Cut-off value for KLK3 gene expression from urine sediment to rationalize diagnosis of prostate cancer

Abstract

Although prostate cancer accounts for the highest number of newly diagnosed cases of cancer in men, it represents a specific diagnostic challenge in modern oncology. The standard diagnosis of prostatic carcinoma begins with the screening of serum concentrations of PSA (Prostate Specific Antigen). If the concentration of serum PSA levels is above 4 ng/mL, the patient is further referred to a digital rectal examination in order to determine an increase in prostate volume. In cases where enlargement of the prostate is observed, the next step is biopsy of prostate tissue. This physically painful and invasive approach to confirm the diagnosis is often unnecessary because, in many cases, the patohistologic analysis determines diagnosis of benign prostatic hyperplasia, and not a tumor. In this study, we investigated the possibilities of detection and measurement of the relative level of gene expression of the KLK3 (Kallikrein-related peptidase 3), PCA3 (Prostate Cancer Gene 3) and TEMPRSS: ERG (Transmembrane protease serine2 and in-ETS erythroblostosis virus E26 oncogene homolog) genes from the urine samples of patients with prostatic diseases and healthy controls. Urine was the sample of choice because it is taken in a non-invasive manner, and could potentially serve to make better selection to biopsy. One of the selected genes (KLK3) differed significantly in the samples of various pathological conditions of the prostate, and therefore we consider that its further investigation is reasonable.

Keywords:

• Prostate cancer
• urine
• gene expression
• KLK3

Introduction

Prostate cancer, benign prostatic hyperplasia (BPH) and prostatitis are the most frequently diagnosed prostate diseases with a variety of effects, and of course various treatment approaches, but with the same diagnostic procedure. The first step in this diagnostic procedure includes measurement of the PSA (Prostate Specific Antigen) concentration in the serum. At a later stage of the diagnostic procedure, digital rectal examination (DRE) is required and subsequently, if needed, a biopsy, which is an extremely painful and invasive step. Tissue biopsy is primarily done in order to confirm or rule out the diagnosis of cancer, but the number of cancer cases that are confirmed by biopsy compared to the number of all bioptic samples, is relatively low. About 30–50% of the biopsy cases do not confirm the existence of neoplastic-related tissue changes [1]; instead they indicate either BPH or prostatitis. In many cases, the biopsy results combined with the results of DRE and serum PSA concentration, are not conclusive enough, and patients are referred to repeated biopsies [2], which cause extra stress in patients.

Therefore, in the past few years in the urological-oncological practice there is ongoing work on the discovery of new and more reliable biomarkers, as well as on the search for new types of samples in which to quantify or determine the presence of selected biomarkers, all in order to reduce the number of patients sent to invasive biopsy. In this study we investigated the possibilities of detection and measurement of the expression of three mRNAs that have been reported as potential biomarkers for prostate cancer in urine samples, which are relatively easily available material for analysis.

In this work, we measured the relative gene expression of KLK3 (Kallikrein-related peptidase 3), PCA3 (Prostate Cancer Gene 3) and TEMPRSS: ERG (Transmembrane protease serine2 and in-ETS erythroblostosis virus E26 oncogene homolog), and determined the ROC (receiver operating characteristic) value for those markers that expressed statistically most significant difference.

Materials and methods

Ethics statement

The study design was approved by the Ethics Committee of the Clinical Center of the Sarajevo University and the Scientific Council of the Institute for Genetic Engineering and Biotechnology, University of Sarajevo.

The collection of biological material was carried out in accordance with the ethical principles of the Helsinki Declaration on Patient Rights. Before sampling, the patients selected for the study were informed on how the sample would be used and signed consent forms for participation in the study.

Samples

For the purposes of this study, we collected a total of 162 urine samples at the Clinic for Urology of the University Clinical Centre in Sarajevo. Urine was collected after DRE due to the increased number of cells originating from the prostate gland in the urine at the end of the process, thus increasing the possibility for the detection of selected markers in the samples.

The collected samples were divided into four groups according to the diagnosis: Group 1—samples with confirmed diagnosis of prostate carcinoma by a physician urologist and by biopsy analysis; Group 2—samples from patients diagnosed with benign hyperplasia, with high values of ASAP (atypical small acinar proliferation) and HGPIN (high-grade prostatic intraepithelial neoplasia); Group 3—samples with histologicaly confirmed precancerous state of the prostate gland and PSA value less than 1.5, with malignance negative DRE; Group 4—control samples in which the histopathological examination showed no signs of tumor. The number of samples from each group, with group average RNA concentration, is given in Table 1.

