Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations

Abstract

The success of antibodies targeting Programmed cell death protein 1 (PD-1) and its ligand L1 (PD-L1) in cancer treatment and the need for improving response rates has led to an increased demand for the development of combination therapies with anti-PD-1/PD-L1 blockers as a backbone. As more and more drugs with translational potential are identified, the number of clinical trials evaluating combinations has increased considerably and the demand to prioritize combinations having potential for success over the ones that are unlikely to be successful is rising. This review aims to address the unmet need to prioritize cancer immunotherapy combinations through comprehensive search of potential drugs and ranking them based on their mechanism of action, clinical efficacy and safety. As lung cancer is one of the most frequently studied cancer types, combinations that showed potential for the treatment of lung cancer were prioritized. A literature search was performed to identify drugs with potential in combination with PD-1/PD-L1 blockers and the drugs were ranked based on their mechanism of action and known clinical efficacy. Nineteen drugs or drug classes were identified from an internal list of lead molecules and were scored for their clinical potential. Efficacy and safety data from pivotal studies was summarized for the selected drugs. Further, overlap of mechanisms of action and adverse events was visualized using a heat map illustration to help screen drugs for combinations. The quantitative scoring methodology provided in this review could serve as a template for preliminary ranking of novel combinations.

Keywords: Cancer; Cancer immunotherapy; Clinical trials; Combination development; Pharmacology.

Fig. 1

Flow chart of the search and elimination process for selection of drugs of interest. *PD-1/PD-L1 class of drugs, were preselected as they are considered as the backbone for combination studies. The final number of drugs selected is 20 (19 + anti-PD-1/PD-L1)

Fig. 2

Pie chart of molecule classification. Coloring is used to identify tumor type, and mechanism of action, with the inner sectors representing development stage. Drugs are classified using a hybrid of multiple components including development stage, tumor type, mechanism of action, and are bucketed as passive or active immunotherapies based on immune response activation. Passive immunotherapies include molecules expressed in low levels; they rectify deficient immune system typically used for patients with impotent immune systems. These could include the monoclonal antibodies targeting malignant cells, adoptive transfer of immune cells, adjuvants, recombinant cytokines, inhibitors of signaling pathways, delivery of cytotoxins, activators of ADCC, tumor antigen targeting, and oncolytic viruses; which typically require multiple administrations to be efficient. Active immunotherapies are designed to activate effector function of immune cells. These include activation of endogenous and long-lasting immune responses including vaccines, blockade by checkpoint inhibitors, oncolytic viruses, immunomodulatory mAbs, immunostimulatory cytokine adjuvants to augment immunotherapy response, mAbs to proinflammatory cytokines, immunogenic cell death inducers such as chemotherapies, and pattern recognition receptor agonists.

Fig. 3

Flow chart showing the point of action for screened drugs. Tumor cell cytotoxicity is mainly achieved by effector T-cells and NK cells, which results in antigen release and reduction in tumor size. Release of antigens along with cellular components such as danger associated molecular patterns (DAMPs) result in maturation of DCs and macrophages, which present antigens and activate the T-cells, and promote their differentiation into effector T-cells. Tumor size is known to negatively affect the activity of effector T-cells and NK cells. Similarly, presence of immunosuppressor cells in tumor microenvironment and exhaustion have negative effects on the activity of effector T-cells and NK cells. Finally, decreased infiltration of effector T-cells and NK cells in the tumor also leads to decreased anti-tumor immune response. In the flow diagram, all the major processes that control the anti-tumor immune response are presented as nodes. (+) indicates positive effect of the molecule/target on the node and (-) indicates inhibitory effect of the molecule/target on the node

Fig. 4

Heat map showing overlap of (A) Mechanism of action (B) Serious AEs and/or Grade 3 or above AEs for screened drugs (A) *chemotherapy has also been shown in some studies to downregulate PD-L1 and PD-L2 expression on DCs and induce cytotoxic activity of CTLs and NK cells, B * Early reports from clinical studies evaluating TIGIT did not report any dose limiting toxicities, except a case of grade 2 diarrhea. **Reduced blood cell count is used as a broad category of AEs and includes direct suppression of bone marrow generation of blood cells as well as indirect reductions in blood cell counts resulting in neutropenia, anemia, decreased lymphocyte count and thrombocytopenia. *** SAEs sorted in the ‘Others’ category are sometimes unique for the drug and cannot be combined as a single category. Early phase 1 studies for anti-Tim-3, anti-Lag-3, AB928 and Reolysin did not report serious adverse events but evidence from studies in larger cohort is not available and are represented accordingly (grey). Data includes rare events and may include AEs that are probably not related to study. ARF, acute renal failure; ALF, acute liver failure