CO Predicting high-risk disease using tissue biomarkers

REVIEW

CURRENTOPINION Predicting high-risk disease using tissue

biomarkers

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0963-0643 � 2013 Wolters Kluwer

Michael J. Donovan and Carlos Cordon-Cardo

Purpose of review

For men newly diagnosed with prostate cancer, there are limited tools to understand the risk of diseaseprogression and guide the treatment decision process. We will provide an overview of current prostatecancer biomarker discovery and validation strategies that are geared toward identifying aggressive,clinically significant disease at the time of diagnosis.

Recent findings

The prostate gland exhibits multiple genetic events leading to both latent and clinically significant prostatecancer. Recent evidence from clinical translational studies has implicated the role of aneuploidy and copy-number variation as significant predictors of aggressive disease. Furthermore, the regulation of NKX3.1 byPim-1 has provided a novel mechanism for the balance between indolence and disease course. Althoughpromising, there are no routine clinically used tissue-based biomarkers for identifying risk of prostate cancerprogression at diagnosis. The TMPRSS2–ERG gene fusion has provided insight into the early developmentof prostate cancer but has not been unequivocally associated with aggressive disease. Importantly, theonly platform relying on intact tissue profiles is the systems pathology analysis program that includeshistomorphometry and quantitative multiplex biomarker assessment (including the evaluation of the prostatecancer stem cell) to construct prognostic algorithms for pretreatment and post-treatment assessment.

Summary

Our objective for this review was to explore the effective use of prostate tissue samples, including fluids,to identify relevant markers of clinically significant disease. We believe that the inherent molecularheterogeneity in prostate cancer requires a multimodal approach, in the context of a systems pathologyplatform, to create the personalized tools for future diagnostic treatment algorithms.

Keywords

active surveillance, biomarkers, liquid biopsy, systems pathology

Department of Pathology, Mt. Sinai School of Medicine, New York City,NY, USA

Correspondence to Michael J. Donovan, PhD, MD, The Mount SinaiSchool of Medicine, Department of Pathology, One Gustave L. LevyPlace, Box 1194, New York City, NY 10029-6574, USA. Tel: +1 212 2414868; e-mail: [email protected]

Curr Opin Urol 2013, 23:245–251

DOI:10.1097/MOU.0b013e32835f89cc

INTRODUCTION

The only biomarker clinically used for detectingthe presence of prostate cancer and monitoringrecurrence post-treatment is prostate-specificantigen (PSA). Accepted as being prostate specificbut not prostate cancer specific, several modifi-cations to serum PSA detection have been suggestedto improve its sensitivity for detecting aggressivedisease, notably PSA velocity/doubling timeand PSA density. Thus far, only PSA density [PSA(ng/ml) divided by prostate volume] has beenincorporated into the 2012 National Comprehen-sive Cancer Network guidelines for definingparameters of very low risk prostate cancer; how-ever, this variable is rarely calculated for themajority of patients and thus, only total PSA istypically available. Of note, a study on a cohort ofmen enrolled in active surveillance demonstratedthat PSA in the absence of other indicators for tumor

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progression such as a positive repeat biopsy andincrease in Gleason grade was not sufficient toinitiate active treatment [1]. Similarly, early resultsfrom the European prostate cancer research inter-national: Active Surveillance trial suggest thatPSA kinetics and PSA density may be the mostappropriate tools for risk stratification and deferredtreatment [2]. Therefore, a variety of studies haveemphasized the combination of gene expressionand proteomic efforts to identify more efficacious

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KEY POINTS

� The established molecular and clinical heterogeneity ofprostate cancer dictates that a multidimensional andintegrative systems pathology program is crucial for thedevelopment of clinically efficacious treatment decisionalgorithms.

� Employing novel fluid-based approaches throughexosomes and circulating tumor cells will provideminimally invasive methods to guide enrollment and/ormonitor patients in Active Surveillance treatmentprograms.

� The ability to identify and quantify cancer stem cells inbiopsy tissue will further enhance patient-riskstratification and improve upon the final treatmentselection process.

Active surveillance in prostate cancer

biomarkers (possibly to replace PSA); however, nonehave advanced to routine clinical practice.

