Research ArticleClinical Studies

Investigative Clinical Study on Prostate Cancer Part IX and X: Estradiol and the Pituitary-Testicular-Prostate Axis at the Time of Initial Diagnosis and Subsequent Cluster Selection of the Patient Population after Radical Prostatectomy

ANTONIO B. PORCARO, CLAUDIO GHIMENTON, ALDO PETROZZIELLO, TEODORO SAVA, FILIPPO MIGLIORINI, MARIO ROMANO, BEATRICE CARUSO, CLAUDIO COCCO, STEFANO ZECCHININI ANTONIOLLI, VINCENZO LACOLA, EMANUELE RUBILOTTA and CARMELO MONACO
Anticancer Research October 2012, 32 (10) 4523-4532;

Abstract

Aim: To evaluate estradiol (E2) physiopathology along the pituitary-testicular-prostate axis at the time of initial diagnosis of prostate cancer (PC) and subsequent cluster selection of the patient population. Patients and Methods: Records of the diagnosed (n=105) and operated (n=91) patients were retrospectively reviewed. Age, percentage of positive cores at-biopsy (P+), biopsy Gleason score (bGS), E2, prolactin (PRL), luteinizing hormone (LH), follicle-stimulating hormone (FSH), total testosterone (TT), free-testosterone (FT), prostate-specific antigen (PSA), pathology Gleason score (pGS), estimated tumor volume in relation to percentage of prostate volume (V+), overall prostate weight (Wi), clinical stage (cT), biopsy Gleason pattern (bGP) and pathology stage (pT), were the investigated variables. None of the patients had previously undergone hormonal manipulations. E2 correlation and prediction by multiple linear regression analysis (MLRA) was performed. At diagnosis, the log E2/log bGS ratio clustered the population into groups A (log E2/log bGS ≤2.25), B (2.25<log E2/log bGS ≤2.48) and C (2.48< log E2/log bGS ≤2.59). The operated population was clustered according to the log E2/log pGS ratio into groups A (log E2/log pGS ≤2.25), B (2.25< log E2/log pGS ≤2.48) and C (2.48< log E2/log pGS ≤2.59). Simple linear regression analysis of bGS and pGS predicting E2 was computed; differences between the clusters were assessed by analysis of variance (ANOVA) and by contingency tables. Results: At diagnosis, E2 was correlated to TT (r=0.32, p=0.0006) and FT (r=0.25, p=0.0009); moreover, E2 was independently-predicted by TT (p=0.009) and bGS (p=0.04) on MLRA. The bGS significantly predicted E2 in all groups. Groups A, B and C differed in mean values for E2 (p<0.0001), TT (p=0.005), FT (p=0.05), P+ (p=0.01) and bGS (p=0.003); moreover, the frequencies of the different bGPs were significantly different in the three groups (p=0.004). Interestingly, groups A, B, and C were associated with high-, intermediate- and low-bGS tumor grade, as well as with low-, intermediate- and high-serum levels of E2, TT and FT, respectively. In the operated population, E2 significantly correlated to FSH (r=-0.20, p=0.04), TT (r=0.34, p=0.0008), FT (r=0.29, p=0.003), bGS (r=0.22, p=0.03) and V+ (r=0.26, p=0.01); moreover, E2 was independently-predicted by TT (p=0.05) and bGS (p=0.03) on MLRA. The pGS significantly predicted E2 in all groups that differed for mean values of E2 (p<0.0001), TT (p=0.004), FT (p=0.002) and pGS (p=0.007), as well as for pT (p<0.0001) and pGS (p=0.008) frequencies. Interestingly, clusters A, B, and C were associated with high-, intermediate- and low-pGS-pT frequencies as well as with low-, intermediate- and high-mean serum levels of E2, TT and FT, respectively. Conclusion: In a diagnosed- and operated-PC population, E2 serum levels were functionally related along the pituitary-testis-prostate cancer axis; also the log E2/log bGS and log E2/log pGS ratio, clustered the population in three groups where the risk of progression might be ranked as high (group A), intermediate (group B) and low (group C). However, further confirmatory studies are needed.

