Fig. 3: Comprehensive correlation analysis of the risk score with drug resistance, immunity, and stemness.

A, B Using the R packages ‘pRRophetic’ and ‘oncoPredict,’ we estimated the IC50 values for commonly used chemotherapeutic drugs in gastric cancer patients from TCGA database. The upper and lower edges of the box represent the interquartile range, the line within the box indicates the median, and the dots denote outliers. Student’s t test was used to compare the statistical difference between the two groups. C Fisher’s exact test was used to compare the proportions of TIDE scores between high and low risk groups in the TCGA cohort. D Fisher’s exact test was used to compare the proportions of TIDE scores between high and low risk groups in the neoadjuvant therapy cohort from our center. E A Student’s t test was conducted to compare the differences in risk scores between TRG 0/1 and TRG 2/3 groups in the neoadjuvant therapy cohort from our center. F The proportions of TRG grades across different risk groups were compared within the neoadjuvant therapy cohort from our center. G, H The ssGSEA algorithm was used to compare stemness pathway enrichment scores and immune cell infiltration scores between the high and low risk groups. Student’s t test was used to compare the statistical difference between the two groups. I Scatter plots illustrate the correlations among LHPP, PSMA7, TOCF1, PRPF3, the risk score, and mRNAsi. All correlation analyses were performed using Pearson’s correlation coefficient for statistical analysis. J Scatter plots depict the correlation between LHPP expression and immune cell infiltration levels across various algorithms. All correlation analyses were performed using Pearson’s correlation coefficient for statistical analysis. K, L GSVA enrichment analysis demonstrated the pathway enrichment profiles of KEGG and HALLMARK pathways across different levels of LHPP expression. *p < 0.05; **p < 0.01; ***p < 0.001.