Dual prognostic role of 2-oxoglutarate-dependent oxygenases in ten cancer types: implications for cell cycle regulation and cell adhesion maintenance

Abstract

Background: Tumor hypoxia is associated with metastasis and resistance to chemotherapy and radiotherapy. Genes involved in oxygen-sensing are clinically relevant and have significant implications for prognosis. In this study, we examined the pan-cancer prognostic significance of oxygen-sensing genes from the 2-oxoglutarate-dependent oxygenase family.

Methods: A multi-cohort, retrospective study of transcriptional profiles of 20,752 samples of 25 types of cancer was performed to identify pan-cancer prognostic signatures of 2-oxoglutarate-dependent oxygenase gene family (a family of oxygen-dependent enzymes consisting of 61 genes). We defined minimal prognostic gene sets using three independent pancreatic cancer cohorts (n = 681). We identified two signatures, each consisting of 5 genes. The ability of the signatures in predicting survival was tested using Cox regression and receiver operating characteristic (ROC) curve analyses.

Results: Signature 1 (KDM8, KDM6B, P4HTM, ALKBH4, ALKBH7) and signature 2 (KDM3A, P4HA1, ASPH, PLOD1, PLOD2) were associated with good and poor prognosis. Signature 1 was prognostic in 8 cohorts representing 6 cancer types (n = 2627): bladder urothelial carcinoma (P = 0.039), renal papillary cell carcinoma (P = 0.013), liver cancer (P = 0.033 and P = 0.025), lung adenocarcinoma (P = 0.014), pancreatic adenocarcinoma (P < 0.001 and P = 0.040), and uterine corpus endometrial carcinoma (P < 0.001). Signature 2 was prognostic in 12 cohorts representing 9 cancer types (n = 4134): bladder urothelial carcinoma (P = 0.039), cervical squamous cell carcinoma and endocervical adenocarcinoma (P = 0.035), head and neck squamous cell carcinoma (P = 0.038), renal clear cell carcinoma (P = 0.012), renal papillary cell carcinoma (P = 0.002), liver cancer (P < 0.001, P < 0.001), lung adenocarcinoma (P = 0.011), pancreatic adenocarcinoma (P = 0.002, P = 0.018, P < 0.001), and gastric adenocarcinoma (P = 0.004). Multivariate Cox regression confirmed independent clinical relevance of the signatures in these cancers. ROC curve analyses confirmed superior performance of the signatures to current tumor staging benchmarks. KDM8 was a potential tumor suppressor down-regulated in liver and pancreatic cancers and an independent prognostic factor. KDM8 expression was negatively correlated with that of cell cycle regulators. Low KDM8 expression in tumors was associated with loss of cell adhesion phenotype through HNF4A signaling.

Conclusion: Two pan-cancer prognostic signatures of oxygen-sensing genes were identified. These genes can be used for risk stratification in ten diverse cancer types to reveal aggressive tumor subtypes.

Keywords: 2-Oxoglutarate-dependent oxygenase; HNF4A; Hypoxia; KDM8; Oxygen-sensing gene; Pan-cancer; Prognosis.

Fig. 1

Schematic diagram of the study design and development of signatures derived from 61 2-oxoglutarate-dependent oxygenase genes. a Three pancreatic adenocarcinoma cohorts were used to define both signatures 1 and 2. Genes found to be prognostic in univariate Cox regression analysis in 2 out of 3 pancreatic adenocarcinoma cohorts were included in signatures 1 and 2. Signature 1 is a marker of good prognosis and consists of 5 genes (KDM8, KDM6B, P4HTM, ALKBH4, and ALKBH7). Signature 2 is a marker of adverse prognosis and consists of 5 genes (KDM3A, P4HA1, ASPH, PLOD1, and PLOD2). Prognosis of both signatures was further confirmed in 10 cancer types using Kaplan–Meier, Cox regression, and receiver operating characteristic analyses. b Forest plots of prognostic genes found to be significant by univariate Cox regression analysis in pancreatic adenocarcinoma cohorts abbreviated as PAAD, PACA-AU, and PACA-CA. Genes were separated into two groups, good and bad prognostic genes. Hazard ratios were denoted as red circles, and turquoise bars represent 95% confidence interval. Significant Wald test P values are indicated in blue. Y-axes represent gene symbols followed by cohort abbreviations. Signature 1 genes are marked in green. Signature 2 genes are marked in red. Full description of cancers is listed in Additional file 1. 2OG, 2-oxoglutarate; TCGA, The Cancer Genome Atlas; ICGC, International Cancer Genome Consortium

