Abstract Metastasis accounts for roughly 90% of cancer-related deaths. A new type of Anti-metastatic agents, known as migrastatics, offer a new therapeutic strategy that targets solely cancer cell migration and invasion while sparing proliferation. The FDA’s introduction of metastasis-free survival as a clinical endpoint in 2018 has created a regulatory framework that supports the development of such agents. By limiting cellular motility rather than inducing cytotoxic stress, migrastatics are expected to impose minimal selective pressure for the emergence of aggressive, drug-resistant subclones. Lysophosphatidic Acid Receptor 1 (LPA1), activated by the endogenous lipid LPA, is a key mediator of metastatic progression in triple-negative breast cancer (TNBC) and several other malignancies. We observed that LPA1 expression in MDA-MB-231 TNBC cells is at least 5-fold higher than in the non-malignant breast epithelial line MCF10A, supporting its role as a viable migrastatic target. Here, we report our medicinal chemistry efforts toward the discovery of novel LPA1 antagonists as potential migrastatic agents for TNBC. The lead compounds identified demonstrate high selectivity and potency, with IC50 values ranging from 16.0 to 107 nM in a cAMP assay and no detectable activity at LPA2 or LPA3. These compounds suppress TNBC cell survival, migration, and invasion without inducing apoptosis or cytotoxicity. These findings are consistent with the mechanistic expectations of migrastatic therapy and support further preclinical development of LPA1-targeted agents for metastatic TNBC. In vivo efficacy and toxicity studies are currently underway. Citation Format: Wenjie Liu, Kelsie L. Thu, Jinqiang Hou. LPA1 antagonists as potential migrastatics for triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7491.

Targeting RNA G-quadruplexes (rG4s) with photosensitizers offers a mechanistically distinct approach for cancer therapy by integrating molecular targeting with photodynamic activity. Here, we report TO-ISe, a selenium-containing rG4-targeting photosensitizer designed for combined photodynamic therapy and immunomodulation. TO-ISe binds rG4s with high affinity (Kd = 860 nM) and exhibits pronounced Type I photodynamic activity. rG4 complex formation enhances radical generation, resulting in selective phototoxicity toward cancer cells (IC50 = 0.16-0.27 μM) with substantially lower toxicity in nonmalignant cells (IC50 = 5.9-7.8 μM). Under dark conditions, TO-ISe suppresses rG4-regulated oncogenes (c-MYC, NRAS and hTERT), leading to mitochondrial dysfunction, ferroptosis, and apoptosis. Upon white-light irradiation (22.1 mW·cm-2), TO-ISe further potentiates antiproliferative efficacy and induces immunogenic cell death via activation of the cGAS-STING pathway. In an orthotopic 4T1 tumor model, TO-ISe (0.5 mg kg-1) with irradiation achieved up to 72.8% tumor growth inhibition. These results highlight TO-ISe as a dual-function rG4-targeting photodynamic immunotherapeutic agent.

We previously described the discovery of carbamate-derived small molecules as potent and selective lysophosphatidic acid receptor 1 (LPA1) antagonists. To further expand the library of LPA1 antagonists and potentially enhance their stability and potency, a urea moiety was introduced in replacement of the carbamate group and a series of LPA1 antagonists based on a urea scaffold were synthesized and evaluated. Within this series, several compounds exhibited potent LPA1 antagonism. Notably, compound 5f emerged as one of the most potent, with an IC50 of 215.2 nM in the cAMP assay and 7.9 nM in the calcium mobilization assay. Compound 5f demonstrated the ability to block LPA-induced cell migration and invasion in the triple-negative breast cancer cell line MDA-MB-231. These findings support further in vivo evaluation of compound 5f as a potential therapeutic agent targeting LPA1. The development of these urea-derived LPA1 antagonists in this study has expanded the repertoire of LPA1 antagonists and holds potential for the development of a novel therapy for metastatic triple-negative breast cancer.

