About

Robert Clarke, PhD, is the Executive Director of the Hormel Institute and a Professor affiliated with the Departments of Biochemistry, Molecular Biology & Biophysics at the University of Minnesota. His research involves collecting multiplatform data, including genomic, transcriptomic, proteomic, and metabolomic data from human breast cancer cell lines, animal models, and patients. He analyzes these data using machine learning and artificial intelligence algorithms to build predictive models of drug resistance, which are then validated mechanistically in experimental in vitro and in vivo models. Dr. Clarke's research is focused on mechanistic translational and transdisciplinary studies in breast cancer, with an emphasis on endocrine responsiveness and drug resistance. His laboratory applies a systems biology approach, utilizing state-of-the-art ‘omics’ technologies, bioinformatics, cellular, and molecular biological techniques to study cell cultures, animal models, and human clinical specimens. His work has involved extensive collaboration with computer scientists and engineers, enabling advanced computational analysis of complex biological data.

Research topics

• Computer Science
• Computational biology
• Genetics
• Biology
• Cell biology
• Internal medicine
• Pathology
• Bioinformatics
• Medicine
• Physics
• Nuclear physics
• Geology
• Particle physics
• Optics

Selected publications

• Effects of vitamin D on biochemical markers of osteoporosis: A meta-analysis of randomised trials

  British Journal Of Nutrition · 2026-04-27

  articleOpen accessSenior authorCorresponding

  Plasma levels of procollagen type 1 N-propeptide (P1NP) and C-terminal telopeptide of type 1 collagen (CTX) are bone turnover markers (BTMs) used to predict risk of fracture. We compared effects of vitamin D supplements on plasma levels of P1NP and CTX in the BEST-D trial (305 participants) after treatment with 2000 IU/day or 4000 IU/day vitamin D3 or placebo. The results of BEST-D were combined in a meta-analysis of all trials of vitamin D vs placebo on levels of P1NP (12 trials, 2654 participants) or CTX (16 trials, 2695 participants). In BEST-D, allocation to vitamin D3 resulted in a dose-dependent increase in 25-hydroxy-vitamin D (25[OH]D) levels, but had no effects on P1NP or CTX. Geometric mean (SE) levels at 12 months were similar for P1NP (41.7 [0.7] vs 42.9 [1.0] ng/mL; p=0.29: either dose vs placebo) and likewise for CTX (0.23 [0.01] vs 0.23 [0.01] ng/mL; p=0.98). In a meta-analysis of 18 trials, the average difference between the within-trial change in P1NP for allocated vitamin D and control was -3.3% (95% CI -5.6 to -1.0, p<0.005). For CTX, this difference was slightly greater (-3.8% [-6.8 to -0.8]; p=0.01). There was no significant heterogeneity between these trials after stratifying trials with or without calcium, higher or lower doses of vitamin D, or lower vs higher pre-treatment levels of 25(OH)D. Overall, vitamin D supplementation was associated with modest reductions in both P1NP and CTX and results provide support for further trials of vitamin D for prevention of fracture in older people.

  PublisherOA PDFDOI

• Pyruvate kinase M2 activation reprograms mitochondria in CD8 T cells, enhancing effector functions and efficacy of anti-PD1 therapy

  Cell Metabolism · 2025-04-08 · 29 citations

  article
  PublisherDOI

• Bayesian identification of differentially expressed isoforms using a novel joint model of RNA-seq data

  PLoS Computational Biology · 2025-01-31 · 1 citations

  articleOpen accessCorresponding

  We develop a Bayesian approach, BayesIso, to identify differentially expressed isoforms from RNA-seq data. The approach features a novel joint model of the sample variability and the deferential state of isoforms. Specifically, the within-sample variability and the between-sample variability of each isoform are modeled by a Poisson-Lognormal model and a Gamma-Gamma model, respectively. Using a Bayesian framework, the differential state of each isoform and the model parameters are jointly estimated by a Markov Chain Monte Carlo (MCMC) method. Extensive studies using simulation and real data demonstrate that BayesIso can effectively detect isoforms of less differentially expressed and differential transcripts for genes with multiple isoforms. We applied the approach to breast cancer RNA-seq data and uncovered a unique set of isoforms that form key pathways associated with breast cancer recurrence. First, PI3K/AKT/mTOR signaling and PTEN signaling pathways are identified as being involved in breast cancer development. Further integrated with protein-protein interaction data, pathways of Jak-STAT, mTOR, MAPK and Wnt signaling are revealed in association with breast cancer recurrence. Finally, several pathways are activated in the early recurrence of breast cancer. In tumors that occur early, members of pathways of cellular metabolism and cell cycle (such as CD36 and TOP2A) are upregulated, while immune response genes such as NFATC1 are downregulated.

