Biology Direct最新文献

Background: Oxidative stress plays a crucial role in the development of diabetic foot ulcers (DFU). However, its underlying mechanisms are not fully understood. The purpose of this study was to use bioinformatics and preliminary validation methods to preliminarily reveal the oxidative stress landscape in DFU.

Methods: Based on the single-cell and bulk RNA sequencing data of DFU, we conducted differential genes screening, machine learning, PPI network construction, immune infiltration analysis, drug prediction, TF-mRNA-miRNA network, cell-cell interaction, pseudotime trajectory analysis, external cohort validation, and in vitro experiments to develop the oxidative stress landscape in DFU.

Results: Bulk RNA-seq analysis identified 63 oxidative stress-related genes of DFU (DORGs), and the top 59 genes were screened out for key nodes with close functional associations. Functional enrichment analysis showed significant involvement in oxidative stress response. Drug prediction highlighted Thymoquinone and Erlotinib as potential therapeutic candidates. Machine learning algorithms (SVM-RFE, LASSO and RF) identified BCL2 and FOXP2 as candidate hub DORGs for DFU diagnosis. Immune cell infiltration analysis indicated a significant presence of naive B cells and CD8 T cells in DFU. The analysis of single-cell RNA sequencing identified a total of 31,787 cells across 10 distinct clusters, with a notably lower proportion of fibroblasts in DFU group than that in the control group. The expression patterns of BCL2 and FOXP2 across the different groups were consistent with findings from bulk RNA sequencing analysis. Notably, fibroblasts derived from DFU patients exhibited the highest oxidative stress scores. Intercellular signaling analysis indicated that fibroblasts serve as crucial communication cells, primarily engaged in COLLAGEN signaling network. Additionally, fibroblasts are categorized into five distinct clusters. Among these, COL6A5+ fibroblasts constitute the predominant cluster in DFU and exhibit low differentiation potential. Furthermore, in vitro experiments successfully established a DFU oxidative stress model of fibroblasts, revealing reduced migration ability in the absence of cell death. Both in vitro findings and external data corroborated the decreased expression levels of BCL2andFOXP2in DFU.

Conclusion: The oxidative stress-related genes BCL2 and FOXP2 could serve as diagnostic markers for DFU. Furthermore, we identified the novel pathogenic mechanism associated with oxidative stress in DFU fibroblasts. This study may offer new insights for the diagnosis and treatment of DFU.

Background: Cancer-associated fibroblasts (CAFs) have been reported to play a significant role in the development and metastasis of various tumors; however, research on their role in promoting prostate cancer (PCa) metastasis under castration conditions remains unclear.

Methods: In this study, we utilized quantitative reverse transcription polymerase chain reaction (qRT-PCR) to detect the expression differences of microRNA-196b-5p (miR-196b-5p) in the exosomes secreted by CAFs before and after castration. We further characterized the transcriptional regulatory landscape through RNA sequencing combined with bioinformatics databases. In vitro and in vivo experiments were conducted to determine the role of miR-196b-5p in promoting tumor migration and metastasis. The dual-luciferase reporter assay, RT-PCR analysis, and Western blot analysis confirmed that miR-196b-5p targets HOXC8 in prostate cancer. Additionally, transwell assays and Western blot analysis were performed to elucidate the role and specific mechanisms of HOXC8 in tumor metastasis.

Results: By analyzing the expression differences of miRNAs in the exosomes secreted by CAFs before and after castration, along with relevant data from databases, we found that miR-196b-5p is highly secreted by CAFs after castration. miR-196b-5p promotes the migration and metastasis of prostate cancer cells. Subsequently, through RNA sequencing analysis and experimental validation, we determined that miR-196b-5p targets HOXC8. This interaction activates the NF-κB pathway, leading to the upregulation of epithelial-mesenchymal transition (EMT)-related protein expression, thereby driving the metastasis of prostate cancer.

Conclusions: Our study elucidates a specific mechanism by which CAF-derived exosomes promote prostate cancer metastasis via miR-196b-5p regulation, contributing to the identification of therapeutic targets for managing tumor metastasis following castration.