The prostate gland is the site of multiple geneticevents that give rise to both latent as well asclinically significant prostate cancer. Recent evi-dence suggests that the latent cancerous foci eitherdo not undergo critical activating events or remainunder active suppression sufficient to maintainin a subclinical state for the life of the individual.The apparent temporal gap between the appearanceof incidental prostate cancer and the emergenceof clinically significant disease suggests that earlyinitiation/progression events may lead to the occur-rence of cellular senescence as a means of tumorsuppression [3]. In particular, the downregulation ofthe tumor suppressor gene NKX3.1 is an early andconsistent event in prostate cancer and associatedwith increased proliferation of prostate epithelialcells and poor prognosis [4–5]. Previous workhas shown that NKX3.1 inactivation leads to anupregulation of the androgen receptor in the mouseprostate representing a possible mechanism for dis-ease progression. Recently, the oncogenic proteinkinase Pim-1 has been shown to stabilize NKX3.1levels in prostate cancer cells (and normal epi-thelium), thereby creating a mechanistic approachtoward indolence [6]. Hypothetically, this linkbetween NKX3.1 modulation and the upregulationof androgen receptor (AR) may be responsible for thedevelopment of the TMPRSS2–ERG fusion gene as aresult of alterations in chromosomal proximity andthe increase in double-strand breaks secondary toandrogen receptor binding [7].

In principle, the molecular basis for the distinc-tion between indolent and aggressive tumors mightinclude differences in the cell type of origin, thegenetic/epigenetic history of the tumor, immune

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modulation and/or mechanism by which tumorsescape suppression like cellular senescence. Under-standing these various molecular pathways thatdrive the oncogenic program should provide keyinsights into the identification of biomarkers usefulfor guiding therapy and possibly the introductionof chemoprevention. The current consensus is thatNKX3.1 loss followed by the TMPRSS2–ERG trans-location represents early events for in-situ prostatecancer. Subsequent loss or downregulation ofmolecules such as PTEN (phosphatase and tensinhomolog), cyclin dependent kinase inhibitorp27 (Kip), retinoblastoma tumor suppressor gene,E cadherin, and TP53 are thought responsible forearly invasion and subsequent metastasis [8,9]. Theexact order of events and their importance withregard to specific stages of disease progression isnot entirely understood; however, regardless oftemporal impact for promoting tumorigenesis, allof the pathways described impact on the regulatoryactivity and function of the androgen receptor(see Fig. 1).

Various combinations of the above genes and/orpathways have been evaluated using in-vivo mousemodels and human tissue cohorts. A recent studyutilized a series of transgenic models and proteinimmunohistochemical assays to identify four pro-teins that together establish a phenotype of growthand metastatic disease. In this study the combineddownregulation of PTEN and mothers againstdecapentaplegic homolog 4 (SMAD-4), a memberof the TGFb/bone morphogenic protein signalingaxis, combined with upregulation of cyclin D1 andthe cell adhesion molecule osteopontin (secretedphosphoprotein-1) was associated with biochemicalrecurrence and lethal metastasis [10]. As with themajority of prostate cancer biomarker studies to date,confirmation and validation is necessary to under-stand the significanceof thisphenotype independentof Gleason grade and PSA.

In addition to mutations and structural changesto the genome including translocations, genes canbe influenced by epigenetic events that involvereversible chemical modifications to DNA or associ-ated proteins such as histones [11]. A well describedepigenetic event in prostate cancer involvesthe methylation of the glutathione S-transferasepromoter region [12]. This enzyme is involved indetoxification of xenobiotics and carcinogens; sub-sequent downregulation is thought to be an earlyevent in prostate cancer development and in somereports, is associated with TMPRSS2 translocationand early invasion. The epigenetic downregulationof specific genes has also been shown to beimportant in more advanced disease includingmetastasis. One example is overexpression of the

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Normalepithelium

TMPRSS2:ERG

Loss of Nkx3.1 Loss of p27Loss of 10q

PTENLoss of 13q

RBLoss of 17p

p53

PSMAoverexpression

Cyclin D1overexpression

ARoverexpression

Rmaseoverexpression

Prostaticintraepithelial

neoplasia (PIN)

Invasivecarcinoma

Metastasis

FIGURE 1. Prostate cancer progression from in situ to early invasion involves a series of complex molecular events that arereadily observed at the protein level with elevated Rmase, prostate specific membrane antigen (PSMA), and concomitantandrogen receptor (AP) dysregulation. Adapted with permission from [9].

Predicting high-risk disease using tissue biomarkers Donovan and Cordon-Cardo

histone methyltransferase EZH2, through DNAmethylation and histone modification, whichdownregulates the tumor suppressor gene RASGTPase-activating protein gene DAB2IP that in turnupregulates the expression of RAS and NF-kB pro-moting tumor growth and metastasis [13]. Under-standing the importance of DAB2IP as a prognostic(or therapeutic indicator) for lethal prostate cancerat diagnosis is currently under investigation. Genemethylation status will continue to be an importantpart of biomarker discovery given the high methyl-ation state of the prostate cancer genome.

