Bisphenol A interacts with DLGAP5 and regulates IL-6/JAK2/STAT3 signaling pathway to promote tumorigenesis and progression of osteosarcoma

Lipocalin-2 promotes NSCLC progression by activating the JAK2/STAT3 signaling pathway

BACKGROUND

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Lipocalin-2 (LCN2), a pleiotropic protein implicated in tumorigenesis and cancer progression, has been associated with multiple malignancies. However, its precise role in NSCLC and the underlying molecular mechanisms remain incompletely understood. This study aimed to elucidate the function of LCN2 in NSCLC, with a particular focus on its involvement in the Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling pathway.

METHODS

LCN2 expression in NSCLC tissues was comprehensively analyzed using bioinformatics tools, including the Universal Analysis of Cancer (UALCAN), The Cancer Genome Atlas (TCGA), UCSC-XENA, and Gene Expression Omnibus (GEO) databases. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were employed to assess LCN2 expression levels in NSCLC cell lines. The functional impact of LCN2 on NSCLC cells, including proliferation, apoptosis, and metastasis, were assessed through a series of in vitro assays, such as Cell Counting Kit-8 (CCK-8), EdU, wound healing, and transwell migration and invasion assays. An in vivo xenograft model was established to investigate the effects of LCN2 on tumor growth and metastasis. Additionally, the involvement of the JAK2/STAT3 signaling pathway was examined using western blotting and pharmacological inhibition with AG490.

RESULTS

LCN2 was significantly upregulated in NSCLC tissues and cell lines, and its elevated expression correlated with poor prognosis. Functional analyses demonstrated that LCN2 knockdown suppressed NSCLC cell proliferation, migration, and invasion while promoting apoptosis. Mechanistically, LCN2 was found to activate the JAK2/STAT3 pathway by interacting with SOCS3, and pharmacological blockade of this pathway effectively abrogated the oncogenic effects of LCN2 overexpression.

CONCLUSIONS

This study identifies LCN2 as a potential oncogene in NSCLC, driving tumor progression through activation of the JAK2/STAT3 signaling pathway. These findings suggest that targeting LCN2 or its downstream signaling components may represent a promising therapeutic strategy for NSCLC.

AhR and STAT3: A Dangerous Duo in Chemical Carcinogenesis

Human chemical carcinogenesis is a multistage process where chemicals or their metabolites cause irreversible changes in normal cell physiology, eventually leading to uncontrolled proliferation, transforming a normal cell into a cancerous one. Signal transducer and activator of transcription 3 (STAT3) is a cytoplasmic transcription factor that regulates cell proliferation, differentiation, apoptosis, angiogenesis, inflammation, and immune responses. Its aberrant activation triggers tumor progression by promoting the expression of oncogenic genes; thus, STAT3 is classified as an oncoprotein. The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that responds to a wide variety of chemicals, including carcinogens like dioxins, inducing genes associated with detoxification, proliferation, and immune regulation. Recent reports show that AhR plays a critical role in cancer development and maintenance. AhR may interact with signaling pathways, like the STAT3 pathway, which mediates the carcinogenic effects of several pollutants. Various chemical agents, such as industrial waste and hydrocarbon compounds, can alter the expression or signaling activity of AhR and STAT3 pathways, leading to different types of cancers. Understanding the complex STAT3-AhR network in the regulation of chemical carcinogenesis could open new avenues for cancer prevention or treatment, particularly in personalized medicine, aiming to improve life expectancy and achieving a complete cure.

Fatty acid metabolism-derived prognostic model for lung adenocarcinoma: unraveling the link to survival and immune response

Background

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors globally, characterized by poor prognosis and high mortality. Abnormal fatty acid metabolism plays a crucial role in LUAD progression. This study aims to develop a prognostic model based on fatty acid metabolism to improve the overall prognosis of LUAD.