Background: Non-small-cell lung cancer (NSCLC) exhibits variable outcomes and remains a leading cause of cancer-related mortality, despite advances in immunotherapy. This study aimed to develop a prognostic model using real-world data (RWD) to stratify patients by survival outcomes and evaluate the benefit of immunotherapy across risk groups.

Methods: A retrospective cohort of 270 patients with NSCLC (2015-2024) treated with chemotherapy alone (54%) or chemoimmunotherapy (46%) was analyzed. Clinical, laboratory (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], monocyte-to-lymphocyte ratio [MLR]), and histopathological data were collected. Multivariate Cox regression identified prognostic factors for overall survival (OS) and validated them via bootstrapping.

Results: The cohort (median age, 65; 78% male) had a median OS of 11.2 months and a median progression-free survival (PFS) of 7.7 months. The final prognostic model incorporated histology (adenocarcinoma vs. large cell/squamous cell carcinoma/rare subtypes: HR = 1.6-2.03), recurrence state (HR = 0.51), and NLR (HR = 1.13). Patients were stratified into low- (median OS = 14.6 months) and high-risk (median OS = 9.6 months; p < 0.001) groups. Immunotherapy significantly increased PFS in low-risk patients (12.2 vs. 7.1 months, p = 0.002) and showed an increasing trend in OS (16.9 vs. 11.3 months, p = 0.12). High-risk patients derived no OS/PFS benefit (p ≥ 0.56).

Conclusion: This RWD-derived prognostic model effectively stratifies NSCLC patients into distinct risk groups. Immunotherapy-chemotherapy provided meaningful PFS improvement in low-risk patients but minimal benefit in high-risk subgroups, underscoring the need for tailored therapeutic strategies.

The prognosis for patients with head and neck cancer (HNC) is usually poor, highlighting the need for new therapeutic strategies. To this end, this study aims to evaluate the antitumor efficacy of a combined treatment with low doses of different molecular targeted drugs, i.e. Y15, a FAK inhibitor, Afatinib (AFA) an ErbB inhibitor and TP-0903, an Axl inhibitor, on HNC. Human cell lines from salivary gland, tongue and pharynx HNC, cultured in 2D and 3D (spheroids) conditions, were used to evaluate the antitumor effects of Y15, AFA and TP-0903, alone or in combination. Cell survival, death and migration were evaluated. Western blotting and immunofluorescence analysis were performed to investigate the expression and activation of proteins involved in signal transduction and epithelial to mesenchymal transition. The combined treatment with low doses of Y15, AFA and TP-0903, was more effective than the individual and dual drug treatments in reducing survival, increasing cell death and reducing migration of HNC cells. The three inhibitors in combination had a synergistic effect in reducing survival of HNC cell lines in both 2D and 3D conditions. Moreover, as compared to the individual inhibitors and their pairwise combinations, the triple drug combination was the only able to simultaneously downregulate Axl, FAK, and N-cadherin while upregulating E-cadherin expression levels. The results reported herein provide compelling preliminary evidence supporting the combined use of Y15, AFA and TP-0903 as a novel therapeutic strategy for HNCs.

Background: Lung adenocarcinoma (LUAD) is one of the common malignant tumors worldwide, and the 5-year survival rate remains unsatisfactory. Reliable prognostic biomarkers are needed to provide references for personalized treatment of patients. Some studies have shown that disulfidptosis-related genes (DRGs) are closely associated with tumorigenesis and development. This study constructed a prognostic risk model to explore the prognostic value of DRGs in LUAD and provide a reference for formulating personalized treatment plans for LUAD patients.

Methods: RNA-seq data of LUAD tissues and adjacent or normal lung tissues were downloaded from TCGA database and GEO database. A risk scores model was constructed through univariate Cox analysis, Lasso analysis, and multivariate Cox analysis. ROC curves and nomogram models were drawn to evaluate the risk model. External validation was performed using LUAD data, data in the LUAD single-cell dataset, and other data in the GEO database. In addition, the immune microenvironment and drug sensitivity of the high-risk and low-risk groups were analyzed. The key gene PPP1R14B in the model was further experimentally verified by in vitro cell experiments.

