Biomarkers and genomics in prostate cancer

Biomarkers and genomics in prostate cancer D. Schrijvers, MD, PhD 1, T. Debacker, MD 2 Biomarkers and genomics are making their entrance in daily clinical practice in many tumour types. In prostate cancer, their use is relatively limited. This article reviews biomarkers and genomics used in different clinical settings such as screening, diagnosis, prognosis, prediction and surrogate endpoints for overall survival and shows an unmet need in prostate cancer. (Belg J Med Oncol 2014;8(4):104-8) Introduction A biomarker is defined as a characteristic that is objectively measured and evaluated as an indicator of normal biological or pathogenic processes, or pharmacologic responses to a therapeutic intervention. 1 Biomarkers are becoming more and more important in cancer because we need factors to identify groups that are in need and benefiting of a certain intervention. In oncology, two important groups of biomarkers are used: Prognostic biomarkers forecast the likely course of disease irrespective of treatment. Predictive biomarkers forecast the likely response to a specific treatment. Biomarkers can be linked to patient- or disease-related factors. Clinical, haematological, biochemical, and genetic factors are being used as biomarkers. Genomics study genes and their functions and related techniques such as determination of different RNA s are becoming part of clinical practice in haematology and oncology. 2 In this review, the status of biomarkers and genomics is discussed in different settings in prostate cancer. Biomarkers and genomics as screening Prostate cancer is a slowly progressing disease and different studies looked at the value of screening to decrease prostate cancer mortality. Several large studies used prostate specific antigen (PSA) in combination with digital rectal examination (DRE) and echography to screen men for prostate cancer. These studies showed that in the screened group, the diagnosis of prostate cancer was higher than in the control group, especially stage II disease. However, there was no improvement in prostate cancer-related mortality after seven and ten years of follow up. 3 Therefore; PSA is not a good biomarker for prostate cancer screening. Also, since there is no survival benefit, prostate cancer screening is not recommended by several scientific organisations. Several high risk groups for prostate cancer development have been defined based on family history. In men with a first-line relative with prostate cancer, the risk of prostate cancer development increases by two-fold, while if there are more than one first-line relative with prostate cancer, the risk increased by five to eleven times. Also, hereditary prostate cancer is present in 5-10% of prostate cancer patients. Genomics may be used to identify men at risk for prostate cancer. In the hereditary breast and ovarian cancer syndrome (BRCA), men carrying a BRCA2 mutation have an increased risk of prostate cancer (odds ratio 4.78; 95% confidence interval 1.87-12.25; P = 0.001), while there is no increased risk in BRCA1 mutation carriers. 4 Different genomic wide association studies resulted in the identification of several biological pathways and single 1 Department of Medical Oncology, Ziekenhuisnetwerk Antwerpen-Middelheim, Antwerp, Belgium, 2 Department of Urology, Ziekenhuisnetwerk Antwerpen-Middelheim, Antwerp, Belgium. Please send all correspondence to: D. Schrijvers, MD, PhD, ZNA Middelheim, Department of Medical Oncology, Lindendreef 1, 2020 Antwerp, Belgium, tel: +32 3 280 40 30, fax: +32 3 281 07 19, email: Dirk.Schrijvers@zna.be. Conflict of interest: D. Schrijvers - studies with abiraterone acetate and cabazitaxel. Keywords: biomarker, diagnosis, genomics, prediction, prognosis, screening, surrogate endpoint. 104

