TMPRSS2-ERG融合基因在国人前列腺癌组织中的表达及其临床意义

目的探讨TMPRSS2-ERG融合基因在中国人群前列腺癌中的发生率以及其临床病理特征和对内分泌治疗的预后价值。方法收集2010年10月到2014年12月前列腺癌穿刺活检标本96例及病例临床病理资料。所有患者均接受内分泌治疗。利用荧光原位杂交技术检测标本中TMPRRS2-ERG融合基因。比较融合基因阳性和阴性患者的临床病理资料分布及预后差异。结果患者年龄范围为51~93岁,中位年龄为77岁;PSA范围为5.0-5000.0ng/m L。Gleason评分7分的有6例(6.3%),Gleason评分=7分的有38例(39.6%),Gleason评分7分的有52例(54.2%)。临床分期T1-T2有32例,T3-T4有64例;M0为35例,M1为61例。穿刺标本TMPRSS2-ERG阳性有19例(19.8%)。缺失型重排有11例,易位型重排亦有11例,同时含有缺失型和易位型重排患者共3例。融合基因阳性和阴性患者在年龄、PSA、Gleason评分、主要Gleason分级、T分期及M分期的临床分布及内分泌治疗预后方面差异均不具有统计学意义(P0.05)。结论中国人群的前列腺癌TMPRSS2-ERG融合基因的发生率与日韩等亚洲国家人群基本一致,约为20%,远低于欧美人群。TMPRSS2-ERG融合基因阳性和阴性患者的年龄、治疗前PSA水平、Gleason评分、主要Gleason分级以及临床分期的分布不存在差异,同时其对内分泌治疗患者的预后不具备预测价值。     

前列腺穿刺方法及阳性预测因素研究进展

随着影像学技术的发展,新的前列腺穿刺方法朝着更加精准的方向迈进.新技术下的多参数核磁介导靶向穿刺及多参数核磁-超声融合穿刺相较于传统的经会阴穿刺在保证穿刺阳性率的同时,减少了穿刺针数.目前经直肠穿刺及经会阴穿刺法仍为我国临床上最广泛应用的穿刺方法.在行前列腺穿刺前,结合相关临床指标对结果进行预测,可避免重复穿刺,提高检出率.目前已有的研究表明,年龄、前列腺特异性抗原、前列腺特异性抗原密度、游离前列腺特异性抗原/总前列腺特异性抗原、前列腺体积、直肠指诊、前列腺健康指数、前列腺癌基因3为前列腺穿刺结果的预测因素.中国前列腺癌联盟的预测模型比较适合中国人群.     

ERG基因及其与前列腺癌关系

因属于ETS转录因子家族,在很多肿瘤中高表达,与肿瘤的血管生成、转移、浸润、抑制凋亡有关,ERG基因在前列腺癌中主要受TMPRSS2-ERG融合基因的调节。近一半以上的前列腺癌病例表达TMPRSS2-ERG融合基因,其中ERG基因可能是前列腺癌的重要标志物,它的检测有助于前列腺癌的诊断和治疗方法的选择。TMPRSS2-ERG融合基因的存在还会影响前列腺癌病人的预后。本文就ERG基因的生物学特征、作用机制、TMPRSS2-ERG的融合机制以及ERG基因与前列腺癌的诊断、治疗和预后的关系作一综述。     