The endocrine system involved in prostate cancer (PC) biology includes the hypothalamus, the pituitary gland, the testes and the adrenals. Follicle stimulating hormone (FSH) and luteinizing hormone (LH) are secreted from the gonadotrophic cells located in the anterior pituitary; they are also called gonadotropins because they stimulate the gonads. Most gonadotrophs secrete only LH or FSH, but some appear to secrete both hormones. Prolactin (PRL) is a polypeptide hormone which is secreted by the pituitary lactotroph cells. The interstitial cells of Leydig are responsible for the production of 95% of all circulating androgens in the form of testosterone. Approximately 98% of the circulating androgens are bound to plasma proteins, including a specific beta-globulin, testosterone-binding globulin (TeBG). Free-testosterone (FT) in the blood is the physiologically important fraction. LH, FSH, PRL, androgens and estrogens are the hormones regulating the function of the prostate. Etiological and stimulatory factors of PC are still not completely understood. The main evidence from the reported literature shows that PC is androgen-dependent (1), increases the levels of prostate-specific antigen (PSA) (2), is related to the rate of increase of PSA for its extent and prognosis (3, 4), and pre-treatment serum total-testosterone (TT) and FT levels may both be abnormal (5-12). Human benign prostatic hyperplasia and PC tissues have been found to express LH and FSH receptors (13-17). These findings suggest that gonadotrophins may promote cancer either indirectly by stimulating testicular production of hormones or directly through their receptors located in the prostate gland (18). Locally produced PRL has been documented in prostate tumors and shows tumor growth potency, acting via autocrine/paracrine mechanisms; a novel class of compounds with therapeutic potential to target PRL receptors (PRLR) signaling, namely competitive PRLR antagonists, have also been developed (19, 20). PC is an interesting tumor for clinical endocrine investigation. Unfortunately, at the moment we ignore the natural history of PC physiopathology (21). The pituitary axis in PC has long been investigated and it has been suggested that this tumor type may produce a substance that alters the normal function of the pituitary–testicular axis which results in abnormal serum LH and FSH levels (5, 9-12, 22-29). It has been suggested that the impact of PC on the hypothalamic–pituitary axis may be more profound in high-grade tumors (27), but this hypothesis has not been confirmed (30). Since the pioneering work of Huggins and Hodges (1), androgens have been universally considered pivotal in the regulation of normal prostatic function and malignant prostate growth. However, a bulk of experimental evidence has accumulated to support an equally important role for estrogens in the development and progression of human prostate cancer. Estrogens induce systemic effects by acting through the pituitary gland to indirectly lower androgen levels, as well as by having effects that directly target prostate tissue by specific estrogen receptors (ER). Estrogens and their receptors are implicated in PC development and progression. There is a significant potential for the use of ER-α antagonists and ER-β agonists to prevent prostate cancer and delay disease progression (31). Locally-produced or metabolically-transformed estrogens may differently affect the proliferative activity of prostate cancer cells. Estrogens may either stimulate or reduce PC cell growth, also depending on the receptor status. In particular, an imbalance of ER-α antagonists and ER-β expression may be critical in determining the ultimate effects of estrogens on PC cell growth (32). There is a controversial and unclear literature on E2 related to PC risk. Indeed, plasma levels of E2 might have been related to PC risk (33-35), or might not (24, 36-40). Clinical investigations have focused on relating serum E2 levels on PC grade, but the literature is also unclear and controversial. Indeed, it has been shown that E2 serum levels might be correlated to high-grade PC (25, 41-44), but also that they might not (30, 45). Serum E2 levels associated with high-grade PC can be either significantly lower (25, 41), or higher (43, 44); similarly, they were higher in low- (41, 42) but also in high-stage PC (44), as well as being significantly higher in non-metastatic PC (41, 42). Interestingly, low pre-treatment plasma levels of E2 have been associated with shorter disease-specific survival (42). This study aimed at evaluating E2 physiopathology along the pituitary-testicular-prostate axis at the time of initial diagnosis of PC and subsequently to cluster a selection of the patient population after radical prostatectomy in relation to clinical-pathological variables.

