International journal of molecular medicine最新文献

Despite advances in HER2‑targeted therapy for HER2‑positive breast cancer, resistance to trastuzumab and tumor recurrence remain major barriers to durable outcomes. The present study evaluated the therapeutic potential of ebastine, a second‑generation H1‑antihistamine, as a repurposing candidate to overcome trastuzumab resistance by targeting HER2 signaling and cancer stem cell (CSC)‑associated phenotypes in HER2‑positive breast cancer cells. Molecular docking studies revealed that ebastine bound to the ATP‑binding site of the HER2 tyrosine kinase domain, thereby suppressing the phosphorylation of HER2, p95HER2 and HER3, as assessed by immunoblotting. Immunoprecipitation assay further demonstrated that this binding disrupted HER2/HER3 and HER2/EGFR heterodimerization, leading to reduced downstream AKT activation. Ebastine significantly decreased aldehyde dehydrogenase (ALDH)1 activity, decreased the CD44^high/CD24^low CSC‑like population, as assessed by flow cytometry, and inhibited mammosphere formation. In a trastuzumab‑resistant xenograft model, ebastine markedly suppressed tumor growth, decreased the Ki‑67 proliferation index and angiogenesis and induced apoptosis. These effects were accompanied by decreased expression of HER2, HER3, ALDH1, CD44, and vimentin in tumor tissues, as determined by immunohistochemistry. Furthermore, serum biochemical analyses revealed no significant hepatotoxicity or nephrotoxicity, indicating a favorable in vivo safety profile. These findings demonstrated that ebastine effectively disrupts key pathways involved in CSC‑like traits and HER2 activity, even under trastuzumab‑resistant conditions. Its multifaceted inhibitory effects support the repositioning of ebastine as a promising therapeutic strategy for treating refractory HER2‑positive breast cancer.

Metabolic reprogramming is a hallmark feature of malignant tumors. These metabolic pathways are regulated in a cell‑autonomous manner by oncogenic signaling and transcriptional networks, and tracking their metabolic reprogramming is frequently used in the diagnosis, detection and treatment of cancer. There are currently promising therapeutic prospects for a variety of types targeting fixed core metabolic pathways in tumor metabolic reprogramming. Among these, inosine monophosphate (IMP) is an essential intermediate in purine nucleotide synthesis that demonstrates significant target potential. Nevertheless, further research is needed to elucidate the regulatory networks that control IMP metabolism in tumor cells. This review combines the latest insights into IMP metabolism into an interesting conceptual framework. This includes the supply of IMP precursor substrates (reprogramming of glucose metabolism, serine/one‑carbon metabolism, glutamine and mitochondrial metabolism), the dynamic regulation of important enzymes [phosphoribosyl pyrophosphate synthetase, phosphoribosyl pyrophosphate amidotransferase, IMP dehydrogenase (IMPDH)], purinosomes and signaling pathways (RAS‑ERK, PI3K/AKT‑mTORC1 and Hippo‑YAP) that ultimately regulate IMP synthesis in tumor cells. Additionally, it focused on downstream associations between IMPDH and the immune microenvironment, offering a fresh perspective for current research on tumor therapy targeting IMP metabolism.

Following the publication of the above article, an interested reader drew to the authors' attention that the control β‑actin western blots shown in Figs. 2C and 5A were strikingly similar, even though the experimental conditions reported in these figures were different. After having re‑examined the original data, the authors have realized that these western blots were inadvertently included in Fig. 2C erroneously. The revised version of Fig. 2, now incorporating the correct data for the β‑actin bands in Fig. 2C, is shown below. The authors confirm that the error associated with this figure did not have a significant impact on either the results or the conclusions reported in this study, and all the authors agree with the publication of this Corrigendum. The authors are grateful to the Editor of International Journal of Molecular Medicine for allowing them the opportunity to publish this Corrigendum; furthermore, they apologize to the readership of the Journal for any inconvenience caused. [International Journal of Molecular Medicine 43: 1778‑1788, 2019; DOI: 10.3892/ijmm.2019.4085].