Developing a more complete understanding ofthe underlying biology of prostate cancer requiresthe integration of multiple disciplines includingin-vivo models, tumor genomics, and clinicaloutcomes. The following sections will highlightsome of the specific strategies currently underwayto identify the important drivers of disease andelucidate pathways that in the future should proveimportant in the appropriate management ofpatients newly diagnosed with prostate cancer.

Genetic susceptibility and integrativegenomics of prostate cancer

Deciphering the underlying mechanism(s) respon-sible for prostate cancer progression requires amultidisciplinary approach that includes clinical–molecular pathology, integrative genomics, andfunctional molecular imaging. This section willhighlight some important developments in prostatecancer tumor genomics and discuss the impact ofclinical–tumoral heterogeneity and complex tumorgenetics on the discovery of relevant genes, and

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pathways associated with disease progression.Despite the increased diagnosis and stage shift ofprostate cancer as a result of PSA screening, overallmortality has not changed substantially suggest-ing that many indolent, subclinical cancers arebeing diagnosed and treated [14–18]. As a resultthe traditional genetic-risk susceptibility studies inprostate cancer have shifted their emphasis towarddisease aggressiveness over early diagnosis and toidentify a molecular signature of lethal prostatecancer. Several studies have attempted to identifydiscriminating risk variants; however, the resultsthus far have been mostly inconclusive. Of rele-vance, a recent meta-analysis of genome-wideassociation studies has identified the carcino-embryonic antigen gene family as being useful fordetermining those men with clinically significantprostate cancer [19].

We will review some of the more promisingexamples arising from recent DNA-based studiesincluding a novel integrative genomics platformthat employs exome sequencing and copy numberto generate a sub-group classification scheme forprostate cancer that is independent of traditionalpathologic variables.

TMPRSS2–ETS family gene translocation:role in clinically significant disease

The previous identification of a chromosomalrearrangement leading to a fusion of the andro-gen-regulated TMPRSS2 gene (21q22) with ETStranscription factor family members, either ERG orETV1, has provided new insight into the underlyingbiology of prostate cancer [20]. The TMPRSS2–ERG


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gene fusion has since been identified fairly consist-ently in approximately 50% of all PSA screenedprostate cancers in several well characterizedprostatectomy series [21,22]. Histologically, thetranslocation has been identified in both high-grade prostatic intraepithelial neoplasia andinvasive cancer suggesting a role in early prostatecancer development; however, mouse trans-genic models evaluating aberrant expression ofERG under control of the prostate-specific promoterprobasin found that ERG was insufficient to producea cancerous phenotype. It was only when ERGwas combined with haplo-insufficiency of PTENthat a phenotype of rapid cancer developmentwas observed [23–24]. The authors hypothesize thatETS gene rearrangements may represent progressionevents as opposed to initiation of prostate tumori-genesis.

Some studies have linked the translocationto a more aggressive disease phenotype althoughthis has not been confirmed in more recentstudies evaluating ETS alterations and clinicaloutcome with the possible exception of ERGduplication and aneuploidy [25,26]. In a compre-hensive prostatectomy series by Gopalan et al. [27],the TMPRSS2 translocation was associated withlower grade and not biochemical recurrence,metastasis or death. In this study, a DNA indexassessment revealed that the majority of tumorswith copy-number increase of TMPRSS2–ERG hadgeneralized aneuploidy and the aggressivenesswas not related specifically to a rearranged chromo-some. There is evidence to suggest that the presenceof the TMPRSS2 translocation in urine, especiallyin conjunction with PCA3 gene, improvesthe sensitivity to detect prostate cancer; however,whether it is important for identifying high-risk disease has not yet been confirmed [27–29].Additional multicenter studies evaluating thisprognostic marker in well-defined patient cohortsare required to better understand the importanceof TMPRSS2 translocation with clinically signifi-cant disease.

A recently described LNCaP (prostate cancercell) model has identified a novel mechanism forthe development of a TMPRSS2 translocation inprostate cancer [7]. In this cell-based assay theandrogen receptor, acting together with a numberof key enzymes induced by androgens and geno-toxic stress, is able to create double-stranded breaksthat allowed for translocations to occur suggestingthat the translocation is an early event in the genesisof prostate cancer. The ability to temporally under-stand and then effectively measure these ‘oncogenicdrivers’ will no doubt be critical for decipheringthe underlying biology that is high-risk, in spite



of clinical–pathologic characteristics that arenoninformative.