Patients and Methods

The study involved 105 individuals diagnosed with PC; it also investigated 91 operated patients. The total patient population under the testosterone study is over 235 individuals, but this communication does not include those patients who were not simultaneously assessed for E2 and pituitary hormones. The descriptive statistics of the patient population with treatments performed up to the time of this communication, are shown in Table I. All the patients had histologically-proven carcinoma of the prostate and had not previously received 5α-reductase inhibitors, LH-releasing hormone analogs or testosterone replacement treatment. The 14-core transrectal ultrasound scan (TRUS)-guided prostate biopsy technique was routinely used and additional cores were taken when a lesion on either TRUS or digital rectal examination was evident. The biopsy Gleason score (bGS) was used to grade the tumors. Patients were classified according to primary tumor stage, lymph node and metastatis status, using the TNM categories, recommended by the 1997 International Union Against Cancer TNM classification system (46). After informed signed consent, simultaneous pre-treatment serum samples were obtained from a cubital vein, at least one month after TRUS biopsy between 8.00-8.30 a.m., for measuring serum E2, PRL, FSH, LH, TT, FT and PSA levels. The samples were analyzed at the same laboratory of our hospital. E2 (normal values <200 pmol/l), PRL (range=3.07-20.05 μg/l), FSH (range=1.0-14 IU/l), LH (range=2.0-10 IU/l), TT (normal range=9-29 nmol/l) and PSA (normal range=2-4 μg/l) were measured by immunochemiluminescent tests performed by the ADVIA Centaur XP Immunoassay System (Siemens Company). Free-testosterone (FT normal range=31-163 pmol/l) was measured by a immunoradiometric test (DSL, USA). The prostatectomy specimens were fixed in toto overnight (10% neutral-buffered formhaldeyde), coated with India ink and then weighed (Wi). Tissue sections of 4 μm were prepared in standard fashion and stained with hematoxylin and eosin. Seminal vesicle invasion was defined as tumor involvement of the muscular wall (pT3b). Invasion of the bladder neck was staged as pT4 disease. Surgical margins (pR) were stated as free-(pR−) or involved in cancer (pR+). Tumors were graded according to the Gleason grading system and the Gleason score was computed after summing up the two patterns, prevalent and secondary, structuring the tumor. Overall cancer volume, related as a percentage of prostate volume (V+), was evaluated. Biopsy and prostatectomy specimens were assessed by our experienced pathologists.

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Table I.

Summary and descriptive statistics of the patient population.

Statistical methods. Age, percentage of positive cores at TRUS biopsy (P+), bGS, E2, PRL, FSH, LH, TT, FT, PSA, pGS, V+ and Wi were the continuous clinical variables considered. Categorical variables were cT, pT and biopsy Gleason pattern (bGP). Correlation and multiple linear regression analysis (MLRA) of the investigated variables on E2 were computed. For clustering the PC population at diagnosis, E2 was assumed as a power function predicted by the bGS. The power function was computed according to the formula E2=bGS^(k) and it was transformed into a linear function by using the base 10 logarithms as follows: log E2=k × log bGS. The constant of proportionality from the empirical data, k, was computed as log E2/log bGS ratio; moreover, it was used for ranking the patient population as group A: log E2/log bGS ≤2.25; B: 2.25<log E2/log bGS≤2.48; and C: 2.48 <log E2/log bGS≤2.59. The log E2/log bGS ratio, as a clustering model, was assessed by computing simple linear regression analysis of bGS predicting E2; differences between the clusters were also assessed by analysis of variance (ANOVA) for the continuous variables and by contigency tables for categorial variables, such as bGP (3+3, 3+4, ≥4+3) and cT. For clustering the operated PC population, a non-linear relation between E2 and pGS was assumed and the calculations were carried out exactly as for bGS above. The log E2/log pGS ratio was then ranked similarly for clustering the patient population as group A: log E2/log pGS ≤2.25; B: 2.25<log E2/log pGS ≤2.48); and C: 2.48<log E2/log pGS ≤2.59. Scatter plots of E2 relating to pGS, as a power and double logarithmic function, were computed for the different sub-clusters. The log E2/log pGS ratio, as a clustering model, was assessed by computing simple linear regression analysis of pGS predicting E2 in group A, B and C; differences between the clusters were also assessed by analysis of variance (ANOVA) for the continuous variables and by contigency tables for categorial variables, such as pT and pGS.