Positron emission tomography (PET) is a common imaging technique and can provide accurate information about the size, shape, and location of tumors. Recent evidence has shown that G-quadruplex structures (G4s) are identified in human oncogenes, and these special structures are recognized as diagnostic cancer markers and drug targets for anticancer therapies. Although a number of techniques for in vivo imaging of G4s have been developed, achieving sufficient sensitivity and selectivity in vivo remains challenging. Herein, we have engineered and developed a radiolabeled peptide probe [18F]AlF-NOTA-RHAU18 targeting mitochondrial DNA G4s for in vivo PET imaging. The results of the study indicate that this probe is able to visualize and detect solid tumors in living homozygous mice. In addition, the distribution of the probe in cancer cells was investigated using FITC-RHAU18. This work may offer new insights into the development of cancer diagnostic tools by targeting in vivo G4s.

The adoption of AI techniques within the domain of drug design provides an opportunity for systematic and efficient exploration of the vast chemical search space. In recent years, advancements in this domain have been driven by AI frameworks, including deep reinforcement learning (DRL). However, the scalability and performance of existing DRL methodologies are constrained by prolonged training periods and inefficient sample data utilization. Furthermore, generalization capabilities of these models have not been fully investigated. To overcome these limitations, we take a multi-objective optimization perspective and introduce SMORE-DRL, a fragment and transformerbased multi-objective DRL architecture for the optimization of molecules across multiple pharmacological properties, including binding affinity to both single and dual cancer protein targets. Our approach involves pretraining a transformer-encoder model on molecules encoded by a novel hybrid fragment-SMILES representation method. Fine-tuning is performed through a novel gradient-alignment-based DRL, where lead molecules are optimized by selecting and replacing their fragments with alternatives from a fragment dictionary, ultimately resulting in more desirable drug candidates. Our findings indicate that SMOREDRL is superior to current models for lead optimization in terms of quality, efficiency, scalability, and robustness. Furthermore, SMORE-DRL demonstrates the capability of generalizing its optimization process to lead molecules that are not present during the pretraining or fine-tuning phases.

BACKGROUND:Drug design is a challenging and important task that requires the generation of novel and effective molecules that can bind to specific protein targets. Artificial intelligence algorithms have recently showed promising potential to expedite the drug design process. However, existing methods adopt multi-objective approaches which limits the number of objectives.RESULTS:In this paper, we expand this thread of research from the many-objective perspective, by proposing a novel framework that integrates a latent Transformer-based model for molecular generation, with a drug design system that incorporates absorption, distribution, metabolism, excretion, and toxicity prediction, molecular docking, and many-objective metaheuristics. We compared the performance of two latent Transformer models (ReLSO and FragNet) on a molecular generation task and show that ReLSO outperforms FragNet in terms of reconstruction and latent space organization. We then explored six different many-objective metaheuristics based on evolutionary algorithms and particle swarm optimization on a drug design task involving potential drug candidates to human lysophosphatidic acid receptor 1, a cancer-related protein target.CONCLUSION:We show that multi-objective evolutionary algorithm based on dominance and decomposition performs the best in terms of finding molecules that satisfy many objectives, such as high binding affinity and low toxicity, and high drug-likeness. Our framework demonstrates the potential of combining Transformers and many-objective computational intelligence for drug design.

Drug discovery is a time-consuming and expensive process. Artificial intelligence (AI) methodologies have been adopted to cut costs and speed up the drug development process, serving as promising in silico approaches to efficiently design novel drug candidates targeting various health conditions. Most existing AI-driven drug discovery studies follow a single-target approach which focuses on identifying compounds that bind a target (i.e., one-drug-one-target approach). Polypharmacology is a relatively new concept that takes a systematic approach to search for a compound (or a combination of compounds) that can bind two or more carefully selected protein biomarkers simultaneously to synergistically treat the disease. Recent studies have demonstrated that multi-target drugs offer superior therapeutic potentials compared to single-target drugs. However, it is intuitively thought that searching for multi-target drugs is more challenging than finding single-target drugs. At present, it is unclear how AI approaches perform in designing multi-target drugs. In this paper, we comprehensively investigated the performance of multi-objective AI approaches for multi-target drug design. Our findings are quite counter-intuitive demonstrating that, in fact, AI approaches for multi-target drug design are able to efficiently generate more high-quality novel compounds than the single-target approaches while satisfying a number of constraints.