Results: In this study, a risk model composed of four genes was constructed, and the overall survival (OS) of the low-risk group was higher than that of the high-risk group (P < 0.001). The area under the curve (AUC) of the ROC curves of the training set risk model at 1-, 3-, and 5-year were 0.767, 0.759, and 0.711, respectively. Drug sensitivity analysis showed that there was a statistical significance between the high-risk and low-risk groups of patients for drugs such as gefitinib, afatinib, lapatinib, and paclitaxel (P < 0.001). The results of in vitro cell experiments showed that the proliferation and migration of knockdown PPP1R14B LUAD cells were significantly inhibited, and the number of apoptosis of LUAD cells was significantly increased (P < 0.05).

Conclusion: The risk model constructed based on four DRGs can predict the prognosis of LUAD patients with relative accuracy. There are differences in the immune microenvironment between the high-risk and low-risk groups. Patients in the high-risk group are more sensitive to drugs such as gefitinib, afatinib, lapatinib, and paclitaxel, providing a reference for personalized treatment of LUAD patients. Knockdown PPP1R14B significantly inhibited the proliferation and migration of LUAD cells and promoted the apoptosis of LUAD cells.

Background: Ovarian cancer is a complicated and heterogeneous disease. In this study, we investigated the functional significance of the gene TIMM8B, which is differentially expressed in ovarian cancer to better understand the molecular processes involved in the development of this disease.

Methods: RNA sequencing was performed on ovarian cancer tissues and adjacent noncancerous tissues. The mRNA expression profiles obtained from the sequencing data (transcripts), TCGA-OV, and GSE14407 were subsequently used to identify common DEGs. GO, KEGG pathway, and PPI network analyses of these common DEGs were conducted. The expression of TIMM8B was examined in ovarian cancer tissues and cell lines. The effects of TIMM8B on cellular behaviors, such as proliferation, apoptosis, migration, invasion, and energy metabolism, were assessed by conducting cell-based assays. Additionally, the regulation of these processes by TIMM8B through the mtROS/ASK1/JNK signaling pathway was investigated.

Results: A total of 233 common DEGs were identified in ovarian cancer. The results of the GO analysis revealed enrichment in extracellular matrix organization, collagen-containing extracellular matrix, and transmembrane transporter activity, among others. The results of the KEGG pathway analysis revealed the involvement of DEGs in pathways such as oxidative phosphorylation and glycolysis/gluconeogenesis. TIMM8B was upregulated in ovarian cancer tissues and cell lines. TIMM8B enhanced oxidative phosphorylation, glycolysis, proliferation, migration, and invasion and inhibited apoptosis in ovarian cancer cells. TIMM8B was found to exert its effects through the suppression of mtROS/ASK1/JNK signaling.

Conclusion: TIMM8B may regulate the mtROS/ASK1/JNK pathways, leading to an increase in oxidative phosphorylation and glycolysis. Targeting TIMM8B and its associated signaling pathway may help in the development of new treatment approaches for ovarian cancer.

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by excessive macrophage infiltration and extracellular matrix deposition. The progress of IPF is promoted by M2 macrophages which produce pro-fibrotic factors and induce fibroblast differentiation. SESN3 was upregulated in lung tissues of IPF patients and mice with bleomycin-induced pulmonary fibrosis. However, the role of SESN3 in IPF and its related mechanisms remain largely unknown.

Methods: Here, we used IL-4/13 to induce macrophage M2 polarization in RAW264.7 cells and constructed a mouse model of pulmonary fibrosis by intratracheal injection of bleomycin. Adenoviruses targeting SESN3 were constructed to infect RAW264.7 cells and BLM-induced mice to assess the function of SESN3 in macrophage M2 polarization in the progress of IPF and mRNA-seq and Co-IP-MS analysis were performed to find the downstream factors.