建立预测中国人前列腺重复穿刺活检阳性的数学模型

目的:建立可以预测国人经直肠超声引导下重复穿刺活检阳性的数学模型。方法:170例在首次穿刺活检诊断为前列腺良性病变的患者行重复穿刺。记录并分析患者的年龄、前列腺体积、血清PSA、游离PSA(f-PSA)/总PSA(t-PSA)、PSA上升速度、PSA密度(PSAD)、直肠指检(DRE)、首次穿刺病理结果等相关因素。将变量通过逐步回归建立回归方程,在此基础上建立重复穿刺活检阳性的危险评分数学模型。该模型的预测价值通过受试者工作曲线下面积来评估。结果:170例前列腺重复穿刺活检的患者中,前列腺癌的穿刺检出率为31.8%(54/170)。建立的数学模型影响因素包括:患者的年龄、前列腺体积、PSA、f-PSA/t-PSA、PSA上升速度、PSAD、DRE、首次穿刺结果是否为上皮内瘤变。该模型预测价值较高,曲线下面积为82.4%,大于患者PSAD、前列腺体积、PSA上升速度、f-PSA/t-PSA、DRE等单因素的66.9%、72.6%、69.6%、69.3%、58.5%。结论:该数学模型是临床多因素综合分析基础上建立的,可以很好地预测前列腺重复穿刺活检阳性的概率。     

单中心前列腺穿刺活检结果查询表的建立

目的：综合利用PSA及其相关参数建立能够简便查询的前列腺穿刺阳性率查询表.方法纳入2009年7月至2015年3月在解放军总医院行前列腺穿刺活检的患者,收集前列腺体积、游离PSA(free PSA,fPSA)和总PSA(total PSA,tPSA)等临床资料.多因素Logistic回归分析预测前列腺癌的独立性影响因素,并利用相关因素建立前列腺穿刺阳性结果查询表.结果资料完整且病理结果为前列腺癌和前列腺增生的患者纳入研究,共1077例.根据PSA水平分为0~2.5、2.6~4.0、4.1~10.0、10.1~20.0和＞20.0 ng/ml 5组,前列腺癌检出率分别为20.9％、20.0％、37.3％、48.1％和80.2％,随着PSA水平的升高,前列腺癌检出率也明显升高.多因素Logistic回归分析发现tPSA、fPSA和前列腺体积均为前列腺癌的独立性预测因素,tPSA、fPSA百分比(free to total PSA,f/tPSA)和PSA密度(PSA density,PSAD)在前列腺癌和前列腺增生两组间存在显著差异(P＜0.05),综合利用上述3个指标建立前列腺阳性穿刺查询表.结论本研究根据 tPSA、f/tPSA和PSAD建立的查询表为临床前列腺穿刺活检提供了一个简便实用的阳性率查询工具.     

DOPEY2在TMPRSS2-ERG基因融合阴性前列腺癌中的表达及临床意义

目的探讨DOPEY2在TMPRSS2-ERG基因融合阴性前列腺癌中的表达及其临床意义。方法本研究通过RT-PCR和Western Blot技术检测前列腺癌细胞株VCa P和PC-3中ERG和DOPEY2的表达情况,同时,采用免疫组化技术检测46例前列腺癌根治术后的石蜡标本中ERG和DOPEY2的表达情况,分析两者的表达以及与临床病理特征之间的关系。结果 DOPEY2在TMPRSS2-ERG基因融合阳性前列腺癌细胞株VCa P中的m RNA和蛋白表达水平,均比TMPRSS2-ERG基因融合阴性前列腺癌细胞株PC-3低,且差异均有统计学意义(P0.05)。免疫组化结果显示,DOPEY2在TMPRSS2-ERG基因融合阴性组织中的阳性表达率高于基因融合阳性组(76.5%和33.3%,P0.05),且DOPEY2阳性的患者具有较高的Gleason分级和T分期(P0.05)。ERG蛋白的阳性率为26.1%(12/46),且与低Gleason评分组相关,而与患者的年龄、血浆PSA值,病理T分期和远处转移等参数均无相关性。结论 DOPEY2在TMPRSS2-ERG基因融合阴性前列腺癌中的表达高于TMPRSS2-ERG基因融合阳性前列腺癌,DOPEY2可能作为一个有潜力的分子标记物指导前列腺癌分期及判断预后。     