Table 1. Prognostic markers in different situations in prostate cancer. Patient-related Disease-related Others Early stage disease Performance status Co-morbidity Gleason sum in primary tumour T stage PSA Positive tumour margins Perineural invasion Hormone-sensitive metastatic disease Performance status Age Co-morbidity Gleason in primary tumour PSA kinetics Time to reach PSA nadir Castration-resistant metastatic disease Performance status Gleason sum in primary tumour Anaemia Age Visceral disease C-reactive protein Pain Type of progression Lactate dehydrogenase Number sites of disease PSA and PSA by RT-PCR PSA kinetics Albumin Circulating tumour cell count VEGF levels Interleukin-6 levels Chromogranin-A Alkaline phosphatase (bone) Serum TRAP-5b + other bone turnover markers Urine N-telopeptide PSA: prostate specific antigen; RT-PCR: reverse transcription polymerase chain reaction; VEGF: vascular endothelial growth factor; TRAP: tartrate-resistant acid phosphatase. nucleotide polymorphisms associated with an increased risk of prostate cancer. 5,6 At the moment, these techniques are not used in clinical practice and the implication of carrying a mutation in relation to the real risk, as well as primary and secondary prevention and treatment approaches are not well defined. Biomarkers and genomics as diagnostic The diagnosis of prostate cancer is made by a biopsy and this remains the gold standard. However, prostatic biopsies could lead to morbidity and mortality due to complications. The identification of patients who could benefit of a biopsy in daily clinical practice is crucial. Several biomarkers have been studied to limit the number of biopsies in men but all are flawed. Prostate specific antigen is a serum marker that is easily determined. However, at a PSA cut-off point of 4 ng/ml it has a sensitivity of 86% and a specificity of 33%, which means that in patients with a PSA within the normal range, 7-29% have prostate cancer and 1-7% have a prostate cancer with a Gleason score of above seven. 7 The ratio of free to total PSA (f/t PSA) has been used to discriminate between benign prostate hypertrophy and prostate cancer in men with a PSA between 4-10 ng/ml and a negative DRE. The sensitivity in different studies varied between 90-98% but the specificity was low varying from 7-38%. This means that around 10% of prostate cancer can be missed while the number of spared biopsies is between 7 and 38%. 8 PSA kinetics have been studied to improve the diagnostic performance linked to a single PSA determination. PSA velocity determines the absolute annual increase in serum PSA (ng/ml/year), while the PSA doubling time looks at the exponential increase of serum PSA 4 105

Table 2. Gene and microrna expression in relation to different prognostic outcomes. Genomic marker Role in prostate cancer Prognostic role Genes CCL-2 Increased cell growth, invasion, metastasis Tumour volume, Gleason score PTEN Decreased invasion, migration Gleason score, stage, BCR, metastasis TMPRSS2-ERG Increased tumour genesis, androgen independence Diagnosis, androgen independence Myc Increased proliferation Progression, survival, BCR after radiation IL-1 Increased tumour genesis Progression IL-6 Increased proliferation Progression TGF-β Increased cell growth, angiogenesis, suppression immune cells Cancer-specific survival IL-7 Immune resistance Cancer-specific survival Micro RNA mir-31 Down regulated invasion Gleason mir-96 Overexpression decrease zinc uptake Gleason mir-145 Upregulated or downregulated Gleason mir-205 Downregulation invasion Gleason, stage mir-32 Overexpression cell survival EPE mir-196a Overexpression cell survival EPE mir-221/222 Overexpression cell survival and proliferation Stage mir-125b Inhibits apoptosis Stage MiR-21 Down regulated invasion and migration BCR mir-135b Overexpression genomic instability BCR mir-194 Overexpression hypomethylation, genomic instability BCR EPE: extracapsular extension; BCR: biochemical recurrence; CCL-2: chemokine (C-C motif) ligand 2; PTEN: phosphatase and tensin homolog; TMPRSS2: transmembrane protease, serine 2; IL: interleukin; TGF: transforming growth factor. over time. Their use in the diagnosis of prostate cancer is limited due to the background noise in relation to the total prostate volume and the presence of benign prostatic hypertrophia, the variations in interval between PSA determinations and the acceleration and deceleration of both over time. 9 The prostate health index (PHI) combines the total PSA, the protein-free PSA and the pro-psa, a subcategory of free PSA. It has a sensitivity of 90% and a specificity of 31.1 %, which makes it a poor diagnostic tool. 10 The prostate cancer gene 3 (PCA3) score is based on the determination of mrna in urine sediment after three strokes of prostatic massage during DRE. At the diagnostic utility score, defined as higher than 35, it has a sensitivity of 61% and a specificity of 70%. This means that at this cut-off, 39% of prostate cancer will be missed, thus making it a poor diagnostic test. 11 In men with a metastatic adenocarcinoma of primary unknown origin, genomic analysis can be used to determine the organ of origin of the disease. Several gene signature profiling tests (e.g. THEROS CancerTYPE ID, Pathwork Tissue of Origin Test, CupPrint, and CUP assay) have been used but their accuracy varies between 76 to 89%, making them less than ideal tests for the diagnosis of prostate cancer. Currently, biopsy remains the golden standard for diagnosing prostate cancer but some tests may indicate men with a higher risk of prostate cancer in need of a biopsy. However, many tests have problems of sensitivity and specificity for detecting prostate cancer accurately. Biomarkers and genomics as prognostic The prognosis of prostate cancer at diagnosis depends on patient-related factors such as life expectancy determined by the calendar and physiologic age, the patient s condi- 106

