The Prognostic Significance of Anisomycin-Activated Phospho-c-Jun NH2-Terminal Kinase (p-JNK) in Predicting Breast Cancer Patients' Survival Time

Bioinformatics approach reveals the modulatory role of JUN in atorvastatin-mediated anti-breast cancer effects

Atorvastatin, a widely prescribed cholesterol-lowering drug, has recently shown potential anticancer effects. However, its influence on gene expression and its biological functions in cancer, in particular breast cancer, still unclear. We aim to identify the dysregulated genes associated with atorvastatin treatment and the main players in their biological network. A total of 103 differentially expressed genes (DEGs) in the unified signature were identified, and the functional enrichment analysis suggested their relation to multiple cancer-related pathways. JUN was identified as the hub gene in the protein-protein interaction (PPI) network and was shown to be responsive to atorvastatin in breast cancer. Atorvastatin exhibited notable predicted cytotoxicity against breast cancer lines, with the activity positively correlated with JUN expression. JUN was significantly downregulated in breast cancer expression inversely correlated with cancer progression, whereas higher JUN expression was linked with better survival outcomes. Atorvastatin may directly interact with JUN protein forming a more compact and stable conformation. These findings demystify the potential therapeutic mechanism of atorvastatin in breast cancer, possibly by fine tuning of JUN expression. As such, JUN might serve as a valuable prognostic biomarker in breast cancer.

The role of the PKCζ/JNK signaling pathway in regulating the development of femoral head necrosis

Osteonecrosis of the femoral head (ONFH) is a debilitating condition characterized by the death of bone cells in the hip joint, resulting in profound disability. This condition has a significant global prevalence. Glucocorticoid (GC)-induced apoptosis of bone cells serves as a crucial cellular mechanism underlying ONFH. The protein kinase C zeta (PKCζ) and c-Jun N-terminal kinase (JNK)/c-Jun cascades have been implicated in the progression of ONFH, yet their interrelationship and contributions to disease development remain unclear. The objective of this study was to investigate the combined impact of PKCζ and JNK/c-Jun signaling on dexamethasone (Dex)-induced apoptosis in osteoblasts in vitro and in GC-induced ONFH rat models in vivo. In vitro experiments were conducted using hFOB1.19 osteoblastic cells to scrutinize the effects of Dex-induced apoptosis. The role of the PKCζ/JNK/c-Jun signaling pathway in this process was examined using naringenin-7-O-β-D-Glucuronide (N7G), a PKC inhibitor, and anisomycin, a JNK activator. The findings were further validated using a rat model of ONFH in vivo. Our results revealed that PKCζ activation augmented JNK/c-Jun signaling and facilitated Dex-induced osteoblast apoptosis. Inhibition of PKCζ with N7G mitigated these effects, while JNK activation with anisomycin intensified them. Similar regulatory effects on osteoblast apoptosis and ONFH progression were observed in the in vivo rat models. Glucocorticoids can induce osteoblast apoptosis and contribute to the development of ONFH by activating the PKCζ/JNK/c-Jun signaling pathway. This study provides compelling evidence supporting the potential therapeutic value of comprehending the pathogenesis of ONFH and developing targeted treatments for this debilitating condition.

Unveiling the role of RAC3 in the growth and invasion of cisplatin-resistant bladder cancer cells

Bladder cancer is one of the most prevalent cancers worldwide, and its morbidity and mortality rates have been increasing over the years. However, how RAC family small GTPase 3 (RAC3) affects the proliferation, migration and invasion of cisplatin-resistant bladder cancer cells remains unclear. Bioinformatics techniques were used to investigate the expression of RAC3 in bladder cancer tissues. Influences of RAC3 in the grade, stage, distant metastasis, and survival rate of bladder cancer were also examined. Analysis of the relationship between RAC3 expression and the immune microenvironment (TIME), genomic mutations, and stemness index. In normal bladder cancer cells (T24, 5637, and BIU-87) and cisplatin-resistant bladder cancer cells (BIU-87-DDP), the expression of RAC3 was detected separately with Western blotting. Plasmid transfection was used to overexpress or silence the expression of RAC3 in bladder cancer cells resistant to cisplatin (BIU-87-DDP). By adding activators and inhibitors, the activities of the JNK/MAPK signalling pathway were altered. Cell viability, invasion, and its level of apoptosis were measured in vitro using CCK-8, transwell, and flow cytometry. The bioinformatics analyses found RAC3 levels were elevated in bladder cancer tissues and were associated with a poor prognosis in bladder cancer. RAC3 in BIU-87-DDP cells expressed a higher level than normal bladder cancer cells. RAC3 overexpression promoted BIU-87-DDP proliferation. The growth of BIU-87-DDP cells slowed after the knockdown of RAC3, and RAC3 may have had an impact on the activation of the JNK/MAPK pathway.

