Metastasis is an important factor contributing to poor prognosis in patients with gastric cancer; yet, the molecular mechanism leading to this cell behavior is still not well understood. In this study, we explored the role of cysteine protease inhibitor SN (Cystatin SN, CST1) in promoting gastric cancer metastasis. We hypothesized that CST1 could regulate gastric cancer progression by regulating GPX4 and ferroptosis. Whole transcriptome sequencing suggested that the expression of CST1 was significantly increased in metastatic cancer, and high CST1 expression was correlated with a worse prognosis. Our data further confirmed that the overexpression of CST1 may significantly promote the migration and invasion of gastric cancer cells in vitro and enhance liver, lung, and peritoneal metastasis of gastric cancer in nude mice. Meanwhile, high expression of CST1 promoted the epithelial-mesenchymal transition (EMT) of gastric cancer cells. Mechanistically, a co-immunoprecipitation experiment combined with mass spectrometry analysis confirmed that CST1 could interact with GPX4, a key protein regulating ferroptosis. CST1 relieves GPX4 ubiquitination modification by recruiting OTUB1, improving GPX4 protein stability and reducing intracellular reactive oxygen species (ROS), thereby inhibiting ferroptosis and, in turn, promoting gastric cancer metastasis. Moreover, clinical data suggested that CST1 is significantly increased in peripheral blood and ascites of gastric cancer patients with metastasis; multivariate Cox regression model analysis showed that CST1 was an independent risk factor for the prognosis of gastric cancer patients. Overall, our results elucidated a critical pathway through which high CST1 expression protects gastric cancer cells from undergoing ferroptosis, thus promoting its progression and metastasis. CST1 may be used as a new oncological marker and potential therapeutic target for gastric cancer metastasis.

Numerous aberrant splicing events are implicated in tumor progression, yet comprehensive reports on splicing factors and events associated with peritoneal metastasis in gastric cancer (GCPM) are lacking. In this study, PTBP3 is found to be significantly overexpressed in peritoneal metastatic tissues of gastric cancer compared to primary tumor tissues, and higher PTBP3 expression correlates with poorer prognosis. Using gastric cancer cells and patient‐derived organoids (PDO), the role of PTBP3 in promoting tumor invasion and proliferation is investigated. Mechanistically, through full‐length transcriptome sequencing, PTBP3 mediates exon 4 skipping in its target gene COX11, leading to shorter transcripts that impair COX11 protein function, reducing mitochondrial copper content and enabling tumor cells to evade cuproptosis. Antisense oligonucleotide (ASO) drugs targeting the short COX11 transcripts effectively degrade mRNA, disrupting copper homeostasis. In PDO‐based xenograft models, exogenous copper ionophores combined with ASO drugs induce excessive copper accumulation in mitochondria, triggering proteotoxic stress and cuproptosis. Overall, PTBP3‐mediated exon 4 skipping in COX11 pre‐mRNA is critical for tumor cell survival and progression in GCPM, offering potential therapeutic strategies targeting copper metabolism.

The peritoneum is the most common metastatic site of advanced gastric cancer and is associated with extremely poor prognosis. Endothelial-specific molecule 1 (ESM1) was found to be significantly associated with gastric cancer peritoneal metastasis (GCPM); however, the biological functions and molecular mechanisms of ESM1 in regulating GCPM remain unclear. Herein, we demonstrated that ESM1 expression was significantly upregulated in gastric cancer tissues and positively correlated with platelet endothelial cell adhesion molecule-1 (CD31) levels. Moreover, clinical validation, in in vitro and in vivo experiments, confirmed that ESM1 promoted gastric cancer angiogenesis, eventually promoting gastric cancer peritoneal metastasis. Mechanistically, ESM1 promoted tumor angiogenesis by binding to c-Met on the vascular endothelial cell membrane. In addition, our results confirmed that ESM1 upregulated VEGFA, HIF1α, and MMP9 expression and induced angiogenesis by activating the MAPK/ERK pathway. In conclusion, our findings identified the role of ESM1 in gastric cancer angiogenesis and GCPM, thus providing insights into the diagnosis and treatment of advanced gastric cancer.

The peritoneum is the most common site of metastasis in advanced gastric cancer (GC), and the mechanisms underlying this process of gastric cancer peritoneal metastasis (GCPM) remain largely elusive. Mesothelial-mesenchymal transition (MMT) plays a crucial role in the progression of GCPM. In our current study, the data confirmed that GC-derived exosomes could significantly promote peritoneal metastasis through an MMT-dependent manner in vivo and in vitro. Using RNA-seq, we successfully identified a key circular RNA (circPTBP3). The expression of exosomal circPTBP3 in the plasma of GCPM patients was significantly upregulated and closely correlated with tumor differentiation, depth of invasion, lymphatic invasion, peritoneal metastasis, and TNM stage. Exosomal circPTBP3 thus serves as a reliable diagnostic and prognostic indicator in GCPM patients. Mechanistically, exosomal circPTBP3 could effectively promote the MMT phenotype of mesothelial cells in vitro. Located in the nucleus, circPTPB3 was found to recruit transcription factor AP-2-beta (TFAP2B) to the serum- and glucocorticoid-inducible kinase 1 (SGK1) promoter sites, thereby initiating its transcription in mesothelial cells. These findings suggest that exosomal circPTPB3 functions as a pivotal mediator in facilitating the interplay between GC cells and mesothelial cells, and it provides a promising diagnostic indicator and therapeutic target for GCPM patients.

