About

Robert Chapkin, Ph.D., holds the Allen Endowed Chair in Nutrition and Chronic Disease Prevention in the Texas A&M College of Agriculture and Life Sciences Department of Nutrition, with a dual appointment in the Department of Biochemistry and Biophysics. His research focuses on dietary and microbial modulation for the prevention of cancer and chronic inflammatory diseases. Chapkin's work has been continuously funded by the National Institutes of Health for over 35 years, reflecting his sustained contributions to nutrition science. He has authored or co-authored more than 300 scientific research publications, demonstrating a prolific and impactful career in advancing understanding of nutrition and health. Chapkin has received numerous prestigious awards, including the Mary Swartz Rose Senior Investigator Award from the American Society for Nutrition (ASN), recognizing his outstanding research on the safety and efficacy of bioactive compounds for human health. He was also named a Fellow of the American Association for the Advancement of Science in 2018 for his scientifically and socially distinguished efforts to advance science and its applications. Additionally, he is a National Cancer Institute Outstanding Investigator Awardee and has received the National Nutrition Program Faculty Scholar Award from the PEW Foundation, as well as multiple honors from ASN such as the Osborne and Mendel Award and the Bio-Serv Award in Experimental Animal Nutrition. Chapkin's induction as a Fellow of the American Society for Nutrition in 2024 honors his significant lifetime achievements and scholarly contributions to the field of nutrition throughout his career at Texas A&M.

Research topics

• Biology
• Biochemistry
• Cell biology
• Pharmacology
• Chemistry
• Artificial Intelligence
• Medicine
• Bioinformatics
• Computational biology
• Computer Science
• Genetics
• Psychiatry
• Internal medicine
• Molecular biology
• Cancer research
• Endocrinology

Selected publications

• Brewed Coffee and Its Components Act Through Orphan Nuclear Receptor 4A1 (NR4A1)

  Nutrients · 2026-03-10

  articleOpen access

  Background/Objective: Coffee is the most highly consumed beverage worldwide, and coffee drinkers exhibit decreased mortality and protection from aging-related diseases. This study investigates the role of orphan nuclear receptor 4A1 (NR4A1) in mediating the effects of brewed coffee and the major polyphenolic and polyhydroxy compounds in brewed coffee and also in determining their binding to NR4A1. Methods: The interactions of brewed coffee and several of the major individual compounds in brewed coffee with the ligand-binding domain of NR4A1 were determined using a fluorescent binding assay. For specific compounds, binding was also carried out by surface plasmon resonance, and molecular docking studies were also performed. NR4A1-responsive Rh30 cancer cells were used as models to determine NR4A1-dependent transactivation, cell growth inhibition and inhibition of specific gene products, and in some studies, knockdown of NR4A1 by RNA interference was also determined. Inhibition of lipopolysaccharide-induced IkBα by key polyphenolics was also investigated in RAW264.7 macrophages. Results: Brewed coffee and several polyphenolics, including caffeic acid, ferulic acid, chlorogenic acid, p-coumaric acid, several cinnamic acid derivatives, kahweol, and cafestrol, bound NR4A1 in binding assays, and most Kd values were <10 µM. Brewed coffee and the major polyphenolics inhibited growth of NR4A1-responsive Rh30 cells, and this was attenuated in NR4A1-deficient Rh30 cells. These same compounds also exhibited NR4A1-dependent effects on transactivation and gene product responses in Rh30 and RAW264.7 macrophages and exhibited inverse NR4A1 agonist activity. In contrast, the NR4A1-dependent activity of caffeine and quinic acid was highly variable, suggesting that they are selective NR4A1 ligands. Conclusions: The results of this study demonstrate that brewed coffee and its major polyphenolics and polyhydroxy constituents are NR4A1 ligands and that NR4A1 may play an important role in the health-protective effects of coffee. These results, coupled with recent studies, indicate that NR4A1 and its ligands may play an important role in diet and health.

  PublisherOA PDFDOI

• A Commentary on Dual Orphan Nuclear Receptor 4A1 (NR4A1) and NR4A2 Ligands

  Journal of Cellular Immunology · 2026-04-27

  articleOpen accessSenior author

  1,1-Bis(3’-indolyl)-1-(3,5-disubstitutedphenyl)methane (DIM-3,5) compounds in the presence or absence of a 4-hydroxylphenyl group bind both orphan nuclear receptor 4A1 (NR4A1) and NR4A2. In cancer cells, these compounds bind and inactivate pro-oncogenic NR4A1 and NR4A2 and downstream pathways acting as inverse agonists that inhibit cancer cell growth, survival, migration and invasion, and induce ferroptosis. Similar results are observed in endometriotic cells where the DIM-3,5 dual NR4A1/2 ligands inhibit NR4A1/NR4A2-mediated pro-endometriotic genes and pathways. The potency of these DIM-3,5 dual NR4A1/NR4A2 ligands is also observed in tumor infiltrating lymphocytes where both receptors are expressed and regulate comparable functions.

