Prostate cancer is the most common cancer in men and diagnosis involves a combination of assessments. Levels of the biomarker prostate-specific antigen (PSA) are commonly measured, but do not always equate to cancer status. Testing of PSA in combination with other biomarkers may help to improve diagnostic and prognostic accuracy, as well as minimizing overdiagnosis as well as unnecessary intervention. This article provides a summary of the information currently known about biomarkers showing promise for use in prostate cancer screening.
by Dr Alexandra Tabakin, Dr Sung Un Bang and Dr Isaac Y. Kim
Introduction
Prostate cancer is the most commonly diagnosed cancer type in the USA and second leading cause of cancer deaths in men. In 2018, there will be an estimated 164 690 new cases with an estimated 29 430 deaths [1]. Although many prostate cancers are indolent in nature and can be safely monitored with active surveillance, a significant proportion of patients will require intervention with surgery, radiation, or other therapies. One of the major challenges in treating prostate cancer is risk stratification and differentiating clinically significant prostate cancers in order to avoid overdiagnosis and overtreatment [2]. To do so, patients undergo risk stratification, which conventionally includes a combination of prostate-specific antigen (PSA) screening, digital rectal exam (DRE), trans-rectal ultrasonography (TRUS)-guided biopsy. Currently clinically insignificant prostate cancer, according to Epstein criteria, is defined as cancer with preoperative PSA <10ng/ml, clinical stage <T1c, Gleason score <6, PSA density <0.15, <2 positive biopsy cores, and <50% cancer involvement in any core [3–5]. However, as we learn more about the heterogeneity of prostate cancer tumours, various serum biomarkers have been investigated to improve diagnostic and prognostic accuracy and minimize treatment. In this review, we discuss various biomarkers and their utilization for the prediction of clinically significant prostate cancer.
Serum biomarkers
PSA
PSA, or prostate-specific antigen, is a serine protease released by the prostate. PSA gained notoriety in the 1980s when it was reported to have various uses including screening, monitoring disease progression, and detecting recurrence of the cancer. As PSA screening for prostate cancer increased, the incidence of prostate cancer also rose in the 1990s. However, PSA only has a 25–40% specificity rate for prostate cancer and can be elevated with infection, trauma, and benign prostatic hyperplasia (BPH) [6]. In fact, about 15% of men with a low level of PSA (<4.0 ng/ml) have prostate cancer [7].
Because the harms of biopsy and prostate cancer treatment may outweigh the benefits in some patients with clinically insignificant prostate cancer, efforts have been made to improve the validity of PSA in differentiating benign conditions and prostate cancer. One such effort is the use of free PSA; those with an elevated PSA and a lower serum percentage of free PSA (%f-PSA) are more likely to have BPH rather than prostate cancer [8]. The Prostate Health Index (PHI) formula incorporates serum total PSA, free PSA, and the [−2]proPSA to discriminate Gleason 3+4 and greater cancers with 90% sensitivity and 17% specificity [9]. 4K score is another novel test which is comprised of total PSA, free PSA, intact PSA, and human kallikrein-related peptidase 2 to detect clinically significant prostate cancer and discern those who would benefit from a prostate biopsy while preventing 30–58% of biopsies [10].
PAP
Prostatic acid phosphatase (PAP) was the first popularized prostate cancer serum biomarker, but was eventually replaced by PSA, as it is less sensitive in diagnosing prostate cancer and detecting recurrence. Elevated PAP level has been associated with a high risk of bone metastases [11], significantly shortened overall survival [12] as well as disease-free survival [13], and increased risk of biochemical recurrence [14]. Interestingly, recent studies have shown that PAP may be useful in detecting high-risk clinically significant prostate cancer patients; it is speculated that PAP may be associated with micro-metastatic disease prior to treatment, and therefore, predict response to treatment [15].
NLR, ANC, ALC
Inflammation and tissue microenvironment are important factors in cancer development. Although the temporal relationship is not well established, a lymphocyte-mediated immune response is thought to occur early in the development of prostate cancer. Neutrophil-to-lymphocyte ratio (NLR) compares the activity of both neutrophils and lymphocytes in the inflammatory response. NLR is a useful prognostic biomarker in mCRPC, where a higher score correlates less relative lymphocyte activity and a worse prognosis. When looking at localized low-risk prostate cancer, studies have shown that NLR is not associated with upstaging, upgrading, or biochemical recurrence. However, increased absolute lymphocyte count (ALC) and absolute neutrophil count (ANC) were associated with upstaging and lower 5-year biochemical recurrence-free survival. More development on these markers may guide clinicians in re-stratifying patients who meet conventional criteria for low-risk prostate cancer [16].
Urine biomarkers
PCA3
Urinary prostate cancer antigen 3 (PCA3) is among the most promising non-invasive biomarker among non-PSA based tests, as it is overexpressed in over 95% of prostate cancers [6]. PCA3 is a long noncoding RNA collected from shed prostate cells during urination. PCA3 is a more specific biomarker for prostate cancer because, unlike PSA, PCA3 levels are not influenced by prostate size, BPH, prostatitis, or the use of 5α-reductase inhibitors [17]. At the genetic level, PCA3 may help distinguish between prostate cancer and high-grade prostatic intraepithelial neoplasia (HG-PIN), as PCA3 is seldom expressed in HG-PIN [18]. Several studies have demonstrated that a higher PCA3 score correlates with clinically significant prostate cancer and larger tumour volume, therefore potentially aiding in selecting patients for active surveillance [19]. In 2012, the FDA approved the PROGENSA PCA3 assay predict men who would benefit from a repeat biopsy in those with a previous negative prostate biopsy [6]. In a recent meta-analysis of 46 clinical trials, the sensitivity and specificity of PROGENSA PCA3 was 65% and 73%, respectively [20].