Cancer cell dormancy is a critical phase in cancer development, wherein cancer cells exist in a latent state marked by temporary but reversible growth arrest. This dormancy phase contributes to anticancer drug resistance, cancer recurrence, and metastasis. Treatment strategies aimed at cancer dormancy can be categorized into two contradictory approaches: inducing cancer cells into a dormant state or eliminating dormant cells. While the former seeks to establish permanent dormancy, the latter aims at eradicating this small population of dormant cells. In this review, we explore the current advancements in therapeutic methods targeting cancer cell dormancy and discuss future strategies. The concept of cancer cell dormancy has emerged as a promising avenue for novel cancer treatments, holding the potential for breakthroughs in the future.

The peptide hormone ghrelin is produced in cardiomyocytes and acts through the myocardial growth hormone secretagogue receptor (GHSR) to promote cardiomyocyte survival. Administration of ghrelin may have therapeutic effects on post-myocardial infarction (MI) outcomes. Therefore, there is a need to develop molecular imaging probes that can track the dynamics of GHSR in health and disease to better predict the effectiveness of ghrelin-based therapeutics. We designed a high-affinity GHSR ligand labeled with 18F for imaging by PET and characterized its in vivo properties in a canine model of MI. Methods: We rationally designed and radiolabeled with 18F a quinazolinone derivative ([18F]LCE470) with subnanomolar binding affinity to GHSR. We determined the sensitivity and in vivo and ex vivo specificity of [18F]LCE470 in a canine model of surgically induced MI using PET/MRI, which allowed for anatomic localization of tracer uptake and simultaneous determination of global cardiac function. Uptake of [18F]LCE470 was determined by time-activity curve and SUV analysis in 3 regions of the left ventricle-area of infarct, territory served by the left circumflex coronary artery, and remote myocardium-over a period of 1.5 y. Changes in cardiac perfusion were tracked by [13N]NH3 PET. Results: The receptor binding affinity of LCE470 was measured at 0.33 nM, the highest known receptor binding affinity for a radiolabeled GHSR ligand. In vivo blocking studies in healthy hounds and ex vivo blocking studies in myocardial tissue showed the specificity of [18F]LCE470, and sensitivity was demonstrated by a positive correlation between tracer uptake and GHSR abundance. Post-MI changes in [18F]LCE470 uptake occurred independently of perfusion tracer distributions and changes in global cardiac function. We found that the regional distribution of [18F]LCE470 within the left ventricle diverged significantly within 1 d after MI and remained that way throughout the 1.5-y duration of the study. Conclusion: [18F]LCE470 is a high-affinity PET tracer that can detect changes in the regional distribution of myocardial GHSR after MI. In vivo PET molecular imaging of the global dynamics of GHSR may lead to improved GHSR-based therapeutics in the treatment of post-MI remodeling.

Metastasis is responsible for about 90 % of cancer deaths. Anti-metastatic drugs, termed as migrastatics, offer a distinctive therapeutic approach to address cancer migration and invasion. However, therapeutic exploitation of metastasis-specific targets remains limited, and the effective prevention and suppression of metastatic cancer continue to be elusive. Lysophosphatidic acid receptor 1 (LPA1) is activated by an endogenous lipid molecule LPA, leading to a diverse array of cellular activities. Previous studies have shown that the LPA/LPA1 axis supports the progression of metastasis for many types of cancer. In this study, we report the synthesis and biological evaluation of fluorine-containing triazole derivatives as potent LPA1 antagonists, offering potential as migrastatic drugs for triple negative breast cancer (TNBC). In particular, compound 12 f, the most potent and highly selective in this series with an IC50 value of 16.0 nM in the cAMP assay and 18.4 nM in the calcium mobilization assay, inhibited cell survival, migration, and invasion in the TNBC cell line. Interestingly, the compound did not induce apoptosis in TNBC cells and demonstrated no cytotoxic effects. These results highlight the potential of LPA1 as a migrastatic target. Consequently, the LPA1 antagonists developed in this study hold promise as potential migrastatic candidates for TNBC.

