The immunological landscape and silico analysis of key paraptosis regulator LPAR1 in gastric cancer patients.

This study aims to identify key regulators of paraptosis in gastric cancer (GC) and explore their potential in guiding therapeutic strategies, especially in stomach adenocarcinoma (STAD). Genes associated with paraptosis were identified from the references and subjected to Cox regression analysis in the TCGA-STAD cohort. Using machine learning models, LPAR1 consistently ranked highest in feature importance. Multiple sequencing data showed that LPAR1 was significantly overexpressed in cancer-associated fibroblasts (CAFs). LPAR1 expression was significantly higher in normal tissues, and ROC analysis demonstrated its discriminative ability. Copy number alterations and microsatellite instability were significantly associated with LPAR1 expression. High LPAR1 expression correlated with advanced tumor grades and specific cancer immune subtypes, and multivariate analysis confirmed LPAR1 as an independent predictor of poor prognosis. LPAR1 expression was associated with different immune response metrics, including immune effector activation and upregulated chemokine secretion. High LPAR1 expression also correlated with increased sensitivity to compounds, such as BET bromodomain inhibitors I-BET151 and RITA, suggesting LPAR1 as a biomarker for predicting drug activity. FOXP2 showed a strong positive correlation with LPAR1 transcriptional regulation, while increased methylation of LPAR1 promoter regions was negatively correlated with gene expression. Knockdown of LPAR1 affected cell growth in most tumor cell lines, and in vitro experiments demonstrated that LPAR1 influenced extracellular matrix (ECM) contraction and cell viability in the paraptosis of CAFs. These findings suggest that LPAR1 is a critical regulator of paraptosis in GC and a potential biomarker for drug sensitivity and immunotherapy response. This underscores the role of CAFs in mediating tumorigenic effects and suggests that targeting LPAR1 could be a promising strategy for precision medicine in GC.

Transcriptome data-based status of PI3K/AKT/mTOR pathway indicates heterogeneity and immune modulation in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer with limited treatment options. The PI3K/AKT/mTOR pathway is commonly activated in PDAC and plays a critical role in its progression. METHODS AND RESULTS: In this study, the effect of taselisib (a selective PI3K inhibitor) on PDAC cell proliferation was investigated, and a significant decrease in viability was observed with increasing concentrations of taselisib. Differential analysis on samples from the Genotype-Tissue Expression and The Cancer Genome Atlas databases revealed 24 dysregulated PI3K/AKT/mTOR pathway-related genes (PRGs). Unsupervised clustering-based analysis of transcriptome cohorts revealed two clusters with high consistency between RNA-seq and microarray cohorts. Cluster B had higher enrichment of immune cells, particularly CD8+ T cells, and lower levels of immunosuppressive Treg cells. Moreover, we investigated the relationship between drug sensitivity and different clusters and found that cluster A had a better response to PI3K/AKT/mTOR pathway-related inhibitors and chemotherapy. Finally, cluster A exhibited significant activation of PI3K/AKT/mTOR and related oncogenic pathways, contributing to poor prognosis. The study also developed a risk score based on the expression profiles of PRGs and machine learning, which showed a significant increase in overall survival time among patients in the low-risk group. Importantly, the PI3K/AKT/mTOR pathway could be used to better predict individual risk scores, as evidenced by stratified survival analysis. CONCLUSIONS: These findings suggest that targeting the PI3K/AKT/mTOR pathway may have therapeutic potential in PDAC, and distinct pathway states, immune modulation and tumor microenvironments have prognostic value.

Transcriptomic landscape of endothelial cells: Key tumor microenvironment components indicating variable clinical outcomes in pancreatic ductal adenocarcinoma.