  PublisherDOI

• DLL1-responsive PD-L1 ⁺ tumor-associated macrophages promote endocrine resistance in breast cancer

  Science Translational Medicine · 2025-11-05 · 1 citations

  article

  Estrogen receptor–positive (ER + ) luminal breast cancer comprises 75% of patients with breast cancer and presents notable treatment challenges because of endocrine resistance. The effectiveness of immunotherapy in endocrine therapy–resistant luminal breast cancer remains unclear. This limitation is due in part to a lack of immunocompetent preclinical models investigating the comprehensive involvement of immune cells in the tumor microenvironment (TME) in the context of endocrine resistance. In this study, we identified a subtype of immunosuppressive (M2-like) programmed death ligand 1–positive (PD-L1 + ) tumor-associated macrophages (TAMs) critically fostering resistance to tamoxifen (TMX) and fulvestrant (FV) through maintaining cancer stem cell (CSC) activity in new mouse models. These TAMs are recruited by Delta-like ligand 1 (DLL1), a Notch signaling ligand expressed in luminal tumor cells, through the CCR3/CCL7 axis. Combination therapy with anti-DLL1 and anti–PD-L1 antibodies with TMX reduced tumor growth and associated CSCs and reprogrammed the immunosuppressive TME in both preclinical mouse models and patient-derived explants, thus laying the foundation for a future combined immune-endocrine therapy in these patients.

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• CN150 Nurturing appropriate inpatient oncology care skill sets in oncology and non-oncology nursing staff

  Annals of Oncology · 2025-09-01

  article
  PublisherDOI

• BLIMP-1-dependent differentiation of T follicular helper cells into Foxp3+ T regulatory type 1 cells

  Frontiers in Immunology · 2025-02-24 · 3 citations

  articleOpen access

  T-regulatory-type-1 (TR1) cells are a subset of interleukin-10-producing but Foxp3 – Treg cells that arise in response to chronic antigenic stimulation. We have shown that systemic delivery of autoimmune disease-relevant peptide-major histocompatibility complex class II (pMHCII)-coated nanoparticles (pMHCII-NP) triggers the formation of large pools of disease-suppressing Foxp3 – TR1 cells from cognate T-follicular helper (TFH) cell precursors. Here we show that, upon treatment withdrawal, these Foxp3 – TR1 cells spontaneously differentiate into a novel immunoregulatory Foxp3 + TR1 subset that inherits epigenetic and transcriptional hallmarks of their precursors, including clonotypic T-cell receptors, and is distinct from other Foxp3 + Treg subsets. Whereas the transcription factor BLIMP-1 is dispensable for development of conventional Foxp3 + Treg cells, it is necessary for development of Foxp3 + TR1 cells. In a model of central nervous system autoimmunity, abrogation of BLIMP-1 or IL-10 expression in the Foxp3 – and/or Foxp3 + TR1 subsets inhibits their development or anti-encephalitogenic activity. Thus, the TFH-TR1 transdifferentiation pathway results in the generation of two distinct autoimmune disease-suppressing, IL-10-producing TR1 subsets that are distinguished by the expression of Foxp3 and Foxp3 target genes.

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• Molecular mechanisms underlying TXNIP’s anti-tumor role in breast cancer, including interaction with a novel, pro-tumor partner: CAST

  Cell Death and Disease · 2025-04-02 · 4 citations

  articleOpen access

  Thioredoxin-interacting protein (TXNIP) plays a pivotal role in glucose metabolism and redox signaling. Its emerging function as a potent suppressor of cell proliferation in various cancer contexts underscores its importance in cancer development. In a previous study, we found TXNIP activation by UNC0642, an inhibitor of histone methyltransferase G9A, significantly inhibited MDA-MB-231 breast cancer cell proliferation in vitro and tumor growth in vivo. Here, we demonstrated that TXNIP knockdown increased MDA-MB-231 tumor growth and metastasis in a mouse model. Reintroducing TXNIP into TXNIP-deficient HCC-1954 breast cancer cells decreased cell proliferation and migration while boosting the generation of reactive oxygen species, alongside reductions in mitochondrial respiration, mitochondrial membrane potential, and glycolysis. To elucidate the mechanisms underlying TXNIP's antitumor effects in breast cancer cells, we conducted co-immunoprecipitation and proteomic analyses that revealed calpastatin (CAST) as a novel TXNIP-interacting protein in MDA-MB-231 and HCC-1954 cells. Overexpression of CAST, an endogenous inhibitor of calpains, significantly increased xenograft tumor growth for both MDA-MB-231 and HCC-1954 cells, underscoring its novel role as a tumor promoter. In addition, we identified a positive correlation between the expression of TXNIP and interleukin-24 (IL-24), a molecule that induces cancer-specific apoptosis in several breast cancer cell lines. Our findings also show TXNIP's ability to decrease activation of STAT3, a key driver of oncogenesis. Finally, cells with high levels of TXNIP expression displayed increased susceptibility to IL-24 and WP1066, a specific STAT3 inhibitor, suggesting possible predictive value for TXNIP. Collectively, these findings unveil novel TXNIP-dependent pathways that may contribute to breast cancer pathogenesis, enriching our understanding of this molecule's intricate role in cancer and potentially paving the way for clinical translation.

