Integrated Analysis of the Expression Characteristics, Prognostic Value, and Immune Characteristics of PPARG in Breast Cancer

METTL3 promotes drug resistance to oxaliplatin in gastric cancer cells through DNA repair pathway

Gastric cancer (GC) poses a significant threat to human health and remains a prevalent form of cancer. Despite clinical treatments, the prognosis for Gastric cancer patients is still unsatisfactory, largely due to the development of multidrug resistance. Oxaliplatin (OXA), a second-generation platinum drug, is commonly recommended for adjuvant and palliative chemotherapy in Gastric cancer; however, the underlying mechanisms of acquired resistance to Oxaliplatin in Gastric cancer patients are not yet fully understood. In this study, we aimed to explore the potential mechanisms of Oxaliplatin resistance in Gastric cancer by employing bioinformatics analysis and conducting in vitro experiments. Specifically, we focused on investigating the role of methyltransferase-like 3 (METTL3). Our findings revealed that the knockdown of METTL3 significantly impeded the proliferation and migration of Gastric cancer cells. METTL3 knockdown induced apoptosis in OXA-resistant Gastric cancer cells and enhanced their sensitivity to Oxaliplatin. Furthermore, we found that DNA repair pathways were significantly activated in OXA-resistant Gastric cancer cells, and METTL3 knockdown significantly inhibited DNA repair pathways. Another important finding is that METTL3 knockdown and OXA-induced Gastric cancer cell death are additive, and the targeted METTL3 can assist Oxaliplatin treatment. Collectively, our findings suggest that METTL3 knockdown can augment the sensitivity of Gastric cancer cells to Oxaliplatin by impeding DNA repair processes. Consequently, targeting METTL3 holds great promise as a viable adjuvant strategy in the treatment of Gastric cancer patients.

Molecular basis of breast cancer with comorbid depression and the mechanistic insights of Xiaoyaosan in treating breast cancer-associated depression

Depression and breast cancer (BC) have been found to have a shared genetic basis, multiple loci of effect, and a presumed causal relationship. The treatment of BC combined with depression poses significant challenges. This study aims to use bioinformatics and network pharmacology to explore the molecular basis of BC combined with depression and to elucidate the potential mechanisms of Xiaoyaosan (XYS) in treating this disease. The molecular background of BC complicated with depression was discovered via data mining and bioinformatics. The molecular mechanism of XYS in the treatment of BC with depression was investigated by network pharmacology. The binding affinity between targets and active compounds was evaluated by molecular docking. The impact of XYS on the gene and protein expression of matrix metallopeptidase 9 (MMP9) in microglial cells was assessed using RT-quantitative PCR and western blot analysis, respectively. Differential expression analysis was conducted to identify genes associated with BC, revealing that 2958 genes were involved, with 277 of these genes also being related to depression. XYS was found to contain 173 active compounds and 342 targets, with 44 of these targets being involved in regulating the progression of BC and depression. Enrichment analysis was performed to identify pathways associated with these targets, revealing that they were related to cell proliferation, catalytic activity, cell communication, and interleukin-18 signaling and LXR/RXR activation. Network analysis was conducted to identify key targets of Xiaoyaosan in treating BC combined with depression, with EGF, interleukin 6, epidermal growth factor receptor, and peroxisome proliferator activated receptor gamma being identified as important targets. Molecular docking was also performed to assess the binding affinity between key targets and active compounds, with puerarin showing the strongest affinity for MMP9. In microglial cells, XYS significantly enhances the gene and protein expression of MMP9. This study elucidated the pharmacological mechanism of co-treatment for BC patients complicated with depression and the pharmacological mechanism of XYS against BC plus depression.

Asiaticoside hampers epithelial–mesenchymal transition by promoting PPARG expression and suppressing P2RX7‐mediated TGF‐β/Smad signaling in triple‐negative breast cancer

Triple-negative breast cancer (TNBC) accounts for 10-20% of all human ductal adenocarcinomas and has a poor prognosis relative to other subtypes because of its high propensity to develop metastases. Here, the anticancer effects of asiaticoside (AC) against TNBC and the possible underlying mechanism were examined. We found that AC inhibited the TGF-β1 expression and the SMAD2/3 phosphorylation in TNBC cells, thereby impairing the TGF-β/SMAD signaling. AC inhibited the migration, invasion, and epithelial-mesenchymal transition (EMT) of TNBC cells by suppressing the TGF-β/SMAD signaling. Meanwhile, AC inhibited the lung metastasis of TNBC cells in vivo and the expression of p-SMAD2/3 and vimentin, and increased the expression of E-cadherin and ZO-1 in the lung. Peroxisome proliferator activated receptor gamma (PPARG) was identified as a potential target of AC. AC increased PPARG expression, while PPARG knockdown attenuated the therapeutic effect of AC. AC-mediated PPARG overexpression suppressed the transcription of P2X purinoceptor 7 (P2RX7). The restoration of P2RX7 reversed the therapeutic effect of AC. These results suggested that AC blocked P2RX7-mediated TGF-β/SMAD signaling by increasing PPARG expression, thereby suppressing EMT in TNBC.

Identification of NAD+ Metabolism-Derived Gene Signatures in Ovarian Cancer Prognosis and Immunotherapy

Background: Nicotinamide adenine dinucleotide (NAD⁺) has emerged as a critical regulator of cell signaling and survival pathways, affecting tumor initiation and progression. In this study it was investigated whether circulating NAD⁺ metabolism-related genes (NMRGs) could be used to predict immunotherapy response in ovarian cancer (OC) patients.

Method: In this study, NMRGs were comprehensively examined in OC patients, three distinct NMRGs subtypes were identified through unsupervised clustering, and an NAD⁺-related prognostic model was generated based on LASSO Cox regression analysis and generated a risk score (RS). ROC curves and an independent validation cohort were used to assess the model’s accuracy. A GSEA enrichment analysis was performed to investigate possible functional pathways. Furthermore, the role of RS in the tumor microenvironment, immunotherapy, and chemotherapy was also investigated.

Result: We found three different subgroups based on NMRGs expression patterns. Twelve genes were selected by LASSO regression to create a prognostic risk signature. High-RS was founded to be linked to a worse prognosis. In Ovarian Cancer Patients, RS is an independent prognostic marker. Immune infiltrating cells were considerably overexpressed in the low-RS group, as immune-related functional pathways were significantly enriched. Furthermore, immunotherapy prediction reveal that patients with low-RS are more sensitive to immunotherapy.

Conclusion: For a patient with OC, NMRGs are promising biomarkers. Our prognostic signature has potential predictive value for OC prognosis and immunotherapy response. The results of this study may help improve our understanding of NMRG in OCs.