Genetic mutations
TMPRSS2::ERG
TMPRSS2::ERG, or T2:ERG, gene fusions constitute 90% of gene fusions implicated in prostate cancer, as well as half of all prostate cancers [21, 22]. When the androgen responsive regulatory element TMPRSS2 and the gene for the transcription factor ERG are fused together, androgen-driven genes are overexpressed and tumorigenesis occurs [21]. When used alone, urinary T2:ERG RNA has a reported 86% specificity and 45% sensitivity in prostate cancer detection. However, when used in conjunction with PCA3, specificity and sensitivity improve to 90% and 80%, respectively [6, 23]. Moreover, this test may prevent up to 42% of unnecessary biopsies, limiting healthcare costs [24].
PTEN
Loss of the tumour-suppressor gene, PTEN, or phosphatase and tensin homologue, leading to activation of the PI3K/AKT/mTOR signalling has been found in both early stage and castrate-resistant prostate cancers. Preclinical data show that PI3K pathway activation is related to resistance to androgen deprivation, leading to disease progression and poor response to treatment. In mouse models, conditional deletion of PTEN initially led to the development of prostate hyperplasia and later on invasive and metastatic prostate cancers likely by modulating the p110β catalytic subunit of PI3K. In addition, ablation of p110β hindered AKT signalling and reduced tumorigenesis [25]. In a cohort of 77 men, loss of PTEN at initial prostate biopsy was predictive of the development of castrate-resistant prostate cancer, response to androgen deprivation therapy, and prostate-cancer-specific mortality [26]. Additionally, decreased PTEN expression has been associated with increased risk of biochemical and clinical recurrence after prostatectomy [27]. Therefore, the association between castrate-resistant prostate cancer and PTEN loss as well as PI3K/AKT/mTOR pathway activation suggests that PTEN may have prognostic value in prostate cancer risk stratification.
CHD1
The CHD1 gene, encoding chromodomain helicase DNA-binding protein 1, is commonly deleted in 10–26% of all prostate cancers. The loss of CHD1 affects the ability to repair DNA double-strand breaks via homologous recombination. CHD1 deletion has generally been associated with a poor prognosis. However, studies have demonstrated tumours with CHD1 deletions to be sensitive to both PARP inhibitors and carboplatin, both in vitro and in vivo, suggesting that future research may be able to identify to response to treatment based off of tumour genotypes [28].
Circulating biologics
Circulating tumour cells
Circulating tumour cells (CTCs) are defined as cells that leave the site of a primary cancer, travel through the bloodstream, and settle at other sites in the body where they grow into new tumours, or metastases [29]. In 2004, CellSearch Circulating Tumor Cell System was approved by the FDA as an assay for enumerating CTCs. In recent studies, CTC count, deemed the ‘liquid biopsy’, has been shown to have a role in predicting overall survival and response to treatment, risk stratification, and detecting metastases. In addition, using CTCs to detect biomarkers, such as ERG, PTEN, and AR may allow for personalized treatments based on tumour genomes [9, 30].
Circulating exosomes
Circulating prostate cancer-related exosomes are double-membrane vesicles carrying RNA and pro-oncogenic molecules, which induce malignant transformation in normal cells. ExoDx prostate Intelliscore urine exosome assay (developed by Exosome Diagnostics Inc.) detects exosomal RNA expression of ERG, PCA3 and SPDEF (SAM pointed domain containing ETS transcription factor) in voided urine samples. A score is generated that is able to predict high-grade prostate cancer (Gleason >7) with a negative predictive value of 91%. This assay may be useful in discriminating clinically significant prostate cancer and reducing the number of unnecessary biopsies [31].
Conclusion
The emergence and widespread usage of PSA as a routine screening test for prostate cancer allows for early detection and risk stratification. Testing for PSA in combination with novel biomarkers such as PCA3, TMPRSS2::ERG, PTEN, and others may improve our diagnostic abilities, given the heterogeneity of prostate cancers and their treatments. There are many challenges in establishing useful biomarkers including creating affordable and accessible testing, determining cut-offs, and determining accuracy. As the clinical utility of these biomarkers is further defined, we hope to better risk stratify patients and select appropriate treatments early on in diagnosis. Further research efforts should focus on the synergism between the Epstein criteria, biomarker utility, and how to best bring these tools from bench to bedside.
References
1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018; 68(1): 7–30.
2. Lees K, Durve M, Parker C. Active surveillance in prostate cancer: patient selection and triggers for intervention. Curr Opin Urol 2012; 22(3): 210–215.
3. D’Amico AV, Whittington R, Malkowicz SB, Weinstein M, Tomaszewski JE, Schultz D, et al. Predicting prostate specific antigen outcome preoperatively in the prostate specific antigen era. J Urol 2001; 166(6): 2185–2188.
4. Epstein JI, Chan DW, Sokoll LJ, Walsh PC, Cox JL, Rittenhouse H, et al. Nonpalpable stage T1c prostate cancer: prediction of insignificant disease using free/total prostate specific antigen levels and needle biopsy findings. J Urol 1998; 160(6): 2407–2411.
5. Klotz L, Zhang L, Lam A, Nam R, Mamedov A, Loblaw A. Clinical results of long-term follow-up of a large, active surveillance cohort with localized prostate cancer. J Clin Oncol 2010; 28(1): 126–131.
6. Sanguedolce F, Cormio A, Brunelli M, D’Amuri A, Carrieri G, Bufo P, et al. Urine TMPRSS2: ERG fusion transcript as a biomarker for prostate cancer: literature review. Clin Genitourin Cancer 2016; 14(2): 117–121.
7. Prensner JR, Rubin MA, Wei JT, Chinnaiyan AM. Beyond PSA: the next generation of prostate cancer biomarkers. Sci Transl Med 2012; 4(127): 127rv3.