前列腺穿刺活检结果预测模型的建立

目的基于前列腺特异性抗原(PSA)等指标,建立能够预测前列腺穿刺活检结果的数学模型.方法收集2009年7月至2015年3月在解放军总医院进行前列腺穿刺活检患者的年龄、前列腺体积、游离PSA(fPSA)和总PSA(tPSA)等临床资料.所有研究对象中随机选择80％为建模组,其余20％为验证组.在建模组中利用单因素和多因素 Logistic 分析筛选出预测前列腺癌的独立性影响因素,构建回归方程,并以此为基础建立预测前列腺穿刺结果的数学模型.利用受试者工作特征(receiver operating characteristic,ROC)曲线评估该模型对前列腺癌的诊断价值,并与临床常用的 PSA 及其相关参数比较诊断价值的差异.结果选取资料完整且 tPSA 100 ng/ml以下的患者纳入研究,共958例.其中建模组767例(tPSA 4~20 ng/ml者587例),验证组191例.在建模组中,将所有指标纳入单因素和多因素 Logistic 回归分析,发现年龄、tPSA 和前列腺体积是前列腺癌独立的预测因素.将所有指标(包括 fPSA)纳入回归方程,构建数学模型Y＝－4．765＋0.074×(年龄)＋0．057×(tPSA)＋0．052×(fPSA)－0．029×(前列腺体积).在建模组和验证组中, ROC曲线分析显示该模型预测前列腺癌的 ROC 曲线下面积高于 tPSA、f/tPSA 和 PSA 密度.取Y＝－0．076,即约登指数最大值作为本模型最佳临界值,预测前列腺癌的灵敏度为76．2％、特异度为76．6％、阳性预测值76．5％、阴性预测值76．3％.结论本预测模型与单独应用PSA及其相关参数相比具有更高的诊断价值,并且可以在不增加患者检查项目的前提下提高预测前列腺癌的能力.     

基于PI-RADS v2评分在PSA 4～10ng/mL患者前列腺癌预测模型的构建及验证

目的:联合核磁共振第2版前列腺影像报告和数据系统(prostate imaging reporting and data system version 2,PI-RADS v2)与其他临床指标,建立前列腺特异性抗原(PSA)"灰区"(4～10 ng/mL)患者的前列腺癌(prostate cancer, PCa)预测模型,并验证模型的准确性。方法:回顾性分析2016年1月—2020年12月在我院行前列腺穿刺活检的PSA"灰区"患者的临床资料,包括年龄、血清PSA、游离/总PSA比值(f/tPSA)、前列腺体积(prostate volume, PV)、PSA密度(PAS density, PASD)、经直肠前列腺超声(transrectal ultrasonography, TRUS)结果、PI-RADS v2评分等临床指标。其中2016年1月—2019年12月纳入病例作为模型构建组,2020年1月—2020年12月为模型验证组。采用二元logistic单因素及多因素分析计算PCa的独立预测因素,依据回归系数建立预测模型,通过ROC曲线下面积(area under curve, AUC...     

建立一种简易评分系统预测前列腺穿刺活检前列腺癌阳性率

目的:分析经直肠前列腺穿刺活检前列腺癌阳性率的预测因素。方法:总结2006年1月至2014年4月进行经直肠超声引导下前列腺穿刺活检患者的资料,包括年龄(age)、体质指数(BMI)、症状(syptoms)、直肠指检(DRE)、血清总PSA(t PSA)、游离PSA(f PSA)、游离PSA与总PSA比值(f/t PSA)、前列腺体积(PV)、PSA密度(PSAD)。通过单因素方差分析和多因素回归模型,筛选与活检阳性率相关的危险因素。在此基础上构建一个评分系统作为在活检前预测前列腺癌阳性率的工具,并通过受试者工作特征(ROC)曲线计算假阳性率,以检测评分系统的敏感性。结果:在385例经直肠超声引导下穿刺活检患者中,共139例患者被诊断为前列腺癌,阳性率36.1%。单因素分析显示,在活检阳性组和阴性组之间,年龄(P<0.01)、DRE(P<0.01)、t PSA(P<0.01)、f PSA(P<0.01)、f/t PSA(P<0.01)、PV(P<0.01)和PSAD(P<0.01)在前列腺癌患者中比例均高于活检阴性人群。将单因素回归有意义的因素纳入多因素逐步Logistic分析,结果显示,年龄、t PSA、f/t PSA、PV和PSAD是经直肠反复前列腺活检阳性的独立影响因素,其比值比(ORs)及其相应的95%可信区间(95%CIs)分别为1.07(1.05~1.16)、1.05(1.02~1.15)、0.97(0.86~0.99)、0.98(0.87~0.96)和1.79(1.48~2.06)。根据其OR值,设定年龄>71岁(中位数)、t PSA>14.1μg/L(中位数)、f/t PSA<14.07(中位数)、PV<42.8 ml(中位数)、PSAD>0.31μg/L/ml(中位数)分别各计1分,总分为5分。将385例患者的资料通过评分系统计算前列腺癌的检出率,发现评分为0、1、2、3、4、5分的患者前列腺癌的检出率分别为7.69%、8.98%、15.19%、39.39%、54.55%和72.15%。ROC曲线提示曲线下面积为0.82(95%CI:0.80~0.84,P<0.01)。另外,评分3~5分的患者比0~2分的患者前列腺癌的检出率高50%以上(64%vs 11%,P<0.01)。结论:该评分系统可以帮助泌尿科医师确定需要行前列腺活检的患者。     