Donation after circulatory death (DCD) is a key source of liver grafts but it is associated with more severe ischemia‑reperfusion injury (IRI) and poorer transplant outcomes compared with donation after brain death. Hypothermic machine perfusion (HMP) effectively decreases DCD graft injury, but its protective molecular mechanisms remain unclear. Kruppel‑like factor 2 (KLF2) is an endothelial protective transcription factor induced by hemodynamic mechanical stimulation. However, the role of KLF2 in IRI during HMP in DCD livers is unclear. Rat livers undergoing DCD modeling followed by static cold storage (CS) or HMP were used to assess KLF2 expression and macrophage efferocytosis. Injury was assessed by serum alanine transferase/aspartate transferase levels, histology, TUNEL apoptosis assay and immunofluorescence (IF) for in situ efferocytosis. Protein markers were analyzed via western blotting, immunohistochemistry and IF. In vitro, HUVECs and macrophages were subjected to simulated CS/reperfusion. Macrophages efferocytosis was quantified using fluorescently labeled apoptotic Jurkat cells. Mechanisms were explored by RNA sequencing and co‑immunoprecipitation. Compared with the CS group, HMP decreased pathological injury, apoptosis and inflammation in DCD liver injury. KLF2 expression was upregulated. However, knockdown of KLF2 abrogated these endothelial protective effects in vitro. Furthermore, overexpression of KLF2 enhanced macrophage efferocytosis, whereas suppression of KLF2 impaired this. Moreover, enhanced efferocytosis contributed to inflammation resolution, ultimately improving overall graft injury and decreasing apoptosis. Mechanistically, KLF2 inhibited the NOD‑like receptor protein 3 (NLRP3) inflammasome to suppress pyroptosis, thereby indirectly enhancing efferocytosis. HMP alleviated IRI in DCD liver grafts by upregulating endothelial KLF2, which inhibited NLRP3 inflammasome‑mediated pyroptosis, thereby improving the inflammatory microenvironment and promoting macrophage efferocytosis.

Sepsis‑induced vasoplegia, a life‑threatening complication of sepsis, has become a focal point of research endeavors aimed at determining its complex mechanisms. However, existing investigations predominantly focus on the role of endothelial cells (ECs) in sepsis, inadvertently dismissing the pivotal contribution of vascular smooth muscle cells (VSMCs). The present review highlights the frequently underappreciated role of VSMCs in sepsis‑induced vasodilation, and provides a comprehensive and systematic elucidation of the associated pathophysiological mechanisms. The current review examines the structural characteristics, localization, phenotypic transitions and heterogeneity of VSMCs, emphasizing their critical role in maintaining vascular homeostasis and regulating blood pressure. Subsequently, the review delves into the multifaceted effects of sepsis on VSMCs. Direct injury to VSMCs in sepsis occurs through pathogens. Additionally, the sepsis‑associated cytokine storm can activate key signaling pathways, such as the NF‑κB and p38 MAPK pathways, leading to a phenotypic shift in VSMCs from a contractile state to a synthetic state, thus enhancing their proliferative and migratory abilities. Concurrently, sepsis disrupts the intricate interaction between ECs and VSMCs, and interferes with calcium homeostasis, ultimately resulting in reduced vascular reactivity and abnormal vascular remodeling. Together, these mechanisms contribute to sepsis‑related vascular dysfunction and multiorgan failure. The in‑depth analysis of these processes in the present review offers novel insights into the pathological mechanisms of sepsis‑induced vasoplegia. The current study also provides a theoretical foundation for the development of clinical intervention strategies targeting VSMCs, with the potential to advance sepsis treatment strategies.

Diabetic cardiomyopathy (DCM) is a significant complication in patients with diabetes, but its pathogenesis is not fully understood. In recent years, dynamic regulation of lipid droplets (LDs) balance has gradually become a new therapeutic direction with great potential. LDs regulate lipid storage, energy supply and interconnected drivers; for instance, oxidative damage, inflammation, autophagy, ferroptosis, affect the function and cellular homeostasis of cardiomyocytes, macrophages and fibroblasts, and thus participate in DCM. The present review discusses the multiple functions of LDs in regulating DCM by affecting cell homeostasis and summarizes the research progress of therapies targeting LDs and related metabolic pathways, which may inform novel strategies for preventing and treating DCM.