8. Grossklaus DJ, Smith JA, Shappell SB, Coffey CS, Chang SS, Cookson MS. The free/total prostate-specific antigen ratio (%fPSA) is the best predictor of tumor involvement in the radical prostatectomy specimen among men with an elevated PSA. Urol Oncol 2002; 7(5): 195–198.
9. Chistiakov DA, Myasoedova VA, Grechko AV, Melnichenko AA, Orekhov AN. New biomarkers for diagnosis and prognosis of localized prostate cancer. Semin Cancer Biol 2018; doi: 10.1016/j.semcancer.2018.01.012.
10. Parekh DJ, Punnen S, Sjoberg DD, Asroff SW, Bailen JL, Cochran JS, et al. A Multi-institutional prospective trial in the USA confirms that the 4Kscore accurately identifies men with high-grade prostate cancer. Eur Urol 2015; 68(3): 464–470.
11. Whitesel JA, Donohue RE, Mani JH, Mohr S, Scanavino DJ, Augspurger RR, et al. Acid phosphatase: its influence on the management of carcinoma of the prostate. J Urol 1984; 131(1): 70–71.
12. Johnson DE, Prout GR, Scott WW, Schmidt JD, Gibbons RP, et al. Clinical significance of serum acid phosphatase levels in advanced prostatic carcinoma. Urology 1976; 8(2): 123–126.
13. Moul JW, Connelly RR, Perahia B, McLeod DG. The contemporary value of pretreatment prostatic acid phosphatase to predict pathological stage and recurrence in radical prostatectomy cases. J Urol 1998; 159(3): 935–940.
14. Han M, Piantadosi S, Zahurak ML, Sokoll LJ, Chan DW, Epstein JI, et al. Serum acid phosphatase level and biochemical recurrence following radical prostatectomy for men with clinically localized prostate cancer. Urology 2001; 57(4): 707–711.
15. Faiena I, Kim S, Farber N, Kwon YS, Shinder B, Patel N, et al. Predicting clinically significant prostate cancer based on pre-operative patient profile and serum biomarkers. Oncotarget 2017; 8(65): 109783–109790.
16. Kwon YS, Han CS, Yu JW, Kim S, Modi P, Davis R, et al. Neutrophil and lymphocyte counts as clinical markers for stratifying low-risk prostate cancer. Clin Genitourin Cancer 2016; 14(1): e1–8.
17. Roobol MJ, Schröder FH, van Leeuwen P, Wolters T, van den Bergh RCN, van Leenders GJLH, et al. Performance of the prostate cancer antigen 3 (PCA3) gene and prostate-specific antigen in prescreened men: exploring the value of PCA3 for a first-line diagnostic test. Eur Urol 2010; 58(4): 475–481.
18. Wei W, Leng J, Shao H, Wang W. High PCA3 scores in urine correlate with poor-prognosis factors in prostate cancer patients. Int J Clin Exp Med 2015; 8(9): 16606–16612.
19. Ploussard G, Epstein JI, Montironi R, Carroll PR, Wirth M, Grimm M-O, et al. The contemporary concept of significant versus insignificant prostate cancer. Eur Urol 2011; 60(2): 291–303.
20. Cui Y, Cao W, Li Q, Shen H, Liu C, Deng J, et al. Evaluation of prostate cancer antigen 3 for detecting prostate cancer: a systematic review and meta-analysis. Sci Rep 2016; 6: 25776.
21. Burkhardt L, Fuchs S, Krohn A, Masser S, Mader M, Kluth M, et al. CHD1 is a 5q21 tumor suppressor required for ERG rearrangement in prostate cancer. Cancer Res 2013; 73(9): 2795–2805.
22. Tomlins SA, Laxman B, Varambally S, Cao X, Yu J, Helgeson BE, et al. Role of the TMPRSS2-ERG gene fusion in prostate cancer. Neoplasia 2008; 10(2): 177–188.
23. Salami SS, Schmidt F, Laxman B, Regan MM, Rickman DS, Scherr D, et al. Combining urinary detection of TMPRSS2: ERG and PCA3 with serum PSA to predict diagnosis of prostate cancer. Urol Oncol 31(5): 566–571.
24. Sanda MG, Feng Z, Howard DH, Tomlins SA, Sokoll LJ, Chan DW, et al. Association between combined TMPRSS2:ERG and PCA3 RNA urinary testing and detection of aggressive prostate cancer. JAMA Oncol 2017; 3(8): 1085–1093.
25. Crumbaker M, Khoja L, Joshua AM. AR Signaling and the PI3K pathway in prostate cancer. Cancers 2017; 9(4): doi: 10.3390/cancers9040034.
26. Mithal P, Allott E, Gerber L, Reid J, Welbourn W, Tikishvili E, et al. PTEN loss in biopsy tissue predicts poor clinical outcomes in prostate cancer. Int J Urol 2014; 21(12): 1209–1214.
27. Chaux A, Peskoe SB, Gonzalez-Roibon N, Schultz L, Albadine R, Hicks J, et al. Loss of PTEN expression is associated with increased risk of recurrence after prostatectomy for clinically localized prostate cancer. Mod Pathol 2012; 25(11): 1543–1549.
28. Kari V, Mansour WY, Raul SK, Baumgart SJ, Mund A, Grade M, et al. Loss of CHD1 causes DNA repair defects and enhances prostate cancer therapeutic responsiveness. EMBO Rep 2016; 17(11): 1609–1623.
29. West H, Jin JO. Circulating tumor cells. JAMA Oncol 2015; 1(3): 394.
30. Galletti G, Portella L, Tagawa ST, Kirby BJ, Giannakakou P, Nanus DM. Circulating tumor cells in prostate cancer diagnosis and monitoring: an appraisal of clinical potential. Mol Diagn Ther 2014; 18(4): 389–402.