前列腺癌早期诊断相关标志物的研究进展

前列腺癌是男性泌尿生殖系统中最常见的肿瘤之一,我国近年来发病率也逐渐增加。前列腺特异性抗原(PSA)的广泛应用,由于提高了前列腺癌的早期诊断率而降低了患者死亡率,但由于其特异性低,造成了大量的过度诊断与治疗。而以PSA为基础而衍生的一些指标包括[-2]proPSA、前列腺健康指数(PHI)、4Kscore~提高了前列腺癌早期诊断的特异性。此外,尿中的标志物如前列腺癌抗原3(PCA3)、TMPRSS2-ERG融合基因等对指导前列腺癌的早期诊断也发挥了重要作用。其中,PHI和尿PCA3检测已被美国食品药品管理局(FDA)批准用于临床。     

Prospective Multicentre Evaluation of PCA3 and TMPRSS2-ERG Gene Fusions as Diagnostic and Prognostic Urinary Biomarkers for Prostate Cancer

Background

Prostate cancer antigen 3 (PCA3) and v-ets erythroblastosis virus E26 oncogene homolog (TMPRSS2-ERG) gene fusions are promising prostate cancer (PCa) specific biomarkers that can be measured in urine.

Objective

To evaluate the diagnostic and prognostic value of Progensa PCA3 and TMPRSS2-ERG gene fusions (as individual biomarkers and as a panel) for PCa in a prospective multicentre setting.

Design, setting, and participants

At six centres, post–digital rectal examination first-catch urine specimens prior to prostate biopsies were prospectively collected from 497 men. We assessed the predictive value of Progensa PCA3 and TMPRSS2-ERG (quantitative nucleic acid amplification assay to detect TMPRSS2-ERG messenger RNA [mRNA]) for PCa, Gleason score, clinical tumour stage, and PCa significance (individually and as a marker panel). This was compared with serum prostate-specific antigen and the European Randomised Study of Screening for Prostate Cancer (ERSPC) risk calculator. In a subgroup (n = 61) we evaluated biomarker association with prostatectomy outcome.

Outcome measurements and statistical analysis

Univariate and multivariate logistic regression analysis and receiver operating curves were used.

Results and limitations

Urine samples of 443 men contained sufficient mRNA for marker analysis. PCa was diagnosed in 196 of 443 men. Both PCA3 and TMPRSS2-ERG had significant additional predictive value to the ERSPC risk calculator parameters in multivariate analysis (p < 0.001 and resp. p = 0.002). The area under the curve (AUC) increased from 0.799 (ERSPC risk calculator), to 0.833 (ERSPC risk calculator plus PCA3), to 0.842 (ERSPC risk calculator plus PCA3 plus TMPRSS2-ERG) to predict PCa. Sensitivity of PCA3 increased from 68% to 76% when combined with TMPRSS2-ERG. TMPRSS2-ERG added significant predictive value to the ERSPC risk calculator to predict biopsy Gleason score (p < 0.001) and clinical tumour stage (p = 0.023), whereas PCA3 did not.

