Potential new biomarkers for endometrial cancer

Abstract

Background: Incidence of endometrial cancer are rising both in the United States and worldwide. As endometrial cancer becomes more prominent, the need to develop and characterize biomarkers for early stage diagnosis and the treatment of endometrial cancer has become an important priority. Several biomarkers currently used to diagnose endometrial cancer are directly related to obesity. Although epigenetic and mutational biomarkers have been identified and have resulted in treatment options for patients with specific aberrations, many tumors do not harbor those specific aberrations. A promising alternative is to determine biomarkers based on differential gene expression, which can be used to estimate prognosis.

Methods: We evaluated 589 patients to determine differential expression between normal and malignant patient samples. We then supplemented these evaluations with immunohistochemistry staining of endometrial tumors and normal tissues. Additionally, we used the Library of Integrated Network-based Cellular Signatures to evaluate the effects of 1826 chemotherapy drugs on 26 cell lines to determine the effects of each drug on HPRT1 and AURKA expression.

Results: Expression of HPRT1, Jag2, AURKA, and PGK1 were elevated when compared to normal samples, and HPRT1 and PGK1 showed a stepwise elevation in expression that was significantly related to cancer grade. To determine the prognostic potential of these genes, we evaluated patient outcome and found that levels of both HPRT1 and AURKA were significantly correlated with overall patient survival. When evaluating drugs that had the most significant effect on lowering the expression of HPRT1 and AURKA, we found that Topo I and MEK inhibitors were most effective at reducing HPRT1 expression. Meanwhile, drugs that were effective at reducing AURKA expression were more diverse (MEK, Topo I, MELK, HDAC, etc.). The effects of these drugs on the expression of HPRT1 and AURKA provides insight into their role within cellular maintenance.

Conclusions: Collectively, these data show that JAG2, AURKA, PGK1, and HRPT1 have the potential to be used independently as diagnostic, prognostic, or treatment biomarkers in endometrial cancer. Expression levels of these genes may provide physicians with insight into tumor aggressiveness and chemotherapy drugs that are well suited to individual patients.

Keywords: AURKA; Biomarkers; Endometrial cancer; HPRT1; JAG2; PGK1.

Fig. 1

Gene expression in patient samples. HPRT, PGK1, JAG2, and AURKA were analyzed for gene expression in both normal (red line) and malignant (blue histogram) samples. Relative protein expression is quantified on the X-axis (represented as transcripts per million), while the frequency of the expression is plotted on the Y-axis

Fig. 2

Tissue evaluation of AURKA, JAG2, PGK1, and HPRT. Tissues were quantified on a gray scale with lower values indicating darker staining intensity. a AURKA expression and b JAG2 expression was significant between malignant and normal samples, but showed no significance between cancer grade. c PGK1 expression and d HPRT expression showed significance both between normal and malignant samples in addition to between cancer grade

Fig. 3

Gene expression between normal and malignant patient samples. Tissues were quantified on a gray scale with lower values indicating darker staining intensity. Across malignant samples, patients exhibited a variety of expression of each of the genes evaluated that were all significant from each other with the exception of JAG2 and HPRT expression. In addition, normal samples also showed a variety of expression of the genes, with PGK1 showing the highest expression and AURKA showing the lowest expression

Fig. 4

Individual patient expression of biomarkers. Each biomarker and their relative expression is plotted according to the patient. Relative expression is represented on the Y-axis, while the protein evaluated is represented on the X-axis. Individual patients did not show consistent biomarker elevation in any of the stages evaluated

Fig. 5

Survival of patients with elevated levels of JAG2, AURKA, PGK1, and HPRT1. We plotted the survival of patients with the highest 20% expression of each respective biomarker (red line) and compared them to the patients with the lowest 20% expression (blue line) over the course of 100 months. We found no statistically significant difference in survival with regards to high and low expression of PGK1 or JAG2, but found significant decreases in survival in patients with an elevation of AURKA (p-value < 0.0001) and HPRT1 (p-value = 0.041)

Fig. 6

Cell lines ranked by their relative expression of JAG2, AURKA, PGK1, and HPRT1. Cell lines were ranked according to their gene expression level (transcripts per million) and the 10 highest expressing and 10 lowest expressing cell lines are shown

Fig. 7

Drug responses of cell lines with elevated JAG2. The 20 cell lines with the highest and lowest expression for each target gene from the previous analysis in Fig. 6 (X-axis) were evaluated via their Activity Area (ActArea) in response to drug treatments. Drug responses are represented by individual graphs with the mean ActArea plotted on the Y-axis. Drugs with a high ActArea indicate sensitivity, while drugs with a low ActArea indicate resistance. The mean ActArea is represented by a line within the figure to indicate the average increase or reduction between the high expressing and low expressing cell lines

Fig. 8

Drug responses of cell lines with elevated PGK1. The 20 cell lines from the previous analysis in Fig. 6 were evaluated via their ActArea in response to drug treatments. The mean ActArea is represented by a line within the figure to indicate the average increase or reduction between the high expressing and low expressing cell lines

Fig. 9

Drug responses of cell lines with elevated HPRT1. The 20 cell lines from the previous analysis in Fig. 6 were evaluated via their ActArea in response to drug treatments. The mean ActArea is represented by a line within the figure to indicate the average increase or reduction between the high expressing and low expressing cell lines

Fig. 10

Drug responses of cell lines with elevated AURKA. The 20 cell lines from the previous analysis in Fig. 6 were evaluated via their ActArea in response to drug treatments. The mean ActArea is represented by a line within the figure to indicate the average increase or reduction between the high expressing and low expressing cell lines

Fig. 11

Drugs that lower the expression of JAG2, HPRT1, AURKA, and PGK1. Cell lines (x-axis) were evaluated for their expression of AURKA and HPRT1 pre and post treatment with drugs (y-axis). The relative changes in protein expression are indicated by the heat map legend and show the variety of responses to various drugs. The events and their effects on target gene expression are indicated by the bar graphs