Materials and methods

Bioinformatics analyses were performed using TCGA and GEO datasets, supplemented by cell experiments. A total of 309 fatty acid metabolism-related genes were identified from MsigDB. Differentially expressed genes were analyzed using the 'limma' R package. A prognostic model was constructed using LASSO regression and validated with survival analyses via the 'survminer', 'survival', and 'pROC' R packages. The analysis included somatic mutations, tumor mutation burden, clinical correlations, stemness analysis, cytokine correlations, and enrichment analysis. Protein interaction networks were constructed using STRING and Cytoscape, while immune cell infiltration and immunotherapy responses were evaluated with the 'oncoPredict' R package. Results were validated through cell experiments and immunohistochemistry staining of lung tissues.

Results

We identified 125 differentially expressed genes related to fatty acid metabolism, with 33 genes significantly associated with prognosis. Patients in the high-risk group had poorer overall survival and progression-free survival, and the risk score correlated with gender, N stage, clinical stage, and T stage. The risk score was also associated with cancer stem cells, with a significantly higher mRNAsi index in the high-risk group. Additionally, the risk score correlated with various cytokine expressions and showed significant enrichment in cell cycle pathways. Key genes like CDK1 were highly expressed in LUAD cell lines and validated in clinical samples. The low-risk group showed better responses to immune checkpoint inhibitors, with the risk score correlating with immune checkpoint gene expression.

Conclusion

This study successfully established a novel prognostic model based on fatty acid metabolism, which provides valuable insights for the treatment of LUAD.

Unveiling the impact of estrogen exposure on ovarian cancer: a comprehensive risk model and immune landscape analysis

This study examines the impact of estrogenic compounds like bisphenol A (BPA), estradiol (E2), and zearalenone (ZEA) on human ovarian cancer, focusing on constructing a risk model, conducting gene set variation analysis (GSVA), and evaluating immune infiltration. Differential gene expression analysis identified 980 shared differentially expressed genes (DEGs) in human ovarian cells exposed to BPA, E2, and ZEA, indicating disruptions in ribosome biogenesis and RNA processing. Using the cancer genome atlas ovarian cancer (TCGA-OV) dataset, a least absolute shrinkage and selection operator (LASSO)-based risk model was developed incorporating prognostic genes 4-hydroxyphenylpyruvate dioxygenase like (HPDL), Thy-1 cell surface antigen (THY1), and peptidase inhibitor 3 (PI3). This model effectively stratified ovarian cancer patients into high-risk and low-risk categories, showing significant differences in overall survival, disease-specific survival, and progression-free survival. GSVA analysis linked HPDL expression to pathways related to the cell cycle, DNA damage, and repair, while THY1 and PI3 were associated with apoptosis, hypoxia, and proliferation pathways. Immune infiltration analysis revealed distinct immune cell profiles for high and low-expression groups of HPDL, THY1, and PI3, indicating their influence on the tumor microenvironment. The findings demonstrate that estrogenic compounds significantly alter gene expression and oncogenic pathways in ovarian cancer. The risk model integrating HPDL, THY1, and PI3 offers a strong prognostic tool, with GSVA and immune infiltration analyses providing insights into the interplay between these genes and the tumor microenvironment, suggesting potential targets for personalized therapies.

Quercetin exerts anti-tumor immune mechanism by regulating IL-6/JAK2/STAT3 signaling pathway to deplete Treg cells

Breast cancer is still the leading cause of death among women worldwide. Due to the lack of effective drug targets, triple-negative breast cancer has a worse prognosis and higher mortality compared with other types of breast cancer, and chemotherapy is still the main treatment for triple-negative breast cancer at present. Quercetin (QUE) is a flavonoid compound found in a variety of fruits and vegetables. The mechanism of QUE has been extensively studied, such as prostate cancer, colon cancer, ovarian cancer, etc. However, the anti-tumor immune mechanism of QUE in triple-negative breast cancer remains unclear. Therefore, we assessed the anti-tumor immune effects of QUE on triple-negative breast cancer using both 4T1 cells and a xenograft mouse model of 4T1 cells. In vitro, we examined the inhibitory effects of QUE on 4T1 cells and its molecular mechanisms through MTT, Transwell, ELISA, and Western blotting. In vivo, by establishing a xenograft mouse model, we utilized flow cytometry, immunohistochemistry, ELISA, and Western blotting to evaluate the anti-tumor immune effects of QUE on triple-negative breast cancer. The results indicate that QUE inhibits the proliferation, migration, and invasion of 4T1 cells, concurrently significantly suppressing the IL-6/JAK2/STAT3 signaling pathway. Furthermore, it depletes Treg cell content in 4T1 xenograft mice, thereby improving the tumor immune microenvironment and promoting the cytotoxicity of relevant tumor immune cells. These findings suggest that QUE may serve as a potential adjuvant for immune therapy in triple-negative breast cancer.