Conclusions

TMPRSS2-ERG had independent additional predictive value to PCA3 and the ERSPC risk calculator parameters for predicting PCa. TMPRSS2-ERG had prognostic value, whereas PCA3 did not. Implementing the novel urinary biomarker panel PCA3 and TMPRSS2-ERG into clinical practice would lead to a considerable reduction of the number of prostate biopsies.     

Towards Early and More Specific Diagnosis of Prostate Cancer? Beyond PSA: New Biomarkers Ready for Prime Time

ContextThe current standard for early detection of prostate cancer (PCa) consists of a digital rectal examination (DRE) and a serum test for prostate-specific antigen (PSA). However, there is no definitive PSA level that can accurately differentiate men with cancer from men with benign prostatic hyperplasia. A large population of men with chronically elevated serum PSA and one or more negative prostate biopsies has now emerged who are at risk of developing clinically significant prostate cancer as they age. However, serum PSA and its derivative assays may not allow effective monitoring of these patients for PCa, and many consequently undergo repeat biopsies. While prostate biopsy remains the gold standard for PCa diagnosis, this method has its own limitations and associated comorbidities.ObjectiveMore accurate diagnostic tests are needed to help guide decisions to biopsy the prostate, and recent developments are reviewed in this paper.Evidence acquisitionPublications on prostate cancer gene 3 (PCA3) since 1999, the date the gene was described for the first time.Evidence synthesisDirect detection of cancer cells in biological fluids is attractive due to the expected improvement in specificity compared with the measurement of surrogate protein markers in blood. In addition, gene-based assays for cancer cell detection should be synergistic with immunoassays for blood antigens. PCA3 levels in urine is the first commercially available noninvasive molecular test for the diagnosis of PCa and therefore provides a case study for the successful translation of a molecular marker from the research laboratory to clinical practice.ConclusionsThis paper describes the development of PCA3-based molecular urine tests, and we also review the most recent data demonstrating the potential diagnostic and prognostic utilities of PCA3 and the initial findings of the TMPRSS2-ERG gene fusion testing.     

Development of a new nomogram for predicting the probability of a positive initial prostate biopsy in Japanese patients with serum PSA levels less than 10 ng/mL

Objectives:   Although several nomograms for prostate cancer detection have been developed for Western populations, the models constructed on Japanese data would be more useful for the Japanese population because of various differences between Western and Asian populations. We previously developed a model for predicting the probability of a positive initial prostate biopsy using clinical and laboratory data from Japanese males. In the present study, a predictive model for Japanese males with a prostate-specific antigen (PSA) < 10 ng/mL was developed to guide decision-making for prostate biopsies.
Methods:   The age, total PSA level, free to total PSA ratio, prostate volume, and the digital rectal examination findings of 1037 Japanese males with a PSA < 10 ng/mL undergoing initial prostate biopsy as part of individual screening were analyzed. For study validation, 20% of these data was randomly reserved. Logistic regression analysis estimated relative risk, 95% confidence intervals, and P -values.
Results:   Age and the independent predictors of a positive biopsy result (elevated PSA, decreased free to total PSA ratio, small prostate volume, and abnormal digital rectal examination findings) were used to develop a predictive nomogram. The area under the receiver operating characteristic curve was significantly higher for the model (73.0%) than for PSA alone (55.0%). If externally validated, the use of this nomogram could reduce unnecessary biopsies by 26% and overall prostate biopsies by 7.8%.
Conclusions:   This predictive nomogram could provide more precise risk-analysis information for individual Japanese patients with PSA levels less than 10 ng/mL and may help to identify patients who need a prostate biopsy.     

