Prognostic and chemotherapeutic response prediction by proliferation essential gene signature: Investigating POLE2 in bladder cancer progression and cisplatin resistance

Abstract

Background: Bladder cancer (BLCA) is the most common genitourinary malignancy. Proliferation essential genes (PEGs) are crucial to the survival of cancer cells. This study aimed to build a PEG signature to predict BLCA prognosis and treatment efficacy. Methods: BLCA PEGs and differentially expressed PEGs were identified using DepMap and TCGA-BLCA datasets, respectively. Based on the prognostic analysis of the differentially expressed PEGs, a PEG model was constructed. Subsequently, we analyzed the relationship between the PEG signature and prognosis of BLCA patients as well as their response to chemotherapy. Finally, we performed random forest analysis to target and functional experiments to validate the most significant PEG which is associated with BLCA progression. CCK-8, invasion, migration, and chemosensitivity assays were performed to assess effects of gene knockdown on BLCA cell proliferation, invasion and migration abilities, and cisplatin chemosensitivity. Results: We screened 10 prognostic PEGs from 201 differentially expressed PEGs and used them to construct a PEG signature model. Patients with high PEG signature score (PEGs-high) exhibited worse OS and lower sensitivity to chemotherapy than those with PEGs-low. We also found significant correlations between the PEG score and previously defined BLCA molecular subtypes. This suggests that the PEG score may effectively predict the molecular subtypes which have distinct clinical outcomes. Random forest analysis revealed that POLE2 (DNA polymerase epsilon subunit 2) was the most significant PEG differentiating BLCA tissue and normal tissue. Bioinformatic analysis and an immunohistochemistry staining assay confirmed that POLE2 was significantly up-regulated in tumor tissues and was associated with poor survival in BLCA patients. Moreover, POLE2 knockdown inhibited the ability of cell clone formation, proliferation, invasion, immigration and IC50 of cisplatin. Conclusion: The PEG signature acts as a potential predictor for prognosis and chemotherapy response in BLCA patients. POLE2 is a key PEG and plays a remarkable role in promoting the malignant progression and cisplatin resistance of BLCA.

Keywords: CRISPR-Cas9; POLE2; bioinformatic analysis; bladder cancer; proliferation; tumor promoter.

Figure 1

Expression and functional enrichment of proliferation essential genes (PEGs) in the BLCA. (A) Heat map and (B) volcano plot showing the differential expression of the 699 PEGs in BLCA patients from the TCGA-BLCA dataset. (C) KEGG enrichment of the 189 significantly up-regulated PEGs in the BLCA.

Figure 2

Identification of proliferation essential gene (PEG) subtypes in the BLCA. (A) PEG subtypes of C1 and C2 clustered by consensus matrix heatmap. (B) PCA analysis displaying a remarkable difference between the C1 and C2 subtypes. (C) Kaplan-Meier analysis, (D) gene set enrichment analysis, and (E) abundance differences of infiltrating immune cell types between the C1 and C2 subtypes. NS: p>0.05; *, p<0.05; **, p<0.01; ***, p<0.001.

Figure 3

Construction of a proliferation essential gene (PEG) signature predicting the prognosis of the BLCA. (A) Poor prognosis associated PEGs identified by univariate Cox regression analysis in the BLCA. (B) The optimal lambda determined by partial likelihood deviation of the least absolute shrinkage and selection operator (LASSO) coefficient profiles. (C) LASSO coefficient distribution of the 10 PEGs used for signature construction. (D) The chromosomal locations of the 10 prognostic PEGs. (E) The associations between the 10 PEGs and the biological pathways involved. (F) The mutation landscape of the 10 PEGs in BLCA patients from the TCGA-BLCA dataset.

Figure 4

Differences in clinicopathological characteristics and survival between BLCA patients with the proliferation essential genes (PEGs)-low and -high subtypes. (A&B) Landscape of genomic alterations in patients with (A) PEGs-low and (B) PEGs-high subtypes. (C) Differences in tumor mutation burden (TMB) between the PEGs-low and PEGs-high subtypes. (D) Difference of the PEG signature score in BLCA patients with low and high grades. (E) Difference of the PEG signature score in BLCA patients with different stages. (F) Risk score and survival status distributions, and mRNA expression of the 10 prognostic PEGs in patients from the TCGA-BLCA dataset. (G-J) The overall survival differences between patients with PEGs-low and PEGs-high subtypes from the TCGA-BLCA, GSE13507, GSE31684 and GSE32894 datasets. (K) Differences in the PEG score between the five different molecular subtypes based on TCGA system . (L)Differences in the PEG score between the six molecular subtypes based on the Consensus system . Luminal papillary: LumP, luminal nonspecified: LumNS, luminal unstable: LumU, stroma-rich, basal/squamous: Ba/Sq, and neuroendocrine-like: NE-like. (M) ROC curves showing the accuracy of the PEG signature in prediction of the TCGA and Consensus molecular subtypes. (N) Hallmark enrichment in the PEGs-low and PEGs-high subtypes. NS: p>0.05; *, p<0.05; **, p<0.01; ***, p<0.001.

Figure 5

Drug sensitivity prediction and chemotherapy response comparisons in the BLCA patients. The correlation between GDSC drug sensitivity and gene expression of the 10 prognostic proliferation essential genes (PEGs). (B) Overall survival difference between the PEGs-low and PEGs-high BLCA patients who received chemotherapy. (C) Comparison of chemotherapy responses in BLCA patients with PEGs-low and PEGs-high subtypes.

Figure 6

POLE2 expression in the BLCA and its relationship with overall survival. (A&B) Random forest displaying the most important proliferation essential gene (PEG) — POLE2 among the 10 prognostic PEGs. (C-G) Comparisons of POLE2 expression between the BLCA and normal tissues from the datasets (C) GSE13507, (D) GSE37851, (E) GSE40335, (F) GSE52519 and (G) GSE65635. (H) Overall survival difference in BLCA patients with high- and low-POLE2 expression from the GSE13507 dataset. (I&J) Representative immunohistochemistry (IHC) images of POLE2 protein in (I) the BLCA tissues and (J) paired normal urothelial tissues. (K) Histogram of the IHC score revealing markedly higher protein expression of POLE2 in BLCA tissues than in normal tissues. (L) An enhanced protein level of POLE2 in the muscle-invasive BLCA compared to the non-muscle invasive BLCA suggested by the IHC assay. (M) Comparison of POLE2 protein levels between the high-grade non-muscle invasive BLCA and the low-grade non-muscle invasive using the IHC assay. (N) Comparison of POLE2 protein levels between the high-grade muscle invasive BLCA and the low-grade muscle invasive using the IHC assay. *, p<0.05; **, p<0.01; ***, p<0.001.

Figure 7

The effects of POLE2 knockdown on the BLCA cell stemness, proliferation, invasion and migration. (A) The relationship between the POLE2 expression and RNA stemness score (RNAss) in the BLCA. (B) POLE2 expression in the T24 cells transfected with POLE2-short hairpin RNAs (POLE2-shRNAs, including POLE2-shRNA1 and POLE2-shRNA2). (C-F) Effects of POLE2 knockdown on (C) T24 cell stemness assessed by the clonogenic assay, (D) T24 cell growth determined by the CCK-8 assay, (E) T24 cell migration distance after 48 hours transfection determined by the scratch assay, and (F) the T24 cell invasion capability. (G) Effects of POLE2 knockdown on cisplatin chemotherapy resistance. **, p<0.01.