Medicinal Research Reviews最新文献

Heat shock protein 90 (Hsp90) is an established and clinically validated anticancer target. By regulating the folding and maturation of diverse client proteins, it is indirectly involved in carcinogenesis. Key breast cancer oncogenic drivers, including estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2, are established Hsp90 clients, making breast cancer models widely used for Hsp90 inhibitor evaluation. However, N-terminal inhibitors are well known to induce a heat shock response (HSR), representing a major limitation in cancer therapy. This has driven the development of alternative modalities, such as C-terminal inhibitors, which in several cases avoid HSR induction. To evaluate Hsp90 inhibitors and characterize their proteomic effects, most studies employ western blotting (WB) as the primary method. On WB, different inhibitors are tested across various concentrations, time points, and breast cancer cell lines for their effects on client, heat shock, and other proteins. This generates extensive data sets that outline the expected WB performance of Hsp90 inhibitors. In this review, we focus on 10 protein families that are commonly used to assess Hsp90 inhibition in in vitro breast cancer models and represent all 10 cancer hallmarks. We provide basic structural and functional information on these families and comprehensively describe the effects of N- and C-terminal inhibitors on their levels. We summarize WB-based observations for more than 100 Hsp90 inhibitors, outlining the characteristic effects of N- and C-terminal inhibition, highlighting opportunities for future research, and ending with a suggestion for the WB method design based on best practices observed in literature.

Central nervous system (CNS) tumors are the most common solid malignancies in children, comprising a highly heterogeneous group of neoplasms defined by distinct molecular alterations and clinical behaviors. Advances in molecular genetics have underscored the relevance of specific signaling pathways in driving pediatric tumorigenesis, among which the fibroblast growth factors (FGFs) and their receptors (FGFRs) have emerged as critical regulators of CNS development and tumor biology. The strict regulation of this system is frequently disrupted in cancer contexts, leading to abnormal activation that promotes tumor growth, invasion, and therapy resistance. Recent genomic profiling studies confirm that FGFR gene aberrations (i.e., activating point mutations, amplifications, and fusions) occur in a non-negligible fraction of pediatric CNS tumors. Notably, FGFR alterations are found in approximately 9% of pediatric gliomas, representing a higher incidence compared to adult gliomas. Across a broader survey of pediatric solid and brain tumors, activating FGFR aberrations were measurable in approximately 3% of cases. This prevalence establishes the FGF/FGFR axis as a measurable therapeutic vulnerability in defined patient subsets. Therefore, a deeper understanding of the role of the FGF/FGFR system across different pediatric CNS tumor subtypes is essential for elucidating disease mechanisms and identifying novel therapeutic opportunities. This review outlines the characteristics of major pediatric CNS tumors and discusses the role and potential therapeutic targeting of the FGF/FGFR system.

p21-activated kinase 4 (PAK4), a critical effector of Ras homologous (Rho) GTP hydrolases (GTPases), promotes tumor progression and confers resistance to therapy by regulating malignant cellular phenotypes-such as proliferation, metastasis, and evasion of apoptosis-as well as by remodeling the tumor microenvironment (TME). Within tumor cells, PAK4 promotes proliferation by activating phosphoinositide 3-kinase (PI3K)/AKT and mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) signaling pathways. It enhances invasive and metastatic potential through cytoskeletal reorganization mediated by phosphorylation of effector proteins such as LIM domain kinase 1 (LIMK1)/cofilin and actin nucleation-promoting factor WASL (N-WASP). Furthermore, PAK4 facilitates immune evasion by stabilizing programmed cell death ligand 1 (PD-L1) and inhibiting pyroptosis. At the TME level, PAK4 is activated by hypoxia-inducible factor 1-alpha (HIF-1α), inflammatory cytokines, and extracellular matrix (ECM) stiffness. This activation reprograms the immune landscape, induces aberrant angiogenesis, and promotes metabolic acidosis via the Warburg effect, collectively fostering an immunosuppressive and therapy-resistant niche. Small-molecule PAK4 inhibitors (e.g., KPT-9274, PF-3758309, compound 55) and degraders (e.g., CPS-021) effectively suppress tumor growth in preclinical models. Combining these agents with immune checkpoint blockade, chemotherapy, or radiotherapy reverses therapy resistance and reprograms the TME. Elevated PAK4 expression correlates significantly with poor patient prognosis and resistance to immunotherapy, positioning it as both a predictive biomarker and a promising therapeutic target. Elucidating the PAK4-TME axis provides a mechanistic foundation for developing novel combinatorial strategies targeting the tumor microenvironment.