31. McKiernan J, Donovan MJ, O’Neill V, Bentink S, Noerholm M, Belzer S, et al. A novel urine exosome gene expression assay to predict high-grade prostate cancer at initial biopsy. JAMA Oncol 2016; 2(7): 882–889.
The authors
Alexandra Tabakin MD,
Sung Un Bang MD, Isaac Yi Kim MD PhD
Section of Urologic Oncology, Rutgers Cancer Institute of New Jersey and Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA
*Corresponding author
E-mail: kimiy@cinj.rutgers.edu
Biomarkers for the prediction of clinically significant prostate cancer
, /in Featured Articles /by 3wmediaProstate cancer is the most common cancer in men and diagnosis involves a combination of assessments. Levels of the biomarker prostate-specific antigen (PSA) are commonly measured, but do not always equate to cancer status. Testing of PSA in combination with other biomarkers may help to improve diagnostic and prognostic accuracy, as well as minimizing overdiagnosis as well as unnecessary intervention. This article provides a summary of the information currently known about biomarkers showing promise for use in prostate cancer screening.
by Dr Alexandra Tabakin, Dr Sung Un Bang and Dr Isaac Y. Kim
Introduction
Prostate cancer is the most commonly diagnosed cancer type in the USA and second leading cause of cancer deaths in men. In 2018, there will be an estimated 164 690 new cases with an estimated 29 430 deaths [1]. Although many prostate cancers are indolent in nature and can be safely monitored with active surveillance, a significant proportion of patients will require intervention with surgery, radiation, or other therapies. One of the major challenges in treating prostate cancer is risk stratification and differentiating clinically significant prostate cancers in order to avoid overdiagnosis and overtreatment [2]. To do so, patients undergo risk stratification, which conventionally includes a combination of prostate-specific antigen (PSA) screening, digital rectal exam (DRE), trans-rectal ultrasonography (TRUS)-guided biopsy. Currently clinically insignificant prostate cancer, according to Epstein criteria, is defined as cancer with preoperative PSA <10ng/ml, clinical stage <T1c, Gleason score <6, PSA density <0.15, <2 positive biopsy cores, and <50% cancer involvement in any core [3–5]. However, as we learn more about the heterogeneity of prostate cancer tumours, various serum biomarkers have been investigated to improve diagnostic and prognostic accuracy and minimize treatment. In this review, we discuss various biomarkers and their utilization for the prediction of clinically significant prostate cancer.
Serum biomarkers
PSA
PSA, or prostate-specific antigen, is a serine protease released by the prostate. PSA gained notoriety in the 1980s when it was reported to have various uses including screening, monitoring disease progression, and detecting recurrence of the cancer. As PSA screening for prostate cancer increased, the incidence of prostate cancer also rose in the 1990s. However, PSA only has a 25–40% specificity rate for prostate cancer and can be elevated with infection, trauma, and benign prostatic hyperplasia (BPH) [6]. In fact, about 15% of men with a low level of PSA (<4.0 ng/ml) have prostate cancer [7].
Because the harms of biopsy and prostate cancer treatment may outweigh the benefits in some patients with clinically insignificant prostate cancer, efforts have been made to improve the validity of PSA in differentiating benign conditions and prostate cancer. One such effort is the use of free PSA; those with an elevated PSA and a lower serum percentage of free PSA (%f-PSA) are more likely to have BPH rather than prostate cancer [8]. The Prostate Health Index (PHI) formula incorporates serum total PSA, free PSA, and the [−2]proPSA to discriminate Gleason 3+4 and greater cancers with 90% sensitivity and 17% specificity [9]. 4K score is another novel test which is comprised of total PSA, free PSA, intact PSA, and human kallikrein-related peptidase 2 to detect clinically significant prostate cancer and discern those who would benefit from a prostate biopsy while preventing 30–58% of biopsies [10].
PAP
Prostatic acid phosphatase (PAP) was the first popularized prostate cancer serum biomarker, but was eventually replaced by PSA, as it is less sensitive in diagnosing prostate cancer and detecting recurrence. Elevated PAP level has been associated with a high risk of bone metastases [11], significantly shortened overall survival [12] as well as disease-free survival [13], and increased risk of biochemical recurrence [14]. Interestingly, recent studies have shown that PAP may be useful in detecting high-risk clinically significant prostate cancer patients; it is speculated that PAP may be associated with micro-metastatic disease prior to treatment, and therefore, predict response to treatment [15].
NLR, ANC, ALC
Inflammation and tissue microenvironment are important factors in cancer development. Although the temporal relationship is not well established, a lymphocyte-mediated immune response is thought to occur early in the development of prostate cancer. Neutrophil-to-lymphocyte ratio (NLR) compares the activity of both neutrophils and lymphocytes in the inflammatory response. NLR is a useful prognostic biomarker in mCRPC, where a higher score correlates less relative lymphocyte activity and a worse prognosis. When looking at localized low-risk prostate cancer, studies have shown that NLR is not associated with upstaging, upgrading, or biochemical recurrence. However, increased absolute lymphocyte count (ALC) and absolute neutrophil count (ANC) were associated with upstaging and lower 5-year biochemical recurrence-free survival. More development on these markers may guide clinicians in re-stratifying patients who meet conventional criteria for low-risk prostate cancer [16].
Urine biomarkers
PCA3
Urinary prostate cancer antigen 3 (PCA3) is among the most promising non-invasive biomarker among non-PSA based tests, as it is overexpressed in over 95% of prostate cancers [6]. PCA3 is a long noncoding RNA collected from shed prostate cells during urination. PCA3 is a more specific biomarker for prostate cancer because, unlike PSA, PCA3 levels are not influenced by prostate size, BPH, prostatitis, or the use of 5α-reductase inhibitors [17]. At the genetic level, PCA3 may help distinguish between prostate cancer and high-grade prostatic intraepithelial neoplasia (HG-PIN), as PCA3 is seldom expressed in HG-PIN [18]. Several studies have demonstrated that a higher PCA3 score correlates with clinically significant prostate cancer and larger tumour volume, therefore potentially aiding in selecting patients for active surveillance [19]. In 2012, the FDA approved the PROGENSA PCA3 assay predict men who would benefit from a repeat biopsy in those with a previous negative prostate biopsy [6]. In a recent meta-analysis of 46 clinical trials, the sensitivity and specificity of PROGENSA PCA3 was 65% and 73%, respectively [20].