HOXB5 promotes the progression and metastasis of osteosarcoma cells by activating the JAK2/STAT3 signalling pathway

Objective

To investigate the involvement of the homeobox gene B5 (HOXB5) in the progression and metastasis of osteosarcoma.

Methods

The expression of HOXB5 in human osteosarcoma tissues and its correlation with clinical indicators were investigated using bioinformatics analysis and immunohistochemical labelling. Human osteosarcoma cells (HOS, MG63, U2OS, and Saos-2) and normal human osteoblasts (hFOB1.19) were cultivated. The expression of HOXB5 in these cells was detected using western blotting (WB) and RT‒PCR. Two cell lines exhibiting elevated HOXB5 expression were chosen and divided into three groups: the blank group (mock), control group (control) and transfection group (shHOXB5). The transfection group was infected with lentivirus expressing shRNAs targeting HOXB5. The transfection efficiency was detected by WB. Cell proliferation suppression was measured by CCK-8 and 5-ethynyl-2'-deoxyuridine (EdU) assays; the percentage of apoptotic cells was determined by flow cytometry; and cell migration and invasion were detected via the Transwell chamber test. WB was utilized to determine the protein expression of genes linked to metastasis (MMP2, MMP9), apoptosis (Bax, Bcl-2), and the JAK2/STAT3 pathway (JAK2, p-JAK2, STAT3, p-STAT3).

Results

In osteosarcoma tissues, HOXB5 expression was elevated and strongly correlated with distant metastasis. Silencing HOXB5 reduced the proliferation, migration and invasion of osteosarcoma cells; prevented the progression and metastasis of tumours in tumour-bearing nude mice; and reduced the activation of key proteins in the JAK2/STAT3 signalling pathway.

Conclusion

Through the JAK2/STAT3 signalling pathway, HOXB5 plays a crucial role in the malignant progression of osteosarcoma and is a promising target for osteosarcoma treatment.

DLGAP5 promotes lung adenocarcinoma growth via upregulating PLK1 and serves as a therapeutic target

BACKGROUND

Human discs large-associated protein 5 (DLGAP5) is reported to play a pivotal role in regulating the cell cycle and implicate in tumorigenesis and progression of various cancers. Our current research endeavored to explore the prognostic value, immune implication, biological function and targeting strategy of DLGAP5 in LUAD through approaches including bioinformatics, network pharmacology analysis and experimental study.

METHODS

Multiple databases, including TCGA, GEO, CPTAC and Human Protein Atlas, were utilized to explore the expression and clinical significance of DLGAP5 in LUAD. The genetic alterations of DLGAP5 were assessed through cBioPortal and COSMIC databases. The relationship between DLGAP5 expression and genetic abnormalities of driver genes in LUAD was analyzed through TIMER2.0 database. CancerSEA database was utilized to explore the function of DLGAP5 in 14 different states in LUAD at single-cell resolution. GDSC database was utilized to analyze the impact of DLGAP5 on IC50 of frequently-used anti-LUAD drugs. CIBERSORT method and TIMER2.0 database was utilized to explore the relationship between DLGAP5 and tumor immune infiltration. Network pharmacology was applied to screen potential DLGAP5 inhibitor. In vitro and in vivo experiments were utilized to evaluate biological function and downstream targets of DLGAP5, and the effect of screened DLGAP5 inhibitor on LUAD growth.

