Comprehensive Analysis of CDC27 Related to Peritoneal Metastasis by Whole Exome Sequencing in Gastric Cancer

Riping Wu, Qiaolian Li, Fan Wu, Chunmei Shi, Qiang Chen, Riping Wu, Qiaolian Li, Fan Wu, Chunmei Shi, Qiang Chen

Abstract

Introduction: The peritoneum is the most common metastatic site of gastric cancer and is associated with a dismal prognosis. However, there is no reliable biomarker for predicting peritoneal metastasis (PM).

Materials and methods: Whole-exome sequencing (WES) was performed on formalin-fixed, paraffin-embedded (FFPE) samples from 63 patients with stage I-III gastric cancer and circulating tumor DNA (ctDNA) samples from 10 patients with stage IV gastric cancer. Differentially expressed genes (DEGs) were identified between the PM and non-PM groups and analyzed by multiple bioinformatics analyses. Univariate and multivariate Cox regression analyses were used to identify the risk factors for PM and a risk score model was developed.

Results: The number of mutant genes and the tumor mutation burden (TMB) in the PM group were higher than those in the non-PM group (p < 0.05). There was a significant positive correlation between the number of mutant genes and the TMB (R2 = 0.9997). The risk of PM was significantly higher in the high TMB group than in the low TMB group (p = 0.045). Forty-nine DEGs were identified as associated with PM in gastric cancer. CDC27 mutations were associated with a higher risk for PM and poor survival. The CDC27 mutations were located in the Apc3 region, the TPR region, and the phosphorylation region, and new mutation sites were not included in the TCGA database. Multivariable Cox regression analysis demonstrated that pathological T stage, poor tumor differentiation, Borrmann type, and CDC27 mutations were independent predictive factors of PM. A risk score model was constructed that demonstrated good performance.

Conclusion: Through WES, we identified 49 DEGs relevant to PM in gastric cancer. CDC27 mutations were independently associated with PM by statistical and bioinformatics analyses. A risk score model was built and was demonstrated to effectively discriminate gastric cancer patients with and without PM.

Keywords: CDC27; gastric cancer; peritoneal metastasis; whole-exome sequencing.

Conflict of interest statement

The authors declare that there are no conflicts of interest in this work.

© 2020 Wu et al.

Figures

Figure 1
Figure 1
(A) Heatmap of mutated genes in stage I–III GC patients by WES. (B) Number of each type of mutation. (C) Number of SNV and Indels in all mutations. (D) Distribution of point mutation types in SNV. E. Number of mutation sites in each sample. (F) Median and interquartile range of each mutation type. (G) Top 30 genes with the most mutation sites. Abbreviations: GC, gastric cancer; WES, whole exome sequencing; SNV, single nucleotide variation.
Figure 2
Figure 2
(A) The number of mutant genes in PM patients was higher than that of non-PM patients. (B) TMB in PM patients was higher than that of non-PM patients. (C) The positive correlation between TMB and the number of mutant genes. (D) Patients with high TMB have a higher risk of PM than low TMB patients. (E) The PM group was associated with a worse OS compared to the non-PM group. (F) The heatmap demonstrated that these 49 genes could discriminate patients with and without PM. Abbreviations: PM, peritoneal metastasis; TMB, tumor mutation burden; OS, overall survival.
Figure 3
Figure 3
(A) Heatmap of all variant genes detected in ctDNA; (B) Bubble map of KEGG analysis in ctDNA samples; (C) Display of CDH1, CTNNB1 and TP53 mutated only in PM patients in the Wnt pathway and downstream abnormal cell function in ctDNA samples. Abbreviations: GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; PM, peritoneal metastasis.
Figure 4
Figure 4
(A) Biological process GO analysis of differentially mutated genes in FFPE samples. (B) Cellular component GO analysis of differentially mutated genes in FFPE samples. (C) KEGG analysis of differentially mutated genes associated with peritoneal metastasis in gastric cancer patients in FFPE samples. (D) Protein-protein interaction network analysis of 49 differential genes (The line between the genes indicates that there is interaction between the two proteins, green and blue are two clusters respectively). (E) CDC27 mutation was associated with a significantly higher risk of postoperative PM. (F) CDC27 mutation was associated with a significantly lower overall survival. (G) CDC27 mutation was associated with a significantly lower disease-free survival. (H) Lollipop plot of CDC27 amino acid mutation in our study. (I) Lollipop plot of CDC27 amino acid mutation in TCGA database of gastric cancer patients. Abbreviations: GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; PM, peritoneal metastasis; FFPE, formalin-fixed, paraffin-embedded; TCGA, The Cancer Genome Atlas.
Figure 5
Figure 5
(A) Tuning parameter selection in the LASSO model. (B) LASSO coefficient profiles of 49 DEGs. (C) Time-dependent ROC analysis of the risk score model. (D) The risk score distribution of gastric patients; (E) The overall survival status of gastric patients; (F) The heatmap of four parameters in the low-risk and high-risk groups. Abbreviations: LASSO, least absolute shrinkage and selection operator; DEGs, differentially expressed genes.

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