Table 1. Number of samples by group and mean RNA concentration.

Group	Number of samples	Mean RNA concentration (ng/µL)
1—prostate carcinoma	45	16.0
2—benign hyperplasia	15	2.4
3—PSA < 1.5 and negative DRE	53	2.9
4—healthy controls	49	3.8
∑	162

Urine was collected in the amount of 25–50 mL, stored at 4˚C and no later than 4 h after taking was transported to the laboratory for further processing. Together with urine samples, we received data of the PSA levels from the urologist.

Extraction of total mRNA

Extraction of total mRNA from the urine samples was performed following an initial centrifugation step for collection of cell precipitates. In the second centrifuging step, the cell precipitates were stabilized with phosphate buffered saline (PBS). The extraction was done using a NucleoSpin® RNA isolation kit (Macherey-Nagel Gmbh & Co., Duren, Germany).

The concentration of the isolated total RNA samples was measured using a Qubit® 2.0 fluorometer (Invitrogen, Life Technologies, Oregon, USA) and a Qubit RNA FS Assay kit. Following equilibration of the RNA concentration, reverse transcription was performed, using “Gold GeneAmp® RNA PCR Core Kit” (“Applied Biosystems”, CA, USA) in an Eppendorf Mastercycler gradient PCR machine.

Expression analysis

The relative expression of the KLK3, PCA3 and TEMPRSS: ERG genes was determined using SYBR green based (Power SYBR Green® kit, Applied Biosystems, Ca., USA) real-time polymerase chain reaction (PCR) with the primer sets listed in Table 2. An Applied Biosystems 7300 Real time PCR system (Applied Biosystems, Ca., USA) was used. As a reference, for normalization we used glyceraldehyde 3-phosphate dehydrogenase (GAPDH), with the primer pair shown in Table 2.

Table 2. Primers used in this study.

Primer	Forward (5'–3')	Reverse (5'–3')
KLK3	TCCAATGACGTGTGTGCGCA	CCTTGATCCACTTCCGGTAA
PCA3	CCGAGGGAGACCAGGAAGAT	ATCGATGACCCAAGATGGCG
TMPRSS1-ERG	CGCGGCAGGAAGCCTTA	TCCGTAGGCACACTCAAACAAC
GAPDH	TGAAGGTCGGAGTCAACGGA	CATCGCCCCACTTGATTTTGG

To calculate the relative expression levels, the obtained Ct values were converted into ΔCt values using the DataAssist ™ Software v3.01, which represents the difference between the Ct value of the studied gene and the housekeeping gene (ΔCt_KLK3 = Ct_KLK3 − Ct_GAPDH, ΔCt_PCA3 = Ct_PCA3 − Ct_GAPDH and ΔCt_TMPRSS-ERG = Ct_TMPRSS-ERG − Ct_GAPDH). The relative expression of each of the mRNAs was investigated with the same software, calculated in the form of a 2^−ΔCt value (2^−ΔCt _{(investigated gene)} = ΔCt_{(each patient)} − ΔCt_{(control group mean value)}).

Thus generated ΔCt and 2^−ΔCt values were used for further analysis of the relative gene expression (REST software) as well as for comparative analysis of the relative gene expression among the researched groups. We are also used these values for correlation analysis between the expression levels of the selected genes and the PSA levels. In addition, these values were also used for the determination of the ROC (Receiver operating characteristic) values in the groups between which there were statistically significant differences in the gene expression.

Data analysis

Statistical analysis was performed using DataAssist ™ Software, REST software (Relative expression software tool) and MedCalc software in order to obtain information on relative gene expression, ROC values, variance analysis (ANOVA). Adjustment was done by Walch’s t-test.

Results and discussion

The success of RNA extraction and reverse transcription was 82% (133 samples) out of 162 samples that were collected. The concentration of isolated total RNA was 6.8 ng/µL on average, and ranged from 1 ng/µL to 96 ng/µL (Table 1). The highest average concentration of RNA was measured in the group of patients with prostate cancer (16 ng/µL). In the other groups, the RNA concentration was as follows: in Group 2 (patients with BPH), 2.4 ng/µL; in Group 3 (PSA < 1.5, negative DRE and histologically confirmed precancerous state of prostate gland), 2.9 ng/µL; and 3.8 ng/µL in Group 4 (the healthy controls).

