Predicting Immunotherapy Response in Head and Neck Cancer
"Notes from the Lab" spotlights innovative work addressing problems in cancer research and care from Columbia investigators, post-docs, fellows, and students.
The Momen-Heravi Lab
We are actively exploring the complex interplay between the immune system, microenvironment and tumor to identify molecular targets for head and neck cancer, primarily, and other solid tumor treatments.
The Research
“SP140 inhibits STAT1 signaling, induces IFN-γ in tumor-associated macrophages, and is a predictive biomarker of immunotherapy response”, published in the Journal for ImmunoTherapy of Cancer.
The cancer problem we are solving
Immunotherapy has revolutionized the treatment landscape of cancer, offering a new strategy to provide precise, tailored treatments for each individual patient. However, immunotherapy is beneficial in only a subset of patients. It is still a very new field, and we don’t yet know which patients will respond to immunotherapy and which will not, as we do not have reliable biomarkers for predicting patients’ response. That’s the bottleneck in the field we are addressing: understanding and predicting immunotherapy responders to move towards personalized medicine.
We investigate prognostic and predictive biomarkers for patient selection to improve immunotherapy response in different tumors. We’re focused on head and neck cancer, but we are also interested in patient response from different tumor types. Right now, there are no predictive biomarkers for response to immunotherapy in head and neck cancer. Very little data is available about how well head and neck and cancer patients do on immunotherapy drugs, or data that can help us identify patient selection for therapies.
A bit of background
About a decade ago, we started really understanding that studying tumors are not limited only to cancer cells; we now know the tumor microenvironment, comprising the different cells, including T cells and macrophages, all play a very important role in tumor progression, pathogenesis and the aggressiveness of tumors and also their response to therapy. Historically, most of the efforts and most of the studies have focused on T cells alone. But right now, we know that just looking at T cells offers us a very limited view. Tumor-associated macrophages (TAMs) are very abundant cell types in the tumor microenvironment and comprise up to 50% of tumor mass. TAMs play an important role in cancer progression and response to therapy but their subtypes and diverse functional roles have not been fully studied.
What this new research uncovers
We evaluated the correlation between SP140 expression, an epigenetic reader, in head and neck squamous cell carcinoma (HNSCC) TAMs and clinical outcomes. Epigenetic readers are a group of proteins that assist other protein interactions with DNA elements to mediate cellular and physiological outcomes.
We used complementary bioinformatics and experimental approaches to study the association of SP140 expression with tumor mutation burden, patient survival, signaling pathways of TAMs, and essentially to dissect overall response to immunotherapy. We found that SP140 is differentially expressed in TAMs across many cancer types, including HNSCCs, and high expression of SP140 correlates with improved survival and a favorable response to immunotherapy. Functional activation of SP140 by a CRRIPR gene-editing activation system in macrophages resulted in inhibiting cancer cells proliferation. This highlights the opportunity of altering, or editing, macrophages to fight cancer cells.
As a result of this work, high expression of SP140 in HNSCC patients can be used as a predictive biomarker for therapeutic decision making around immunotherapy.
Next steps
We are currently exploring the idea to move this research to the bedside and apply this finding as a prospective biomarker for patient selection. Perhaps we could use this as a tool to prospectively decide which patients will have a more favorable response to a certain type of immunotherapy. This work is also increasing our knowledge of how we can engineer tumor associated macrophages to increase patient response to immunotherapy. We are actively work to further uncover mechanisms behind how immunotherapy works—or doesn’t work—for individual patients.