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• Risk thresholds for soft versus hard cardiovascular disease outcome models for initiating statin therapy among Chinese adults: a cost-utility analysis

  BMC Medicine · 2025-07-01 · 1 citations

  articleOpen access

  BACKGROUND: Current guidelines for atherosclerotic cardiovascular disease (ASCVD) primary prevention mostly recommend risk scores that predict risk of non-fatal myocardial infarction, fatal ischemic heart disease (IHD), and fatal or non-fatal ischemic stroke (hard outcomes), ignoring the burden from other non-fatal IHD outcomes. We explored the optimal risk thresholds for statin initiation using non-laboratory-based soft and hard ASCVD outcome models and compared the cost-utility of such models in the Chinese population. METHODS: We constructed Markov cohort models to estimate the incidence of ASCVD events, costs, and quality-adjusted life years (QALYs) over a lifetime from a social perspective. The simulation cohort was constructed using data from the China Kadoorie Biobank (CKB). Input data included cost, utility, statin efficacy, and other parameters were derived from published literature. We used CKB-ASCVD models to predict 10-year risk and different risk thresholds to guide statin initiation. The incremental cost-effectiveness ratio (ICER) was estimated as cost per QALY gained. Sensitivity analyses were performed to explore the uncertainty in the models. RESULTS: The optimal risk threshold was 18% for the soft ASCVD model and 10% for the hard ASCVD model, with ICERs of $7013.48/QALY and $6540.71/QALY, respectively. The optimal thresholds were robust in stratified analyses by region and sex, and one-way sensitivity analyses over a wide range of input parameters. Probabilistic sensitivity analyses showed that these optimal thresholds had around 70% chance of being cost-effective. When analyzed by age group, above optimal thresholds were cost-effective in adults aged 30-59 years but not in those aged 60-75 years. The threshold strategies based on soft ASCVD model were mostly cost-saving compared with those based on hard models to treat the same proportions of the population. CONCLUSIONS: The risk threshold of 18% for soft ASCVD model and 10% for hard ASCVD model have acceptable cost-utility profiles in the Chinese population. The soft ASCVD model is more cost-effective than the hard model and should be used as a screening tool for ASCVD primary prevention.

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• DDN3.0: determining significant rewiring of biological network structure with differential dependency networks

  Bioinformatics · 2024-06-01 · 11 citations

  articleOpen access

  MOTIVATION: Complex diseases are often caused and characterized by misregulation of multiple biological pathways. Differential network analysis aims to detect significant rewiring of biological network structures under different conditions and has become an important tool for understanding the molecular etiology of disease progression and therapeutic response. With few exceptions, most existing differential network analysis tools perform differential tests on separately learned network structures that are computationally expensive and prone to collapse when grouped samples are limited or less consistent. RESULTS: We previously developed an accurate differential network analysis method-differential dependency networks (DDN), that enables joint learning of common and rewired network structures under different conditions. We now introduce the DDN3.0 tool that improves this framework with three new and highly efficient algorithms, namely, unbiased model estimation with a weighted error measure applicable to imbalance sample groups, multiple acceleration strategies to improve learning efficiency, and data-driven determination of proper hyperparameters. The comparative experimental results obtained from both realistic simulations and case studies show that DDN3.0 can help biologists more accurately identify, in a study-specific and often unknown conserved regulatory circuitry, a network of significantly rewired molecular players potentially responsible for phenotypic transitions. AVAILABILITY AND IMPLEMENTATION: The Python package of DDN3.0 is freely available at https://github.com/cbil-vt/DDN3. A user's guide and a vignette are provided at https://ddn-30.readthedocs.io/.