Results

The results of correlation and MLRA on E2 are reported in Table II. In the diagnosed PC population, E2 was significantly correlated to TT (r=0.32, p=0.0006) and FT (r=0.25, p=0.0009); moreover, E2 was independently-predicted by TT (p=0.009) and bGS (p=0.04) on MLRA. In the operated PC patients, E2 was significantly correlated to FSH (r=−0.20, p=0.04), TT (r=0.34, p=0.0008), FT (r=0.29, p=0.003), bGS (r=0.22, p=0.03) and V+ (r=0.26, p=0.01); moreover, E2 was independently-predicted by TT (p=0.05) and bGS (p=0.03) on MLRA. The results of simple linear regression analysis and ANOVA of the clustered population are reported in Table IIIB and IIIA, respectively. In the diagnosed PC population, the bGS significantly predicted E2 in all groups (p<0.0001 for each); groups A, B and C were also significantly different for mean values of E2 (p<0.0001), TT (p=0.005), FT (p=0.05), P+ (p=0.01) and bGS (p=0.003). In the operated PC patients, the pGS significantly predicted E2 in group A (p=0.002), B (p<0.0001) and C (p=0.05); groups A, B and C were also significantly different for mean values of E2 (p<0.0001), TT (p=0.004), FT (p=0.002) and pGS (p=0.007). The results of contingency table analysis of the category variables of the patient population are given in Table IV. In the diagnosed PC population (see Table IVA), the frequencies of bGP were significantly different in the three groups (p=0.004). In the operated PC patients (see Table IVB), the three clusters were significantly different for pT (p<0.0001) and pGS (p=0.008) frequencies. In the operated PC population, scatter plots of pGS predicting E2 and log-pGS predicting log-E2 are displayed in Figures 1 and 2, respectively, where the significance of the different power of the curves (Figure 1) or slopes of the lines (Figure 2) are evident. Figure 3 shows the scatter plot of E2 versus TT for the different clusters (A, B, and C), according to the log E2/log pGS ratio, of the operated PC patients.

Discussion

In the present investigation, we have shown that E2 was significantly correlated, along the pituitary-testis-prostate axis, to FSH, TT, FT, bGS and V+ in a PC population at-diagnosis; moreover, E2 was also independently- and significantly-predicted by both TT and bGS, indicating a functional relationship along the pituitary-testis-prostate cancer axis (see Table II), as also confirmed by Miller et al. who showed that radical prostatectomy influences the hypothalamic pituitary axis by increasing serum testosterone, percent FT, E2, LH and FSH, while reducing serum dihydrotestosterone (DHT) levels (9). Serum levels of E2, TT and FT were significantly correlated, as expected, because aromatization of androgens in peripheral tissues is a major source of estrogens in men. As a theory, these finding also suggested a potential prognostic role of E2 in the natural history of prostate cancer (47-50).

The present study showed that the functional relationship between E2 and bGS/pGS might be nonlinear and follow a power function pattern, especially for high grade tumors. These findings suggested the linearization of the predictor (bGS/pGS) and response (E2) variables by the base 10 logarithms and then clustered the prostate cancer population by ranking the log E2/log bGS/pGS ratio, as displayed, for E2 versus pGS, in Figures 1 and 2, where the non-linear and linear patterns are clearly evident. The predicting models (A, B and C) of bGS/pGS on E2 were effective since the co-efficients of the predictor variables were all significant (see Table IIIB), suggesting different tumor phenotypes related to each group.

Interestingly, as displayed in Tables IIIA and IV, groups A, B, and C were associated with high-, intermediate- and low-frequencies of bGP, pGS and pT, as well as with low-, intermediate- and high-serum E2, TT and FT levels, respectively. These findings suggest that there is an evident association between E2 and prostate cancer phenotype by ranking the log E2/log bGS/pGS ratio expressing the constant of proportionality computed by the empirical data from the prostate cancer population. The evidence of the present study suggests that the log E2/log bGs/pGS ratio selected significant potential prognostic clusters in which the risk of progression might be ranked as being high (group A), intermediate (group B) and low (group C); the log E2/log bGS/pGS clusters might also have potential as clinical models for further investigations. As a theory, E2 might have a potential prognostic role in the natural history of PC (47-50). We have shown in our previous investigations that there was an evident association between pituitary hormones and the PC phenotype (51-53). The present findings have also confirmed that FT and TT might have key roles in prostate cancer biology along the pituitary–testis-prostate axis, being involved in complicated feedback systems which in part might be explained by both linear and non-linear mathematical laws (54-57).