Oncogenes and tumor suppressors inprostate cancer

Although no single genetic lesion has beenidentified as the hallmark of prostate cancer, therehave been a number of significant candidatesincluding the transcription factor (oncogene)androgen receptor and the tumor suppressorgenes PTEN, retinoblastoma gene (RB), and TP53,as mentioned previously [8,9]. Noteworthy hasbeen the lack of a specific mutation profile for thesegenes in early-stage tumors and that the mutationincidence increases in metastatic and hormone-resistant disease. It seems more likely that thecumulative effect on prostate tumor growth is morea reflection of gene loss and gain of function eitherdirectly through overexpression (e.g. androgenreceptor) or ubiquitination (e.g. p27) that impactson cell-cycle regulation and other drivers of tumorgrowth [4–6]. We believe that efforts designedto measure and integrate multiple intersectinggenomic and protein pathways, such as with asystems-based pathology platform (see below), willbe able to unravel this complexity and ideally createa more relevant disease phenocopy than isolatedmutational investigative studies.

THE ROLE OF NEW TECHNOLOGIES

Advancements in various high-throughput mole-cular technologies including genome-wide associ-ation, array comparative genomic hybridization(aCGH), and high-throughput exome sequencinghave made considerable advances toward under-standing the biology of prostate cancer but haveyet to yield a consistent phenotype of aggressivedisease. Interestingly, a recent genome-wide associ-ation study surveying 196 lethal cases and 368long-term survivors was not able to identify geneticvariants associated with prostate cancer mortality,further emphasizing the challenges facing thesetypes of analyses [30]. At the DNA level, a numberof aCGH studies have identified recurrent aberra-tions that have been selectively confirmed. Some ofthe more important changes include deletionsat 5q21, 6q15, 8p21 (NKX3.1), 21q22 (TMPRSS2–ERG fusion), 10q23 (PTEN), and 13q (retinoblastomatumor); gains at 8q24 (CMYC) and 16p13; and haplo-insufficiency for TP53, PARP1, ATM, and DNA-dependent protein kinase catalytic subunit [31].The evidence suggests that prostate cancer proceedsalong a limited number of genetic pathways thatmay serve to create subtypes of prostate cancer




comparable to what has been identified in othersolid malignancies including breast cancer.

Interestingly, a complete whole genomesequencing of seven prostate cancer specimensidentified a series of chromosomal breaks andrearrangements that were associated with chromo-somal alterations including histone methylation[32]. In this analysis abnormalities were identifiedin the PTEN gene and a gene that encodes aPTEN-interacting protein [membrane associatedguanylate kinase, WW and PDZ (protein proteinbinding region) domain-containing protein 2,MAGI2]. The data supports a role for employingsuch global sequencing efforts in an attemptto identify potentially relevant pathways drivingtumor progression. In this approach, the identifi-cation of a driver pathway may aid in identifyingthose tumors likely to progress as well as guidingselective therapy, that is, the use of PI3K/mamma-lian target of rapamycin/AKT inhibitors [33]. Thecategorization of prostate cancer based on pathwayabnormalities may help guide future treatmentdecisions including surgery vs. radiation vs. selec-tive targeted agents.

Unfortunately, many of the reported expressionstudies have been limited owing to modest cohortsize, short follow-up time, and surrogate end-pointssuch as PSA recurrence and the use of heterogeneous(i.e. multi-cell type) tissue samples in the selectedanalysis platform. As a result, these approacheshave not been able to reliably identify robustsubtypes of prostate cancer with discriminatingprognoses. A genomic study by Taylor et al. [34]has provided the perfect template for future gene-based discovery programs through an integrativeprofiling platform that incorporates DNA copy-number, mRNA expression, and focused exonresequencing to identify disease relevant signatures.The study found three specific pathways importantfor prostate cancer progression including PI3K, RAS/RAF, and androgen receptor. In addition, copy-number alteration from primary tumors appearedto play a very significant role in prostate cancersubgroups with respect to outcome and riskstate, independent of Gleason. This was especiallynoteworthy for the TMPRSS2 translocation group inwhich loss of both PTEN and TP53 was identified.Interestingly, using curated mRNA microarraysignature profiles, Markert et al. [35], were able tomolecularly classify prostate cancer into threeprognostic groups, one subset with very poor out-come exhibiting stem-cell signatures coupled withinactivation of PTEN and TP53, another group withintermediate survival outcome and the TMPRSS2–ERG translocation and a third, heterogeneous groupwith a more benign clinical course.