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• Abstract PO5-23-08: Adenylosuccinate lyase is essential for proliferation and mitochondrial function of endocrine therapy resistant breast cancer cells

  Cancer Research · 2024-05-02

  article

  Abstract Eighty percent of breast cancers express estrogen receptor alpha (ERα, ESR1) at the time of diagnosis. Endocrine therapy (ET) is the standard treatment that either block estrogen mediated ER activation (such as tamoxifen, fulvestrant) or suppress estrogen synthesis (such as exemestane, letrozole, or anastrozole). While ET is initially effective, emergence of ET-resistance is common and possess a major clinical challenge. Hence, there is an ongoing need to develop new treatments for ET-resistant-ERα positive breast cancer. In this study we investigated the role of adenylosuccinate lyase (ADSL), an enzyme of the de-novo purine biosynthesis pathway as a potential target of ET-resistant breast cancer. The protein level of ADSL in two independent ET-resistant cell line model LCC9 and T47D-4HT cells were significantly higher in comparison to its parental ET-sensitive cell lines, MCF7 and T47D cells, respectively. Transient knockdown of ADSL using two independent siRNA in both LCC9 and T47D-4HT cells results in a significant decrease of cell growth, colony, and spheroid formation. Notably, reduced ADSL levels in LCC9 cells prevented the cells from progressing from G1 to S phase of cell cycle with concurrent elevation of cyclin D1/D3, CDK2/4, and cyclin E. On the other hand, in T47D-4HT cells, ADSL reduction caused cells to accumulate in S-phase of cell cycle and showed lower levels of total cyclin D1 protein. Mechanistically, in LCC9 cells (but not in T47D-4HT cells), ADSL depletion induced DNA replication stress which activates (phosphorylate) ataxia-telangiectasia-mutated-and-Rad3-related kinase (ATR) and its major downstream effector checkpoint kinase 1 (Chk1) that in turn failed to de-phosphorylate the inhibitory-phospho-groups of cyclin-dependent kinase 2 (CDK2). In addition, ADSL depletion perturbed the mitochondrial function in both LCC9 and T47D-4HT cells. Oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) was lower in both the cells along with the mitochondrial membrane potential. Pertinently, lower concentration of AICAR (5-aminoimidazole-4-carboxamide-1-β-D-ribofuranoside), a product of ADSL enzyme function, partially rescued the cell growth and restored mitochondrial membrane potential in ADSL-depleted LCC9 cells. To further understand the global effects of ADSL depletion we performed RNA-sequencing of LCC9 and T47D-4HT cells after ADSL depletion and compared with respective control siRNA transfected cells followed by gene set enrichment analysis. Intriguingly, diverse effect was observed in LCC9 and T47D-4HT cells as very few genes were found to be commonly regulated between these two cell lines. Analysis of clinical data sets revealed high level of ADSL transcript was associated with adverse progression free survival and overall survival in breast cancer patients treated with endocrine therapies. Overall, our findings demonstrate that ADSL-mediated de novo purine synthesis is critical for cellular growth, proliferation, and mitochondrial function of endocrine therapy-resistant breast cancer cells. Therefore, targeting ADSL is a novel potential therapeutic approach for ERα positive ET- resistant breast cancer. Citation Format: Anil Yadav, Lu Jin, Robert Clarke, Surojeet Sengupta. Adenylosuccinate lyase is essential for proliferation and mitochondrial function of endocrine therapy resistant breast cancer cells [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-23-08.

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Recent grants

• NIH Grant U01CA184902

  NIH · $2.7M · 2021

• NIH Grant R55CA051782

  NIH · $100k · 1993

• Cancer Host Interactions Program

  NIH · $38.7M · 1997–2029

• NIH Grant R01CA058022

  NIH · $1.7M · 2002

• NIH Grant U54CA149147

  NIH · $5.4M · 2016

Frequent coauthors

• Jianhua Xuan

  279 shared

• Leena Hilakivi‐Clarke

  272 shared

• Ayesha N. Shajahan‐Haq

  Georgetown University Medical Center

  228 shared

• Alan Zwart

  MedStar Georgetown University Hospital

  207 shared

• Katherine L. Cook

  Atrium Health Wake Forest Baptist

  187 shared

• Rebecca B. Riggins

  183 shared

• Yue Wang

  Alibaba Group (China)

  181 shared

• Anni Wärri

  University of Turku

  172 shared

Education

• D.Sc., Biochemistry

  Queen's University Belfast

  1999

• Postdoctoral Fellowship, Medical Breast Cancer Section

  National Cancer Institute

  1988

• Ph.D., Biochemistry

  Queen's University Belfast

  1986

• M.Sc., Biochemistry

  Queen's University Belfast

  1982

• B.Sc., Biological Sciences

  University of Ulster at Jordanstown

  1979

Awards & honors

• Dr. James E. Rubin Medical Memorial Award
• Graduating Medical Student Research Award
• Veneziale-Steer Award
• Dr. Marvin and Hadassah Bacaner Research Awards
• Schmidt Steer Award