Establishment of a circular RNA regulatory stemness-related gene pair signature for predicting prognosis and therapeutic response in colorectal cancer

Abstract

Background: Colorectal cancer (CRC) is a common malignant tumor of the digestive tract with a poor prognosis. Cancer stem cells (CSCs) affect disease outcomes and treatment responses in CRC. We developed a circular RNA (circRNA) regulatory stemness-related gene pair (CRSRGP) signature to predict CRC patient prognosis and treatment effects.

Methods: The circRNA, miRNA, and mRNA expression profiles and clinical information of CRC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CRSRGPs were established based on stemness-related genes in the competing endogenous RNA (ceRNA) network. A CRSRGP signature was generated using the least absolute shrinkage and selection operator (Lasso) and Cox regression analysis of TCGA training set. The prognosis was predicted by generating a nomogram integrating the CRSRGP signature and clinicopathologic features. The model was validated in an external validation set (GSE17536). The antitumor drug sensitivity and immunotherapy responses of CRC patients in the high-risk group (HRG) and low-risk group (LRG) were evaluated by the pRRophetic algorithm and immune checkpoint analysis.

Results: We established an 18-CRSRGP signature to predict the prognosis and treatment responses of CRC patients. In the training and external validation sets, risk scores were used to categorize CRC patients into the HRG and LRG. The Kaplan-Meier analysis showed a poor prognosis for patients in the HRG and that subgroups with different clinical characteristics had significantly different prognoses. A multivariate Cox analysis revealed that the CRSRGP signature was an independent prognostic factor. The nomogram integrating clinical features and the CRSRGP signature efficiently predicted CRC patient prognosis, outperformed the current TNM staging system, and had improved practical clinical value. Anticancer drug sensitivity predictions revealed that the tumors of patients in the HRG were more sensitive to pazopanib, sunitinib, gemcitabine, lapatinib, and cyclopamine. Analysis of immune checkpoint markers demonstrated that patients in the HRG were more likely to benefit from immunotherapy.

Conclusion: An efficient, reliable tool for evaluating CRC patient prognosis and treatment response was established based on the 18-CRSRGP signature and nomogram.

Keywords: circRNA; colorectal cancer; immune; nomogram; stemness-related gene pair signature.

Figure 1

Flowchart of the analysis.

Figure 2

(A) Interaction patterns of the 14 differentially expressed circRNAs in CRC. Red, blue, and green represent microRNA response elements, RNA-binding proteins, and open reading frames, respectively. (B) A stemness-related network in the ceRNA network in CRC (section). Red, pink, and blue represent circRNAs, miRNAs, and mRNAs, respectively. CircRNAs, circular RNAs; CRC, colorectal cancer; ceRNA, competing endogenous RNA.

Figure 3

(A) Time-dependent ROC curve for the CRSRGP signature risk score in the training set. A risk score of 0.071 was used as the cutoff value to divide patients into the HRG and LRG. Risk score of the CRSRGP signature in the two sets. (B) Distribution of patients with different risk scores in the training set and external validation set. The purple and yellow points represent patients in the HRG and patients in the LRG, respectively. (C) Survival status of patients with different risk scores in the training set and external validation set. The purple and yellow points represent patients who were dead and alive, respectively. (D) Heatmap of the prognostic signature scores in the training set and external validation set. The purple and yellow points represent patients in the HRG and patients in the LRG, respectively. (E) Survival analysis of patients in the training set and external validation set. The survival curve shows that patients in the HRG had a poorer outcome than patients in the LRG. ROC, receiver operating characteristic; CRSRGP, circular RNA regulatory stemness-related gene pair; HRG, high-risk group; LRG, low-risk group.

Figure 4

Subgroup analyses of the overall survival of CRC patients in TCGA database. (A) Age ≤ 65 years. (B) Age > 65 years. (C) Male. (D) Female. (E) Stage I+II. (F) Stage III+IV. (G) M0 stage. (H) M1 stage. (I) With colon polyps. (J) Without colon polyps. CRC, colorectal cancer; TCGA, The Cancer Genome Atlas.

Figure 5

Univariate and multivariate Cox analyses of CRC. (A) Univariate analysis. (B) Multivariate analysis. (C) Relationship between the CRSRGP signature and clinical characteristics (***p < 0.001, **p < 0.01, *p < 0.05). CRC, colorectal cancer; CRSRGP, circular RNA regulatory stemness-related gene pair.

Figure 6

Nomogram used to predict the prognosis of CRC patients at 1, 3, and 5 years. (A) Nomogram based on the CRSRGP signature and clinical features. ROC analysis of the ability to predict overall survival based on (B) the nomogram and (C) stage. (D) Calibration curve for the predictive accuracy of the nomogram. CRC, colorectal cancer; CRSRGP, circular RNA regulatory stemness-related gene pair; ROC, receiver operating characteristic.

Figure 7

Functional enrichment analysis of CRSRGPs. (A) CRSRGP ceRNA network. (B) GO enrichment analysis. (C) KEGG enrichment analysis. (D) Gene set enrichment analysis. CRSRGPs, circular RNA regulatory stemness-related gene pairs; ceRNA, competing endogenous RNA; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Figure 8

Correlation between the CRSRGP signature and immunogenicity. The relationship between the CRSRGP signature and (A) the tumor microenvironment, (B) immune cell infiltration, and (C) immune function (***p < 0.001, **p < 0.01, *p < 0.05). CRSRGP, circular RNA regulatory stemness-related gene pair.

Figure 9

CRSRGP signature in CRC treatment. Differences in the estimated IC50 values of (A) gefitinib, (B) pazopanib, (C) sunitinib, (D) gemcitabine, (E) lapatinib, and (F) cyclopamine between the HRG and LRG. (G) Differences in the expression levels of immune checkpoint proteins between the HRG and LRG (***p < 0.001, **p < 0.01, *p < 0.05). CRSRGP, circular RNA regulatory stemness-related gene pair; CRC, colorectal cancer; IC50, half-maximal inhibitory concentration; HRG, high-risk group; LRG, low-risk group.