Key messages for clinical practice 1. Biomarkers and genomics are needed but are lacking in prostate cancer. 2. Nomograms can be used for explaining patient prognosis and risk for different endpoints. tion and co-morbidity profile and disease-related factors such as pathological characteristics of the primary tumour (e.g. Gleason score), stage of the disease, and the level of PSA. Based on the disease-related factors, patients are classified in different prognostic groups such as low risk (Gleason score 6, clinical stage T1-2a, PSA < 10 ng/ml), intermediate risk (Gleason score 7, clinical stage T2b, PSA 10-20 ng/ml) and high risk (Gleason score 8, clinical stage T2c-3a, PSA > 20 ng/ml). 9 In patients with different disease stages (at diagnosis, recurrent disease, castration-resistant disease) several other factors have been defined as prognostic parameters (Table 1). 10,12 Nomograms have been developed in different disease situations and after specific treatments in prostate cancer. They are useful in clinical practice to explain the prognosis to the patient in different situations. Several genomic tests have been developed to predict the prognosis of patients with prostate cancer. Oncotype DX prostate cancer test is an RNA expression test that tests for a 17-gene panel (androgen pathway, cellular organisation, proliferation, stromal response) and is a predictor of high grade and/or pt3 disease. Prolaris is also an RNA expression test based on a 46-gene panel including genes looking at cell cycle progression and cell growth. It is a predictor of 10-year prostate cancer mortality. 13 Although both tests were approved by the Food and Drug Administration (FDA) in the USA, they were not validated in prospective studies and their costs are relatively high (e.g. Prolaris $3,400; Oncotype DX $3,820). Genes and microrna are differently expressed in different situations and gene and/or microrna profiling may be of benefit in determining prognosis for different outcomes (Table 2). 14 They are currently not used in clinical practice. Biomarkers and genomics as predictive Biomarkers and genomics for selecting an adequate treatment are, as yet, not available in clinical practice. In patients with castration-resistant prostate cancer (CRPC), the expression of class III β-tubulin, the silencing of BMI1 gene and the presence of CYP1B1-432ValVal genotype are being studied to see if they can predict response to docetaxel. 15 Biomarkers as surrogate markers for prostate cancer survival Since the median survival of patients with prostate cancer depending on their disease stage is good, overall survival is an endpoint that is not readily reached. Therefore, surrogate endpoints that can predict survival outcome are needed in this patient population to hasten treatment development. The Prentice criteria can be used to determine the value of a surrogate endpoint in relation to the real endpoint. They state that the treatment or intervention must affect the surrogate and true endpoints; that there should be a consistent association between the surrogate and true endpoints with the treatment or intervention; and that there is an association between the surrogate and true endpoints. 16 Circulating tumour cells (CTC) have been tested in different studies in patients with metastatic CRPC to be a surrogate for overall survival. When abiraterone acetate was tested in this setting, it fulfilled all Prentice criteria and the twelve-week CTC number, and the lactate dehydrogenase level biomarker panel demonstrated survival surrogacy at the individual patient level progressing after chemotherapy. 17 However, in a similar patient population, CTC could not predict overall survival in patients treated with the combination of docetaxel and prednisone with or without lenalidomide. 18 Conclusion Biomarkers and genomics presently have limited value in the clinical management of prostate cancer. PSA remains the most widely used biomarker in opportunistic screening while patient- and disease-related factors may be used to determine prognosis. However, there is an unmet need of biomarkers and genomics in prostate cancer to better select patients for specific treatments in different settings. 4 107

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