Urological research is facing future challenges, the most difficult one is the
fast and meaningful transfer of the massive amount of data from research basic
to clinical practice. Between the most important issues that research should
focus in the next years are targeting of tumor stem cells, clinical application
of biomarkers, and wide application of genetic profiling of urological
neoplasms. Several clinical implications are expected, from diagnosis to
selection of candidates for different treatment modalities, to modulation of
sequential treatment plans, to prognosis. A number of clinical trials based on
research data from the hottest issues are in the pipeline. In this review, we
will focus on new insights from recent work worlwide in urological research,
with particular attention to high-risk nonmuscle-invasive and muscle-invasive
bladder cancer, prostate cancer, and kidney cancer. Cancer care is moving
towards a personalized approach in patient management. The most important issues
in urological research point strongly in this direction and show an enormous
potential for the rapid landing of Urology in the era of personalized
medicine.
BuettnerRWolfJThomasRKLessons learned from lung cancer genomics: the emerging concept
of individualized diagnostics and treatment. J Clin
Oncol. 2013; 31(15): 1858–1865.
3.
BarretinaJCaponigroGStranskyN. The Cancer Cell Line Encyclopedia enables predictive
modelling of anticancer drug sensitivity.
Nature. 2012; 483(7391): 603–607.
4.
JerónimoCHenriqueREpigenetic biomarkers in urological tumors: a systematic
review. Cancer Lett. 2014;
342(2): 264–274.
5.
JemalABrayFCenterMMFerlayJWardEFormanDGlobal cancer statistics. CA Cancer J
Clin. 2011; 61(2): 69–90.
6.
PatschanOSjödahlGChebilG, Lund Bladder Cancer Group (LBCG). Molecular
classification of T1 urothelial bladder cancer identifies high-risk
subtypes. Abstract No.: AM14-1750. http://www.uroweb.org/?id=187&aid=812. Accessed February 10,
2015.
7.
National Comprehensive
Cancer Network, I. NCCN Clinical Practice Guidelines in Oncology for Bladder
Cancer, 2012 V.1.2012.
8.
IyerGHanrahanAJMilowskyMI. Genome sequencing identifies a basis for everolimus
sensitivity. Science. 2012;
338(6104): 221.
9.
NeuzilletYPredictive markers of response to neoadjuvant chemotherapy before
cystectomy for bladder cancer, and the molecular characterization of
nonresponder tumors. http://eaustockholm2014.uroweb.org/en/the-congress/awards.
Accessed February 10, 2015.
10.
Cancer Genome Atlas
Research Network. Comprehensive molecular
characterization of urothelial bladder carcinoma. Nature.
2014; 507(7492): 315–322.
11.
KamatAMVlahouATaylorJA. Considerations on the use of urine markers in the
management of patients with high-grade non-muscle-invasive bladder
cancer. Urol Oncol. 2014;
32(7): 1069–1077.
van RhijnBWCattoJWGoebellPJ. Molecular markers for urothelial bladder cancer
prognosis: toward implementation in clinical practice.
Urol Oncol. 2014; 32(7): 1078–1087.
14.
GerlingerMCattoJWOrntoftTFRealFXZwarthoffECSwantonCIntratumour heterogeneity in urologic cancers: from molecular
evidence to clinical implications. Eur
Urol. 2015;
67:729–737.
RebouissouSBernard-PierrotIde ReynièsA. EGFR as a potential therapeutic target for a subset of
muscle-invasive bladder cancers presenting a basal-like
phenotype. Sci Transl Med.
2014; 6(244): 244ra91.
17.
RampiasTVgenopoulouPAvgerisM. A new tumor suppressor role for the Notch pathway in
bladder cancer. Nat Med. 2014;
20(10): 1199–1205.
18.
DraytonRMDudziecEPeterS. Reduced expression of miRNA-27a modulates cisplatin
resistance in bladder cancer by targeting the cystine/glutamate exchanger
SLC7A11. Clin Cancer Res.
2014; 20(7): 1990–2000.
19.
GazzanigaPde BerardinisERaimondiC. Circulating tumor cells detection has independent
prognostic impact in high-risk non-muscle invasive bladder
cancer. Int J Cancer. 2014;
135(8): 1978–1982.