Prostate cancer gene 3 urine assay for prostate cancer in Japanese men undergoing prostate biopsy

Objectives: To examine the clinical utility of the prostate cancer gene 3 (PCA3) urine test in predicting prostate cancer in Japanese men undergoing prostate biopsy. Method: The study group included 105 men who underwent extended prostate biopsy based on an elevated serum prostate‐specific antigen (PSA). In all cases, the patients' race was Asian. Urine specimens were collected after digital rectal examination, and PCA3 score (PCA3/PSA mRNA) was determined in the urine using the APTIMA PCA3 assay. PCA3 score was investigated for a correlation with serum PSA, prostate volume (PV), PSA density and biopsy outcome. Results: All urine samples collected were successfully analyzed (i.e. the informative specimen rate was 100%). Biopsy showed prostate cancer in 38 men (36%). The PCA3 score was not associated with serum PSA nor PV. The median PCA3 score in prostate cancer was significantly higher than that in negative biopsy (59.5 vs 14.2 P < 0.0001). The probability of prostate cancer was 69% at a PCA3 score of more than 50 and 5% at a PCA3 score of less than 20. On multivariable logistic regression, PSA density (P < 0.05) and PCA3 score (P < 0.0001) were the independent predictors for prostate cancer. There was no significant difference in AUC between PCA3 score and PSA density. The combination of PCA3 score and PSA density increased the AUC from 0.72 for PSA alone to 0.88. Conclusion: The specificity of the PCA3 urine assay for prostate cancer was excellent in Japanese men undergoing biopsy. PCA3 score could improve the prediction for prostate cancer and help to better select men who might benefit from prostate biopsy.     

A nomogram based on age,prostate-specific antigen level,prostate volume and digital rectal examination for predicting risk of prostate cancer

Nomograms for predicting the risk of prostate cancer developed using other populations may introduce sizable bias when applied to a Chinese cohort. In the present study, we sought to develop a nomogram for predicting the probability of a positive initial prostate biopsy in a Chinese population. A total of 535 Chinese men who underwent a prostatic biopsy for the detection of prostate cancer in the past decade with complete biopsy data were included. Stepwise logistic regression was used to determine the independent predictors of a positive initial biopsy. Age, prostate-specific antigen (PSA), prostate volume (PV), digital rectal examination (DRE) status, % free PSA and transrectal ultrasound (TRUS) findings were included in the analysis. A nomogram model was developed that was based on these independent predictors to calculate the probability of a positive initial prostate biopsy. A receiver-operating characteristic curve was used to assess the accuracy of using the nomogram and PSA levels alone for predicting positive prostate biopsy. The rate for positive initial prostate biopsy was 41.7% (223/535). The independent variables used to predict a positive initial prostate biopsy were age, PSA, PV and DRE status. The areas under the receiver-operating characteristic curve for a positive initial prostate biopsy for PSA alone and the nomogram were 79.7% and 84.8%, respectively. Our results indicate that the risk of a positive initial prostate biopsy can be predicted to a satisfactory level in a Chinese population using our nomogram. The nomogram can be used to identify and counsel patients who should consider a prostate biopsy, ultimately enhancing accuracy in diagnosing prostate cancer.     

Prostate cancer detection in the "grey area" of prostate-specific antigen below 10 ng/ml: head-to-head comparison of the updated PCPT calculator and Chun's nomogram, two risk estimators incorporating prostate cancer antigen 3

Background

Prostate cancer antigen 3 (PCA3) holds promise in diagnosing prostate cancer (PCa), but no consensus has been reached on its clinical use. Multivariable predictive models have shown increased accuracy over individual risk factors.

Objective

To compare the performance of the two available risk estimators incorporating PCA3 in the detection of PCa in the “grey area” of prostate-specific antigen (PSA) <10 ng/ml: the updated Prostate Cancer Prevention Trial (PCPT) calculator and Chun's nomogram.

Design, setting, and participants

Two hundred eighteen patients presenting with an abnormal PSA (excluding those with PSA >10 ng/ml) and/or abnormal digital rectal examination were prospectively enrolled in a multicentre Italian study between October 2008 and October 2009. All patients underwent ≥12-core prostate biopsy.