Endothelial cells (ECs) present in the tumor microenvironment (TME) exhibit significant diversity that may impact the efficacy of anti-tumor treatments. Thus, our study sought to elucidate the various clusters of ECs present in pancreatic ductal adenocarcinoma (PDAC) and explore their possible interactions and influence on clinical outcomes. We obtained single-cell transcriptome data from 24 PDAC tumors and 11 normal pancreases, minimizing any batch effects between samples. Next, we compared the relative abundance of various ECs clusters across distinct sample types. Pseudo-time analysis was employed to investigate the differentiation origin of ECs. A variety of bioinformatics methods were used to investigate potential communication between ECs and malignant cells, as well as assess metabolic changes, pathway alterations, and immune-related markers expression within distinct EC clusters. Lastly, we investigated the impact of particular ECs clusters on patient prognosis in bulk transcriptome data. Our study identified seven distinct clusters of ECs, denoted as CA4+ ECs, MMP2+ ECs, SPP1+ ECs, MT1F+ ECs, CCL5+ ECs, RGS5+ ECs, and TYROBP+ ECs. Pseudo-time analysis suggested that the loss of CA4+ ECs and MT1F+ ECs may promote malignant progression. Cell communication elucidated that MT1F+ ECs exhibited the strongest outgoing interaction strength, whereas RGS5+ ECs displayed the strongest incoming interaction strength. Furthermore, TYROBP+ ECs exhibited greater metabolic activity, and notably, CCL5+ ECs displayed increased expression of immune-related molecules. Lastly, across cohorts of bulk transcriptome levels, CA4+ ECs, MT1F+ ECs, and RGS5+ ECs consistently demonstrated prognostic indicative effects. PDAC patients exhibit the presence of seven distinct EC clusters, each demonstrating significant metabolic and immunological heterogeneity. Targeted therapeutic approaches directed toward CA4+ ECs and MT1F+ ECs may prove advantageous in addressing challenges associated with PDAC treatment. Additionally, variations in the relative abundance of CA4+ ECs, MT1F+ ECs, and RGS5+ ECs were indicated as predictive of patient prognosis.

The Crosstalk Between Immune Infiltration, Circulating Tumor Cells, and Metastasis in Pancreatic Cancer: Identification of HMGB3 From a Multiple Omics Analysis.

Metastasis is the major cause of death in patients with pancreatic ductal adenocarcinoma (PDAC), and circulating tumor cells (CTCs) play an important role in the development of metastasis. However, few studies have uncovered the metastasis mechanism of PDAC based on CTCs. In this study, the existing bulk RNA-sequencing (bulk RNA-seq) and single-cell sequencing (scRNA-seq) data for CTCs in pancreatic cancer were obtained from the Gene Expression Omnibus (GEO) database. Analysis of tumor-infiltrating immune cells (TIICs) by CIBERSORT showed that the CTCs enriched from the peripheral blood of metastatic PDAC were found to contain a high proportion of T cell regulators (Tregs) and macrophages, while the proportion of dendritic cells (DCs) was lower than that enriched from localized PDAC. Through weighted gene co-expression network analysis (WGCNA) and the result of scRNA-seq, we identified the hub module (265 genes) and 87 marker genes, respectively, which were highly associated with metastasis. The results of functional enrichment analysis indicated that the two gene sets mentioned above are mainly involved in cell adhesion and cytoskeleton and epithelial-mesenchymal transition (EMT). Finally, we found that HMGB3 was the hub gene according to the Venn diagram. The expression of HMGB3 in PDAC was significantly higher than that in normal tissues (protein and mRNA levels). HMGB3 expression was significantly positively correlated with both EMT-related molecules and CTC cluster-related markers. Furthermore, it was also found that HMGB3 mutations were favorably related to tumor-associated immune cells through the TIMER2.0 online tool. We further demonstrated that PDAC patients with higher HMGB3 expression had significantly worse overall survival (OS) in multiple datasets. In summary, our study suggests that HMGB3 is a hub gene associated with EMT in CTCs, the formation of CTC clusters, and infiltration patterns of immune cells favorable for tumor progression and metastasis to distant organs.