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

Upregulation of TTYH3 by lncRNA LUCAT1 through interacting with ALYREF facilitates the metastasis in non-small cell lung cancer

Metastasis is the predominant culprit of cancer-associated mortality in non-small cell lung cancer (NSCLC). Tweety homolog 3 (TTYH3) reportedly functions vitally in the development of diverse cancers, including NSCLC; nevertheless, its role in NSCLC metastasis remains ambiguous. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blot were initially employed to detect TTYH3 expression in NSCLC and normal lung epithelial cells. Subsequently, A549 and NCI-H1650 cells were chosen as NSCLC models in vitro and transfected with short hairpin RNAs (sh-TTYH3, sh-LUCAT1, and sh-ALYREF) or overexpression plasmids (oe-ALYREF and oe-TTYH3). Transwell assays were used for migrative and invasive tests. Epithelial mesenchymal transformation (EMT)-related proteins (E-cadherin, N-cadherin, Vimentin, and Snail) were measured by western blot. A mouse lung metastasis model was built to define the function of TTYH3 in NSCLC metastasis, followed by hematoxylin-eosin staining. RNA pull-down, RNA immunoprecipitation, qRT-PCR, western blot, and actinomycin D assays were adopted to determine the relationships among LUCAT1, ALYREF, and TTYH3. TTYH3 was highly expressed in NSCLC cells relative to normal lung cells. Functionally, TTYH3 knockdown restrained NSCLC migration, invasion, EMT, and metastasis. Mechanistic experiments demonstrated that LUCAT1 bound to ALYREF. After LUCAT1 knockdown, TTYH3 expression and mRNA stability were reduced, which was reversed by ALYREF overexpression. Furthermore, ALYREF overexpression counteracted the inhibitory effects of LUCAT1 knockdown on NSCLC cell migration, invasion, and EMT. TTYH3 overexpression eliminated the suppressive functions of ALYREF downregulation in NSCLC progression. LUCAT1 promotes TTYH3 expression via interacting with ALYREF, thereby facilitating NSCLC migration, invasion, and EMT.

An integrative analysis based on multiple cell death patterns identifies an immunosuppressive subtype and establishes a prognostic signature in lower-grade glioma

BACKGROUND

Cell death modulates the biological behaviors of tumors. However, the comprehensive role of the multiple forms of cell death in lower-grade glioma (LGG) is unknown.

METHODS

We collected the transcriptional data of LGG patients from public repositories to comprehensively examine six cell death patterns (autophagy, apoptosis, cuproptosis, necroptosis, ferroptosis, and pyroptosis) in LGG samples and systematically correlated these patterns with patient survival, underlying biological processes, and drug sensitivity using serial bioinformatics analysis, clinical sample validation and in vitro assays.

RESULTS

We identified and independently validated three reproducible cell death-based clusters associated with distinct clinical outcomes and tumor microenvironment characteristics. The Tumor Immune Dysfunction and Exclusion algorithm was applied for predicting how these three clusters would respond to immune checkpoint blockade (ICB) therapy; we found potential resistance of cluster B to ICB therapy. We also performed drug screening to identify cluster-specific drugs. Furthermore, a scoring system, designated as the CDPM score, was developed to estimate the cell death patterns of patients with LGG; this system could predict both LGG patients' prognosis and immunotherapy efficacy. By performing multiplex immunofluorescence staining, we validated the correlations of GNAL expression with the molecular and clinical features of LGG in an independent LGG cohort. Finally, in vitro assays showed that GNAL promoted apoptosis and inhibited the proliferation of LGG cells.

CONCLUSION

The new cell death-based subtype system indicates several features of LGG biology and reveals novel insights into the use of precision medicine for treating LGG. The CDPM score could be used to predict the immunotherapy response and prognosis of LGG patients; moreover, it could indicate a novel direction for improving LGG management.

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.

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.

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.

Circulating extracellular vesicles containing S100A9 reflect histopathology, immunophenotype and therapeutic responses of liver metastasis in colorectal cancer patients

BACKGROUND

Metastasis is the principal cause of cancer treatment failure and an area of dire diagnostic needs. Colorectal cancer metastases to the liver (CRCLMs) are predominantly classified into desmoplastic and replacement based on their histological growth patterns (HGPs). Desmoplastic responds well to current treatments, while replacement HGP has a poor prognosis with low overall survival rates.

METHODS

We hypothesised that complex cellular response underlying HGPs may be reflected in the proteome of circulating extracellular vesicles (EVs). EV proteomics data was generated through LC-MS/MS and analysed with Maxquant and Perseus. To validate the S100A9 signature, ELISA was performed, and IHC and IF were conducted on tissue for marker detection and colocalization study.

RESULTS

Plasma EV proteome signature distinguished desmoplastic from the replacement in patients with 22 differentially expressed proteins, including immune related markers. Unsupervised PCA analysis revealed clear separation of the two lesions. The marker with the highest confidence level to stratify the two HGPs was S100A9, which was traced in CRCLM lesions and found to colocalize with macrophages and neutrophils. EV-associated S100A9 in plasma may reflect the innate immunity status of metastatic lesions and their differential therapeutic responses.

CONCLUSION

Plasma EV-derived S100A9 could be useful in personalising therapy in patients with CRCLM.