GRP78, a member of the HSP70 superfamily, is an endoplasmic reticulum chaperone protein overexpressed in various cancers, making it a promising target for cancer imaging and therapy. Positron emission tomography (PET) imaging offers unique advantages in real time, noninvasive tumor imaging, rendering it a suitable tool for targeting GRP78 in tumor imaging to guide targeted therapy. Several studies have reported successful tumor imaging using PET probes targeting GRP78. However, existing PET probes face challenges such as low tumor uptake, inadequate in vivo distribution, and high abdominal background signal. Therefore, this study introduces a novel peptide PET probe, [18F]AlF-NOTA-c-DVAP, for targeted tumor imaging of GRP78. [18F]AlF-NOTA-c-DVAP was radiolabeled with fluoride-18 using the aluminum-[18F]fluoride ([18F]AlF) method. The study assessed the partition coefficients, stability in vitro, and metabolic stability of [18F]AlF-NOTA-c-DVAP. Micro-PET imaging, pharmacokinetic analysis, and biodistribution studies were carried out in tumor-bearing mice to evaluate the probe's performance. Docking studies and pharmacokinetic analyses of [18F]AlF-NOTA-c-DVAP were also performed. Immunohistochemical and immunofluorescence analyses were conducted to confirm GRP78 expression in tumor tissues. The probe's binding affinity to GRP78 was analyzed by molecular docking simulation. [18F]AlF-NOTA-c-DVAP was radiolabeled in just 25 min with a high yield of 51 ± 16%, a radiochemical purity of 99%, and molar activity within the range of 20-50 GBq/μmol. [18F]AlF-NOTA-c-DVAP demonstrated high stability in vitro and in vivo, with a logD value of -3.41 ± 0.03. Dynamic PET imaging of [18F]AlF-NOTA-c-DVAP in tumors showed rapid uptake and sustained retention, with minimal background uptake. Biodistribution studies revealed rapid blood clearance and excretion through the kidneys following a single-compartment reversible metabolic model. In PET imaging, the T/M ratios for A549 tumors (high GRP78 expression), MDA-MB-231 tumors (medium expression), and HepG2 tumors (low expression) at 60 min postintravenous injection were 10.48 ± 1.39, 6.25 ± 0.47, and 3.15 ± 1.15% ID/g, respectively, indicating a positive correlation with GRP78 expression. This study demonstrates the feasibility of using [18F]AlF-NOTA-c-DVAP as a PET tracer for imaging GRP78 in tumors. The probe shows promising results in terms of stability, specificity, and tumor targeting. Further research may explore the clinical utility and potential therapeutic applications of this PET tracer for cancer diagnosis.

The development of site-specific, target-selective and biocompatible small molecule ligands as a fluorescent tool for real-time study of cellular functions of RNA G-quadruplexes (G4s), which are associated with human cancers, is of significance in cancer biology. We report a fluorescent ligand that is a cytoplasm-specific and RNA G4-selective fluorescent biosensor in live HeLa cells. The in vitro results show that the ligand is highly selective targeting RNA G4s including VEGF, NRAS, BCL2 and TERRA. These G4s are recognized as human cancer hallmarks. Moreover, intracellular competition studies with BRACO19 and PDS, and the colocalization study with G4-specific antibody (BG4) in HeLa cells may support that the ligand selectively binds to G4s in cellulo. Furthermore, the ligand was demonstrated for the first time in the visualization and monitoring of dynamic resolving process of RNA G4s by the overexpressed RFP-tagged DHX36 helicase in live HeLa cells.

