Activating Inducible T-cell Costimulator Yields Antitumor Activity Alone and in Combination with Anti-PD-1 Checkpoint Blockade

Tutorial on Conditional Simulations With a Tumor Size-Overall Survival Model to Support Oncology Drug Development

The gold standard for regulatory approval in oncology is overall survival (OS). Because OS data are initially limited, early drug development decisions are often based on early efficacy endpoints, such as objective response rate and progression-free survival. Tumor size (TS)-OS models provide a framework to support decision-making on potential late-stage success based on early readouts, through leveraging TS data with limited follow-up and treatment-agnostic TS-OS link functions, to predict longer-term OS. Conditional simulations (also known as Bayesian forecasting) with TS-OS models can be used to simulate long-term OS outcomes for an ongoing study, conditional on the available TS and OS data at interim data cuts of the same study. This tutorial provides a comprehensive overview of the steps involved in using such conditional simulations to support better informed drug development decisions in oncology. The tutorial covers the selection of the TS-OS framework model; applying the TS-OS model to the interim data; performing conditional simulations; generating relevant output; as well as correct interpretation and communication of the output for decision making.

Development of a Joint Tumor Size-Overall Survival Modeling and Simulation Framework Supporting Oncology Development Decision-Making

Tumor size-overall survival (TS-OS) models can support decision-making in oncology drug development by predicting long-term OS based on TS data from early data cuts and baseline patient factors. The current work describes the development of a TS-OS framework capable of predicting OS across a variety of treatment modalities and mechanisms of action in patients with non-small cell lung cancer from seven clinical studies. The presented framework jointly models TS with a bi-exponential Stein model and OS with an accelerated failure time log-normal survival model. In the corresponding link function between TS and OS, the most significant predictor of OS was the tumor growth rate (kg), applied via an Emax function. Time to tumor growth and baseline TS were additional TS predictors informing OS. Albumin, total protein, and neutrophil-to-lymphocyte ratio were selected from the tested baseline factors as the most significant predictors of OS. Significant baseline covariates for the TS model included number of target lesions on baseline TS, tumor PD-L1 expression on tumor shrinkage rate, and lactate dehydrogenase levels on kg. The TS-OS framework model adequately describes the OS distributions within this specific set of treatment modalities-chemotherapies, immuno-oncology treatments, and combinations thereof-using a single treatment-independent link function, supporting the use of the framework to support evaluation and design of future studies. Our findings contribute to a body of literature exploring and qualifying TS-OS modeling as a methodology capable of supporting and accelerating oncology drug development.

Unlocking the potential of exosomes: A new frontier in liver cancer liquid biopsy

Liquid biopsy has emerged as one of the non-invasive diagnostic strategies for cancer, offering significant advantages over traditional tissue biopsies. Exosomes the nanoscale extracellular vesicles, have significantly been in the spotlight of research and investigation as highly informative biomarkers in liquid biopsy. These vesicles, which are secreted by a variety of cells, including tumor cells, contain useful information on the molecular characteristics of the parent cell and could be used as a mirror into the processes underlying cancer biology. The analysis of the biomolecular exosomal cargo, including proteins, nucleic acids, and lipids, has shown great promise for the development of sensitive and specific liquid biopsy-based biomarkers for cancer detection, monitoring, and prognosis. This review discusses the role of exosomes in the liver cancer development and metastatic process, including their ability to transfer oncogenic material and facilitate tumor progression. It also explores the application of exosomes as a tool for early cancer detection, monitoring disease status, and predicting prognosis, with a specific focus on liver cancer. Exosomes hold great promise as a minimally invasive liquid biopsy approach that could revolutionize the way we diagnose and manage this deadly disease.