Although using fresh frozen tissue is preferred,the ability to identify a reasonable source of high-quality material with comprehensive clinicalfollow-up is limited. This has been especiallychallenging for prostate cancer in which only afew studies have screened reasonable numbersof patients with extended follow-up to identifyrelevant signatures for disease course. The Tayloret al. [34] study described above serves to illustrateseveral relevant points including the necessity ofusing high-quality material for assessing tumorgenomes and the importance of relying on integra-tive analytic approaches (i.e. mutation detection,copy-number alteration, and expression changes),especially relevant for tumors that exhibit a highdegree of both molecular and clinical heterogeneitylike prostate cancer.

Systems-based (precise) pathology foridentifying high-risk disease

A recently described mechanism for helpingto bridge these various investigational studieswith clinical medicine has been through the intro-duction of an analytic modeling platform known assystems pathology [36,37,38

&

,39]. The derived sys-tems-based pathology models utilize the patient’sown clinical data and intact tissue specimensto construct a baseline phenotype for defininga clinical-risk state. These biological-quantitativemodels also provide a biomarker profile that canbe linked to treatment and outcome. Systems patho-logy represents a major advance in the standardpractice of tissue-based pathology through its integ-ration of molecular and imaging data with thepatient’s clinical history. These dissimilar data setsare effectively analyzed with machine learninganalytics that select features based on their associ-ation with a clinical event. This results in a highlyaccurate multivariate predictive model that ident-ifies an individual’s probability of experiencing aspecific outcome over time. The working hypothesiswas that by using this approach and expandingthe clinical–pathological variables to includestandardized and objective morphometric featuresand molecular biomarkers, one could develop amore robust tool for predicting patient outcome.

The systems pathology program was ableto produce clinically effective models to predictoutcome both at the time of diagnosis (using thepatient’s own biopsy tissue, Pxþ biopsy test, [40

&

]) orpostsurgery (Px prostatectomy test, [41

&

]). Thequantitative and standardized assessment of specificbiomarkers such as androgen receptor and Ki67(utilizing quantitative multiplex immunofluore-scence, image analysis, and morphometry) have



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proven quite successful in stratifying patients andguiding treatment decisions including enrollmentin active surveillance programs, brachytherapy þ/�hormones, salvage radiotherapy, and surgicalapproach (i.e. incorporation of a lymph nodedissection and extent of surgical margin) [39].Most recently the biopsy Pxþ model was appliedon a large cohort (n¼181) of men enrolled inan active surveillance program and successfullypredicted time to treatment (i.e. exit from activesurveillance) with a concordance index (CI), of 0.65,(hazard ratio 3.6, P<0.0001) [42

&

]. Furthermore,these multiplex strategies should prove especiallyuseful for identifying and quantifying (i.e. count-ing) complex rare-cell events such as the cancerstem cell load (i.e. individual cells that are:CK18–/HLA1–/GLI1–2þ/Notch2þ) characterizedby Domingo–Domenech et al. [43

&

]. Being ableto evaluate this cell population in biopsy tissuesections will further identify those men most likelyto have lethal (e.g. de-novo chemoresistant) disease.

Finally, the future of tissue biomarker analysisin prostate cancer will undoubtedly involve acombination of the approaches outlined in thisreview including quantitative biomarker thresholdscoupled with morphometry (systems pathology),RNA expression profiles, and genomic changesrepresented as single-nucleotide polymorphismsor methylation signatures. In addition, there areseveral promising fluid-based methodologies thatwill add a further level of complexity for improvingpatient-risk stratification. One novel technologyincludes the gene expression signature found withinurine and/or serum isolated exosomes. It is nowfairly well established that the tumor exosomepopulation contains almost the entire transcrip-tome including a broad representation of longnoncoding transcripts [44]. For patients presentingfor a biopsy, the identification of nondigital rectalexam urine-derived exosomal PCA-3, TMPRSS2, ERGand other relevant prostate cancer-specific geneswill provide the next generation of fluid-basedtests for both early diagnosis and treatment [45].An additional approach will include the isolationand characterization of circulating tumor cells(CTC). There are a variety of new nanotechnologiesthat have improved upon yield and specificity,thereby making the CTC accessible for furtherinterrogation and at earlier time points in thedisease process [46].

