Drs. Robert Chapkin, Gus Wright, James Cai, and Stephen Safe received a new NIH grant to perform a single cell multi-omic analysis of the colon tumor microenvironment to probe the mechanistic underpinnings of NR4A1-dependent modulation of T-cell exhaustion.

Story by Jennifer Gauntt, VMBS Communications

February 1, 2023

Preliminary data indicate that the compounds developed in the laboratory of Dr. Stephen Safe both kill tumors and rejuvenate the immune system, which becomes exhausted as it responds to cancer.

A team of Texas A&M University researchers has received a $2.3-millon grant from the National Institutes of Health to further explore a unique immunotherapy that could be the first of its kind to treat colon cancer and could hold the key to treating other forms of cancer as well.

The collaborative, four-year project will determine how to best utilize a new class of drugs developed in the laboratory of Dr. Stephen Safe, a Distinguished Professor in the Texas A&M School of Veterinary Medicine & Biomedical Sciences’ (VMBS) Department of Veterinary Physiology & Pharmacology. The project will also explore the effects of the new compounds on human and murine cancer cells.

Led by Safe, the team also includes VMBS researchers Gus Wright and James Cai, as well as College of Agriculture and Life Sciences researcher Robert Chapkin and Houston Methodist Hospital oncologist Maen Abdelrahim.

Safe’s compounds target two receptors—NR4A1 and NR4A2—that are normally responsible for helping humans and animals lower stress levels but are overexpressed in colon cancer and other solid tumors.

“In the case of solid tumors, these two receptors are bad; they regulate the growth of a cell, how it metastasizes, how it invades, and how it survives,” Safe said. “When we screened these receptors, we found out that our compounds that we’ve been working on over the years bind with high affinity (binding strongly). Binding can sometimes be bad, making the tumor worse, or binding can be good, by being an antagonist. In this case, the compounds are antagonists—they just wipe out the tumor.”

Not only does their preliminary data indicate that their compounds act as an immunotherapy and kill the tumor, but the compounds also rejuvenate the immune system, which becomes exhausted as it responds to cancer.

“Immune cells play a very important role in cancer treatment,” Safe said. “But what happens with tumor development is that eventually, the immune cells just get exhausted and become unable to mount a ‘tumor-killing’ response.

“Dr. Jim Allison and Dr. Tasuku Honjo’s Nobel Prize-winning work found that at least one of the reasons the immune cells don’t work is that they’re not only exhausted, but they don’t function because tumors can suppress immune cells, especially T-cells (which target specific foreign particles, such as cancer cells) and thereby avoid immune cell-dependent tumor surveillance (the tumors are misidentified as immune cells by the immune system),” Safe said.

Immunotherapies work by separating the T-cells from the tumor, allowing the immune system to destroy the tumor the way it would any other infection in your body.

“One of the signals (the communication mechanism between T-cells and tumors), or checkpoints, is a gene called PD-L1, which is a checkpoint inhibitor; checkpoints bring the immune cell and the tumor cell together,” Safe said. “We found that in breast and colon cancer, NR4A1 regulates PD-L1 in the tumor, and treatment with our antagonist decreases PD-L1 expression and sensitizes the tumor to immune surveillance, killing it.”

By isolating the immune cells, Wright, an associate research scientist in the VMBS’ Department of Veterinary Pathobiology, was able to analyze the T-cells for markers of exhaustion and determined that with Safe’s compounds, those markers were “wiped out.”

“Previous studies showed that NR4A1 played a role in T-cell exhaustion, and our unique NR4A1 antagonists not only target NR4A1 in the tumor but also in T-cells; this dual targeting (the killing of the tumor and rejuvenating the immune system) is consistent with their high anticancer activity in mouse models.”

In the next phase of their research, the team will use the NIH grant to explore other areas of how the compounds work to, hopefully, prepare it for clinical trials.

While Safe works to “maximize” the compounds—that is, to select the most effective molecules for achieving their end goal—and to assess compound dosages, Abdelrahim, who is co-principal investigator on the project, will be examining the effects of the compound on human tissue; Wright will be working to further explore implications on the immune system; Cai, an associate professor in the VMBS’ Department of Integrative Biosciences, will be investigating how other individual cell types are affected by the compounds; and Chapkin, the Allen Endowed Chair in Nutrition & Chronic Disease Prevention and a University Distinguished Professor, will be further analyzing effects of NR4A1-targeting compounds on colonic epithelial stem cells in tumors.

Chapkin, Wright, and Cai will also perform a single cell multi-omic analysis of the colon tumor microenvironment to probe the mechanistic underpinnings of NR4A1-dependent modulation of T-cell exhaustion.

Ultimately, Safe believes their NR4A1-targeting drugs will also attenuate other types of cancer, including breast cancer, glioblastoma, and rhabdomyosarcoma, the most common soft tissue sarcoma in children.

“A lot of drugs that oncologists use now just target the specific genes/pathways in tumor cell—the drug kills it and the tumor usually regresses,” he said. “Those drugs are effective and inhibit some tumor growth, but they’re only targeting the tumor; they’re not targeting immune cells. I’m not sure how many drugs currently being used target both the tumor and the immune cells, but ours do, and this accounts for their potency in preclinical animal models.”

