Current Medicinal Chemistry - Online First

The development and progression of non-small cell lung cancer (NSCLC) are intricately linked to immune cell activation, but its related signature has not been reported.

This study combines in silico and in vitro approaches. TCGA-NSCLC and Gene Expression Omnibus (GEO) datasets were utilized to develop and validate a prognostic signature based on cell activation genes. The signature’s validity was assessed through the identification of genomic, transcriptomic, tumor microenvironment (TME), and single-cell infiltration characteristics. The function of the candidate gene RORA was verified using CCK8, apoptosis, colony formation, wound healing, and transwell assays. The detailed mechanism of RORA was investigated through ChIP-PCR, luciferase assays, Western blot, and ROS detection.

The prognostic signature was constructed from TCGA-NSCLC datasets and validated in six independent datasets (GSE30219, GSE33072, GSE37745, GSE41271, GSE42127, GSE50081). The signature was associated with LRP1B and RYR2 mutations, NSCLC-related pathways, drug response, and immune cell infiltration. The candidate gene RORA significantly inhibits the proliferation and migration abilities of NSCLC cell lines (A549 and NCI-H1299). Furthermore, the transcription factor RORA promotes ZNF490 expression, which subsequently inhibits NUDFs expression and oxidative phosphorylation (oxphos).

The signature highlighted its significance with genomic features that were frequently reported as prognostic indicators (LRP1B and RYR2 mutations, cancer-related infiltration and pathway infiltration), and putative treatment response (IC50 in the TCGA dataset). Its detailed mechanism of candidate gene RORA revealed its role in oxphos, highlighting the crosstalk between metabolism and immune activation.

The model is robust and effectively reflects NSCLC heterogeneity while predicting prognosis. RORA promotes the expression of ZNF490 to inhibit NUDFs and oxidative phosphorylation.

Limited studies have explored how ferroptosis and Epithelial-Mesenchymal Transition (EMT) jointly affect the prognosis of Esophageal Squamous Cell Carcinoma (ESCC). This study aimed to develop a clinical prognostic model based on the combined impact of ESCC.

Gene expression levels and clinical data of ESCC patients were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Using Cox regression analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, we identified nine prognostic genes to build a predictive model. Immune cell infiltration was evaluated using CIBERSORT and single-sample Gene Set Enrichment Analysis methods. Finally, in vitro experiments were conducted to assess the oncogenic effects of ACSL3 and VIM.

We developed a Ferroptosis-EMT Integrated Score (FEIS) based on nine key genes. High-FEIS patients had worse survival, increased immune infiltration, and higher expression of immune checkpoints. A nomogram was built for prognosis prediction, and in vitro studies confirmed the tumor-promoting roles of ACSL3 and VIM.

The FEIS model robustly predicts ESCC prognosis by integrating ferroptosis and EMT, offering novel biomarkers for personalized immunotherapy, though further validation is warranted.

Our study introduced a novel prognostic tool that integrates ferroptosis and EMT-related biomarkers and offers valuable insights for developing personalized treatment strategies for ESCC patients.

Prostate cancer is the fourth most commonly diagnosed cancer worldwide and the eighth leading cause of cancer-related mortality, primarily affecting elderly males. Conventional therapeutic approaches, while effective in some cases, often come with substantial side effects, posing particular challenges for older patients. As a result, the exploration of natural compounds from traditional Chinese medicine (TCM) as potential anticancer agents has gained increasing attention. Sesamin, a dietary lignan found in sesame seeds and frequently used in TCM, has shown promise in preliminary studies for its antioxidant, anti-inflammatory, and potential anticancer properties. However, its specific effects and underlying mechanisms against prostate cancer cells remain inadequately characterized.

This study investigated the anticancer effects of sesamin on human prostate cancer DU145 cells. Cell viability was evaluated using MTT assays. Apoptosis induction and cell cycle distribution were assessed by flow cytometry. Protein expression levels of PPAR-γ, p21, and p53 were measured using Western blotting. Additionally, in silico molecular docking was performed using the LibDock algorithm to evaluate sesamin’s binding affinity with the target proteins PPAR-γ and p21.

