Differentially Expressed Genes Associated With Prognosis in Locally Advanced Lymph Node-Negative Prostate Cancer

Abstract

Older age is one of the main risk factors for cancer development. The incidence of prostate cancer, as a multifactorial disease, also depends upon demographic factors, race, and genetic predisposition. Prostate cancer most frequently occurs in men over 60 years of age, indicating a clear association between older age and disease onset. Carcinogenesis is followed by the deregulation of many genes, and some of these changes could serve as biomarkers for diagnosis, prognosis, prediction of drug therapy efficacy, as well as possible therapeutic targets. We have performed a bioinformatic analysis of a The Cancer Genome Atlas (TCGA) data and RNA-Seq profiling of a Russian patient cohort to reveal prognostic markers of locally advanced lymph node-negative prostate cancer (lymph node-negative LAPC). We also aimed to identify markers of the most common molecular subtype of prostate cancer carrying a fusion transcript TMPRSS2-ERG. We have found several genes that were differently expressed between the favorable and unfavorable prognosis groups and involved in the enriched KEGG pathways based on the TCGA (B4GALNT4, PTK6, and CHAT) and Russian patient cohort data (AKR1C1 and AKR1C3). Additionally, we revealed such genes for the TMPRSS2-ERG prostate cancer molecular subtype (B4GALNT4, ASRGL1, MYBPC1, RGS11, SLC6A14, GALNT13, and ST6GALNAC1). Obtained results contribute to a better understanding of the molecular mechanisms behind prostate cancer progression and could be used for further development of the LAPC prognosis marker panel.

Keywords: RNA-Seq; TCGA; TMPRSS2-ERG; locally advanced prostate cancer; prognostic markers.

Figure 1

Heatmap demonstrating log relative expression level of top differentially expressed genes between the groups of adverse and favorable prognosis (TCGA data). Cell colors (blue-white-orange gradient) correspond the binary logarithm of the ratio of the expression level in a current sample to the average level across all the samples (per each gene). Blue - expression level is below the average, orange - above the average. Spearman_r—Spearman’s rank correlation coefficient. -Log10(p) is the negative logarithm of DESeq’s p-value. LogCPM—average binary logarithm of read counts per million (CPM). LogFC—binary logarithm of expression level fold change (samples with adverse prognosis compared to favorable prognosis).

Figure 2

Dotplot showing the results of KEGG pathways enrichment analyses performed for top-40, 80, 250, 500, and 1,000 differentially expressed genes (either overexpressed or downregulated) between the groups of adverse and favorable prognosis (TCGA data). All the genes have passed the following thresholds: DESeq p-value < 0.01, Mann–Whitney p-value < 0.05, average expression-level fold change > 25%. Dot size indicates k/n ratio (“gene ratio”), where k is the number of genes participating in the current KEGG pathway (within top-40, top-80, or other top lists), and n is the number of genes (also within top-40, top-80, or other top lists) annotated as participants of any KEGG pathway (these numbers are provided in the brackets in the bottom of the figure). Dot color indicates the enrichment test FDR (Fisher’s exact test).

Figure 3

Potential markers of unfavorable prognosis in lymph node-negative locally advanced prostate cancer (LAPC) involved in the enriched KEGG pathways (TCGA data). LogFC—trimmed binary logarithm of average expression level fold change (between the groups of favorable and unfavorable prognosis); LogCPM—binary logarithm of read counts per million (CPM).

Figure 4

Heatmap demonstrating log relative expression level of top differentially expressed genes between the groups of adverse and favorable prognosis (TCGA data; TMPRSS2-ERG-positive samples). Cell colors (blue-white-orange gradient) correspond the binary logarithm of the ratio of the expression level in a current sample to the average level across all the samples (per each gene). Blue - expression level is below the average, orange - above the average. Spearman_r—Spearman’s rank correlation coefficient. -Log10(p) is the negative logarithm of DESeq’s p-value. LogCPM—average binary logarithm of read counts per million (CPM). LogFC—binary logarithm of expression-level fold change (sample with adverse prognosis compared to favorable prognosis).

Figure 5

Dotplot showing the results of KEGG pathways enrichment analyses performed for top-40, 80, 250, 500, and 1,000 differentially expressed genes (either overexpressed or downregulated) between the groups of adverse and favorable prognosis (TCGA data; TMPRSS2-ERG-positive samples). All the genes have passed the following thresholds: DESeq p-value < 0.01, Mann–Whitney p-value < 0.05, average expression-level fold change > 25%. Dot size indicates k/n ratio (“gene ratio”), where k is the number of genes participating in the current KEGG pathway (within top-40, top-80, or other top lists), and n is the number of genes (also within top-40, top-80, or other top lists) annotated as participants of any KEGG pathway (these numbers are provided in the brackets in the bottom of the figure). Dot color indicates the enrichment test FDR (Fisher’s exact test).

Figure 6

Potential markers of unfavorable prognosis in lymph node-negative LAPC involved in the enriched KEGG pathways (TCGA data, TMPRSS2-ERG-positive samples). LogFC—trimmed binary logarithm of average expression-level fold change (between the groups of favorable and unfavorable prognosis); LogCPM—binary logarithm of CPM.

Figure 7

Heatmap demonstrating log relative expression level of top differentially expressed genes between the groups of adverse and favorable prognosis (Russian patient cohort). Cell colors (blue-white-orange gradient) correspond the binary logarithm of the ratio of the expression level in a current sample to the average level across all the samples (per each gene). Blue - expression level is below the average, orange - above the average. Spearman_r—Spearman’s rank correlation coefficient. -Log10(p) is the negative logarithm of DESeq’s p-value. LogCPM—average binary logarithm of read counts per million (CPM). LogFC—binary logarithm of expression-level fold change (sample with adverse prognosis compared to favorable prognosis).

Figure 8

Dotplot showing the results of KEGG pathways enrichment analyses performed for top-40, 80, 250, 500, and 1,000 differentially expressed genes (either overexpressed or downregulated) between the groups of adverse and favorable prognosis (Russian patient cohort). All the genes have passed the following thresholds: DESeq p-value < 0.01, Mann–Whitney p-value < 0.05, average expression-level fold change > 25%. Dot size indicates k/n ratio (“gene ratio”), where k is the number of genes participating in the current KEGG pathway (within top-40, top-80 or other top lists), and n is the number of genes (also within top-40, top-80, or other top lists) annotated as participants of any KEGG pathway (these numbers are provided in the brackets in the bottom of the figure). Dot color indicates the enrichment test FDR (Fisher’s exact test).

Figure 9

Potential markers of unfavorable prognosis in lymph node-negative LAPC involved in the enriched KEGG pathways (Russian patient cohort). LogFC—trimmed binary logarithm of average expression-level fold change (between the groups of favorable and unfavorable prognosis); LogCPM—binary logarithm of read counts per million (CPM).