TTYH3, a potential prognosis biomarker associated with immune infiltration and immunotherapy response in lung cancer

TTYH3 promotes the malignant progression of oral squamous cell carcinoma SCC-9 cells by regulating tumor-associated macrophage polarization

OBJECTIVE

This study was designed to investigate the biological role and the reaction mechanism of Tweety family member 3 (TTYH3) in oral squamous cell carcinoma (OSCC).

DESIGN

The mRNA and protein expressions of TTYH3 were assessed with RT-qPCR and western blot. After silencing TTYH3 expression, the proliferation of OSCC cells were detected using cell counting kit-8 (CCK-8) assay, 5-ethynyl-2'-deoxyuridine (EdU) staining and colony formation assay. Cell migration and invasion were detected using wound healing and transwell. Gelatin zymography protease assay was used to detect matrix metalloproteinase-2 (MMP2) and matrix metalloproteinase-2 (MMP9) activity and western blot was used to detect the expressions of proteins associated with proliferation and epithelial-mesenchymal transition (EMT). The mRNA expression of TTYH3 in THP-1-derived macrophage was detected using real-time reverse transcriptase-polymerase chain reaction (RT-qPCR). The number of CD86-positive cells and CD206-positive cells was detected using immunofluorescence assay. RT-qPCR was used to detect the expressions of M2 markers arginase 1 (ARG1), chitinase-like 3 (YM1) and mannose receptor C-type 1 (MRC1).

RESULTS

In this study, it was found that TTYH3 expression was upregulated in OSCC cell lines and TTYH3 knockdown could inhibit the proliferation, migration, invasion and EMT process in OSCC via suppressing M2 polarization of tumor-associated macrophages.

CONCLUSIONS

Collectively, TTYH3 facilitated the progression of OSCC through the regulation of tumor-associated macrophages polarization.

Excavation of gene markers associated with pancreatic ductal adenocarcinoma based on interrelationships of gene expression

Pancreatic ductal adenocarcinoma (PDAC) accounts for 95% of all pancreatic cancer cases, posing grave challenges to its diagnosis and treatment. Timely diagnosis is pivotal for improving patient survival, necessitating the discovery of precise biomarkers. An innovative approach was introduced to identify gene markers for precision PDAC detection. The core idea of our method is to discover gene pairs that display consistent opposite relative expression and differential co-expression patterns between PDAC and normal samples. Reversal gene pair analysis and differential partial correlation analysis were performed to determine reversal differential partial correlation (RDC) gene pairs. Using incremental feature selection, the authors refined the selected gene set and constructed a machine-learning model for PDAC recognition. As a result, the approach identified 10 RDC gene pairs. And the model could achieve a remarkable accuracy of 96.1% during cross-validation, surpassing gene expression-based models. The experiment on independent validation data confirmed the model's performance. Enrichment analysis revealed the involvement of these genes in essential biological processes and shed light on their potential roles in PDAC pathogenesis. Overall, the findings highlight the potential of these 10 RDC gene pairs as effective diagnostic markers for early PDAC detection, bringing hope for improving patient prognosis and survival.

Genomic insights and prognostic significance of novel biomarkers in pancreatic ductal adenocarcinoma: A comprehensive analysis

Pancreatic ductal adenocarcinoma (PDAC) is a highly prevalent digestive system malignancy, with a significant impact on public health, especially in the elderly population. The advent of the Human Genome Project has opened new avenues for precision medicine, allowing researchers to explore genetic markers and molecular targets for cancer diagnosis and treatment. Despite significant advances in genomic research, early diagnosis of pancreatic cancer remains elusive due to the lack of highly sensitive and specific markers. Therefore, there is a need for in-depth research to identify more precise and reliable diagnostic markers for pancreatic cancer. In this study, we utilized a combination of public databases from different sources to meticulously screen genes associated with prognosis in pancreatic cancer. We used gene differential analysis, univariate cox regression analysis, least absolute selection and shrinkage operator (LASSO) regression, and multivariate cox regression analysis to identify genes associated with prognosis. Subsequently, we constructed a scoring system, validated its validity using survival analysis and ROC analysis, and further confirmed its reliability by nomogram and decision curve analysis (DCA). We evaluated the diagnostic value of this scoring system for pancreatic cancer prognosis and validated the function of the genes using single cell data analysis. Our analysis identifies six genes, including GABRA3, IL20RB, CDK1, GPR87, TTYH3, and KCNA2, that were strongly associated with PDAC prognosis. Clinical prognostic models based on these genes showed strong predictive power not only in the training set but also in external datasets. Functional enrichment analysis revealed significant differences between high- and low-risk groups mainly in immune-related functions. Additionally, we explored the potential of the risk score as a marker for immunotherapy response and identified key factors within the tumor microenvironment. The single-cell RNA sequencing analysis further enriched our understanding of cell clusters and six hub genes expressions. This comprehensive investigation provides valuable insights into pancreatic PDAC and its intricate immune landscape. The identified genes and their functional significance underscore the importance of continued research into improving diagnosis and treatment strategies for PDAC.

Comparison of the ability of exosomes and ectosomes derived from adipose-derived stromal cells to promote cartilage regeneration in a rat osteochondral defect model

BACKGROUND

Extracellular vesicles (EVs) derived from mesenchymal stromal cells (MSCs) offer promising prospects for stimulating cartilage regeneration. The different formation mechanisms suggest that exosomes and ectosomes possess different biological functions. However, little attention has been paid to the differential effects of EV subsets on cartilage regeneration.

METHODS

Our study compared the effects of the two EVs isolated from adipose-derived MSCs (ASCs) on chondrocytes and bone marrow-derived MSCs (BMSCs) in vitro. Additionally, we loaded the two EVs into type I collagen hydrogels to optimize their application for the treatment of osteochondral defects in vivo.

RESULTS

In vitro experiments demonstrate that ASC-derived exosomes (ASC-Exos) significantly promoted the proliferation and migration of both cells more effectively than ASC-derived ectosomes (ASC-Ectos). Furthermore, ASC-Exos facilitated a stronger differentiation of BMSCs into chondrogenic cells than ASC-Ectos, but both inhibited chondrocyte apoptosis to a similar extent. In the osteochondral defect model of rats, ASC-Exos promoted cartilage regeneration in situ better than ASC-Ectos. At 8 weeks, the hydrogel containing exosomes group (Gel + Exo group) had higher macroscopic and histological scores, a higher value of trabecular bone volume fraction (BV/TV), a lower value of trabecular thickness (Tb.Sp), and a better remodeling of extracellular matrix than the hydrogel containing ectosomes group (Gel + Ecto group). At 4 and 8 weeks, the expression of CD206 and Arginase-1 in the Gel + Exo group was significantly higher than that in the Gel + Ecto group.

CONCLUSION

Our findings indicate that administering ASC-Exos may be a more effective EV strategy for cartilage regeneration than the administration of ASC-Ectos.