20.
WichaMSHayesDFCirculating tumor cells: not all detected cells are bad and not
all bad cells are detected. J Clin Oncol.
2011; 29(12): 1508–1511.
21.
Saucedo-ZeniNMewesSNiestrojR. A novel method for the in vivo
isolation of circulating tumor cells from peripheral blood of cancer
patients using a functionalized and structured medical wire.
Int J Oncol. 2012; 41(4): 1241–1250.
22.
RinkMSoaveAEngelOFischMRiethdorfSPantelK[Tumor cells in the peripheral blood of patients with urothelial
carcinoma of the bladder: detection and impact of
circulating]. Urologe A. 2014;
53(4): 501–508.
WeinsteinJNCollissonEAMillsGBet al;Cancer Genome Atlas Research Network. The
Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet.
2013; 45(10): 1113–1120.
25.
VedderMMMárquezMde Bekker-GrobEW. Risk prediction scores for recurrence and progression of
non-muscle invasive bladder cancer: an international validation in primary
tumours. PLoS One. 2014;
9(6): e96849.
26.
JiangXLiXHuangH. Elevated levels of mitochondrion-associated autophagy
inhibitor LRPPRC are associated with poor prognosis in patients with
prostate cancer. Cancer. 2014;
120(8): 1228–1236.
27.
AhmadIGaoMPatelRLeungHYModelling synergistic interactions between HER2, Sprouty2 and
PTEN in driving prostate carcinogenesis. Asian J
Androl. 2013; 15(3): 323–327.
28.
PuhrMHoeferJNeuwirtH. PIAS1 is a crucial factor for prostate cancer cell
survival and a valid target in docetaxel resistant cells.
Oncotarget. 2014; 5(23): 12043–12056.
29.
OhSJErbHHHobischASanterFRCuligZSorafenib decreases proliferation and induces apoptosis of
prostate cancer cells by inhibition of the androgen receptor and Akt
signaling pathways. Endocr Relat Cancer.
2012; 19(3): 305–319.
30.
PerryASProstate cancer epigenomics. J
Urol. 2013; 189(1): 10–11.
LairdPWThe power and the promise of DNA methylation
markers. Nat Rev Cancer. 2003;
3(4): 253–266.
35.
EggerGLiangGAparicioAJonesPAEpigenetics in human disease and prospects for epigenetic
therapy. Nature. 2004;
429(6990): 457–463.
36.
BibikovaMLinZZhouL. High-throughput DNA methylation profiling using
universal bead arrays. Genome Res.
2006; 16(3): 383–393.
37.
GrassoCSWuYMRobinsonDR. The mutational landscape of lethal castration-resistant
prostate cancer. Nature. 2012;
487(7406): 239–243.
38.
DawsonSJTsuiDWMurtazaM. Analysis of circulating tumor DNA to monitor metastatic
breast cancer. N Engl J Med.
2013; 368(13): 1199–1209.
39.
GiulianoMGiordanoAJacksonS. Circulating tumor cells as early predictors of
metastatic spread in breast cancer patients with limited metastatic
dissemination. Breast Cancer Res.
2014; 16(5): 440.
40.
GoldkornAElyBTangenCM. Circulating tumor cell telomerase activity as a
prognostic marker for overall survival in SWOG 0421: a phase III metastatic
castration resistant prostate cancer trial. Int J
Cancer. 2015;
136:1856–1862.
41.
KhuranaKKGraneRBordenECKleinEAPrevalence of circulating tumor cells in localized prostate
cancer. Curr Urol. 2013;
7(2): 65–69.
42.
RaneJKScaravilliMYlipääA. MicroRNA expression profile of primary prostate cancer
stem cells as a source of biomarkers and therapeutic
targets. Eur Urol. 2015;
67(1): 7–10.
43.
van der HorstGBosLvan der PluijmGEpithelial plasticity, cancer stem cells, and the
tumor-supportive stroma in bladder carcinoma. Mol
Cancer Res. 2012; 10(8): 995–1009.
44.
ÖzdemirBCHenselJSecondiniC. The molecular signature of the stroma response in
prostate cancer-induced osteoblastic bone metastasis highlights expansion of
hematopoietic and prostate epithelial stem cell niches.
