Researchers at the Johns Hopkins Kimmel Cancer Center and Bloomberg~Kimmel Institute for Cancer Immunotherapy have developed a computer model to help identify tumor-fighting immune cells in lung cancer patients receiving immune checkpoint inhibitors.
In their study, published on February 3 in Nature Communications, the team—including first author Zhen Zeng, Ph.D., a bioinformatics research associate at the Kimmel Cancer Center—demonstrated that their three-gene “MANAscore” model can pinpoint the immune cells targeted by immune checkpoint therapies. The model also helped uncover differences linked to patient responses to immunotherapy.
“We have developed a way to identify the cells directly targeted by immune checkpoint inhibitors, and if we can identify them, we can study them,” says the study’s senior author, Kellie Smith, Ph.D., an associate professor of oncology at Johns Hopkins. “If we can study them, that means we can identify better biomarkers and better targets for combination immunotherapy.”
Immune checkpoint inhibitors, such as PD-1 inhibitors, are used to treat a variety of cancer types. These groundbreaking therapies work by activating tumor-fighting immune cells called T cells, which are normally suppressed by the protein PD-1. PD-1 inhibitors “turn on” the patient’s T cells, enabling the immune system to better target and fight cancer. However, not all patients respond to these treatments, and understanding why is crucial for developing better therapies that can help those who don’t respond.
“Tumor-active T cells are very important to a patient’s response to therapy, but they are difficult to find,” Zeng says.
Smith contributed to the development of the MANAFEST technology (Mutation-Associated NeoAntigen Functional Expansion of Specific T Cells), which she and her colleagues first introduced in Cancer Immunology Research in 2018. Their approach combined MANAFEST with single-cell sequencing to identify rare immune cells in six lung cancer patients—a complex process that took several years and millions of dollars. The original study revealed that immune cells activated by immunotherapy shared a common gene expression profile. In their new study, Zeng, Smith, and their team expanded on these findings to create MANAscore.
“Our model allows us to skip a time-consuming and expensive process to identify the cells targeted by immunotherapy, and will help us identify what distinguishes who will respond to these therapies,” Smith says. “We’re not the first to come up with one of these models, but what sets ours apart is that it uses only three genes, while the most commonly used model requires more than 200 genes. Ours is simpler and easier to use.”
The team also discovered significant differences in the T cells activated in the tumors of patients who respond to immune checkpoint therapy compared to those who don’t. Patients who respond have a higher proportion of stem-like memory T cells, which serve as a reservoir for new cells and can evolve into a variety of effective anti-tumor cells, according to Zeng. This finding may help explain why certain patients are better able to respond—these stem-like characteristics may facilitate the rapid expansion of T cells into a larger population of tumor-fighting cells. However, further studies are needed to validate these observations.
“The stem-like characteristics of T cells are critical because they enable self-renewal and long-term persistence,” Zeng says. “This allows for sustained immune responses and the ability to expand into a robust population of effector T cells when needed.”
In the interim, the team is working on developing a clinical test that utilizes multispectral immunofluorescence panels to identify the three-gene signature of T cells that respond to immunotherapy.
“We hope to translate our three-gene signature into a biomarker that clinicians can use to guide cancer care,” Smith says.
Zeng is also using their new model to explore whether the proximity of T cells with the three-gene signature to other immune cells, such as regulatory T cells, plays a role in controlling the immune response.
“We want to apply our model to spatial data to learn whether cell-to-cell interactions among tumor-targeting T cells and other cell types affect clinical outcomes,” Zeng says.
She is also working with laboratories nationwide to investigate whether MANAscore can be applied to patients with various types of cancer. They have created a database of single-cell sequencing data from different cancer types and plan to use the score to identify T cell characteristics specific to responders in each cancer type.
Other scientists who also worked on the research include: Tianbei Zhang, Shuai Li, Sydney Connor, Boyang Zhang, Jordan Wilson, Dipika Singh, Suzanne L. Topalian, Patrick M. Forde, Drew M. Pardoll and Hongkai Ji of Johns Hopkins. Jiajia Zhang of the David Geffen School of Medicine, University of California, Los Angeles; and Yimin Zhao, Rima Kulikauskas, Candice D. Church, Thomas H. Pulliam, Saumya Jani and Paul Nghiem of the Fred Hutchinson Cancer Center and the University of Washington in Seattle also contributed to the research.
The project was given backing by The Mark Foundation for Cancer Research, the Bloomberg~Kimmel Institute for Cancer Immunotherapy, The Mark Foundation Center for Advanced Genomics and Imaging, the Cancer Research Institute, the Lung Cancer Foundation of America, LUNGevity, the American Lung Association, Swim Across
America, the Commonwealth Foundation, Bristol Myers Squibb, the National Institutes of Health, Kelsey Dickson Team Science Courage Research Award: Advancing New Therapies for Merkel Cell Carcinoma, the MCC Patient Gift Fund and the National Foundation for Cancer Research.
Forde gets research backing from AstraZeneca, BioNtech, Bristol Myers Squibb, Novartis and Regeneron; it has been a consultant for AstraZeneca, Amgen, Bristol Myers Squibb, Iteos, Novartis, Star, Surface, Genentech, G1, Sanofi, Daiichi, Regeneron, Tavotek, VBL Therapeutics, Sankyo and Janssen; and serves on a data safety and monitoring board for Polaris.
Smith and Pardoll have filed for patent protection on the MANAFEST technology (serial No. 16/341,862). Pardoll serves as a consultant for Compugen, Shattuck Labs, WindMIL, Tempest, Immunai, Bristol Myers Squibb, Amgen, Janssen, Astellas, Rockspring Capital, Immunomic, and Dracen; owns founders’ equity in Clasp Therapeutics, WindMIL, Trex, Jounce, Enara, Tizona, Tieza, and RAPT; and receives research funding from Compugen, Bristol Myers Squibb, and Enara. Smith has received travel support and honoraria from Illumina Inc.; receives research funding from Bristol Myers Squibb, AbbVie, and AstraZeneca; and holds founder’s equity in Clasp Therapeutics. Topalian receives consulting fees from Bristol Myers Squibb, Dragonfly Therapeutics, PathAI, and Regeneron; receives research grants from Bristol Myers Squibb; has stock options in Dragonfly Therapeutics; and holds a patent related to treating MSI-high cancers with anti-PD-1. These relationships are managed by The Johns Hopkins University in line with its conflict-of-interest policies.
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