Sesamin treatment significantly reduced the viability of DU145 cells in a dose-dependent manner. Flow cytometry revealed increased apoptosis and cell cycle arrest at the G1 phase. Western blot analysis showed upregulated expression of PPAR-γ and p21, while p53 expression remained largely unchanged. Molecular docking analysis demonstrated strong binding affinity of sesamin to PPAR-γ (LibDock score: 125.03) and p21 (LibDock score: 105.45), supporting its involvement in a p53-independent apoptotic mechanism.

The study demonstrates that sesamin exerts significant anticancer effects on prostate cancer DU145 cells by inhibiting cell viability, inducing apoptosis, and causing G1 phase cell cycle arrest. The upregulation of PPAR-γ and p21, coupled with unchanged p53 expression, suggests that sesamin may activate a p53-independent pathway, a valuable feature in treating prostate cancers with defective p53 signaling. Molecular docking results corroborate these findings, indicating direct interactions between sesamin and its molecular targets.

Sesamin exhibits promising antiproliferative and pro-apoptotic activities against DU145 prostate cancer cells. Its potential to act as a G1-phase-specific chemotherapeutic agent via a p53-independent mechanism warrants further investigation and development as a natural candidate for prostate cancer therapy.

Observational studies have suggested associations between circulating metabolites and breast cancer (BC) risk, but the direction and causality of these relationships remain unclear due to confounding and reverse causation. Therefore, we aimed to evaluate the potential causal effects of 1,400 circulating metabolites on BC subtypes using Mendelian randomization (MR) based on GWAS data from European-ancestry populations.

Two-sample and reverse MR analyses were performed to explore potential causal links between metabolites and BC from the FinnGen and Breast Cancer Association Consortium (BCAC) cohorts. The inverse-variance weighted (IVW) approach served as the main analytical method to evaluate these associations. To further ensure the robustness and credibility of the MR findings, sensitivity analyses were conducted, incorporating leave-one-out procedures, the Cochran's Q test, and the MR-Egger intercept test.

Following correction using the False Discovery Rate (FDR) method at a significance level of 0.10, we identified 5alpha-pregnan-3beta,20alpha-diol monosulfate levels (p = 6.7714*10-5, PFDR = 0.0798) and Myristoleate (14:1n5) levels (p =0.0002, PFDR = 0.0798) were associated with an increased risk of ER+ BC. Conversely, the Caffeine to paraxanthine ratio (p =0.0001, PFDR = 0.0798) was associated with a reduced risk. In the reverse MR analysis, interactions were observed between Eicosanedioate (C20-DC) levels, Piperine levels, Caffeine to theobromine ratio, Indolepropionate levels, 1-oleoyl-GPC (18:1) levels, and Oleoylcarnitine levels with BC. Notably, the p-values of intercept terms in MR-Egger regression all exceeded 0.05, suggesting an absence of potential horizontal pleiotropy.

These findings suggested that hormone-related, lipid-related, and diet-derived metabolites might play subtype-specific roles in breast cancer development. The identified metabolites provided mechanistic insights and highlighted potential biological pathways that warrant further functional validation. They may also serve as preliminary biomarkers for future metabolomic and translational research.

Our MR study identified several metabolites that may be causally associated with BC risk. These findings offer potential candidates for further mechanistic investigation and highlight the importance of subtype-specific approaches in metabolomics research.

Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis and a high fatality rate. To predict the prognosis of HNSCC, this study developed a prognostic model based on nitrogen metabolism (NM)-related genes.

This study utilized transcriptomic data and clinical information from HNSCC obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify differentially expressed NM-related genes. Subsequently, an NM-related prognostic risk model was established by integrating univariate Cox regression, LASSO regression, and multivariate Cox regression. Its predictive value was validated using Kaplan-Meier and ROC curves. Further analysis using GSVA and CIBERSORT examined the relationship between the risk model and the tumor microenvironment immune status, while also evaluating chemotherapy drug sensitivity across different risk groups. Finally, protein-protein interaction (PPI) networks and key gene screening were employed, and the functional validation of the core genes was conducted through in vitro experiments.

