Synaptotagmin 11 scaffolds MKK7-JNK signaling process to promote stem-like molecular subtype gastric cancer oncogenesis

Role of SYT11 in human pan-cancer using comprehensive approaches

BACKGROUND

Synaptotagmin 11 (SYT11) plays a pivotal role in neuronal vesicular trafficking and exocytosis. However, no independent prognostic studies have focused on various cancers. In this study, we aimed to summarize the clinical significance and molecular landscape of SYT11 in various tumor types.

METHODS

Using several available public databases, we investigated abnormal SYT11 expression in different tumor types and its potential clinical association with prognosis, methylation profiling, immune infiltration, gene enrichment analysis, and protein-protein interaction analysis, and identified common pathways.

RESULTS

TCGA and Genotype-Tissue Expression (GTEx) showed that SYT11 was widely expressed across tumor and corresponding normal tissues. Survival analysis showed that SYT11 expression correlated with the prognosis of seven cancer types. Additionally, SYT11 mRNA expression was not affected by promoter methylation, but regulated by certain miRNAs and associated with cancer patient prognosis. In vitro experiments further verified a negative correlation between the expression of SYT11 and miR-19a-3p in human colorectal, lung, and renal cancer cell lines. Moreover, aberrant SYT11 expression was significantly associated with immune infiltration. Pathway enrichment analysis revealed that the biological and molecular processes of SYT11 were related to clathrin-mediated endocytosis, Rho GTPase signaling, and cell motility-related functions.

CONCLUSIONS

Our results provide a clear understanding of the role of SYT11 in various cancer types and suggest that SYT11 may be of prognostic and clinical significance.

Enterotoxin-related genes PPFIA4 and SCN3B promote colorectal cancer development and progression

To identify the role of enterotoxin-related genes in colorectal cancer (CRC) development and progression. Upregulated differentially expressed genes shared by three out of five Gene Expression Omnibus (GEO) data sets were included to screen the key enterotoxin-induced oncogenes (EIOGs) according to criteria oncogene definition, enrichment, and protein-protein interaction (PPI) network analysis, followed by prognosis survival, immune infiltration, and protential drugs analyses was performed via integration of RNA-sequencing data and The Cancer Genome Atlas-derived clinical profiles. We screened nine common key EIOGs from at least three GEO data sets. A Cox proportional hazards regression models verified that more alive cases, decreased overall survival, and highest 4-year survival prediction in CRC patients with high-risk score. Protein tyrosine phosphatase receptor type F polypeptide-interacting protein alpha-4 (PPFIA4), STY11, SCN3B, and SPTBN5 were shared in the same PPI network. Immune infiltration results showed that SCN3B and synaptotagmin 11 expression were obviously associated with B cell, macrophage, myeloid dendritic cell, neutrophils, and T cell CD4+ and CD8+ in both colon adenocarcinoma and rectal adenocarcinoma. CHIR-99021, MLN4924, and YK4-279 were identified as the potential drugs for treatment. Finally, upregulated EIOGs genes PPFIA4 and SCN3B were found in colon adenocarcinoma and PPFIA4 and SCN3B were proved to promote cell proliferation and migration in vitro. We demonstrated here that EIOGs promoting a malignancy phenotype was related with poor survival and prognosis in CRC, which might be served as novel therapeutic targets in CRC management.

Constructing a Novel Amino Acid Metabolism Signature: A New Perspective on Pheochromocytoma Diagnosis, Immune Landscape, and Immunotherapy

Pheochromocytoma/paraganglioma (PGPG) is a rare neuroendocrine tumor. Amino acid metabolism is crucial for energy production, redox balance, and metabolic pathways in tumor cell proliferation. This study aimed to build a risk model using amino acid metabolism-related genes, enhancing PGPG diagnosis and treatment decisions. We analyzed RNA-sequencing data from the PCPG cohort in the GEO dataset as our training set and validated our findings using the TCGA dataset and an additional clinical cohort. WGCNA and LASSO were utilized to identify hub genes and develop risk prediction models. The single-sample gene set enrichment analysis, MCPCOUNTER, and ESTIMATE algorithm calculated the relationship between amino acid metabolism and immune cell infiltration in PCPG. The TIDE algorithm predicted the immunotherapy efficacy for PCPG patients. The analysis identified 292 genes with differential expression, which are involved in amino acid metabolism and immune pathways. Six genes (DDC, SYT11, GCLM, PSMB7, TYRO3, AGMAT) were identified as crucial for the risk prediction model. Patients with a high-risk profile demonstrated reduced immune infiltration but potentially higher benefits from immunotherapy. Notably, DDC and SYT11 showed strong diagnostic and prognostic potential. Validation through quantitative Real-Time Polymerase Chain Reaction and immunohistochemistry confirmed their differential expression, underscoring their significance in PCPG diagnosis and in predicting immunotherapy response. This study's integration of amino acid metabolism-related genes into a risk prediction model offers critical clinical insights for PCPG risk stratification, potential immunotherapy responses, drug development, and treatment planning, marking a significant step forward in the management of this complex condition.