Fig. 2

Kaplan–Meier analyses confirming that gene signatures were associated with patients’ overall survival. a Validation of signature 1 (green panels) across multiple cancer types. Kaplan–Meier plots of overall survival in cancer patients stratified based on signature 1 mean expression scores. Patients were median-dichotomized into high- and low-score groups. Signature 1 is a marker of good prognosis, and hence patients with high signature 1 scores had high survival rates. b Validation of signature 2 (red panels) across multiple cancer types. Kaplan–Meier plots of overall survival in cancer patients stratified based on signature 2 mean expression scores. Patients were median-dichotomized into high- and low-score groups. Signature 2 is a marker of adverse prognosis, and hence patients with high signature 2 scores had low survival rates. P values were calculated from the log-rank test. Pancreas #1 = PAAD cohort; Pancreas #2 = PACA-AU cohort; Pancreas #3 = PACA-CA cohort; Liver #1 = LIHC cohort; Liver #2 = LIRI-JP cohort; and Liver #3 = GSE14520 cohort (Additional file 1)

Fig. 3

Tumor subgroup analyses and evaluation of prognosis predictive performance of gene signatures across different malignant grades. Kaplan–Meier plots show independence of a signature 1 (green panels) and b signature 2 (red panels) over the current TNM staging system in predicting prognosis in different cancer cohorts. Patients were sub-grouped according to TNM stages and further stratified using either signature 1 or signature 2 scores. Both signatures successfully identified high-risk patients in different TNM stages. P values were calculated from the log-rank test. Analysis of specificity and sensitivity of c signature 1 (green panels) and d signature 2 (red panels) in predicting prognosis in different cancer cohorts using receiver operating characteristic (ROC) curves. Plots depict comparison of ROC curves of signature 1 or 2 and clinical TNM staging. Both signatures demonstrate incremental values over the current TNM staging system. AUC: area under the curve. TNM: tumor, node, metastasis staging. Liver #2 = LIRI-JP cohort and Liver #3 = GSE14520 cohort (Additional file 1). Representative plots are depicted in this figure. Additional plots are available in Additional file 4

Fig. 4

Relationship between patients’ risks as determined by gene signatures and common genetic mutations. Patients were median-stratified into low or high-risk groups using a signature 1 (green panels) and b signature 2 (red panels). Since signature 1 is a marker of good prognosis, high-risk patients had a lower mean expression of signature 1 genes. Signature 2 is a marker of poor prognosis, hence high-risk patients had a higher mean expression of signature 2 genes. Kaplan–Meier plots depict combined relation of somatic mutations with signatures 1 or 2 on overall survival in cancer patients. P values were calculated from the log-rank test

Fig. 5

Putative tumor suppressive functions of KDM8 occur through processes related to cell cycle regulation and cell adhesion. a Expression of KDM8 was significantly lower in tumor (T) samples than in non-tumor (NT) samples in liver and pancreatic cancer cohorts. Mann–Whitney–Wilcoxon tests were used to compare T and NT samples. Asterisks represent significant P values: *** < 0.0001. b Expression levels of KDM8 decreased with disease progression and malignant grade in liver and pancreatic cancer cohorts. c Significant negative correlation between patients’ KDM8 expression and tumor hypoxia (hypoxia score) in liver and pancreatic cancer cohorts. d Correlation between KDM8 expression and canonical cell cycle regulators in patients with liver or pancreatic cancers. A majority of genes involved in cell-cycle regulation are negatively correlated with KDM8 expression. Liver #1 = LIHC cohort; Liver #2 = LIRI-JP cohort; and Liver #3 = GSE14520 cohort (Additional file 1). e Kaplan–Meier analysis of patients stratified by KDM8 expression. Patients were median-dichotomized into low- and high-expression groups. Patients with low KDM8 expression had significantly shorter overall survival. This was consistent in patients analyzed as a full cohort or sub-categorized according to TNM stage. Liver #1 = LIHC cohort; Liver #2 = LIRI-JP cohort; and Liver #3 = GSE14520 cohort (Additional file 1). f Patients were median-stratified according to KDM8 expression. Differential expression analysis between KDM8-high- and -low groups in liver cancer cohorts revealed 745 differentially expressed genes (DEGs; fold-change > 2 or < − 2). Enrichment of biological pathways associated with DEGs, which include processes related to cell adhesion, inflammation, metabolism, and signal transduction pathways in cancer. g Enrichment of transcription factors (TFs) from the ENCODE database that are potential regulators of KDM8 DEGs. These TFs were predicted to bind near KDM8 DEGs. h Venn diagram depicts the overlap between HNF4A targets (as identified by ENCODE chromatin-immunoprecipitation sequencing dataset) and genes affected by HNF4A loss-of-function (as identified in HNF4A-null mice). Of the 745 DEGs, 148 were identified as direct HNF4A targets, and 110 genes were affected by HNF4A loss-of-function. In the Venn intersection, 45 genes were both HNF4A targets and altered in HNF4A-null mice. i Scatter plot depicts expression patterns of 110 genes affected by HNF4A loss-of-function. Gene names of the 45 HNF4A targets are annotated on the plot. A majority of KDM8-associated genes were down-regulated in the HNF4A-null mice