A merger of math and medicine may help to improve the efficacy of immunotherapies, potentially life-saving treatments that enhance the ability of the patient’s own immune system to attack cancerous tumors.
By creating mathematical models that represent the complex interactions within the tumor microenvironment (TME), the nonmutated cells, connective tissues and blood vessels inside a malignant tumor, Harvard Medical School researchers based at Massachusetts General Hospital can predict how tumors may respond to immunotherapy and how adding other anti-cancer drugs could lead to improved treatment.
In addition, the models suggest that the relative health of a tumor’s blood supply could predict how that tumor will respond to immunotherapy. Their work is described online in Proceedings of the National Academy of Sciences.
Immune checkpoint inhibitors such as pembrolizumab and nivolumab have greatly improved treatment for more than a dozen malignancies, including non-small cell lung cancer, kidney cancer and melanoma, but even in these cancers, only a minority of patients benefit from these immunotherapies.
“An estimated 87 percent of patients currently do not derive long-term benefit from immune checkpoint blocker monotherapy. Therefore, new therapeutic strategies are needed to improve the response rates in patients who are resistant to immune checkpoint inhibition,” said co-author Rakesh Jain, the HMS A. Werk Cook Professor of Radiation Oncology (Tumor Biology) at Mass General.
Impaired perfusion, or flow of blood through vessels in tissues, is a common feature of many tumor types. This can limit the ability of drugs to reach malignant cells and results in hypoxia, abnormally low oxygen levels that can, in turn, lead to suppression of the immune response.
To address this problem, Jain and colleagues used a combination of computational and systems biology techniques to develop a model to determine whether “normalization” of the blood vessels and connective tissues in the TME could improve the efficacy of immunotherapy.
Although others have developed systems-level mathematical models to predict tumor response to immune checkpoint inhibitors, the researchers of the PNAS study are the first to incorporate crucial components and interactions of cells with the TME. Their model also incorporates known mechanisms of immune response to explain how the TME might adversely affect the efficacy of immunotherapy and to predict tumor response to checkpoint inhibitors.
The study points to potential strategies for normalizing the TME to improve the response to immunotherapy. For example, normalization of the stroma with common drugs for treating high blood pressure could improve the treatment of desmoplastic tumors, which are marked by dense tissues and compressed highly abundant but disorganized blood vessels.
Conversely, perfusion in tumors with open, leaky blood vessels could be improved with low-dose anti-angiogenic drugs currently on the market, allowing for better delivery of immunotherapy to target tissues.
“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,” said co-corresponding author Triantafyllos Stylianopoulos of the University of Cyprus.