Identification of GNG7 as a novel biomarker and potential therapeutic target for gastric cancer via bioinformatic analysis and in vitro experiments

Gastric cancer (GC) is one of the most common malignancies with unfavorable prognoses. The present study aimed to identify novel biomarkers or potential therapeutic targets in GC via bioinformatic analysis and in vitro experiments. The Gene Expression Omnibus and The Cancer Genome Atlas databases were used to screen the differentially expressed genes (DEGs). After protein-protein interaction network construction, both module and prognostic analyses were performed to identify prognosis-related genes in GC. The expression patterns and functions of G protein γ subunit 7 (GNG7) in GC were then visualized in multiple databases and further verified using in vitro experiments. A total of 897 overlapping DEGs were detected and 20 hub genes were identified via systematic analysis. After accessing the prognostic value of the hub genes using the online server Kaplan-Meier plotter, a six-gene prognostic signature was identified, which was also significantly correlated with the process of immune infiltration in GC. The results of open-access database analyses suggested that GNG7 is downregulated in GC; this downregulation was associated with tumor progression. Furthermore, the functional enrichment analysis unveiled that the GNG7-coexpressed genes or gene sets were closely correlated with the proliferation and cell cycle processes of GC cells. Finally, in vitro experiments further confirmed that GNG7 overexpression inhibited GC cell proliferation, colony formation, and cell cycle progression and induced apoptosis. As a tumor suppressor gene, GNG7 suppressed the growth of GC cells via cell cycle blockade and apoptosis induction and thus may be used as a potential biomarker and therapeutic target for GC.

TNF-α Secreted from Macrophages Increases the Expression of Prometastatic Integrin αV in Gastric Cancer

The tumor microenvironment comprising blood vessels, fibroblasts, immune cells, and the extracellular matrix surrounding cancer cells, has recently been targeted for research in cancer therapy. We aimed to investigate the effect of macrophages on the invasive ability of gastric cancer cells, and studied their potential mechanism. In transcriptome analysis, integrin αV was identified as a gene increased in AGS cells cocultured with RAW264.7 cells. AGS cells cocultured with RAW264.7 cells displayed increased adhesion to the extracellular matrix and greater invasiveness compared with AGS cells cultured alone. This increased invasion of AGS cells cocultured with RAW264.7 cells was inhibited by integrin αV knockdown. In addition, the increase in integrin αV expression induced by tumor necrosis factor-α (TNF-α) or by coculture with RAW264.7 cells was inhibited by TNF receptor 1 (TNFR1) knockdown. The increase in integrin αV expression induced by TNF-α was inhibited by both Mitogen-activated protein kinase (MEK) inhibitor and VGLL1 S84 peptide treatment. Finally, transcription of integrin αV was shown to be regulated through the binding of VGLL1 and TEAD4 to the promoter of integrin αV. In conclusion, our study demonstrated that TNFR1-ERK-VGLL1 signaling activated by TNF-α secreted from RAW264.7 cells increased integrin αV expression, thereby increasing the adhesion and invasive ability of gastric cancer cells.

Non-kinase targeting of oncogenic c-Jun N-terminal kinase (JNK) signaling: the future of clinically viable cancer treatments

c-Jun N-terminal Kinases (JNKs) have been identified as key disease drivers in a number of pathophysiological settings and central oncogenic signaling nodes in various cancers. Their roles in driving primary tumor growth, positively regulating cancer stem cell populations, promoting invasion and facilitating metastatic outgrowth have led JNKs to be considered attractive targets for anti-cancer therapies. However, the homeostatic, apoptotic and tumor-suppressive activities of JNK proteins limit the use of direct JNK inhibitors in a clinical setting. In this review, we will provide an overview of the different JNK targeting strategies developed to date, which include various ATP-competitive, non-kinase and substrate-competitive inhibitors. We aim to summarize their distinct mechanisms of action, review some of the insights they have provided regarding JNK-targeting in cancer, and outline the limitations as well as challenges of all strategies that target JNKs directly. Furthermore, we will highlight alternate drug targets within JNK signaling complexes, including recently identified scaffold proteins, and discuss how these findings may open up novel therapeutic options for targeting discrete oncogenic JNK signaling complexes in specific cancer settings.

Impad1 and Syt11 work in an epistatic pathway that regulates EMT-mediated vesicular trafficking to drive lung cancer invasion and metastasis

Lung cancer is a highly aggressive and metastatic disease responsible for approximately 25% of all cancer-related deaths in the United States. Using high-throughput in vitro and in vivo screens, we have previously established Impad1 as a driver of lung cancer invasion and metastasis. Here we elucidate that Impad1 is a direct target of the epithelial microRNAs (miRNAs) miR-200 and miR∼96 and is de-repressed during epithelial-to-mesenchymal transition (EMT); thus, we establish a mode of regulation of the protein. Impad1 modulates Golgi apparatus morphology and vesicular trafficking through its interaction with a trafficking protein, Syt11. These changes in Golgi apparatus dynamics alter the extracellular matrix and the tumor microenvironment (TME) to promote invasion and metastasis. Inhibiting Impad1 or Syt11 disrupts the cancer cell secretome, regulates the TME, and reverses the invasive or metastatic phenotype. This work identifies Impad1 as a regulator of EMT and secretome-mediated changes during lung cancer progression.