  PublisherOA PDFDOI

• QuantumXCT: Learning Interaction-Induced State Transformation in Cell-Cell Communication via Quantum Entanglement and Generative Modeling.

  PubMed · 2026-04-09

  article

  discovery of communication programs in complex biological systems and highlights the potential of quantum machine learning in the context of single-cell biology.

  Publisher

• QuantumXCT: Learning Interaction-Induced State Transformation in Cell-Cell Communication via Quantum Entanglement and Generative Modeling

  PubMed Central · 2026-04-02

  preprintOpen access

  Inferring cell-cell communication (CCC) from single-cell transcriptomics remains fundamentally limited by reliance on curated ligand-receptor databases, which primarily capture co-expression rather than the system-level effects of signaling on cellular states. Here, we introduce QuantumXCT, a hybrid quantum-classical generative framework that reframes CCC as a problem of learning interaction-induced state transformations between cellular state distributions. By encoding transcriptomic profiles into a high-dimensional Hilbert space, QuantumXCT trains parameterized quantum circuits to learn a unitary transformation that maps a baseline non-interacting cellular state to an interacting state. This approach enables the discovery of communication-driven changes in cellular state distributions without requiring prior biological assumptions. We validate QuantumXCT using both synthetic data with known ground-truth interactions and single-cell RNA-seq data from ovarian cancer-fibroblast co-culture model. The QuantumXCT model accurately recovered complex regulatory dependencies, including feedback structures, and identified dominant communication hubs such as the PDGFB-PDGFRB-STAT3 axis. Importantly, the learned quantum circuit is interpretable: its entangling topology was translated into biologically meaningful interaction networks, while post hoc contribution analysis quantified the relative influence of individual interactions on the observed state transitions. Notably, by shifting CCC inference from static interaction lookup to learning data-driven state transformations, QuantumXCT provides a generative framework for modeling intercellular communication. This work establishes a new paradigm for de novo discovery of communication programs in complex biological systems and highlights the potential of quantum machine learning in the context of single-cell biology.

  PublisherDOI

• QuantumXCT: Learning Interaction-Induced State Transformation in Cell-Cell Communication via Quantum Entanglement and Generative Modeling

  arXiv (Cornell University) · 2026-04-02

  articleOpen access

  Inferring cell-cell communication (CCC) from single-cell transcriptomics remains fundamentally limited by reliance on curated ligand-receptor databases, which primarily capture co-expression rather than the system-level effects of signaling on cellular states. Here, we introduce QuantumXCT, a hybrid quantum-classical generative framework that reframes CCC as a problem of learning interaction-induced state transformations between cellular state distributions. By encoding transcriptomic profiles into a high-dimensional Hilbert space, QuantumXCT trains parameterized quantum circuits to learn a unitary transformation that maps a baseline non-interacting cellular state to an interacting state. This approach enables the discovery of communication-driven changes in cellular state distributions without requiring prior biological assumptions. We validate QuantumXCT using both synthetic data with known ground-truth interactions and single-cell RNA-seq data from ovarian cancer-fibroblast co-culture model. The QuantumXCT model accurately recovered complex regulatory dependencies, including feedback structures, and identified dominant communication hubs such as the PDGFB-PDGFRB-STAT3 axis. Importantly, the learned quantum circuit is interpretable: its entangling topology was translated into biologically meaningful interaction networks, while post hoc contribution analysis quantified the relative influence of individual interactions on the observed state transitions. Notably, by shifting CCC inference from static interaction lookup to learning data-driven state transformations, QuantumXCT provides a generative framework for modeling intercellular communication. This work establishes a new paradigm for de novo discovery of communication programs in complex biological systems and highlights the potential of quantum machine learning in the context of single-cell biology.

  PublisherOA PDF

• Quantum Generative Modeling of Single-Cell transcriptomes: Capturing Gene-Gene and Cell-Cell Interactions.