Genetic mutations
TMPRSS2::ERG
TMPRSS2::ERG, or T2:ERG, gene fusions constitute 90% of gene fusions implicated in prostate cancer, as well as half of all prostate cancers [21, 22]. When the androgen responsive regulatory element TMPRSS2 and the gene for the transcription factor ERG are fused together, androgen-driven genes are overexpressed and tumorigenesis occurs [21]. When used alone, urinary T2:ERG RNA has a reported 86% specificity and 45% sensitivity in prostate cancer detection. However, when used in conjunction with PCA3, specificity and sensitivity improve to 90% and 80%, respectively [6, 23]. Moreover, this test may prevent up to 42% of unnecessary biopsies, limiting healthcare costs [24].
PTEN
Loss of the tumour-suppressor gene, PTEN, or phosphatase and tensin homologue, leading to activation of the PI3K/AKT/mTOR signalling has been found in both early stage and castrate-resistant prostate cancers. Preclinical data show that PI3K pathway activation is related to resistance to androgen deprivation, leading to disease progression and poor response to treatment. In mouse models, conditional deletion of PTEN initially led to the development of prostate hyperplasia and later on invasive and metastatic prostate cancers likely by modulating the p110β catalytic subunit of PI3K. In addition, ablation of p110β hindered AKT signalling and reduced tumorigenesis [25]. In a cohort of 77 men, loss of PTEN at initial prostate biopsy was predictive of the development of castrate-resistant prostate cancer, response to androgen deprivation therapy, and prostate-cancer-specific mortality [26]. Additionally, decreased PTEN expression has been associated with increased risk of biochemical and clinical recurrence after prostatectomy [27]. Therefore, the association between castrate-resistant prostate cancer and PTEN loss as well as PI3K/AKT/mTOR pathway activation suggests that PTEN may have prognostic value in prostate cancer risk stratification.
CHD1
The CHD1 gene, encoding chromodomain helicase DNA-binding protein 1, is commonly deleted in 10–26% of all prostate cancers. The loss of CHD1 affects the ability to repair DNA double-strand breaks via homologous recombination. CHD1 deletion has generally been associated with a poor prognosis. However, studies have demonstrated tumours with CHD1 deletions to be sensitive to both PARP inhibitors and carboplatin, both in vitro and in vivo, suggesting that future research may be able to identify to response to treatment based off of tumour genotypes [28].
Circulating biologics
Circulating tumour cells
Circulating tumour cells (CTCs) are defined as cells that leave the site of a primary cancer, travel through the bloodstream, and settle at other sites in the body where they grow into new tumours, or metastases [29]. In 2004, CellSearch Circulating Tumor Cell System was approved by the FDA as an assay for enumerating CTCs. In recent studies, CTC count, deemed the ‘liquid biopsy’, has been shown to have a role in predicting overall survival and response to treatment, risk stratification, and detecting metastases. In addition, using CTCs to detect biomarkers, such as ERG, PTEN, and AR may allow for personalized treatments based on tumour genomes [9, 30].
Circulating exosomes
Circulating prostate cancer-related exosomes are double-membrane vesicles carrying RNA and pro-oncogenic molecules, which induce malignant transformation in normal cells. ExoDx prostate Intelliscore urine exosome assay (developed by Exosome Diagnostics Inc.) detects exosomal RNA expression of ERG, PCA3 and SPDEF (SAM pointed domain containing ETS transcription factor) in voided urine samples. A score is generated that is able to predict high-grade prostate cancer (Gleason >7) with a negative predictive value of 91%. This assay may be useful in discriminating clinically significant prostate cancer and reducing the number of unnecessary biopsies [31].
Conclusion
The emergence and widespread usage of PSA as a routine screening test for prostate cancer allows for early detection and risk stratification. Testing for PSA in combination with novel biomarkers such as PCA3, TMPRSS2::ERG, PTEN, and others may improve our diagnostic abilities, given the heterogeneity of prostate cancers and their treatments. There are many challenges in establishing useful biomarkers including creating affordable and accessible testing, determining cut-offs, and determining accuracy. As the clinical utility of these biomarkers is further defined, we hope to better risk stratify patients and select appropriate treatments early on in diagnosis. Further research efforts should focus on the synergism between the Epstein criteria, biomarker utility, and how to best bring these tools from bench to bedside.
References
1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018; 68(1): 7–30.
2. Lees K, Durve M, Parker C. Active surveillance in prostate cancer: patient selection and triggers for intervention. Curr Opin Urol 2012; 22(3): 210–215.
3. D’Amico AV, Whittington R, Malkowicz SB, Weinstein M, Tomaszewski JE, Schultz D, et al. Predicting prostate specific antigen outcome preoperatively in the prostate specific antigen era. J Urol 2001; 166(6): 2185–2188.
4. Epstein JI, Chan DW, Sokoll LJ, Walsh PC, Cox JL, Rittenhouse H, et al. Nonpalpable stage T1c prostate cancer: prediction of insignificant disease using free/total prostate specific antigen levels and needle biopsy findings. J Urol 1998; 160(6): 2407–2411.
5. Klotz L, Zhang L, Lam A, Nam R, Mamedov A, Loblaw A. Clinical results of long-term follow-up of a large, active surveillance cohort with localized prostate cancer. J Clin Oncol 2010; 28(1): 126–131.