Breast cancer (BC) is a highly complex and heterogeneous malignancy and the most prevalent cancer among women worldwide. The diagnosis, prognosis, and the treatment of BC pose significant challenges that are responsible for their limited therapeutic efficacy. Omics-based technologies have gained substantial attention in BC diagnosis through molecular profiling and diverse clinical analytics. The integration of metabolomics, proteomics, transcriptomics, and genomics provides a multidimensional approach to personalized BC diagnosis and treatment through high-throughput molecular profiling. Moreover, the emergence of artificial intelligence (AI) has also supported more accurate and early diagnosis of BC through multimodal integration of diverse datasets. The integration of advanced deep learning (DL) and machine learning (ML) has been extensively exploited for tumor grading, histopathological classification, molecular profiling, diagnostic imaging, and prognostic prediction. This review aims to summarize recent developments in AI-driven multi-omics approaches for the discovery of BC biomarkers. We have also highlighted the integration of omics-based data like metabolomics, proteomics, transcriptomics, and genomics with key AI techniques, including ML and DL, that play a crucial role in the inclusion of multi-omics in cancer and biomarker discovery. We have further discussed AI-based BC screening and diagnostic approaches, as well as the contribution of AI models for patient stratification, biomarker discovery, and prediction of therapeutic response. Additionally, key limitations and challenges, including data heterogeneity, high computational complexity, and model interpretability, have also been highlighted in the present review. Conclusively, we have also outlined future perspectives on the integration of AI and multi-omics to revolutionize precision clinical medicine and improve clinical outcomes in BC theranostics.

The extracellular signal-regulated kinases 1 and 2 (ERK1/2) play central roles in the mitogen-activated protein kinase (MAPK) pathway and have emerged as critical regulators of tumorigenesis. Aberrant ERK1/2 signaling is frequently observed in cancers such as melanoma, pancreatic cancer, and colorectal cancer. This review outlines the historical milestones in ERK1/2 research, from their discovery and structural characterization to their identification as oncogenic drivers and therapeutic targets. We detail the ERK1/2 signaling network, highlighting key upstream regulators, including rat sarcoma (RAS), rapidly accelerated fibrosarcoma (RAF), and mitogen-activated protein kinase kinase (MEK), along with downstream substrates that mediate diverse oncogenic processes. Therapeutic approaches aimed at ERK1/2 currently fall into two main classes: small-molecule inhibitors with single-target specificity and those designed to simultaneously act on dual targets, along with combination therapies designed to overcome resistance and improve efficacy. Furthermore, we explore innovative approaches, including proteolysis-targeting chimeras (PROTACs), autophagy-targeting chimeras (AUTACs), and antibody-drug conjugates (ADCs), which offer promising avenues for selectively modulating ERK1/2 activity. By integrating mechanistic insights with clinical development trends, this review underscores the potential of ERK1/2-targeted therapies in precision oncology.

Monoacylglycerol lipase (MAGL), a member of the endocannabinoid system (ECS), plays a crucial role in physiological processes such as regulating the signal transduction of the ECS and the eicosanoid system. In recent years, MAGL has been validated as a potential therapeutic target for several human diseases. Small-molecule MAGL inhibitors have shown considerable promise for the treatment of neurodegenerative diseases, depression, and cancer, with several candidates having advanced to clinical trials. This review briefly outlines the structural features and physiological functions of MAGL, highlights the associations between MAGL and human diseases, and systematically discusses small-molecule MAGL inhibitors developed for different disorders, with the goal of providing a reference for the discovery of more potent MAGL inhibitors.

To enhance drug discovery efforts, medicinal chemists should evaluate, filter, and utilize relevant structural information about target proteins. Acquiring and interpreting protein structures is crucial for elucidating ligand-receptor interactions and addressing ADME-related considerations, making it an essential aspect of medicinal chemistry. Proteins exhibit diverse structural organizations, and their conformational variability poses challenges for drug design. Here we draw from our own experience how advances in structural biology have improved medicinal chemists’ access to 3D protein structures and dynamics, while stressing the need for model validation and refinement. To highlight the influence of structural biology on drug discovery, we present case studies. Structural insights into P-glycoprotein have been crucial in addressing multidrug resistance, while the analysis of the oncoprotein β-catenin provides valuable guidance for developing future therapeutic strategies based on innovative technology like targeted protein degradation. Finally, we report about multimeric complexes of proteins (Alsin and AP-4) involved in rare HSPs and the contribution of protein–protein interaction analyses to discover mutation-specific drugs.

Alzheimer's disease (AD) is a debilitating neurodegenerative condition characterized by progressive cognitive impairment, memory deterioration, and neuronal dysfunction. Its complex pathophysiology involves multiple interlinked processes, including amyloid-β (Aβ) aggregation, tau hyperphosphorylation, oxidative stress, neuroinflammation, synaptic dysfunction, and cholinergic deficits. Current FDA-approved therapies provide only symptomatic relief and fail to halt disease progression, highlighting the urgent need for more effective treatment strategies. This review provides a comprehensive overview of the pathological mechanisms underlying AD and the emerging therapeutic targets for the design of tractable anti-AD scaffolds, namely, acetylcholinesterase, beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), glycogen synthase kinase-3β (GSK3β), dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), histone deacetylases (HDACs), and soluble epoxide hydrolase (sEH). Emphasis is placed on the paradigm shift from single-target therapies to multitarget-directed ligands (MTDLs), which are increasingly recognized as promising tools to tackle AD's multifactorial pathology. We also discuss recent advances in medicinal chemistry and structure-guided drug discovery campaigns aimed at developing pharmacologically optimized, BBB-penetrant MTDLs. By consolidating mechanistic insights with therapeutic innovation, this review aims to facilitate the development of next-generation therapeutics with enhanced efficacy and disease-modifying potential in AD.