Tumor Microenvironment Drives the Cross-Talk Between Co-Stimulatory and Inhibitory Molecules in Tumor-Infiltrating Lymphocytes: Implications for Optimizing Immunotherapy Outcomes

This review explores some of the complex mechanisms underlying antitumor T-cell response, with a specific focus on the balance and cross-talk between selected co-stimulatory and inhibitory pathways. The tumor microenvironment (TME) fosters both T-cell activation and exhaustion, a dual role influenced by the local presence of inhibitory immune checkpoints (ICs), which are exploited by cancer cells to evade immune surveillance. Recent advancements in IC blockade (ICB) therapies have transformed cancer treatment. However, only a fraction of patients respond favorably, highlighting the need for predictive biomarkers and combination therapies to overcome ICB resistance. A crucial aspect is represented by the complexity of the TME, which encompasses diverse cell types that either enhance or suppress immune responses. This review underscores the importance of identifying the most critical cross-talk between inhibitory and co-stimulatory molecules for developing approaches tailored to patient-specific molecular and immune profiles to maximize the therapeutic efficacy of IC inhibitors and enhance clinical outcomes.

ICOS limits memory-like properties and function of exhausted PD-1 + CD8 T cells

During persistent antigen stimulation, PD-1 + CD8 T cells are maintained by progenitor exhausted PD-1 + TCF-1 + CD8 T cells (Tpex). Tpex respond to PD-1 blockade, and regulation of Tpex differentiation into more functional Tex is of major interest for cancer immunotherapies. Tpex express high levels of Inducible Costimulator (ICOS), but the role of ICOS for PD-1 + CD8 T cell responses has not been addressed. In chronic infection, ICOS-deficiency increased both number and quality of virus-specific CD8 T cells, with accumulation of effector-like Tex due to enhanced survival. Mechanistically, loss of ICOS signaling potentiated FoxO1 activity and memory-like features of Tpex. In mice with established chronic infection, ICOS-Ligand blockade resulted in expansion of effector-like Tex and reduction in viral load. In a mouse model of hepatocellular carcinoma, ICOS inhibition improved cytokine production by tumor-specific PD-1 + CD8 T cells and delayed tumor growth. Overall, we show that ICOS limits CD8 T cell responses during chronic antigen exposure.

Deciphering Regulatory T-Cell Dynamics in Cancer Immunotherapy: Mechanisms, Implications, and Therapeutic Innovations

This Review explores how tumor-associated regulatory cells (Tregs) affect cancer immunotherapy. It shows how Tregs play a role in keeping the immune system in check, how cancers grow, and how well immunotherapy work. Tregs use many ways to suppress the immune system, and these ways are affected by the tumor microenvironment (TME). New approaches to cancer therapy are showing promise, such as targeting Treg checkpoint receptors precisely and using Fc-engineered antibodies. It is important to tailor treatments to each patient's TME in order to provide personalized care. Understanding Treg biology is essential for creating effective cancer treatments and improving the long-term outcomes of immunotherapy.

The future of targeting cytotoxic T-lymphocyte-associated protein-4: Is there a role?

The 2022 yearly Think Tank Meeting in Siena, Tuscany (Italy), organized by the Italian Network for Tumor Biotherapy (NIBIT) Foundation, the Parker Institute for Cancer Immunotherapy and the World Immunotherapy Council, included a focus on the future of integrating and expanding the use of targeting cytotoxic T-lymphocyte-associated protein 4 (CTLA-4). The conference members exchanged their views on the lessons from targeting CTLA-4 and compared the effect to the impact of blocking Programmed cell death protein 1 (PD1) or its ligand (PDL1). The increasing experience with both therapeutic approaches and their combination suggests that targeting CTLA-4 may lead to more durable responses for a sizeable proportion of patients, though the specific mechanism is not entirely understood. Overcoming toxicity of blocking CTLA-4 is currently being addressed with different doses and dose regimens, especially when combined with PD1/PDL1 blocking antibodies. Novel therapeutics targeting CTLA-4 hold the promise to reduce toxicities and thus allow different combination strategies in the future. On the whole, the consent was that targeting CTLA-4 remains an important strategy to improve the efficacy of cancer immunotherapies.