Background and objective: Patients with rheumatoid arthritis (RA) are more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than healthy population, but there is still no therapeutic strategy available for RA patients with corona virus disease 2019 (COVID-19). Guizhi-Shaoyao- Zhimu decoction (GSZD), Chinese ancient experience decoction, has a significant effect on the treatment of Rheumatism and gout. To prevent RA patients with mild-to-moderate COVID-19 from developing into severe COVID-19, this study explored the potential possibility and mechanism of GSZD in the treatment of this population. Methods: In this study, we used bioinformatic approaches to explore common pharmacological targets and signaling pathways between RA and mild-to-moderate COVID-19, and to assess the potential mecha- nisms of in the treatment of patients with both diseases. Beside, molecular docking was used to explore the molecular interactions between GSZD and SARS-CoV-2 related proteins. Results: Results showed that 1183 common targets were found in mild-to-moderate COVID-19 and RA, of which TNF was the most critical target. The crosstalk signaling pathways of the two diseases focused on innate immunity and T cells pathways. In addition, GSZD intervened in RA and mild-to-moderate COVID-19 mainly by regulating inflammation-related signaling pathways and oxidative stress. Twenty hub compounds in GSZD exhibited good binding potential to SARS-CoV-2 spike (S) protein, 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), papain-like protease (PLpro) and human angiotensin- converting enzyme 2 (ACE2), thereby intervening in viral infection, replication and transcription. Conclusions: This finding provides a therapeutic option for RA patients against mild-to-moderate COVID- 19, but further clinical validation is still needed.

Cyclic dimeric guanosine monophosphate (c-di-GMP) is an important second messenger in bacteria. It regulates a wide range of bacterial functions and behaviors including biofilm formation that causes chronic infections and antibiotic resistance. C-di-GMP being as a signal transducer in bacteria is known to exist in monomer and dimer form. Recent studies also discover that c-di-GMP can form higher-order oligomers, such as tetramer and octamer, which may have physiological roles in bacterial cells. Moreover, the tetrameric c-di-GMP structure was reported to link two subunits of a transcription factor (BldD), which controls the progression of multicellular differenti-ation in sporulating actinomycete bacteria and then mediates the dimerization process. Current understanding on higher-order oligomers of c-di-GMP is relatively limited compared to its monomer or dimer structure. To probe and visualize the higher-order structure of c-di-GMP and its associated biofunctions in live bacterial cells with fluorescence techniques for mechanistic study and cellular investigation is important. Nonetheless, the sensitive and selective fluorescent probe with a rapid signal response for higher-order oligomers of c-di-GMP is currently lacking. In the present study, a series of fluorescent probes that preferentially interacted with tetrameric c-di-GMP and generated red fluorescence signal promptly were synthesized and investigated. The interaction mechanism was studied with 1H NMR and molecular docking. In addition, the ligand was demonstrated as an excellent molecular fluorescent probe for bioimaging of tetrameric c-di-GMP structure and monitoring of biofilm formation on both biotic and abiotic surfaces with pathogenic bacteria including Pseudomonas aeruginosa PAO1 and Bacillus subtilis 168.