Subsequently to the publication of the above paper, an interested reader drew to the authors' attention that, concerning the immunofluorescence images shown in Fig. 2C on p. 855, the 'Blank/E‑cadherin' and 'TGF‑β2‑SIS3/E‑cadherin' data panels appeared to show the same data, albeit with different intensities of staining. In addition, in Fig. 3B on p. 856, the GAPDH blots shown for the '7 days' and '28 days' experiment gels were strikingly similar in appearance, in spite of different experiments being reported. After having asked the authors to explain the apparent anomalies in these figures, they realized that they had been assembled erroneously. Corrected versions of Figs. 2 and 3, now showing the correct data for the 'TGF‑β2‑SIS3/E‑cadherin' experiment in Fig. 2C and the GAPDH western blots for the '28 days' experiment in Fig. 3B, are shown opposite and on the next page. The errors made in assembling Figs. 2 and 3 did not grossly affect either the results or the conclusions reported in this paper. All the authors agree with the publication of this corrigendum, and are grateful to the Editor of International Journal of Molecular Medicine for allowing them the opportunity to present this; moreover, the Editor and the authors apologize to the readership for any inconvenience caused. [International Journal of Molecular Medicine 42: 851‑860, 2018; DOI: 10.3892/ijmm.2018.3662].

Follistatin‑like protein 1 (FSTL1), a secreted glycoprotein, serves a key role in regulating various biological processes. The present review explores the molecular mechanisms through which FSTL1 influences inflammation, cellular senescence and tumour progression. As a multifunctional protein with both autocrine and paracrine properties, FSTL1 regulates cell survival, proliferation, differentiation and migration, while also modulating immune responses. Evidence indicates that FSTL1 exerts context‑dependent regulatory effects on pathological conditions by modulating signalling pathways, such as TGF‑β, NF‑κB and MAPK. Furthermore, increased FSTL1 expression has been found in the inflammatory synovial tissues of patients with osteoarthritis and it contributes to nucleus pulposus cell inflammation. In conclusion, the distinctive structural features and widespread expression of FSTL1 position it as a key target for understanding the mechanisms underlying inflammation, senescence and tumourigenesis, providing potential options for novel diagnostic and therapeutic strategies for these conditions.

Following the publication of the above article, an interested reader drew to the authors' attention that, concerning the Transwell migration assay images shown in Fig. 6 on p. 287, the data panels for figure parts 6E (the DMSO experiment) and 6G (the pcDNA3.1+DMSO experiment) contained strikingly similar data, albeit with different sizing of the images, suggesting that these data had been derived from the same original source. Upon investigating this figure, the authors realized that this figure had inadvertently been assembled incorrectly: The data panel for the DMSO group in the HTR‑8/SVneo cell migration assay (Fig. 6E) had been duplicated from the correctly displayed pcDNA3.1+DMSO group panel. The revised version of Fig. 6, now showing the correct data panel for Fig. 6E, is shown on the next page. The authors confirm that the error associated with this figure did not have any significant impact on either the results or the conclusions reported in this study, and all the authors agree with the publication of this Corrigendum. The authors are grateful to the Editor of International Journal of Molecular Medicine for allowing them the opportunity to publish this Corrigendum; furthermore, they apologize to the readership of the Journal for any inconvenience caused. [International Journal of Molecular Medicine 44: 281-290, 2019; DOI: 10.3892/ijmm.2019.4175].

Diabetic kidney disease (DKD) is a microvascular complication of diabetes, characterized by region‑specific metabolic reprogramming that disrupts kidney function and markedly impairs patient prognosis. By enabling in situ visualization and analysis of metabolite distribution within kidney tissue, spatial metabolomics offers a unique advantage in detecting spatial heterogeneity in metabolic alterations, which is inaccessible through conventional metabolomics. This approach not only enhances the understanding of DKD pathophysiology but also provides a solid foundation for the development of precision nephrology strategies informed by spatial metabolite data. The present review discusses the fundamental workflows and spatial resolution capabilities of spatial metabolomics, summarizing the key metabolites involved in regional metabolic disruptions in multiple DKD animal models. Moreover, it highlights notable metabolites, including glucose, succinate, phosphatidylserine, lysophosphatidylglycerol, phosphatidylglycerol, sphingomyelin, phosphatidylcholine, phosphatidylethanolamine, taurine, glutamate, L‑carnitine, choline, adenosine monophosphate and guanosine monophosphate. The continued advancement of imaging technologies and data analysis methodologies is expected to further refine the spatial resolution and precision of spatial metabolomics, thereby facilitating its broader application in clinical practice.