  PubMed · 2025-12-19

  article

  Single-cell RNA sequencing (scRNA-seq) data simulation is limited by classical methods that rely on linear correlations, failing to capture the intrinsic, nonlinear dependencies. No existing simulator jointly models gene-gene and cell-cell interactions. We introduce qSimCells, a novel quantum computing-based simulator that employs entanglement to model intra- and inter-cellular interactions, generating realistic single-cell transcriptomes with cellular heterogeneity. The core innovation is a quantum kernel that uses a parameterized quantum circuit with CNOT gates to encode complex, nonlinear gene regulatory network (GRN) as well as cell-cell communication topologies with explicit causal directionality. The resulting synthetic data exhibits non-classical dependencies: standard correlation-based analyses (Pearson and Spearman) fail to recover the programmed causal pathways and instead report spurious associations driven by high baseline gene-expression probabilities. Furthermore, applying cell-cell communication detection to the simulated data validates the true mechanistic links, revealing a robust, up to 75-fold relative increase in inferred communication probability only when quantum entanglement is active. These results demonstrate that the quantum kernel is essential for producing high-fidelity ground-truth datasets and highlight the need for advanced inference techniques to capture the complex, non-classical dependencies inherent in gene regulation.

  Publisher

• Pesco-Vegetarian Food Components Promote Colonocyte Ferroptosis in Preclinical Mouse Models and a Randomized Crossover Trial in Healthy Human Adults

  Journal of Nutrition · 2025-12-27

  articleOpen accessSenior authorCorresponding

  BACKGROUND: Diet plays a critical role in colorectal cancer (CRC) prevention. Pesco-vegetarians, who consume both high fiber and fish containing n-3 (ω-3) polyunsaturated fatty acid (PUFA), have the lowest CRC risk. Ferroptosis is a form of regulated cell death characterized by the accumulation of lipid hydroperoxides that has emerged as a target for anticancer therapies. OBJECTIVES: This study aimed to assess the broad utility of diet modulation as a promising avenue to modulate ferroptosis in the colon. METHODS: 1) Immortalized young adult mouse colonic epithelial cells (YAMC) were treated with control linoleic acid or docosahexaenoic acid (DHA) ± butyrate (But), followed by cell viability and lipid peroxidation measurements, 2) mice were fed diets containing fish oil and highly fermentable pectin (FP) compared with control corn oil and poorly fermentable cellulose (CC). Colons were isolated and used for bulk and single-cell ribonucleic acid-sequencing (RNA)-seq analysis, 3) a crossover pilot study was conducted by supplementing 30 healthy adults with soluble corn fiber (33 g/d) + fish oil (7.7 g/d n-3 PUFA) (SCF+FO) or maltodextrin + corn oil (MD+CO) for 30 d followed by a 60 d wash period and then 30 d of MD+CO or SCF+FO. Exfoliated colonocyte mRNA was isolated from stool and RNA-seq was performed for transcriptomic analysis. RESULTS: In vitro treatment of DHA and But reduced YAMC cell viability (P < 0.05), increased lipid peroxidation, a key biomarker of ferroptosis, compared with the counterpart group. In vivo FP-fed mice promoted lipid peroxidation in colonocytes relative to the control CC-fed mice (P < 0.05), and the induction of ferroptosis transcriptional networks exclusively in colonic epithelial cells. Furthermore, human subjects supplemented with SCF+FO exhibited an upregulation in intestinal ferroptosis-related gene expression, as compared with similar doses of MD+CO. CONCLUSIONS: Our findings demonstrate that dietary fish oil and fermentable fiber combination induces ferroptosis exclusively in colonocytes. The human pilot study was registered at clinicaltrials.gov as NCT04211766.

  PublisherDOI

• Expression of Prooncogenic Nuclear Receptor 4A (NR4A)-Regulated Genes β1-Integrin and G9a Inhibited by Dual NR4A1/2 Ligands

  International Journal of Molecular Sciences · 2025-04-21 · 1 citations

  articleOpen access

  Bis-indole-derived compounds including 1,1-bis(3'-indolyl)-1-(3,5-disubstitutedphenyl)methane (DIM-3,5) analogs bind both orphan nuclear receptors 4A1 (NR4A1) and NR4A2, and DIM-3,5 compounds act as dual receptor inverse agonists and inhibit both NR4A1- and NR4A2-regulated responses. Chromatin immunoprecipitation assays show that β1-integrin and the methyltransferase gene G9a are regulated by both NR4A1 and NR4A2 acting as cofactors for Sp1- and Sp4-dependent gene expression. DIM-3,5 treatment results in the loss of one or more of these nuclear factors from the β1-integrin and G9a promoters. Single-cell and RNAseq analyses show that both receptors regulate common (<10%) and unique genes in SW480 colon cancer cells; however, functional enrichment analysis of the differentially expressed genes converges to several common pathways and gene ontology terms.