Measurements

PCA3 scores were assessed using the Progensa assay (Gen-Probe, San Diego, CA, USA). Comparisons between the two models were performed using tests of accuracy (area under the receiver operating characteristic curve [AUC-ROC]), calibration plots, and decision curve analysis. Biopsy predictors were identified by univariable and multivariable logistic regression. In addition, performance of PCA3 was analysed through AUC-ROC and predictive values.

Results and limitations

PCa was detected in 73 patients (33.5%). Among predictors included in the models, only PCA3, PSA, and prostate volume retained significant predictive value. AUC-ROC was higher for the updated PCPT calculator compared to Chun's nomogram (79.6% vs 71.5%; p = 0.043); however, Chun's nomogram displayed better overall calibration and a higher net benefit on decision curve analysis. Using a probability threshold of 25%, no high-grade cancers would be missed; the PCPT calculator would save 11% of biopsies, missing no cancer, whereas Chun's nomogram would save 22% of avoidable biopsies, although missing 4.1% non–high-grade cancers. The small number of patients may account for the lack of statistical significance in the predictive value of individual variables or model comparison.

Conclusions

Both Chun's nomogram and the PCPT calculator, by incorporating PCA3, can assist in the decision to biopsy by assignment of an individual risk of PCa, specifically in the PSA levels <10 ng/ml.     

荧光原位杂交技术在前列腺癌诊断中的临床应用

目的建立TMPRSS2/ETS(ERG、ETV1、ETV4)融合基因的荧光原位杂交(FISH)检测和评估方法,并探讨其对于前列腺癌的诊断价值。方法对50例前列腺癌样本、15例正常前列腺组织及20例良性前列腺增生样本应用三组国产FISH探针顺序检测TMPRSS2/ERG、TMPRSS2/ETV1及TMPRSS2/ETV4融合基因,建立FISH技术诊断前列腺癌的阈值,并计算敏感性、特异性、阳性预测值(+PV)和阴性预测值(-PV)。结果三组探针的联合敏感性达到90%,其中TMPRSS2-ERG检测敏感性为78%,总体特异性为100%,阳性预测值为100%,阴性预测值为87.5%。结论应用FISH技术检测TMPRSS2/ETS(ERG、ETV1、ETV4)融合基因诊断前列腺癌具有较高的敏感性和特异性,显示出良好的临床应用前景。     

Proprostate-specific antigen: Its usefulness in the era of multiple-core prostate biopsy

Objective:   To investigate the clinical significance of prostate-specific antigen (PSA)-related markers, including the precursor form of PSA, using the full-range area under the curve of receiver operating characteristics (AUC-ROC), partial AUC-ROC (pAUC-ROC) and multiple logistic regression analyses.
Methods:   Participants consisted of 257 consecutive men (PSA range 4.1–20 ng/mL) undergoing transrectal ultrasonography-guided age-adjusted and prostate volume-adjusted multiple-core prostate biopsy at Gunma University Hospital between January 2003 and May 2005. Sensitivity, specificity, AUC-ROC and pAUC-ROC of the ratio of free PSA to total PSA (free/total PSA), PSA density (PSAD) and PSAD adjusted by transition zone volume, the ratio of [−7/−5] precursor forms of PSA (proPSA) to free PSA (pro/free PSA), the ratio of pro to total PSA and the ratio of pro to free/total PSA (pro/f/t ratio) were investigated. Multiple logistic regression analyses were also carried out to investigate the independency of selected clinical parameters.
Results:   According to pAUC-ROC analyses, pro/free PSA and the pro/f/t ratio were the two best PSA-related parameters in terms of maintaining high sensitivity and avoiding unnecessary biopsy. Multiple regression analyses revealed that not only pro/free PSA, but also age, findings on digital rectal examination and PSAD were independent parameters for predicting biopsy outcomes.
Conclusion:   Pro/free PSA and pro/f/t ratio may be excellent predictive markers for prostate cancer, allowing unnecessary biopsy to be avoided while maintaining high sensitivity at 90% or 95%, in the PSA range 4–20 ng/mL.