RESULTS

High DLGAP5 expression was commonly observed in LUAD and associated with mutation of major driver genes, poor prognosis, high IC50 values of frequently-used anti-LUAD drugs, increasing immune infiltration and elevated immune checkpoint blockade-related genes in LUAD. PLK1 was revealed as a potential DLGAP5 downstream target in LUAD. DLGAP5 overexpression or knockdown significantly promoted or inhibited LUAD cell proliferation and PLK1 expression. PLK1 overexpression well rescued DLGAP5 knockdown-induced cell proliferation inhibition, or vice versa. Furthermore, by virtual screening of an investigational drug library from the DrugBank database, AT9283 was screened and identified as a novel DLGAP5 inhibitor. AT9283 effectively suppressed growth of LUAD cells both in vitro and in vivo. DLGAP5 overexpression significantly reversed AT9283-induced proliferation inhibition. Moreover, AT9283 significantly suppressed DLGAP5 and PLK1 expression, while DLGAP5 overexpression significantly reversed AT9283-induced PLK1 suppression.

CONCLUSION

Our research has demonstrated that DLGAP5 is upregulated in LUAD and exhibits a strong correlation with unfavorable prognosis. Furthermore, DLGAP5 assumes a significant function in the regulation of tumor immunity and treatment outcome of immune checkpoint inhibitors. Of note, we found that DLGAP5 promotes cell proliferation of LUAD via upregulating PLK1. Targeting DLGAP5 by AT9283, our newly identified DLGAP5 inhibitor, suppresses LUAD growth. DLGAP5 may become a promising prognostic biomarker and therapeutic target for patients with LUAD.

Farnesoid X receptor promotes non-small cell lung cancer metastasis by activating Jak2/STAT3 signaling via transactivation of IL-6ST and IL-6 genes

Metastasis accounts for the majority of cases of cancer recurrence and death in patients with advanced non-small cell lung cancer (NSCLC). Farnesoid X Receptor (FXR) is a bile acid nuclear receptor that was recently found to be upregulated in NSCLC tissues. However, whether and how FXR regulates NSCLC metastasis remains unclear. In the present study, it was found that FXR promoted the migration, invasion, and angiogenic ability of NSCLC cells in vitro, and increased NSCLC metastasis in a mouse model in vivo. Mechanistic investigation demonstrated that FXR specifically bound to the promoters of IL-6ST and IL-6 genes to upregulate their transcription, thereby leading to activation of the Jak2/STAT3 signaling pathway, which facilitated tumor migration, invasion, and angiogenesis in NSCLC. Notably, Z-guggulsterone, a natural FXR inhibitor, significantly reduced FXRhigh NSCLC metastasis, and decreased the expression of FXR, IL-6, IL-6ST, and p-STAT3 in the mouse model. Clinical analysis verified that FXR was positively correlated with IL-6, IL-6ST and p-STAT3 expression in NSCLC patients, and was indicative of a poor prognosis. Collectively, these results highlight a novel FXR-induced IL-6/IL-6ST/Jak2/STAT3 axis in NSCLC metastasis, and a promising therapeutic means for treating FXRhigh metastatic NSCLC.

Maternal Exposure to Endocrine-Disrupting Chemicals: Analysis of Their Impact on Infant Gut Microbiota Composition

Endocrine disruptors (EDCs) are chemicals that interfere with the endocrine system. EDC exposure may contribute to the development of obesity, type 2 diabetes, and cardiovascular diseases by impacting the composition of an infant's gut microbiota during the first 1000 days of life. To explore the relationship between maternal urinary levels of Bisphenol-A and phthalates (UHPLC-MS/MS), and the composition of the infant gut microbiota (16S rDNA) at age 12 months (T3) and, retrospectively, at birth (T0), 1 month (T1), and 6 months (T2), stool samples from 20 infants breastfed at least once a day were analyzed. Metataxonomic bacteria relative abundances were correlated with EDC values. Based on median Bisphenol-A levels, infants were assigned to the over-exposed group (O, n = 8) and the low-exposed group (B, n = 12). The B-group exhibited higher gut colonization of the Ruminococcus torques group genus and the O-group showed higher abundances of Erysipelatoclostridium and Bifidobacterium breve. Additionally, infants were stratified as high-risk (HR, n = 12) or low-risk (LR, n = 8) exposure to phthalates, based on the presence of at least three phthalates with concentrations exceeding the cohort median values; no differences were observed in gut microbiota composition. A retrospective analysis of gut microbiota (T0-T2) revealed a disparity in β-diversity between the O-group and the B-group. Considering T0-T3, the Linear Discriminant Effect Size indicated differences in certain microbes between the O-group vs. the B-group and the HR-group vs. the LR-group. Our findings support the potential role of microbial communities as biomarkers for high EDC exposure levels. Nevertheless, further investigations are required to deeply investigate this issue.