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Table II.

Correlation and Multiple Linear Regression Analysis of serum estradiol (E2) along the Pituitary-Testis-Prostate axis in the prostate cancer population.

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Table III.

Analysis of variance (ANOVA) and simple linear regression analysis of biopsy Gleason score (bGS) and pathology Gleason score (pGS) predicting Estradiol (E2) in the prostate cancer population clustered according to the logE2/logpGS and logE2/logpGS ratio.

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Table IV.

Contigency table relating the biopsy Gleason pattern (bGP)/clinical stage (cT) (bGP/cT) to the log of Estradiol (E2)/log biopsy Gleason score (bGS) (log E2/log bGS) clusters and pathology stage (pT)/pathology Gleason score (pGS) (pT/pGS) to the log E2/log pGS clusters of the patient population.

Figure 1.
Figure 1.

Scatter-plot of Estradiol (E2) versus pathology Gleason score (pGS) for clusters A, B and C.

Figure 2.
Figure 2.

Scatter plot of log Estradiol (log E2) versus log pathology Gleason score (log pGS) for clusters A, B and C.

Our mathematical-empirical clinical model correlated to literature findings, showing that low levels of circulating E2 were associated with increased PC risk (33), high-grade and high-pT stage disease (25, 41-42), metastasis stage (41-42) and to shorter disease-specific survival (41). Our model also supports the view that endogenous E2 plays an inhibitory role in the growth, metastazing tendency, and differentiation of the tumor, and that estrogen treatment might be the treatment of choice for those with low-E2 levels; for those with medium- or high-E2 levels, orchiectomy seems to be as valuable as estrogen treatment (41). Moreover, for PC, our model supports the theory that the proportion of androgen-responsive tumor cells was higher in patients with high levels of E2, and therefore even endocrine therapy might be more efficient than in patients with low-levels of E2 (42). The model supports the theory that high-endogenous E2 levels might have an inhibitory effect on the progression of PC (42).

Figure 3.
Figure 3.

Scatter-plot of estradiol (E2) versus total testosterone (TT) for clusters A, B and C.

The present investigation was limited by the small number of patients, but remains intriguing for its findings and challenging for its potential applications in managing clinical PC. However, further confirmatory studies are needed.

Conclusion

In a diagnosed and operated PC population and along the pituitary–testis-prostate axis, E2 was significantly correlated to FSH, TT, FT, bGS and V+; E2 was also significantly and independently predicted by both TT and bGS, indicating a functional relatioship along the pituitary–testis-prostate cancer axis. Because of the high correlation and prediction of bGS/pGS on E2, the prostate cancer population at-diagnosis might be clustered by ranking the patients to the log E2/log bGS and log E2/log pGS ratio into groups A, B and C, associated with prognostic potential where the risk of progression might be assessed as high (group A), intermediate (group B) and low (group C); the log E2 /log b/pGS clusters might also have potential as clinical models for further investigations. However, further confirmatory studies are needed.

  • Received June 1, 2012.
  • Revision received August 5, 2012.
  • Accepted August 7, 2012.

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Investigative Clinical Study on Prostate Cancer Part IX and X: Estradiol and the Pituitary-Testicular-Prostate Axis at the Time of Initial Diagnosis and Subsequent Cluster Selection of the Patient Population after Radical Prostatectomy
ANTONIO B. PORCARO, CLAUDIO GHIMENTON, ALDO PETROZZIELLO, TEODORO SAVA, FILIPPO MIGLIORINI, MARIO ROMANO, BEATRICE CARUSO, CLAUDIO COCCO, STEFANO ZECCHININI ANTONIOLLI, VINCENZO LACOLA, EMANUELE RUBILOTTA, CARMELO MONACO
Anticancer Research Oct 2012, 32 (10) 4523-4532;
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