The average ΔCt and 2^−ΔCt values obtained using DataAssist ™ Software, for the KLK3 gene in Group 1 were 0.167 and 17.09, respectively. In Group 2, the values were 3.89 for ΔCt, and 0.214 for 2^−ΔCt. In Group 3, the average ΔCt was 2.3, and the average value of 2^−ΔCt was 0.452. The average ΔCt value in Group 4 was 3.7, and the average 2^−ΔCt was 0.347 (Table 3).

Table 3. Mean ΔCt and 2^−ΔCt values.

Group/Gene	Mean KLK3 (ΔCt/2^−Δ^Ct)	Mean PCA3 (ΔCt/2^−Δ^Ct)	Mean TMPRSS2:ERG (ΔCt/2^−Δ^Ct)
1	0.16/17.09	34.37/0.004	11.92/0.0124
2	3.89/0.214	10.30/0.196	12.9/0.024
3	2.3/0.452	9.37/0.014	5.99/0.0013
4	3.7/0.347	10.17/0.007	11.59/0.0016

For the PCA3 gene, the average ΔCt value in Group 1 was 34.376, and the average 2^−ΔCt was 0.00412. In the group of patients with BPH (Group 2), the average ΔCt value was 10.303, and the 2^−ΔCt values ranged from 0.00138 to 1.1526, with an average of 0.196. In Group 3, the ΔCt values were 9.374 on average, and the 2^−ΔCt values ranged from 0.000119 to 0.311 with an average of 0.0147. In the control group of patients (Group 4), the ΔCt values were an average of 10.173, and the 2^−ΔCt values ranged from 0.00001892 to 0.101 with an average of 0.00767 (Table 3).

The TMPRSS2:ERG gene was expressed with an average ΔCt value of 11.92 in Group 1, and and average 2^−ΔCt value of 0.0124. The ΔCt values in the group of patients with BPH averaged at 12.9, whereas the average 2^−ΔCt value was 0.024. The expression of the TMPRSS2:ERG gene in Group 2 gave an average ΔCt value of 5.99, and an average 2^−ΔCt value of 0.0013. The ΔCt values for the TMPRSS2:ERG gene in the control group (Group 4) were an average of 11.59, whereas the average 2^−ΔCt values had a value of 0.0016.

The obtained Ct values were used for the further analysis of the differences in the gene expression between the groups, using the REST application. The ΔCt and 2^−ΔCt values were used for analysis of different expression levels between all the groups and the control group using MedCalc software package. Using the same program, variations of Ct and ΔCt values were analyzed using ANOVA test.

REST analysis

We used REST software to analyse the relative gene expression based on the Ct values following real-time PCR. The Ct values for the KLK3 gene in Group 1 varied statistically significantly in relation to the Ct values in the control group (p = 0.005). In Group 2 (BPH) there was neither a significant increase, nor a decrease in the expression of the KLK3 gene in comparison to Group 4 (p = 0.057). Although the P-value was certainly close to the set value of significance (p = 0.05), under the considerations of this study, there were no statistically significant differences in the expression between the patients with BPH and the control group.

In Group 3 (PSA < 1, 5 and negative DRE), the expression of the KLK3 mRNA was significantly increased compared to the control group (p = 0.017). However, there were normal serum concentrations of PSA in this group, suggesting that, at the molecular genetic level, the increase in the synthesis of the mRNA for the KLK3 gene was not accompanied by increased expression of the PSA protein. We could speculate that the expression of this gene was probably subject to post-transcriptional control at the mRNA level.

REST analysis of the Ct values of the PCA3 (DD3) gene revealed that the expression of this gene in Groups 1, 2 and 3 was not statistically significantly different as compared to Group 4 (p < 0.05). Unlike our results, other authors [3–5] have reported increased gene expression of the PCA3 gene in tumour tissue compared to control tissue. This difference can be attributed to fact that, in these studies, the expression is measured in tissues, whereas we measured the mRNA levels in urine samples. PCA3 is a prostate tissue-specific marker and can be found in urine but only in trace amounts. In addition, some researchers agree that the PCA3 gene has reduced gene expression in about 75% of BPH cases [6, 7].