Background: Gastric cancer peritoneal metastasis (GCPM) is an important cause of cancer-related deaths worldwide. Long non-coding RNAs (lncRNAs) play a key role in the regulation of GCPM, but the underlying mechanisms have not been elucidated. Methods: High-throughput RNA sequencing (RNA-seq) was performed on four groups of clinical specimens (non-metastatic gastric cancer primary tumor, adjacent normal gastric mucosal tissue, gastric cancer primary tumor with peritoneal metastasis and adjacent normal gastric mucosal tissue). After sequencing, many lncRNAs and mRNAs were screened for further Weighted Gene Co-expression Network Analysis (WGCNA). GCPM-related hub lncRNAs and genes were identified by cytoHubba and validated by Quantitative real-time PCR (qRT-PCR), Receiver operating characteristic curve (ROC) analysis and Kaplan-Meier survival analysis. GO, KEGG and GSEA showed GCPM-related pathways. Correlation analysis revealed the potential relationship between hub lncRNAs and genes. Results: By analyzing lncRNA expression data by WGCNA, we found that blue module was highly correlated with GCPM (r = 0.44, p = 0.04) and six lncRNAs involved in this module (DNM3OS, lnc-MFAP2-53, lnc-PPIAL4C-4, lnc-RFNG-1, lnc-TRIM28-14 and lnc-YARS2-4) were identified. We then performed qRT-PCR validation of gastric cancer specimens and found that the expression of lnc-RFNG-1 and lnc-TRIM28-14 was significantly increased in gastric cancer tissues with peritoneal metastasis. Kaplan-Meier survival analysis showed shorter overall survival time (OS) for gastric cancer patients with high expression of lnc-TRIM28-14. Receiver operating characteristic curve (ROC) analysis showed that lnc-TRIM28-14 could improve the sensitivity and specificity of GCPM diagnosis. In addition, we identified three key mRNAs (CD93, COL3A1 and COL4A1) associated with gastric cancer peritoneal metastasis through WGCNA analysis and clinical specimen validation. Moreover, there was a positive correlation between lnc-TRIM28-14 and the expression of CD93 and COL4A1 in gastric cancer peritoneal metastasis, suggesting a regulatory relationship between them. Subsequent GO, KEGG and GSEA analysis suggested that ECM-receptor interaction and focal adhesion were the hub pathways of GCPM. Conclusion: In summary, lnc-RFNG-1, lnc-TRIM28-14, CD93, COL3A1 and COL4A1 could be novel tumor biomarkers and potential therapeutic targets for GCPM.

Background: Gastric cancer peritoneal metastasis (GCPM) is a lethal condition. Current diagnostic methods for GCPM, such as imaging and serum tumor markers, lack specificity and sensitivity. Research suggests that utilizing gene signatures to predict GCPM shows significant predictive ability. Nonetheless, the predictability of GCPM using ferroptosis-related genes (FRGs) remains unknown. We aim to construct a nomogram based on FRGs for early diagnosis of GCPM. Methods: RNA sequencing and clinical data of patients with gastric cancer (GC) were downloaded from Gene Expression Omnibus (GEO) databases. GCPM was diagnosed through imaging, biopsy and cytology. A GCPM prediction model was developed based on six distinctively expressed FRGs, and the efficiency of the model was assessed through receiver operating characteristic (ROC) curves in both experimental and validation cohorts. Subsequently, 115 clinical samples were examined by immunohistochemistry (IHC) to validate the prediction model’s accuracy. Results: Our analysis included 282 patients, among whom 54 had GCPM while 228 did not. Patients were randomly distributed into experimental and validation groups at a 3:2 ratio. Least absolute shrinkage and selection operator (LASSO) regression identified the coefficients of six FRGs, with a risk score calculated for every patient. Univariate and multivariate logistic analyses revealed that both risk score and pathological stage were significantly associated with GCPM. The area under the curve (AUC) values for the training and validating sets implied good predictability for GCPM (0.827 and 0.767, respectively). Combining the risk score with the tumor node metastasis (TNM) stage substantially improved predictability (AUCs were 0.916 and 0.848 respectively). Lastly, a nomogram incorporating the risk score and TNM stage was constructed, which shows good clinical utility through decision curve analysis (DCA). The IHC results from 115 clinical samples were consistent with these findings. Conclusions: A nomogram model based on FRGs and clinicopathological features was constructed, demonstrating impressive predictive value for GCPM. This enables timely and personalized therapeutic interventions, thereby benefiting gastric cancer patients.