DLGAP5 Regulates the Proliferation, Migration, Invasion, and Cell Cycle of Breast Cancer Cells via the JAK2/STAT3 Signaling Axis

The aim of this study was to discover new biomarkers to detect breast cancer (BC), which is an aggressive cancer with a high mortality rate. In this study, bioinformatic analyses (differential analysis, weighted gene co-expression network analysis, and machine learning) were performed to identify potential candidate genes for BC to study their molecular mechanisms. Furthermore, Quantitative Real-time PCR and immunohistochemistry assays were used to examine the protein and mRNA expression levels of a particular candidate gene (DLGAP5). And the effects of DLGAP5 on cell proliferation, migration, invasion, and cell cycle were further assessed using the Cell Counting Kit-8 assay, colony formation, Transwell, wound healing, and flow cytometry assays. Moreover, the changes in the JAK2/STAT3 signaling-pathway-related proteins were detected by Western Blot. A total of 44 overlapping genes were obtained by differential analysis and weighted gene co-expression network analysis, of which 25 genes were found in the most tightly connected cluster. Finally, NEK2, CKS2, UHRF1, DLGAP5, and FAM83D were considered as potential biomarkers of BC. Moreover, DLGAP5 was highly expressed in BC. The down-regulation of DLGAP5 may inhibit the proliferation, migration, invasion, and cell cycle of BC cells, and the opposite was true for DLGAP5 overexpression. Correspondingly, silencing or overexpression of the DLGAP5 gene inhibited or activated the JAK2/STAT3 signaling pathway, respectively. DLGAP5, as a potential biomarker of BC, may impact the cell proliferation, migration, invasion, cell cycle, and BC development by modulating the JAK2/STAT3 signaling pathway.

Cytokines as Prognostic Biomarkers in Osteosarcoma Patients: A Systematic Review and Meta-analysis

Osteosarcoma is the most prevalent type of primary bone malignancy in children and adolescents. The effect of cytokines on osteosarcoma prognosis has been studied and reported. This meta-analysis aimed to assess the prognostic value of cytokines as osteosarcoma biomarkers. Databases including PubMed, Embase, and Cochrane Library were searched for studies on the prognostic value of cytokines in osteosarcoma. From the eligible studies, data on overall survival (OS), disease-free survival, and metastasis-free survival (MFS) were extracted. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. A total of 11 studies involving 755 patients were included in this analysis. High macrophage migration inhibitory factor (MIF) expression in tumors was significantly associated with shortened OS (HR = 2.01, 95% CI: 1.18-3.42, P = 0.010) and MFS (HR = 2.51, 95% CI: 1.47-4.01, P = 0.001). Elevated T cell immunoglobulin and mucin domain-3 (Tim-3) levels in serum correlated with increased risk of disease progression in patients with osteosarcoma (HR = 3.14, 95% CI: 2.88-3.03, P < 0.001). However, interleukin 6 (IL-6) and tumor necrosis factor were not substantially associated with osteosarcoma prognosis. Owing to a paucity of research, other relevant cytokines [interferon-α/β receptor, tissue factor, macrophage inhibitory cytokine 1 (MIC-1), and IL-23] could not be combined. In conclusion, MIF levels in tumors and Tim-3 levels in serum can be potential biomarkers of poor prognosis in osteosarcoma. To confirm this finding and implement these biomarkers into clinical applications, additional large-scale, high-quality studies are needed.