6. Sanguedolce F, Cormio A, Brunelli M, D’Amuri A, Carrieri G, Bufo P, et al. Urine TMPRSS2: ERG fusion transcript as a biomarker for prostate cancer: literature review. Clin Genitourin Cancer 2016; 14(2): 117–121.
7. Prensner JR, Rubin MA, Wei JT, Chinnaiyan AM. Beyond PSA: the next generation of prostate cancer biomarkers. Sci Transl Med 2012; 4(127): 127rv3.
8. Grossklaus DJ, Smith JA, Shappell SB, Coffey CS, Chang SS, Cookson MS. The free/total prostate-specific antigen ratio (%fPSA) is the best predictor of tumor involvement in the radical prostatectomy specimen among men with an elevated PSA. Urol Oncol 2002; 7(5): 195–198.
9. Chistiakov DA, Myasoedova VA, Grechko AV, Melnichenko AA, Orekhov AN. New biomarkers for diagnosis and prognosis of localized prostate cancer. Semin Cancer Biol 2018; doi: 10.1016/j.semcancer.2018.01.012.
10. Parekh DJ, Punnen S, Sjoberg DD, Asroff SW, Bailen JL, Cochran JS, et al. A Multi-institutional prospective trial in the USA confirms that the 4Kscore accurately identifies men with high-grade prostate cancer. Eur Urol 2015; 68(3): 464–470.
11. Whitesel JA, Donohue RE, Mani JH, Mohr S, Scanavino DJ, Augspurger RR, et al. Acid phosphatase: its influence on the management of carcinoma of the prostate. J Urol 1984; 131(1): 70–71.
12. Johnson DE, Prout GR, Scott WW, Schmidt JD, Gibbons RP, et al. Clinical significance of serum acid phosphatase levels in advanced prostatic carcinoma. Urology 1976; 8(2): 123–126.
13. Moul JW, Connelly RR, Perahia B, McLeod DG. The contemporary value of pretreatment prostatic acid phosphatase to predict pathological stage and recurrence in radical prostatectomy cases. J Urol 1998; 159(3): 935–940.
14. Han M, Piantadosi S, Zahurak ML, Sokoll LJ, Chan DW, Epstein JI, et al. Serum acid phosphatase level and biochemical recurrence following radical prostatectomy for men with clinically localized prostate cancer. Urology 2001; 57(4): 707–711.
15. Faiena I, Kim S, Farber N, Kwon YS, Shinder B, Patel N, et al. Predicting clinically significant prostate cancer based on pre-operative patient profile and serum biomarkers. Oncotarget 2017; 8(65): 109783–109790.
16. Kwon YS, Han CS, Yu JW, Kim S, Modi P, Davis R, et al. Neutrophil and lymphocyte counts as clinical markers for stratifying low-risk prostate cancer. Clin Genitourin Cancer 2016; 14(1): e1–8.
17. Roobol MJ, Schröder FH, van Leeuwen P, Wolters T, van den Bergh RCN, van Leenders GJLH, et al. Performance of the prostate cancer antigen 3 (PCA3) gene and prostate-specific antigen in prescreened men: exploring the value of PCA3 for a first-line diagnostic test. Eur Urol 2010; 58(4): 475–481.
18. Wei W, Leng J, Shao H, Wang W. High PCA3 scores in urine correlate with poor-prognosis factors in prostate cancer patients. Int J Clin Exp Med 2015; 8(9): 16606–16612.
19. Ploussard G, Epstein JI, Montironi R, Carroll PR, Wirth M, Grimm M-O, et al. The contemporary concept of significant versus insignificant prostate cancer. Eur Urol 2011; 60(2): 291–303.
20. Cui Y, Cao W, Li Q, Shen H, Liu C, Deng J, et al. Evaluation of prostate cancer antigen 3 for detecting prostate cancer: a systematic review and meta-analysis. Sci Rep 2016; 6: 25776.
21. Burkhardt L, Fuchs S, Krohn A, Masser S, Mader M, Kluth M, et al. CHD1 is a 5q21 tumor suppressor required for ERG rearrangement in prostate cancer. Cancer Res 2013; 73(9): 2795–2805.
22. Tomlins SA, Laxman B, Varambally S, Cao X, Yu J, Helgeson BE, et al. Role of the TMPRSS2-ERG gene fusion in prostate cancer. Neoplasia 2008; 10(2): 177–188.
23. Salami SS, Schmidt F, Laxman B, Regan MM, Rickman DS, Scherr D, et al. Combining urinary detection of TMPRSS2: ERG and PCA3 with serum PSA to predict diagnosis of prostate cancer. Urol Oncol 31(5): 566–571.
24. Sanda MG, Feng Z, Howard DH, Tomlins SA, Sokoll LJ, Chan DW, et al. Association between combined TMPRSS2:ERG and PCA3 RNA urinary testing and detection of aggressive prostate cancer. JAMA Oncol 2017; 3(8): 1085–1093.
25. Crumbaker M, Khoja L, Joshua AM. AR Signaling and the PI3K pathway in prostate cancer. Cancers 2017; 9(4): doi: 10.3390/cancers9040034.
26. Mithal P, Allott E, Gerber L, Reid J, Welbourn W, Tikishvili E, et al. PTEN loss in biopsy tissue predicts poor clinical outcomes in prostate cancer. Int J Urol 2014; 21(12): 1209–1214.
27. Chaux A, Peskoe SB, Gonzalez-Roibon N, Schultz L, Albadine R, Hicks J, et al. Loss of PTEN expression is associated with increased risk of recurrence after prostatectomy for clinically localized prostate cancer. Mod Pathol 2012; 25(11): 1543–1549.
28. Kari V, Mansour WY, Raul SK, Baumgart SJ, Mund A, Grade M, et al. Loss of CHD1 causes DNA repair defects and enhances prostate cancer therapeutic responsiveness. EMBO Rep 2016; 17(11): 1609–1623.