Results: For in vitro experiments, SESN3 knockdown promoted the M2 polarization level, the release of pro-fibrosis factors and the activation of fibroblast, overexpression of SESN3 had an opposite trend. For in vivo experiments, the increased degree of pulmonary fibrosis in BLM mice was relieved after overexpression of SESN3. Meanwhile, overexpression of SESN3 repressed the increased macrophage M2 polarization level induced by BLM. Mechanically, FOSL2 was screened out through mRNA-seq and Co-IP-MS analysis due to its binding affinity with SESN3 and the observed downregulation of its downstream pro-fibrotic factor expression. The expression of FOSL2 in the nucleus was down-regulated after SESN3 overexpression. Under IL-4/13 treatment, the increased levels of macrophage M2 polarization and pro-fibrotic factors induced by SESN3 knockdown was recovered after knocking down FOSL2 in RAW264.7 cells.

Conclusion: In summary, our study suggested that SESN3 regulated the IPF process through inhibiting macrophage M2 polarization by targeting the activity of FOSL2.

Background: Pathological complete response (pCR) to neoadjuvant systemic therapy (NAST) is an established prognostic marker in breast cancer (BC). Multimodal deep learning (DL), integrating diverse data sources (radiology, pathology, omics, clinical), holds promise for improving pCR prediction accuracy. This systematic review synthesizes evidence on multimodal DL for pCR prediction and compares its performance against unimodal DL.

Methods: Following PRISMA, we searched PubMed, Embase, and Web of Science (January 2015-April 2025) for studies applying DL to predict pCR in BC patients receiving NAST, using data from radiology, digital pathology (DP), multi-omics, and/or clinical records, and reporting AUC. Data on study design, DL architectures, and performance (AUC) were extracted. A narrative synthesis was conducted due to heterogeneity.

Results: Fifty-one studies, mostly retrospective (90.2%, median cohort 281), were included. Magnetic resonance imaging and DP were common primary modalities. Multimodal approaches were used in 52.9% of studies, often combining imaging with clinical data. Convolutional neural networks were the dominant architecture (88.2%). Longitudinal imaging improved prediction over baseline-only (median AUC 0.91 vs. 0.82). Overall, the median AUC across studies was 0.88, with 35.3% achieving AUC ≥ 0.90. Multimodal models showed a modest but consistent improvement over unimodal approaches (median AUC 0.88 vs. 0.83). Omics and clinical text were rarely primary DL inputs.

Conclusion: DL models demonstrate promising accuracy for pCR prediction, especially when integrating multiple modalities and longitudinal imaging. However, significant methodological heterogeneity, reliance on retrospective data, and limited external validation hinder clinical translation. Future research should prioritize prospective validation, integration underutilized data (multi-omics, clinical), and explainable AI to advance DL predictors to the clinical setting.

In sepsis, immunosuppression is commonly observed as lipopolysaccharide (LPS) tolerance in macrophages. Leukocyte immunoglobulin-like receptor B2 (LILRB2) is an inhibitory receptor on immune cells that may play a crucial role in the immunosuppressive phenotype of LPS-tolerant macrophages, although its exact function in sepsis remains unclear. In this study, macrophages were exposed to single or sequential LPS doses to induce LPS stimulation or tolerance. Cell viability was assessed using CCK-8 assay, apoptosis, and macrophage polarization were detected by flow cytometry, and pro-inflammatory cytokine levels were measured by RT-qPCR and ELISA. Molecular interactions were explored using Co-IP, ChIP, and dual-luciferase assays, while mRNA and protein expression were assessed by RT-qPCR and Western blotting. The results showed that LILRB2 was upregulated in macrophages following LPS stimulation, with a more significant increase in the LPS-tolerant group. Knocking down LILRB2 reversed the immunosuppressive phenotype of LPS-tolerant macrophages and restored the inhibition of MyD88/NF-κB signaling and p65 nuclear translocation caused by LPS tolerance. Mechanistically, LILRB2 interacted with Toll-like receptor 8 (TLR8) to inhibit the MyD88/NF-κB signaling pathway in LPS-tolerant macrophages. Furthermore, the upregulation of the Spi-1 proto-oncogene (SPI1) enhanced the immunosuppressive phenotype by transcriptionally activating LILRB2. In conclusion, SPI1 upregulation promoted the immunosuppressive phenotype of LPS-tolerant macrophages by activating LILRB2 transcription, which inhibited TLR8-mediated MyD88/NF-κB signaling. This study clarifies the role of LILRB2 and its underlying mechanisms in LPS-tolerant macrophages.