BACKGROUND AND OBJECTIVE:Patients with rheumatoid arthritis (RA) are more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than healthy population, but there is still no therapeutic strategy available for RA patients with corona virus disease 2019 (COVID-19). Guizhi-Shaoyao-Zhimu decoction (GSZD), Chinese ancient experience decoction, has a significant effect on the treatment of Rheumatism and gout. To prevent RA patients with mild-to-moderate COVID-19 from developing into severe COVID-19, this study explored the potential possibility and mechanism of GSZD in the treatment of this population. METHODS:In this study, we used bioinformatic approaches to explore common pharmacological targets and signaling pathways between RA and mild-to-moderate COVID-19, and to assess the potential mechanisms of in the treatment of patients with both diseases. Beside, molecular docking was used to explore the molecular interactions between GSZD and SARS-CoV-2 related proteins. RESULTS:Results showed that 1183 common targets were found in mild-to-moderate COVID-19 and RA, of which TNF was the most critical target. The crosstalk signaling pathways of the two diseases focused on innate immunity and T cells pathways. In addition, GSZD intervened in RA and mild-to-moderate COVID-19 mainly by regulating inflammation-related signaling pathways and oxidative stress. Twenty hub compounds in GSZD exhibited good binding potential to SARS-CoV-2 spike (S) protein, 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), papain-like protease (PLpro) and human angiotensin-converting enzyme 2 (ACE2), thereby intervening in viral infection, replication and transcription. CONCLUSIONS:This finding provides a therapeutic option for RA patients against mild-to-moderate COVID-19, but further clinical validation is still needed.

The Aurora kinases (A, B, and C) are a family of three isoform serine/threonine kinases that regulate mitosis and meiosis. The Chromosomal Passenger Complex (CPC), which contains Aurora B as an enzymatic component, plays a critical role in cell division. Aurora B in the CPC ensures faithful chromosome segregation and promotes the correct biorientation of chromosomes on the mitotic spindle. Aurora B overexpression has been observed in several human cancers and has been associated with a poor prognosis for cancer patients. Targeting Aurora B with inhibitors is a promising therapeutic strategy for cancer treatment. In the past decade, Aurora B inhibitors have been extensively pursued in both academia and industry. This paper presents a comprehensive review of the preclinical and clinical candidates of Aurora B inhibitors as potential anticancer drugs. The recent advances in the field of Aurora B inhibitor development will be highlighted, and the binding interactions between Aurora B and inhibitors based on crystal structures will be presented and discussed to provide insights for the future design of more selective Aurora B inhibitors.

As promising therapeutic targets for various types of cancers, Aurora kinases A and B share high sequence and structural similarity, posing a challenge for designing subtype-selective small-molecule inhibitors. Since Aurora kinase A functions as both an oncogene and a haploinsufficient tumor suppressor, selectively inhibiting Aurora kinase B with highly specific inhibitors offers a less toxic anti-cancer strategy. However, the molecular mechanism governing ligand selectivity for Aurora kinase B over A remains unclear. In this study, we used Barasertib, an experimentally validated ligand with 1000-fold selectivity for Aurora kinase B over A, as a template molecule to investigate the selectivity mechanism through molecular dynamics simulations and binding free energy analyses. Our studied showed that in the ATP-binding pocket, the hinge residue Arg159 (-2.21 kcal/mol), exclusive to Aurora kinase B, significantly contributed to Barasertib binding, whereas no such binding occurred with the corresponding residue Leu215 (-0.10 kcal/mol) in Aurora kinase A. In the hydrophobic back pocket, the sum of binding free energies for key residues Lys106, Glu125, and Asp218 in Aurora kinase B (-4.02 kcal/ mol) was substantially lower than that (7.89 kcal/mol) for the corresponding residues Lys162, Glu181, and Asp274 in Aurora kinase A. This finding suggests that binding interactions at the hydrophobic back pocket play a crucial role in Barasertib's selectivity for Aurora kinase B over A. Interestingly, in contrast to the complexes without partner proteins, the binding of partner proteins in both Aurora kinase A and B models induced the aC helix and the beta sheets in the N-lobe to move inward towards the ATP-binding pocket, resulting in a smaller hydrophobic back pocket and unfavorable Barasertib binding. In summary, our results demonstrate how differential ligand behavior arises from a complex interplay of subtle but relevant structural differences upon binding to distinct kinase subtypes. The insights into the structural determinants of subtype selectivity will facilitate the development of highly selective and potent Aurora kinase B inhibitors as drug candidates for cancer therapy.