29. West H, Jin JO. Circulating tumor cells. JAMA Oncol 2015; 1(3): 394.
30. Galletti G, Portella L, Tagawa ST, Kirby BJ, Giannakakou P, Nanus DM. Circulating tumor cells in prostate cancer diagnosis and monitoring: an appraisal of clinical potential. Mol Diagn Ther 2014; 18(4): 389–402.
31. McKiernan J, Donovan MJ, O’Neill V, Bentink S, Noerholm M, Belzer S, et al. A novel urine exosome gene expression assay to predict high-grade prostate cancer at initial biopsy. JAMA Oncol 2016; 2(7): 882–889.
The authors
Alexandra Tabakin MD,
Sung Un Bang MD, Isaac Yi Kim MD PhD
Section of Urologic Oncology, Rutgers Cancer Institute of New Jersey and Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA
*Corresponding author
E-mail: kimiy@cinj.rutgers.edu
Book review: Oral anticoagulants
, /in Featured Articles /by 3wmediaAfter the 3rd volume devoted to parental anticoagulants, it stands to reason that the Clinical Development Department had to turn its attention to the other side of anticoagulant treatment – the oral anticoagulants – in this series launched in 2014 with the objective of publishing a Practical Manual every year.
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This volume, devoted to oral anticoagulants, focuses on Direct Oral Anticoagulants (DOAC) – called New Oral Anticoagulants (NACO in French) – without neglecting the anti-vitamin K (AVK) drugs. The pharmacology, clinical aspects and biological monitoring of each treatment, AVK, anti-Xa and anti-IIa are described in a systematic manner, whilst information about the management and risks associated with these treatments, especially in certain diseases, is also discussed. A final section is devoted to antidotes in the event of complications and bleeding (reversal of anticoagulant effect). Twelve renowned international authors from Europe and North America were involved in the compilation of this book, coordinated by Stago.
Presented in July 2017 at the latest Congress of the International Society of Thrombosis and Haemostasis (ISTH 2017 – Berlin), this 4th opus was extremely well received and all 350 copies available on the Stago booth had gone in just 2 days!
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Scores and algorithms in Haemostasis and Thrombosis (2014) – ref. 28111 – 60 pages
Antiphospholipid syndrome (2015) – ref. 29289 – 76 pages
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, /in Featured Articles /by 3wmediaAutomation and integration of LC-MS/MS services into the clinical laboratory workflow
, /in Featured Articles /by 3wmediaDespite significant inherent advantages of liquid chromatography-tandem mass spectrometry (LC-MS/MS) over immunoassay techniques in clinical laboratory applications, its adoption into routine practice has been slower than might have been expected. The barriers to more widespread uptake are a function of issues in the laboratory workflow. This article analyses those issues and discusses how they can be overcome by improved automation and integration with the laboratory information management system, drawing on examples from the North West London Pathology (NWLP) clinical laboratories at Imperial College Healthcare NHS Trust.
by Dr Emma L. Williams
Introduction
Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has seen over two decades of use in specialist clinical laboratories in the UK, offering a number of significant advantages over immunoassay techniques. These advantages include increased specificity, sensitivity and accuracy, as well as the detection of multiple analytes within a single assay. There is no need for an antibody for analyte detection and the method is not susceptible to the antibody-based interferences that plague immunoassays [1]. LC-MS/MS is suitable for multiple sample matrices and avoids the need for radioactive tracers. LC-MS/MS assays also have a wider dynamic measurement range and have improved between-method bias when compared to immunoassays.
LC-MS/MS initially played a role in specialist clinical laboratories in areas such as newborn screening, inborn errors of metabolism, toxicology and in immunosuppressant and therapeutic drug monitoring. More recently LC-MS/MS has established a role in diagnostic endocrinology, with the first appearance of LC/MS-MS for the measurement of vitamin D in the international vitamin D external quality assurance scheme (DEQAS) in 2005. There are now over 150 labs registered in this scheme using LC/MS-MS for the measurement of vitamin D. However, automated immunoassay still dominates and represents 69% of participants registered in the DEQAS scheme. Why has there not been more widespread adoption?
A number of issues have inhibited wider adoption and routine use of LC/MS-MS in the clinical laboratory. First among these is the use of labour-intensive manual workflows, which result in lower throughput, decreased productivity and longer turnaround time. Furthermore, a high level of technical expertise is needed, not only for method development, but also for troubleshooting assay and equipment failures. In addition to the high initial capital costs of purchasing the equipment, ongoing personnel costs are higher because of the need for more technically competent staff. With a clear understanding of where the bottlenecks in the process arise, these barriers can be overcome.
Figure 1 depicts the six main steps of a typical LC/MS-MS workflow, from sample receipt and extraction, separation in the LC, MS/MS analysis, data review and reporting of the results [2]. Of these steps it is the pre- and post-analytical stages that are the most time consuming and therefore if there is a focus on streamlining these, maximum benefit can be achieved. A number of steps can be taken to streamline the workflow, and these come under three broad headings of reduced manual processes, increased throughput and improved integration. Dependence on manual processes can be reduced by the automation of liquid handling and extraction, use of barcode reading for worklist generation and implementation of automated data analysis. Throughput can be increased with strategic column and sample management and by analyte multiplexing. Integration can be improved by bi-directional interfacing of the LC/MS-MS system to the laboratory information management system (LIMS) allowing automatic worklist upload and results download. These three strategic areas will be discussed in more detail below.
Reduced manual processes
Unlike the case with immunoassay, samples for LC-MS/MS usually require extraction prior to analysis. Historically this extraction step utilized liquid–liquid extraction or protein precipitation, these being carried out after the addition of internal standard to the calibrators, quality controls and patient samples. All of these steps involved manual pipetting and were very slow and time consuming. Use of an automated liquid-handling platform for the pipetting of samples and addition of internal standard allows some of the steps of liquid–liquid extraction and protein-precipitation methods to be automated. These liquid-handling platforms are available from a number of suppliers including Hamilton and Tecan.