The expression level of the TMPRSS2: ERG fusion gene in Groups 1 and 2 did not reach statistically significant differences as compared to the controls in Group 4. In Group 3, the TMPRSS2: ERG gene had significantly reduced expression in comparison with the control group (p = 0.044). The role of the mRNA transcript of this gene is still subject to debate, which is why this gene was included in this study. The greater part of the scientific community agree that the expression level and the presence of the fusion gene can be of importance in the screening and diagnosis of prostate cancer [8–10]. Our results do not support this belief.

MedCalc variation analysis

MedCalc analysis of the variation of the Ct and ΔCt values of the genes of interest between the control group and all other groups pooled together using produced results that were in agreement with the REST analysis results. When we pooled the data for all the patients from Groups 1, 2 and 3 together as one large group, there was statistically significant difference compared to the control group, suggesting that the expression of the KLK3 mRNA was associated with prostate disorders in general. Regardless of whether we tested the Ct or ΔCt values, even after the application of corrective factors, the statistical significance (P value) was below 0.05.

The analysis of the variation of the unadjusted Ct and ΔCt values of the PCA3 gene initially showed statistically significant difference between the groups. However, after adjustment by Walch’s t-test, the P-value increased to 0.33 and 0.32 for ΔCt and Ct values, respectively.

The variations in the gene expression level of the TMPRSS2: ERG gene showed that the P-value was at the level of incidental findings. Our data suggest that there was no difference in the variation of the TMPRSS2: ERG mRNA levels in the target groups.

Analysis of variances between the groups (ANOVA)

Analysis of variances of Ct and ΔCt values between the groups was performed using ANOVA test. The values for the KLK3 gene from Group 1 varied significantly in comparison to all other groups observed individually (Table 4). Also, there was statistically significant difference between Group 3 and Group 4 (Table 4). These results indicate that the Ct and ΔCt values (i.e. the gene expression of the KLK3 gene) could be used as a parameter for better discrimination between different types of prostate disease. This suggestion needs to be confirmed in a larger study with a larger sample pool. This is especially important since prostate cancer and BPH have a very similar symptomatic pattern, and this pattern of false positive results in non-cancerous samples is the main reason for the large number of pathologically tumorous-negative biopsy results.

Table 4. Analysis of variances for KLK3 gene between groups.

Group	1	2	3	4
1	–	P < 0.05	P < 0.05	P < 0.05
2	P < 0.05	–	P ≥ 0.05	P ≥ 0.05
3	P < 0.05	P ≥ 0.05	–	P < 0.05
4	P < 0.05	P ≥ 0.05	P < 0.05	–

The observed values of gene expression of PCA3 gene in the analysis with any REST or in MedCalc showed no significant difference in variation between the control group and all patients together. However by analysis of intergroup differences of the monitored parameters, statistically significant difference was observed between the groups. Particularly noteworthy is the observed difference between the group of subjects with cancer and the groups of patients with BPH (Table 5). The PCA3 gene expression levels in Group 2 were also significantly different from those in Group 3 and Group 4.

Table 5. Analysis of variances for PCA3 gene between groups.

Group	1	2	3	4
1	–	P < 0.05	P ≥ 0.05	P ≥ 0.05
2	P < 0.05	–	P < 0.05	P < 0.05
3	P ≥ 0.05	P < 0.05	–	P ≥ 0.05
4	P ≥ 0.05	P < 0.05	P ≥ 0.05	–

The Ct and ΔCt values for the TMPRSS2: ERG gene did not show statistically significant differences between the groups. The P-value for the mRNA expression level of this gene was always at the level of accidental discovery according to ANOVA.

Correlation analysis between KLK3 expression and serum PSA level

Using MedCalc software we tested for possible correlation between the ΔCt values of the KLK3 gene and the serum PSA level. The correlation was tested for the KLK3 gene only, because PSA is a direct product of this gene, and this gene showed elevated expression in all groups of patients. Testing was done for the control group on the one hand and all groups of patients together on the other hand. We did not find statistically significant correlation between these two parameters (p = 0.736).

Although a statistically significant correlation between the elevated levels of serum PSA and the expression of KLK3 genes is expected, it should be noted that the PSA amount was measured in blood serum before DRE, whereas the expression of the gene for Kallikrein 3 was measured in the urine sample after DRE and, by that, directly from the cells of the prostate which were at that time present in the urine sample.

