February 4, 2020 -- Scientists working at the intersection of math and medicine propose new strategies based on mathematical modeling and known molecular mechanisms to improve the efficacy of lifesaving immunotherapies for cancerous tumors. The work was published on February 3 in the Proceedings of the National Academy of Sciences.
Cancer cells can evade immune responses by activating negative regulatory pathways, known as immune checkpoints, that block T-cell activation. Inhibition is mediated by binding of programmed cell death protein 1 (PD-1) receptor of T cells to the ligand (PD-L1) or binding of cytotoxic T lymphocyte antigen 4 (CTLA-4) receptor of T cells to the B7 molecules in response to various cytokines, such as interferon-γ (IFNγ).
This has led to the development of immune checkpoint blockers (ICBs), such as anti-PD1/anti-PD-L1 and anti-CTLA-4 antibodies. ICBs are used as monotherapies or in combination with other treatments for more than a dozen types of cancer. For example, Keytruda (pembrolizumab) and Opdivo (nivolumab) have improved treatments for non-small cell lung cancer, kidney cancer, and melanoma.
However, "an estimated 87% of patients currently do not derive long-term benefit from immune checkpoint blocker monotherapy," noted study co-author Rakesh Jain, PhD, from the Edwin L. Steele Laboratories in the department of radiation oncology at Massachusetts General Hospital and Harvard Medical School, in a statement. "Therefore, new therapeutic strategies are needed to improve the response rates in patients who are resistant to immune checkpoint inhibition."
The lack of therapeutic effect is attributed to a number of causes, including abnormal tumor microenvironment (TME). This can be caused by dysfunctional blood vessels that hinder the delivery of immunotherapies. The spatiotemporal lack of sufficient tumor blood perfusion can lead to hypoxia, low pH, suppressed immune response, and inadequate medicine delivery -- allowing cancers to thrive.
To address this concern, the researchers used a combination of computational and systems biology techniques to develop a mathematical model to determine whether "normalization" of the blood vessels and stroma (connective tissues) in the TME could improve the efficacy of immunotherapy.
This approach is unique because the researchers incorporated crucial components into their model -- M1- and M2-like tumor-associated macrophages, CD4+, CD8+, regulatory T cells (Tregs), vascular cells, and perivascular cells. With these factors, the researchers simulated how antiangiogenic, stroma normalization, and immunotherapy treatments interact with cells in the TME to explain what might adversely affect immunotherapy efficacy and predicted tumor response to ICBs. The model is justified by favorable agreement of its predictions with a large number of experimental studies.
The study also points to potential strategies for normalizing the TME to improve the response to immunotherapy based on the state of individual tumors. For example, researchers suggest that stroma normalization is beneficial in desmoplastic tumors (dense in connective tissues -- i.e., pancreatic ductal adenocarcinomas). This can be treated with common antiangiogenic drugs (bevacizumab for the treatment of high blood pressure). Whereas vascular normalization improves perfusion in tumors with hyperpermeable vessels with open lumens. These strategies can be used on a case-by-case basis to allow improved delivery of immunotherapies to target tissues.
Moreover, "the identification of tumor perfusion as key to the efficacy of immunotherapy suggests that perfusion could serve as a biomarker of response to immunotherapeutic agents," added co-author Triantafyllos Stylianopoulos, PhD, from the University of Cyprus.
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