With the advent of 96-well plate technology it became possible to carry out fully automated off-line solid phase extraction (SPE) using platforms such as the Freedom Evo (Tecan) and the Biomek NX (Beckman Coulter). More recently, supported liquid extraction (SLE), which allows solvent extraction to occur on a diatomaceous earth inert support, has also become available in a 96-well plate format. The Extrahera system (Biotage) enables automation of SLE by carrying out all of the pipetting and extraction steps required. In the NWLP laboratory, this system is used for the extraction of patient samples for vitamin D measurement by LC-MS/MS. A sample throughput of up to 50,000 samples per annum is achieved with capacity remaining for additional extractions for use in other LC-MS/MS applications. The system is robust and reliable with good pipetting precision and uses disposable pipette tips, thus avoiding sample carry over. Figure 2 depicts the Tecan Freedom Evo 200 and Biotage Extrahera liquid handlers in use in the NWLP laboratory.
In some manufacturers’ LC-MS/MS systems, on-line sample preparation and extraction is enabled by use of turbo flow or 2D chromatography. On-line protein precipitation and SPE is also now available using the Clinical Laboratory Automated sample preparation Module (CLAM)-2000 (Shimadzu Corporation) [3] and the Rapidfire 365 MS system (Agilent) [4] respectively. These latter examples most closely resemble the immunoassay workflow, whereby samples are introduced into the analytical system without any sample preparation or pre-treatment.
Increased throughput
Increased throughput can be achieved through the use of column and sample managers, allowing multiple assay batches to be queued up for overnight analysis of different LC-MS/MS assays. LC multiplexing enables multiple columns to be coupled to one tandem mass spectrometry system, maximizing the MS detection capability. In this approach, the use of quaternary solvent pumps in the LC enables column switching between different columns using different mobile phases. Finally there is analyte multiplexing, which can use manufacturers’ kits or in-house laboratory developed tests (LDTs). This approach enables multiple analytes to be detected in a single chromatographic separation by the use of multiple reaction monitoring for MS/MS detection. Perkin Elmer and Chromsystems both provide kits enabling the simultaneous measurement of multiple steroid hormones within a single assay panel. In the NWLP laboratory an in-house LDT steroid panel for the simultaneous measurement of androstenedione, 17-hydroxyprogesterone and testosterone has been implemented. This multiplexed assay has replaced the previous stand-alone assays for these analytes, thus increasing throughput and offering faster turnaround time. The assay utilizes off-line SPE using Waters Oasis PRiME HLB 96-well plates and the Tecan Freedom Evo 200 automated liquid handler [5].
Improved integration
Improved integration can be achieved by the use of bi-directional interfacing between the LIMS and the LC-MS/MS instrument software. Nowadays, manufacturers of LC-MS/MS systems offer customer support to allow their systems to be interfaced to the LIMS. One example is the MassLynx LIMS interface (Waters), which enables both worklist download and results upload. The MassLynx LIMS interface is accessed via the LC-MS/MS system software allowing sample worklists, created by barcode scanning of the patient samples, to be imported directly. Following peak integration and analyte quantitation the results are directly transmitted from the LC-MS/MS to the LIMS via an HL7 interface. This avoids the need for manual transcription thus saving a great deal of staff time and eliminating transcription errors.
The ultimate aim of LC-MS/MS integration is to achieve complete integration of LC-MS/MS instruments into the automated workflow of high-throughput routine clinical laboratories. With the recent introduction of the Cascadion LC-MS/MS analyser (Thermo Fisher Scientific) this ultimate aim has now been achieved [6]. This analyser offers a complete LC-MS/MS solution including primary blood tube sampling, on-board sample extraction, LIMS connectivity and a random access workflow enabling the provision of a 24/7 service. Traceable manufacturer’s kits are offered for the measurement of a panel of immunosuppressant drugs, testosterone and vitamin D with further assay kits in the development pipeline. The Cascadion analyser is shown in Figure 3.
Summary
LC/MS-MS automation and integration is now a reality, allowing faster sample processing and improved turnaround time, as well as offering increased staff productivity, improved quality and reduced error rate. Staff time is liberated for further service development, allowing the more rapid introduction of validated in-house LDTs into the assay repertoire. Finally there is the possibility of complete analyser integration allowing routine, high-throughput analysis, as is already the standard approach for the common immunoassay platforms. This exciting development will support the more widespread adoption of LC-MS/MS in the routine clinical laboratory by offering complete automation and integration, overcoming the barriers discussed in this article and enabling the inherent advantages of LC/MS-MS in clinical laboratory practice to be more fully realized.
References
1. Jones AM, Honour JW. Unusual results from immunoassays and the role of the clinical endocrinologist. Clin Endocrinol Oxf 2006; 64: 234–244.
2. Zhang YV, Rockwood A. Impact of automation on mass spectrometry. Clin Chim Acta 2015; 450: 298–303.
3. Shimadzu. CLAM-2000. Fully automated sample preparation module for LCMS. (https://www.shimadzu.com/an/lcms/clam/index.html).
4. Jannetto PJ, Langman LJ. High-throughput online solid-phase extraction tandem mass spectrometry: Is it right for your clinical laboratory? Clin Biochem 2016; 49: 1032–1034.
5. Williams EL. LC-MS/MS measurement of serum steroids in the clinical laboratory. Clinical Laboratory International 2017; Sept: 18–20.
6. ThermoFisher Scientific. Cascadion SM Clinical Analyzer (www.thermofisher.com/cascadion).
The author
Emma L. Williams PhD, FRCPath
North West London Pathology, Imperial College Healthcare NHS Trust, London, UK
E-mail: emma.walker15@nhs.net