DHODH inhibition enhances the efficacy of immune checkpoint blockade by increasing cancer cell antigen presentation

Epithelial-mesenchymal transition promotes metabolic reprogramming to suppress ferroptosis

Epithelial-mesenchymal transition (EMT) is a cellular de-differentiation process that provides cells with the increased plasticity and stem cell-like traits required during embryonic development, tissue remodeling, wound healing and metastasis. Morphologically, EMT confers tumor cells with fibroblast-like properties that lead to the rearrangement of cytoskeleton (loss of stiffness) and decrease of membrane rigidity by incorporating high level of poly-unsaturated fatty acids (PUFA) in their phospholipid membrane. Although large amounts of PUFA in membrane reduces rigidity and offers capabilities for tumor cells with the unbridled ability to stretch, bend and twist in metastasis, these PUFA are highly susceptible to lipid peroxidation, which leads to the breakdown of membrane integrity and, ultimately results in ferroptosis. To escape the ferroptotic risk, EMT also triggers the rewiring of metabolic program, particularly in lipid metabolism, to enforce the epigenetic regulation of EMT and mitigate the potential damages from ferroptosis. Thus, the interplay among EMT, lipid metabolism, and ferroptosis highlights a new layer of intricated regulation in cancer biology and metastasis. Here we summarize the latest findings and discuss these mutual interactions. Finally, we provide perspectives of how these interplays contribute to cellular plasticity and ferroptosis resistance in metastatic tumor cells that can be explored for innovative therapeutic interventions.

The perspective of targeting cancer cell metabolism: combination therapy approaches

Cancer cells are considered the most adaptable for their metabolic status, which supports growth, survival, rapid proliferation, invasiveness, and metastasis in a nutrient-deficient microenvironment. Since the discovery of altered glucose metabolism (aerobic glycolysis), which is generally known as a part of metabolic reprogramming and an innate trait of cancer cells, in 1930 via Dr. Otto Warburg, numerous studies have endeavored to recognize various aspects of cancer cell metabolism and find new methods for efficiently eradicating described cells by targeting their energy metabolism. In this way, the outcomes have mainly been promising. Accordingly, outlining the related results will indeed assist us in making a definitive path for developing targeted therapy strategies based on cancer cell-altered metabolism. The present study reviews the key features of cancer cell metabolism and treatment strategies based on them. It emphasizes the importance of targeting cancer cell dysregulated metabolic pathways that influence the cell energy supply and manage cancer cell growth and survival. This trial also introduces a multimodal therapeutic strategy hypothesis, a potential next-generation combination therapy approach, and suggests interdisciplinary research to recognize the complexities of cancer metabolism and exploit them for designing more efficacious cancer therapeutic strategies.

Translational Pharmacokinetic-Pharmacodynamic Modeling of a Novel Oral Dihydroorotate Dehydrogenase (DHODH) Inhibitor, HOSU-53 (JBZ-001)

Background: HOSU-53 (JBZ-001), an orally bioavailable new chemical entity, represents a highly potent dihydroorotate dehydrogenase (DHODH) inhibitor in late preclinical development for application in cancer therapy. Methods: Multiple Good Laboratory Practice (GLP) and non-GLP preclinical studies were conducted in mice, rats, and dogs. Plasma samples of HOSU-53 and dihydroorotate (DHO), the substrate of DHODH, were collected for pharmacokinetic (PK) and pharmacodynamic (PD) assessment and modeling. Two modeling approaches were utilized to understand the PK/PD properties of HOSU-53 and to recommend a first-in-human (FIH) dose. Results: A population PK/PD model was developed using a stochastic approximation of the expectation-maximization method and evaluated using graphical and numerical methods. The PK of HOSU-53 was well described by a two-compartment model with a first-order absorption and linear elimination, and the PD was described by a turnover model. No covariates were considered significant on PK/PD parameters. This model was subsequently used to predict DHO exposures in humans across a range of doses. Additionally, predicted human hepatocellular HOSU-53 concentrations were obtained from a physiologically based PK model constructed in PK-Sim. Conclusions: A first-in-human starting dose of 5 mg once daily was established from the model approaches and will be utilized in the upcoming FIH clinical study.

Targeting both the enzymatic and non-enzymatic functions of DHODH as a therapeutic vulnerability in c-Myc-driven cancer

c-Myc (Myc)-driven cancers exhibit aggressive phenotypes and therapeutic resistance. Here, integrating CRISPR-Cas9 screening, we identify dihydroorotate dehydrogenase (DHODH) as a promising target in Myc-driven cancer. Mechanistically, DHODH interacts with Myc to stabilize it independently of its enzymatic activity, thereby antagonizing SKP2-mediated polyubiquitination and proteasomal degradation. EN4, a Myc transcriptional activity inhibitor, disrupts DHODH-Myc interaction, promoting Myc degradation via SKP2. Additionally, Myc transcriptionally activates DHODH, enhancing pyrimidine biosynthesis and ferroptosis defense, processes dependent on DHODH enzymatic activity. Clinically, DHODH positively correlates with Myc, activating pyrimidine metabolism and ferroptosis defense in Myc-driven cancers. Hyperactivation of the DHODH-Myc axis is linked to colorectal cancer progression and poor prognosis. Therapeutically, combining EN4 with a DHODH enzymatic inhibitor demonstrates potent antitumor efficacy in Myc-driven colorectal cancer. Overall, our findings elucidate the metabolic and non-metabolic roles of DHODH in Myc-driven cancer, underscoring its dual potential as a therapeutic target addressing both enzymatic and non-enzymatic functions.