PLoS One. 2014; 9(12): e114530.
45.
GandelliniPGiannoniECasamicheleA. miR-205 hinders the malignant interplay between prostate
cancer cells and associated fibroblasts. Antioxid
Redox Signal. 2014; 20(7): 1045–1059.
46.
CederJAJanssonLEhrnströmRARönnstrandLAbrahamssonPAThe characterization of epithelial and stromal subsets of
candidate stem/progenitor cells in the human adult prostate.
Eur Urol. 2008; 53(3): 524–531.
47.
Al-UbaidiFLSchultzNEgevadLGranforsTHelledayTCastration therapy of prostate cancer results in downregulation
of HIF-1α levels. Int J Radiat Oncol Biol
Phys. 2012; 82(3): 1243–1248.
48.
Al-UbaidiFLSchultzNLosevaOEgevadLGranforsTHelledayTCastration therapy results in decreased Ku70 levels in prostate
cancer. Clin Cancer Res. 2013;
19(6): 1547–1556.
49.
FuQMoulJWBañezL. Preoperative predictors of pathologic stage T2a and
pathologic Gleason score ≤6 in men with clinical low-risk prostate cancer
treated with radical prostatectomy: reference for active
surveillance. Med Oncol. 2013;
30(1): 326.
50.
CanfieldSEKibelASKemeterMJFebboPGLawrenceHJMoulJWA guide for clinicians in the evaluation of emerging molecular
diagnostics for newly diagnosed prostate cancer. Rev
Urol. 2014; 16(4): 172–180.
51.
TosoianJJJohnBullETrockBJ. Pathological outcomes in men with low risk and very low
risk prostate cancer: implications on the practice of active
surveillance. J Urol. 2013;
190(4): 1218–1222.
52.
BishoffJTFreedlandSJGerberL. Prognostic utility of the cell cycle progression score
generated from biopsy in men treated with prostatectomy.
J Urol. 2014; 192(2): 409–414.
53.
CrawfordEDScholzMCKarAJ. Cell cycle progression score and treatment decisions in
prostate cancer: results from an ongoing registry.
Curr Med Res Opin. 2014; 30(6): 1025–1031.
54.
FreedlandSJGerberLReidJ. Prognostic utility of cell cycle progression score in
men with prostate cancer after primary external beam radiation
therapy. Int J Radiat Oncol Biol Phys.
2013; 86(5): 848–853.
55.
CooperbergMRSimkoJPCowanJE. Validation of a cell-cycle progression gene panel to
improve risk stratification in a contemporary prostatectomy
cohort. J Clin Oncol. 2013;
31(11): 1428–1434.
56.
CuzickJBerneyDMFisherGet al;Transatlantic Prostate Group. Prognostic
value of a cell cycle progression signature for prostate cancer death in a
conservatively managed needle biopsy cohort. Br J Cancer.
2012; 106(6): 1095–1099.
57.
CullenJRosnerILBrandTC. A biopsy-based 17-gene genomic prostate score predicts
recurrence after radical prostatectomy and adverse surgical pathology in a
racially diverse population of men with clinically low- and
intermediate-risk prostate cancer. Eur
Urol. 2015;
68:123–131.
58.
KnezevicDGoddardADNatrajN. Analytical validation of the Oncotype DX prostate cancer
assay: a clinical RT-PCR assay optimized for prostate needle
biopsies. BMC Genomics. 2013;
14(1): 690.
59.
FüttererJJBrigantiADe VisschereP. Can clinically significant prostate cancer be detected
with multiparametric magnetic resonance imaging?A systematic review of the literature. Eur Urol.
2015;
68:1045–1053.
60.
PanebiancoVBarchettiFSciarraA. Multiparametric magnetic resonance imaging
vs. standard care in men being evaluated for
prostate cancer: a randomized study. Urol Oncol. 2015;
33(1): 17.e1–17.e7.
61.
HugossonJCarlssonSOverdetection in screening for prostate cancer.
Curr Opin Urol. 2014; 24(3): 256–263.
62.