  PublisherOA PDFDOI

• Targeting polyunsaturated fatty acids desaturase FADS1 inhibits renal cancer growth via ATF3-mediated ER stress response

  Biomedicine & Pharmacotherapy · 2025-03-23 · 5 citations

  articleOpen access

  Fatty Acid Desaturase 1 (FADS1) is a rate-limiting enzyme controlling the bioproduction of long-chain polyunsaturated fatty acids (PUFAs). Increasing studies suggest that FADS1 is a potential cancer target. Our previous research has demonstrated the significant role of FADS1 in cancer biology and patient survival, especially in kidney cancers. We aim to explore the underlying mechanism in this study. We found that pharmacological inhibition or knockdown of the expression of FADS1 significantly reduced the intracellular conversion of long-chain PUFAs, effectively inhibits renal cancer cell proliferation, and induces cell cycle arrest. The stable knockdown of FADS1 also significantly inhibits tumor formation in vivo . Mechanistically, we showed that while FADS1 inhibition induces endoplasmic reticulum (ER) stress, FADS1 expression is augmented by ER-stress inducer, suggesting a necessary role of PUFA production in response to ER stress. FADS1-inhibition sensitized cellular response to ER stress inducers, leading to cell apoptosis. Also, FADS1 inhibition-induced ER stress leads to activation of the PERK/eIF2α/ATF4/ATF3 pathway. Inhibiting PERK or knockdown of ATF3 rescued FADS1 inhibition-induced ER stress and cell growth suppression, while ATF3-overexpression aggravates the FADS1 inhibition-induced cell growth suppression and leads to cell death. Metabolomic analysis revealed that FADS1 inhibition results in decreased level of UPD-N-Acetylglucosamine, a critical mediator of the unfolded protein response, as well as impaired biosynthesis of nucleotides, possibly accounting for the cell cycle arrest. Our findings suggest that PUFA desaturation is crucial for rescuing cancer cells from persistent ER stress, supporting FADS1 as a new therapeutic target. • FADS1 inhibition suppresses renal cancer cell proliferation and tumor growth. • FADS1 inhibition induces ER stress via the PERK/eIF2α/ATF4/ATF3 pathway. • Targeting FADS1 sensitizes cancer cells to ER stress inducers, leading to apoptosis. • ATF3 is a key mediator for the FADS1 inhibition-induced cancer cell growth suppression. • FADS1 inhibition disrupts metabolic pathways of nucleotide and protein metabolism.

  PublisherDOI

• Exploring cell-to-cell variability and functional insights through differentially variable gene analysis

  npj Systems Biology and Applications · 2025-03-20 · 6 citations

  articleOpen access

  Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular variability by capturing gene expression profiles of individual cells. The importance of cell-to-cell variability in determining and shaping cell function has been widely appreciated. Nevertheless, differential expression (DE) analysis remains a cornerstone method in analytical practice. Current computational analyses overlook the rich information encoded by variability within the single-cell gene expression data by focusing exclusively on mean expression. To offer a deeper understanding of cellular systems, there is a need for approaches to assess data variability rather than just the mean. Here we present spline-DV, a statistical framework for differential variability (DV) analysis using scRNA-seq data. The spline-DV method identifies genes exhibiting significantly increased or decreased expression variability among cells derived from two experimental conditions. Case studies show that DV genes identified using spline-DV are representative and functionally relevant to tested cellular conditions, including obesity, fibrosis, and cancer.

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01CA129444

  NIH · $2.1M · 2017

• Molecular basis for dietary chemoprevention

  NIH · $6.3M · 2016–2023

• Diet and the colonic exfoliome: a novel, non-invasive approach to testing interventions in humans

  NIH · $446k · 2020–2023

• NIH Grant R01DK053055

  NIH · $823k · 2004

• Dietary Flavonoids-Microbiota-Ah Receptor Interactions in the Gut

  NIH · $1.9M · 2018–2023

Frequent coauthors

• Laurie A. Davidson

  208 shared

• Joanne R. Lupton

  162 shared

• David N. McMurray

  124 shared

• Yang‐Yi Fan

  113 shared

• Evelyn Callaway

  Texas A&M University

  111 shared

• Ivan Ivanov

  Mitchell Institute

  83 shared

• Stephen Safe

  Texas A&M University

  74 shared

• Nancy D. Turner

  Texas A&M University

  69 shared

Labs

• Chapkin LabPI

Education

• Post-doc/Cell Biology

  University of California, Davis

  1988

• PhD/Nutrition & Physiological Chemistry

  University of California, Davis

  1986

• MS/Nutrition

  University of Guelph

  1983

• BS/Nutrition & Biochemistry

  University of Guelph

  1981

Awards & honors

• American Society for Nutrition 2024 Fellow