-VEGF drugs have anticancer effects in people with renal cell carcinoma who had already been treated with checkpoint inhibitors. All of the VEGF-targeting drugs had anticancer effects, irrespective of what checkpoint inhibitor treatment people had received before. There were different amounts of evidence available for the different anti-VEGF drugs. The anti-VEGF cabozantinib had the largest amount of evidence. Importantly, previous checkpoint inhibitor treatment did not seem to affect the number or type of side-effects associated with anti-VEGF drugs. Results from ongoing, well-designed studies will be helpful to confirm these results. Our findings may be useful for doctors considering using anti-VEGF drugs in patients with renal cell carcinoma who have received checkpoint inhibitor treatment.

Exploring the synergistic effects of cabozantinib and a programmed cell death protein 1 inhibitor in metastatic renal cell carcinoma with machine learning.

Clinical evidence supports the combination of cabozantinib with an immune checkpoint inhibitor for the treatment of metastatic clear cell renal cell carcinoma (mccRCC) and suggests a synergistic antitumour activity of this combination. Nevertheless, the biological basis of this synergy is not fully characterized. We studied the mechanisms underpinning the potential synergism of cabozantinib combined with a PD1 inhibitor in mccRCC and delved into cabozantinib monotherapy properties supporting its role to partner these combinations. To model physiological drug action, we used a machine learning-based technology known as Therapeutic Performance Mapping Systems, applying two approaches: Artificial Neural Networks and Sampling Methods. We found that the combined therapy was predicted to exert a wide therapeutic action in the tumour and the microenvironment. Cabozantinib may enhance the effects of PD1 inhibitors on immunosurveillance by modulating the innate and adaptive immune system, through the inhibition of VEGF-VEGFR and Gas6-AXL/TYRO3/MER (TAM) axes, while the PD1 inhibitors may boost the antiangiogenic and pro-apoptotic effects of cabozantinib by modulating angiogenesis and T-cell cytotoxicity. Cabozantinib alone was predicted to restore cellular adhesion and hamper tumour proliferation and invasion. These data provide a biological rationale and further support for cabozantinib plus PD1 inhibitor combination and may guide future nonclinical and clinical research.

Chemoproteomic Approach to Explore the Target Profile of GPCR ligands: Application to 5-HT1A and 5-HT6 Receptors.

Determination of the targets of a compound remains an essential aspect in drug discovery. A complete understanding of all binding interactions is critical to recognize in advance both therapeutic effects and undesired consequences. However, the complete polypharmacology of many drugs currently in clinical development is still unknown, especially in the case of G protein-coupled receptor (GPCR) ligands. In this work we have developed a chemoproteomic platform based on the use of chemical probes to explore the target profile of a compound in biological systems. As proof of concept, this methodology has been applied to selected ligands of the therapeutically relevant serotonin 5-HT1A and 5-HT6 receptors, and we have identified and validated some of their off-targets. This approach could be extended to other drugs of interest to study the targeted proteome in disease-relevant systems.

Chemical probes for the recognition of cannabinoid receptors in native systems.

Receptors made visible: The described biotin-tagged small-molecule probes with excellent affinities for the CB(1) and CB(2) cannabinoid receptors (CB(1)R and CB(2)R) enable direct visualization of these receptors in native cellular systems, including neurons, microglia, and immune cells. This method could overcome some of the limitations of current methodologies and may help to dissect the complexity of the endogenous cannabinoid system.

Development of endocannabinoid-based chemical probes for the study of cannabinoid receptors.

We report the synthesis of new chemical probes (1a,b, 2a-c, 3a-c) based on the structure of the main endocannabinoids for their use in biological systems directly or via click chemistry. As proof of concept, 2-arachidonyl glyceryl ether based biotinylated 3b enables direct visualization of CB(1) receptor in cells. These results represent the starting point for the development of advanced small molecule chemical probes able to generate valuable information about the cannabinoid receptors.

Ligand-based approach to in silico pharmacology: nuclear receptor profiling.

Bioactive ligands are a valuable and increasingly accessible source of information about protein targets. On the basis of this statement, a list of 25 nuclear receptors was described by a series of bioactive ligands extracted directly from bibliographical sources, stored properly in an annotated chemical library, and mathematically represented using the recently reported SHED molecular descriptors. Analysis of this ligand information allowed for derivation of a threshold of nuclear receptor concern. If the similarity of one molecule to any of the molecules annotated to one particular nuclear receptor is below that threshold, the molecule receives an alert on the probability of having affinity below 10 microM for that nuclear receptor. On this basis, a linkage map was constructed that reveals the interaction network of nuclear receptors from the perspective of their active ligands. This ligand-based approach to nuclear receptor profiling was subsequently applied to four external chemical libraries of 10,000 molecules targeted to proteases, kinases, ion channels, and G protein-coupled receptors. The percentage of each library that returned an alert on at least one nuclear receptor was reasonably low and varied between 4.4 and 9.7%. In addition, ligand-based nuclear receptor profiling of a set of 2944 drugs provided an alert for 153 drugs. For some of them, namely, acitretin, telmisartan, phenyltoloxamine, tazarotene, and flumazenil, bibliographical evidence could be found indicating that those drugs may indeed have some potential off-target residual affinity for the nuclear receptors annotated. Overall, the present findings suggest that ligand-based approaches to protein family profiling appear as a promising means toward the establishment of novel tools for in silico pharmacology.