Phosphorylation of Bcl-2 by JNK confers gemcitabine resistance in lung cancer cells by reducing autophagy-mediated cell death

The most common cancer-related death in the world is non-small cell lung cancer (NSCLC). Gemcitabine (GEM) is a common and effective first-line chemotherapeutic drug for the treatment of NSCLC. However, the long-term use of chemotherapeutic drugs in patients usually induces cancer cell drug resistance, leading to poor survival, and prognosis. In this study, to observe and explore the key targets and potential mechanisms of NSCLC resistance to GEM, we first cultured lung cancer CL1-0 cells in a GEM-containing medium to induce CL1-0 cells to develop GEM resistance. Next, we compared protein expression between the parental and GEM-R CL1-0 cell groups. We observed significantly lower expression of autophagy-related proteins in GEM-R CL1-0 cells than in parental CL1-0 cells, indicating that autophagy is associated with GEM resistance in CL1-0 cells. Furthermore, a series of autophagy experiments revealed that GEM-R CL1-0 cells had significantly reduced GEM-induced c-Jun N-terminal kinase phosphorylation, which further affected the phosphorylation of Bcl-2, thereby reducing the dissociation of Bcl-2 and Beclin-1 and ultimately reducing the generation of GEM-induced autophagy-dependent cell death. Our findings suggest that altering the expression of autophagy is a promising therapeutic option for drug-resistant lung cancer.

PD-L1 Protein Expression Is Associated With Good Clinical Outcomes and Nomogram for Prediction of Disease Free Survival and Overall Survival in Breast Cancer Patients Received Neoadjuvant Chemotherapy

Objective

This study aims to investigate the potential prognostic significance of programmed death ligand-1 (PD-L1) protein expression in tumor cells of breast cancer patients received neoadjuvant chemotherapy (NACT).

Methods

Using semiquantitative immunohistochemistry, the PD-L1 protein expression in breast cancer tissues was analyzed. The correlations between PD-L1 protein expression and clinicopathologic characteristics were analyzed using Chi-square test or Fisher’s exact test. The survival curve was stemmed from Kaplan-Meier assay, and the log-rank test was used to compare survival distributions against individual index levels. Univariate and multivariate Cox proportional hazards regression models were accessed to analyze the associations between PD-L1 protein expression and survival outcomes. A predictive nomogram model was constructed in accordance with the results of multivariate Cox model. Calibration analyses and decision curve analyses (DCA) were performed for the calibration of the nomogram model, and subsequently adopted to assess the accuracy and benefits of the nomogram model.

Results

A total of 104 breast cancer patients received NACT were enrolled into this study. According to semiquantitative scoring for IHC, patients were divided into: low PD-L1 group (61 cases) and high PD-L1 group (43 cases). Patients with high PD-L1 protein expression were associated with longer disease free survival (DFS) (mean: 48.21 months vs. 31.16 months; P=0.011) and overall survival (OS) (mean: 83.18 months vs. 63.31 months; P=0.019) than those with low PD-L1 protein expression. Univariate and multivariate analyses indicated that PD-L1, duration of neoadjuvant therapy, E-Cadherin, targeted therapy were the independent prognostic factors for patients’ DFS and OS. Nomogram based on these independent prognostic factors was used to evaluate the DFS and OS time. The calibration plots shown PD-L1 based nomogram predictions were basically consistent with actual observations for assessments of 1-, 3-, and 5-year DFS and OS time. The DCA curves indicated the PD-L1 based nomogram had better predictive clinical applications regarding prognostic assessments of 3- and 5-year DFS and OS, respectively.

Conclusion

High PD-L1 protein expression was associated with significantly better prognoses and longer DFS and OS in breast cancer patients. Furthermore, PD-L1 protein expression was found to be a significant prognostic factor for patients who received NACT.

A Novel Risk Model Based on Lipid Metabolism-Associated Genes Predicts Prognosis and Indicates Immune Microenvironment in Breast Cancer

BACKGROUND

Breast cancer (BRCA) is the most common tumor in women, and lipid metabolism involvement has been demonstrated in its tumorigenesis and development. However, the role of lipid metabolism-associated genes (LMAGs) in the immune microenvironment and prognosis of BRCA remains unclear.

METHODS

A total of 1076 patients with BRCA were extracted from The Cancer Genome Atlas database and randomly assigned to the training cohort (n = 760) or validation cohort (n = 316). Kaplan-Meier analysis was used to assess differences in survival. Consensus clustering was performed to categorize the patients with BRCA into subtypes. Using multivariate Cox regression analysis, an LMAG-based prognostic risk model was constructed from the training cohort and validated using the validation cohort. The immune microenvironment was evaluated using the ESTIMATE and tumor immune estimation resource algorithms, CIBERSORT, and single sample gene set enrichment analyses.

RESULTS

Consensus clustering classified the patients with BRCA into two subgroups with significantly different overall survival rates and immune microenvironments. Better prognosis was associated with high immune infiltration. The prognostic risk model, based on four LMAGs (MED10, PLA2G2D, CYP4F11, and GPS2), successfully stratified the patients into high- and low-risk groups in both the training and validation sets. High risk scores predicted poor prognosis and indicated low immune status. Subgroup analysis suggested that the risk model was an independent predictor of prognosis in BRCA.

CONCLUSION

This study demonstrated, for the first time, that LMAG expression plays a crucial role in BRCA. The LMAG-based risk model successfully predicted the prognosis and indicated the immune microenvironment of patients with BRCA. Our study may provide inspiration for further research on BRCA pathomechanisms.