CONCLUSION

One of the crucial roles for any given biomarkeris to provide information that has clinical utility,efficacy, and is actionable; adjusting a treatment



regimen (e.g. surgical margins, nerve-sparing,radiation field, dose, and bimodal therapy) orprocedure and/or therapeutic choice (i.e. targetedtherapy) based on likelihood of response. As thisreview has illustrated, the underlying biology ofprostate cancer is complex, host and tumor driven,and requires a more comprehensive assessment assupported through a systems approach. We believethat the prostate cancer test of the future willbe multidimensional and temporal, combiningtissue-derived attributes (morphometry/protein)with genomic and RNA expression patterns, andthen incorporating a series of fluid-based exosomeand/or CTC profiles during the course of the diseaseto provide a complete systems-based, precise, andpatient-centric algorithm that drives managementdecisions.

Acknowledgements

The authors would like to thank Dr Laurie Klotz forhis role in promoting Active Surveillance as a viabletreatment option for men recently diagnosed withprostate cancer.

Conflicts of interest

There are no conflicts of interest.

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This was the seminal paper in which the systems pathology analytic programwas first described in detail and then applied in a clinical setting. By utilizingmorphometry, immunohistochemistry, and subsequently quantitative multipleximmunofluorescence on formalin-fixed tissue samples the group was able toidentify a set of features that predicted the likelihood of biochemical recurrenceafter surgery. The concept of multi analyte tissue analysis with immunofluore-scence was introduced and compared with standard immunohistochemistry tofurther illustrate how this approach, when integrated with the systems pathologyplatform, is able to improve accuracy of prediction when compared with standardclinical nomograms.39. Donovan MJ, Costa J, Cordon-Cardo C. Systems pathology: a paradigm

shift in the practice of diagnostic and predictive pathology. Cancer 2009;115:3078–3084.

40.&

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Leveraging on the systems pathology platform, the authors applied the approach tothe diagnostic prostate needle biopsy specimen to predict the likely course ofdisease progression including significant disease consisting of metastasis and/ordeath on men who were all treated with curative intent surgery. This is the largeststudy to date (n¼1027 patients) using whole section analysis of the fixed biopsyspecimen to predict features associated with disease outcome.41.&

Donovan MJ, Hamann S, Clayton M, et al. Systems pathology approach for theprediction of prostate cancer progression after radical prostatectomy. J ClinOncol 2008; 26:3923–3929.

The authors applied the methods from the seminal Journal of Clinical Investiga-tionpaper on a separate 758 patient cohort to predict clinically significant disease(i.e. distant metastasis and or androgen-independent recurrence) postsurgery. Theobjective was to identify men that may be better served with early adjuvant therapypostsurgery. In this model, high levels of the androgen receptor were associatedwith a shorter time to castrate-resistant disease suggesting that androgenreceptorlevels in the de novo, untreated specimen, are important in identifyingclinically significant disease. This result was further confirmed in a variety ofsubsequent publications.42.&

Donovan MJ, Khan FH, Powell D, et al. Previously developed systems-basedmodel (Prostate Pxþ) identifies favorable-risk prostate cancer for men enrolledin active surveillance program. J Urol 2011; 185:e517–e518.

The authors applied the biopsy model from the Journal of Urology paper to a cohortof 181 patients enrolled in two Active Surveillance programs. They found thatfeatures present within the diagnostic biopsy tissue, including androgen receptorlevels, were able to identify which men were more likely to be treated, that is,likelihood of higher Gleason grade on a subsequent biopsy or shorter PSAdoubling time).43.&

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The role of the cancer stem cell as a mechanism for primary chemoresistance is anovel approach toward understanding disease potential, especially pretreatment.Through the efforts of systems pathology and multiplex immunoflouorescence,it will be possible to determine if the stem-cell load (based on the expression ofmultiple markers) can become a useful tool for screening all diagnostic biopsies(and prostatectomy specimens), as a way to predict disease outcome andultimately guide novel therapeutic strategies.44. Anand PK. Exosomal membrane molecules are potent immune response

modulators. Commun Integr Biol 2010; 3:405–408.45. Nilsson J, Skog J, Nordstrand A, et al. Prostate cancer-derived urine

exosomes: a novel approach to biomarkers for prostate cancer. Br J Cancer2009; 100:1603–1607.

46. Diamond E, Lee GY, Akhtar NH, et al. Isolation and characterization ofcirculating tumor cells in prostate cancer. Front Oncol 2012; 2:131.



CO Predicting high-risk disease using tissue biomarkers

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