Multi-omics and single-cell analysis reveals machine learning-based pyrimidine metabolism-related signature in the prognosis of patients with lung adenocarcinoma

Background: Pyrimidine metabolism is a hallmark of tumor metabolic reprogramming, while its significance in the prognostic and therapeutic implications of patients with lung adenocarcinoma (LUAD) still remains unclear. Methods: In this study, an integrated framework of various machine learning and deep learning algorithms was used to develop the pyrimidine metabolism-related signature (PMRS). Its efficacy in genomic stability, chemotherapy and immunotherapy resistance was evaluated through comprehensive multi-omics analysis. The single-cell landscape of patients between PMRS subgroups was also elucidated. Subsequently, the biological functions of LYPD3, the most important coefficient factor in the PMRS model, were experimentally validated in LUAD cell lines. Results: The PMRS model with "random survival forest" algorithm exhibited the best performance and was utilized for further analysis. It displayed excellent accuracy and stability in various model evaluation assays. Compared to the PMRS-high subgroup, patients with lower PMRS scores had better survival outcomes, more stable genomic characteristics and higher sensitivity to immunotherapy. Single-cell analysis indicated that as PMRS increased, epithelial cells gradually exhibited malignant phenotypes with enhanced pyrimidine metabolism, while PMRS-high patients showed an inhibitory status of tumor immune microenvironment. Further experiments indicated that LYPD3 promoted the malignant progression in LUAD cell lines. Conclusion: Our study constructed the PMRS model, highlighting its potential value in the treatment and prognosis of LUAD patients and providing new insights into the individualized precision treatment for LUAD patients.

Fenamates: Forgotten treasure for cancer treatment and prevention: Mechanisms of action, structural modification, and bright future

Fenamates as classical nonsteroidal anti-inflammatory agents are widely used for relieving pain. Preclinical studies and epidemiological data highlight their chemo-preventive and chemotherapeutic potential for cancer. However, comprehensive reviews of fenamates in cancer are limited. To accelerate the repurposing of fenamates, this review summarizes the results of fenamates alone or in combination with existing chemotherapeutic agents. This paper also explores targets of fenamates in cancer therapy, including COX, AKR family, AR, gap junction, FTO, TEAD, DHODH, TAS2R14, ion channels, and DNA. Besides, this paper discusses other mechanisms, such as regulating Wnt/β-catenin, TGF-β, p38 MAPK, and NF-κB pathway, and the regulation of the expressions of Sp, EGR-1, NAG-1, ATF-3, ErbB2, AR, as well as the modulation of the tumor immune microenvironment. Furthermore, this paper outlined the structural modifications of fenamates, highlighting their potential as promising leads for anticancer drugs.

Gemcitabine Modulates HLA-I Regulation to Improve Tumor Antigen Presentation by Pancreatic Cancer Cells

Pancreatic cancer is a lethal disease, harboring a five-year overall survival rate of only 13%. Current treatment approaches thus require modulation, with attention shifting towards liberating the stalled efficacy of immunotherapies. Select chemotherapy drugs which possess inherent immune-modifying behaviors could revitalize immune activity against pancreatic tumors and potentiate immunotherapeutic success. In this study, we characterized the influence of gemcitabine, a chemotherapy drug approved for the treatment of pancreatic cancer, on tumor antigen presentation by human leukocyte antigen class I (HLA-I). Gemcitabine increased pancreatic cancer cells' HLA-I mRNA transcripts, total protein, surface expression, and surface stability. Temperature-dependent assay results indicated that the increased HLA-I stability may be due to reduced binding of low affinity peptides. Mass spectrometry analysis confirmed changes in the HLA-I-presented peptide pool post-treatment, and computational predictions suggested improved affinity and immunogenicity of peptides displayed solely by gemcitabine-treated cells. Most of the gemcitabine-exclusive peptides were derived from unique source proteins, with a notable overrepresentation of translation-related proteins. Gemcitabine also increased expression of select immunoproteasome subunits, providing a plausible mechanism for its modulation of the HLA-I-bound peptidome. Our work supports continued investigation of immunotherapies, including peptide-based vaccines, to be used with gemcitabine as new combination treatment modalities for pancreatic cancer.