Transcriptional landscape and predictive potential of long noncoding RNAs in peritoneal recurrence of gastric cancer
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a novel long noncoding RNA (lncRNA)-based score to predict peritoneal recurrence in gastric cancer (GC) patients. The integrated score effectively forecasts recurrence-free survival, aiding clinical decision-making for GC management.
Area Of Science
- Oncology
- Molecular Biology
- Genomics
Background
- Long noncoding RNAs (lncRNAs) are implicated in gastric cancer (GC) progression and metastasis.
- Predictive biomarkers for peritoneal recurrence in GC patients are limited.
- Tissue-derived lncRNAs offer potential for predicting GC peritoneal recurrence.
Purpose Of The Study
- Investigate the lncRNA transcriptional landscape in GC with peritoneal metastasis (PM).
- Develop an integrated lncRNA-based score for predicting peritoneal recurrence after gastrectomy.
- Evaluate the clinical utility of the lncRNA score for patient stratification.
Main Methods
- Analyzed lncRNA transcriptome in paired peritoneal, tumor, and normal tissues from GC patients.
- Identified key lncRNAs through interactive analysis with TCGA and validation cohorts.
- Constructed and validated a nomogram-based risk score using LASSO and COX regression models.
- Assessed lncRNA roles in GC peritoneal metastasis via in vitro and in vivo assays.
Main Results
- Screened five essential lncRNAs for a peritoneal metastasis (PM) risk score to predict peritoneal recurrence-free survival (pRFS).
- Developed an integrated nomogram score (PM risk score, pT, pN, tumor size) predicting 5-year pRFS with AUC 0.79.
- Demonstrated CASC15 promotes GC cell invasion, migration, and peritoneal metastasis by activating JNK and p38 pathways.
Conclusions
- A novel lncRNA-based integrated score was successfully constructed.
- This score effectively predicts peritoneal recurrence in GC patients.
- The findings provide a valuable tool for clinical management of GC.
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