ROC analysis

By ROC analysis within the MedCalc program, we determined the limiting value for KLK3 genes that could distinguish between all the groups, as well as between Group 1 and all other groups together. The data for the expression levels of the KLK3 mRNA were further analyzed statistically because of the results which were obtained by statistical analysis done earlier.

The analysis of the group of healthy control subjects, on the one hand, with all the other groups together, showed that the KLK3 mRNA 2^−ΔCt value of 0.94 separated the two groups with specificity of 94.79%, and sensitivity of 48.65% (p < 0.0001). This means that when the 2^−ΔCt value is greater than 0.94, in 94.79% of the cases will be confirmed as negative for malignancy, or when it is less, the probability of positive diagnosis will be 48.65%. This finding needs to be tested on a larger sample and, if confirmed, it could eventually be applied for better selection of patients for biopsy. It would indicate that patients with a 2^−ΔCt value greater than 0.94 (in our study) have lesser chance to develop malignancy, and instead of biopsy, they can have their serum PSA level monitored more often.

When we analyzed the KLK3 mRNA data between the individual groups, we first worked on the ROC analysis between the groups of patients with cancer and Group 2 (BPH). The resulting 2^−ΔCt predictive limit value of 0.685, with a specificity of 100% and sensitivity of 51.35%, separated the two groups (p < 0.0001). In practice, as stated previously, this means that when the KLK3 mRNA 2^−ΔΔCt value was greater than 0.685, all the cases observed by us were confirmed to be malignancy negative, or when the value was less, the possibility of positive BPH diagnosis was 51.35%. These results are promising and suggest that the KLK3 mRNA level in the urine could serve as a complement indicator to the serum level of PSA as a monitored parameter for biopsy prior to biopsy. This type of analysis, after further investigation on larger cohorts of patients, could be included in urological medical practice as additional confirmation for better differential diagnosis between prostatic carcinoma and BPH.

There was a significant difference (p = 0.0072) between group 1 (carcinomas) and 3 (negative DRE and PSA < 1.5) for the obtained predictive limit values of 1.07, with specificity of 95% and sensitivity of 45% for the 2^−ΔCt values. The derived Ct values tested by ROC analysis between Groups 2 and 3 and Groups 2 and 4 did not show a statistically significant difference (p > 0.05 in both cases). On the other hand, ROC analysis of the 2^−ΔCt values between Group 3 and Group 4 showed a statistically significant difference (p = 0.0013) for the value of 0.45 with specificity of 92.6%, and 41.4 sensitivity.

Based on the obtained results, we suggest that the analysis of the KLK3 mRNA level in the urine is a non-invasive approach that could improve the screening efficiency for malignant prostate diseases and reduce the number of biopsies. We have found that alternative sources of that clinical information can be sought in urine [11, 12]. The benefit of validation of new and non-invasive screening procedures lies in that they would significantly reduce the psychological distress that patients experience but also the financial costs of public screening programs. One approach for better diagnosis of prostate malignancy can be the combined analysis of several markers which correlate with this disease [13].

Based on quantization of target mRNA of three genes, KLK3, PCA3 and TMPRSS2:ERG, using Real time PCR, we conclude that urine can serve as a starting material for RNA isolation, although it has lower concentration of RNA than samples from blood and tissue. RNA from urine samples can also be succesfully translated into cDNA molecules. By the relative quatification method, we determined that the KLK3 gene has relatively good potential for discrimination of patients with prostate carcinoma from patients with benign hyperplasia.

Conclusions

Urine as a type of clinical sample represents valuable source of biological information. It is possible to isolate high-quality total RNA that can be used for analysis of differential expression of tissue-specific and constitutive gene expression. The KLK3 gene was differentially expressed in the investigated diagnostic groups. Increased expression of the KLK3 gene was associated with the presence of prostate cancer. A cut-off value of 0.94 of KLK3 gene expression was identified: In our study, expression levels greater than 0.94, confirm with a 95% confidence a negative diagnosis of malignant disease; values less than 0.94 indicate a probability of 50% that a person has malignant prostate disease. The clinical value of the results of this study needs to be confirmed in a larger clinical sample and the general population before any clinical application.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Funded by Federal ministry of science and education, FBiH, BiH (0101-7552-7/15).