 

$1.19 million grant will leverage single-cell sequencing technology

The Texas A&M University System has received a $1.19 million grant from the National Institutes of Health, NIH, for a multidisciplinary collaboration to study the intricate connections between genomics, nutrition and health. Understanding these connections will help in the diagnosis and treatment of cancer and other diseases.

Yang Ni, Ph.D., an assistant professor in the College of Arts and Sciences Department of Statistics, will be the principal investigator for the effort. The project, which aims to create a toolset for interpreting and correlating novel genetic information, is titled “Bayesian differential causal network and clustering methods for single-cell data.”

Co-investigators for the project will be Robert Chapkin, Ph.D, Distinguished Professor and Allen Endowed Chair in the College of Agriculture and Life Sciences Department of Nutrition and Department of Biochemistry and Biophysics, and James Cai, Ph.D., associate professor in the School of Veterinary Medicine and Biomedical Sciences Department of Veterinary Integrative Biosciences.

The project aims to advance single-cell data science, the study of how genes and gene expression differ among individual cells in one organism. Because cancer arises from genetic abnormalities in individual cells, scientists believe that single-cell data science will reveal medically important information.

This NIH award is tied to a pending grant to the Cancer Prevention and Research Institute of Texas, CPRIT, to assess gene-environment-lifestyle interactions in cancer. Chapkin is spearheading that effort in collaboration with Ken Ramos, M.D., Ph.D., executive director at Texas A&M’s Institute of Biosciences and Technology.

Ramos and Chapkin have also submitted a $6 million grant titled “Gene-environment-lifestyle interactions in cancer” to the CPRIT to create a new regional center of excellence in cancer research.

Chapkin said the NIH grant’s goals and personnel will complement the establishment of a single-cell data science core at Texas A&M that will serve as a shared-resource facility.

Purpose and goals of single-cell technology

The emergence of new technologies such as single-cell RNA sequencing and spatial profiling has brought about many methods to study gene regulation and cell differentiation in the single cells of multicellular organisms.

Ni will lead the effort, along with students and postdocs, to develop and implement new statistical methods for discovering causal gene regulation and molecular cell types with single-cell RNA-sequencing data.

“We will also work closely with Drs. Chapkin and Cai to solve real-world biological and biomedical problems,” he said.

“New methods are required to compare molecular differences at the single-cell level, so we can translate the knowledge advanced by single-cell RNA sequencing and spatial mapping to improve disease diagnosis, treatment and prevention,” Ni said.

Single-cell technology and high-throughput sequencing have enabled entirely new realms of biology, such as “deep phenotyping” and personalized medicine.

“In these applications, big data provide insights into cures for various diseases, including cancer,” Chapkin said.

Single-cell data allows for the detection of cell-to-cell interactions, gene networks and the spatial organization of gene expression in tissue samples.

“There is a consensus that single-cell multiomics data, in which data sets of different groups are combined during analysis, and spatial information will be driving next-generation solutions in oncology,” Chapkin said.

He said this type of single-cell multiomic research, is highly innovative.

“It will enable the characterization of previously unapproachable clinical phenomena, such as ’deep landscapes’ of cancer heterogeneity that will reveal more about the dynamics of the tumor microenvironment,” Chapkin said.

Ni said a long-term goal of the project is to develop novel statistical methods for generating and evaluating new hypotheses about complex cellular processes across disparate sample groups, such as disease subtypes and treatment groups.

Specifically, Ni said the team will work to design and validate Bayesian network and clustering models. The novel statistical models and related analytical tools will help accurately describe changes in gene regulation and cell differentiation in response to experimental interventions at the single-cell level under different experimental conditions.

“Without such tools, mechanistically understanding gene regulatory activities and cell differentiation will likely remain difficult,” he said. “And the proposed methods would be widely applicable to a range of data generated under different experimental conditions, disease subtypes and treatment groups.”

Single-cell modeling and connecting

A Bayesian network model governs the probability and causal rules of a set of variables. An example would be a Bayesian network representing the probable relationships between diseases and their symptoms.

“In a Bayesian network model, first you identify main variables in the problem you want to solve,” explained Ni. “Then you specify or learn the structure of the network, which is the causal relationships between all the variables identified. After that, you determine the probability rules governing the relationships between those variables.”

Cai is also an affiliated faculty member in the College of Engineering Department of Electrical and Computer Engineering, and the Cai lab members develop analytical frameworks to study single-cell genomics data gathered from various types of cells.

In this project, he will play a bridging and coordinating role by connecting statisticians with molecular biologists to create an interface between human genetics, computational statistics and data science.

Sharing the results

Ni will lead the effort to disseminate the project’s results more broadly through open-source software, conference presentation, graduate and undergraduate education and mentoring, and hosting interdisciplinary workshops and symposia.

“We’re arranging for these workshops to provide travel stipends to help underrepresented students in STEM and encourage their participation,” he noted.

To help prepare next-generation researchers, statisticians and data scientists and improve public statistical literacy and engagement, Ni will also host data science competitions designed to engage undergraduate students.

“I also plan to develop a new graduate course on causal networks, and supervise the research of postdoctoral, graduate and undergraduate researchers,” he said.

Link to AgriLife Today:  https://agrilifetoday.tamu.edu/2022/11/30/1-19-million-grant-will-leverage-single-cell-sequencing-technology/