We identified 10 key NM-related genes (GLS, ASNS, EXT2, HPRT1, SLC7A5, SMS, B3GNT8, GATM, NAGK, and SULT1B1) to construct a prognostic risk model. The GSVA analysis revealed that the low-risk group was enriched in immune-related pathways, while the high-risk group favored metabolic pathways. Additionally, the low-risk group exhibited higher levels of immune cell infiltration. We discovered that gefitinib, belinostat, erlotinib, and phenformin were more effective against cancer cells with lower risk scores. The PPI network screening identified key hub genes, including LORICRIN. Experimental validation demonstrated that LORICRIN overexpression significantly suppressed migration and invasion in HNSCC cells, suggesting its potential tumor-suppressive role in carcinogenesis and progression.

This study emphasizes the links between NM signatures, immune regulation, and signaling pathways, underscoring their potential in the HNSCC mechanism research.

Our study established a NM-related gene signature closely linked to immune microenvironment and drug sensitivity, highlighting potential biomarkers and therapeutic targets for prognosis and personalized therapy in HNSCC.

Osteosarcoma is a highly aggressive cancer with a notably low five-year survival rate. Although aspirin has demonstrated potential in inhibiting the malignant progression of osteosarcoma, the underlying mechanisms remain unclear.

In this study, RNA sequencing (RNA-seq) was employed to identify the downstream targets of aspirin in osteosarcoma cells. Then, we examined the expression and clinical significance of PDE4D using osteosarcoma patient samples, tissue microarrays, and data from the TARGET and GTEx databases. The effects of PDE4D on cell growth and mobility were assessed by CCK-8, colony formation, transwell, and wound-healing assays. To explore how aspirin influenced the NF-κB/p65/PDE4D axis, we performed qRT-PCR, Western blotting, luciferase reporter assays, etc. Additionally, mouse models with subcutaneous tumors were used to confirm the roles of aspirin and PDE4D.

Our results showed that aspirin significantly impeded the proliferation, migration, and invasion of osteosarcoma cells by various functional assays. RNA-seq identified PDE4D as a key target modulated by aspirin treatment in osteosarcoma. Clinically, PDE4D was highly expressed in osteosarcoma cells and tissues, and higher levels of PDE4D were linked to poorer patient outcomes. Functionally, PDE4D served as an oncogene that promoted the malignant traits of osteosarcoma both in vitro and in vivo. Mechanistically, our findings revealed that NF-κB/p65 directly interacted with the core region of the PDE4D promoter, increasing its expression.

The findings of this study reveal a novel mechanism whereby aspirin exerts its anti-tumor effects by inhibiting the NF-κB/p65/PDE4D axis, providing a mechanistic basis for its therapeutic potential. Further validation in different animal models of osteosarcoma is warranted.

Aspirin suppressed the malignant progression of osteosarcoma by targeting the NF-κB/p65/PDE4D axis, positioning PDE4D as a potential therapeutic target for aspirin-based treatment strategies.

Radiotherapy remains a cornerstone of treatment for non-small cell lung cancer (NSCLC). Despite its critical role, the emergence of radiation resistance remains a significant hurdle, often leading to therapeutic failure and disease progression. This research aimed to investigate the expression of Pellino E3 ubiquitin protein ligase family member 3 (PELI3) in NSCLC and examine its involvement in modulating the tumor's response to radiation.

To quantify PELI3 levels in NSCLC tissues, real-time PCR and Western blotting techniques were employed. The effects of silencing PELI3 on cancer cell proliferation were evaluated using CCK-8 and colony formation assays. Furthermore, an in vivo mouse xenograft model was used to corroborate the in vitro results.

PELI3 expression was markedly elevated in NSCLC tumor samples relative to normal tissues and showed a strong association with clinical features, such as tumor volume, lymph node involvement, and radiotherapy responsiveness. Further analysis revealed that PELI3 promoted epithelial-to-mesenchymal transition (EMT) following radiation exposure. Suppressing PELI3 expression mitigated radiation-induced EMT in both cellular and animal models.

Elevated PELI3 promotes radiation-induced EMT and radioresistance in NSCLC. Suppressing PELI3 reverses EMT features and enhances radiosensitivity in vitro and in vivo, highlighting PELI3 as a potential biomarker and therapeutic target to improve radiotherapy outcomes.

These findings suggest that PELI3 could serve as a valuable prognostic marker in NSCLC and may represent a promising target to improve tumor sensitivity to radiotherapy.