SchootsIGPetridesNGigantiF. Magnetic resonance imaging in active surveillance of
prostate cancer: a systematic review. Eur
Urol. 2015;
67:627–636.
63.
BulMZhuXValdagniR. Active surveillance for low-risk prostate cancer
worldwide: the PRIAS study. Eur Urol.
2013; 63(4): 597–603.
64.
BrattOCarlssonSHolmbergE. The Study of Active Monitoring in Sweden (SAMS): a
randomized study comparing two different follow-up schedules for active
surveillance of low-risk prostate cancer. Scand J
Urol. 2013; 47(5): 347–355.
65.
EhdaieBVertosickESpalivieroM. The impact of repeat biopsies on infectious
complications in men with prostate cancer on active
surveillance. J Urol. 2014;
191(3): 660–664.
66.
Kats-UgurluGRoodinkIde WeijertM. Circulating tumour tissue fragments in patients with
pulmonary metastasis of clear cell renal cell carcinoma.
J Pathol. 2009; 219(3): 287–293.
67.
Kats-UgurluGOosterwijkEMuselaersS. Neoadjuvant sorafenib treatment of clear cell renal cell
carcinoma and release of circulating tumor fragments.
Neoplasia. 2014; 16(3): 221–228.
68.
CreightonCJMorganMGunaratnePHet al;Cancer Genome Atlas Research Network.
Comprehensive molecular characterization of clear cell renal cell
carcinoma. Nature. 2013; 499(7456): 43–49.
69.
GerlingerMRowanAJHorswellS. Intratumor heterogeneity and branched evolution revealed
by multiregion sequencing. N Engl J Med.
2012; 366(10): 883–892.
70.
GnarraJRToryKWengY. Mutations of the VHL tumour suppressor gene in renal
carcinoma. Nat Genet. 1994;
7(1): 85–90.
71.
KapurPPeña-LlopisSChristieA. Effects on survival of BAP1 and PBRM1 mutations in
sporadic clear-cell renal-cell carcinoma: a retrospective analysis with
independent validation. Lancet Oncol.
2013; 14(2): 159–167.
72.
LatifFToryKGnarraJ. Identification of the von Hippel-Lindau disease tumor
suppressor gene. Science.
1993; 260(5112): 1317–1320.
73.
MochHAn overview of renal cell cancer: pathology and
genetics. Semin Cancer Biol.
2013; 23(1): 3–9.
74.
PawłowskiRMühlSMSulserTKrekWMochHSchramlPLoss of PBRM1 expression is associated with renal cell carcinoma
progression. Int J Cancer.
2013; 132(2): E11–E17.
75.
Peña-LlopisSVega-Rubín-de-CelisSLiaoA. BAP1 loss defines a new class of renal cell
carcinoma. Nat Genet. 2012;
44(7): 751–759.
76.
VarelaITarpeyPRaineK. Exome sequencing identifies frequent mutation of the
SWI/SNF complex gene PBRM1 in renal carcinoma.
Nature. 2011; 469(7331): 539–542.
77.
JunkerK[Possibilities of molecular diagnosis of renal cell
carcinoma]. Aktuelle Urol.
2014; 45(5): 370–373.
78.
SrigleyJRDelahuntBEbleJNet al;ISUP Renal Tumor Panel. The International
Society of Urological Pathology (ISUP) Vancouver Classification of Renal
Neoplasia. Am J Surg Pathol. 2013; 37(10): 1469–1489.
SrinivasanRRickettsCJSourbierCLinehanWMNew strategies in renal cell carcinoma: targeting the genetic and
metabolic basis of disease. Clin Cancer
Res. 2015; 21(1): 10–17.
81.
Oosterwijk-WakkaJCBoermanOCMuldersPFOosterwijkEApplication of monoclonal antibody G250 recognizing carbonic
anhydrase IX in renal cell carcinoma. Int J Mol
Sci. 2013; 14(6): 11402–23.
82.
EscudierBJKoscielnySLopatinM. Validation of a 16-gene signature for prediction of
recurrence after nephrectomy in stage I-III clear cell renal cell carcinoma
(ccRCC). 2014 ASCO Annual Meeting. J Clin
Oncol. 2014; 32: 5s
(suppl; abstr 4502).
