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    Topic review

    Urinary Bladder Cancer

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    Submitted by: Sarah Minkler

    Definition

    Urinary bladder cancer (UBC) is the most common malignancy of the urinary tract in humans, with an estimated global prevalence of 1.1 million cases over 5 years. Because of its high rates of recurrence and resistance to chemotherapy, UBC is one of the most expensive cancers to treat, resulting in significant health care costs.

    1. Introduction

    Urinary bladder cancer (UBC) is a common urogenital malignancy causing approximately 80,000 new cases and 18,000 deaths each year in the United States alone [1][2]. Urothelial carcinoma accounts for 90% of bladder cancers and can be categorized into non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) subtypes; although the majority of UBC present as NMIBC, the MIBC subtype is associated with the highest risk of developing metastases. Overall, 75% of patients diagnosed with high-risk bladder cancer will experience tumor recurrence, advancement of cancer, or decease within 10 years of their diagnosis [1]. Transurethral resection (TUR) of all visible lesions is a standard treatment for NMIBC but is associated with a high recurrence rate [3]. Intravesical chemotherapy and immunotherapy have demonstrated significant benefit in delaying disease recurrence in patients with NMIBC [4]. In MIBC patients, neoadjuvant chemotherapy with platinum-based drugs has been offered prior to local definitive treatment and has been associated with lower rates of recurrence and survival benefits [5][6]. Recently, a myriad of clinical trials has been launched to investigate the efficacy of immune checkpoint inhibitors combined with neoadjuvant therapy [7][8][9]. The outcome of these clinical trials may significantly change the therapeutic landscape of MIBC patients as half of MIBC patients are not eligible to receive platinum-based neoadjuvant chemotherapy [10]. In patients receiving treatment with neoadjuvant therapy, pathological complete response (pCR, pT0N0) rates have been observed in 20% to 50% of cases [6][7][9]. While there is still room to develop more effective neoadjuvant therapies and increase pCR rates, avoiding surgery in bladder cancer patients who completely respond to neoadjuvant therapy is a continuing challenge faced by many urologic oncologists. Additionally, disease recurrence has been reported in a subset of patients initially diagnosed with pCR, highlighting the need to identify patients who present with occult metastasis at the time of surgery, as they could benefit from active surveillance and additional therapy to prevent disease recurrence. There is a critical need to identify those patients who can safely avoid surgery following neoadjuvant therapy, as well as those who need follow-up and additional therapy [11][12][13].

    2. Current Precision Medicine-Approaches for the Treatment of Bladder Cancer Are Promising but Have Significant Drawbacks

    To date, bladder cancer management decisions have been based on conventional histological features including tumor stage, lymph node status, and histology variant at the time of diagnosis. Half of patients treated with neoadjuvant therapy, however, do not respond to treatment, highlighting our current inability to accurately predict those patients who will respond to chemotherapy [6][7][9]. Pathological factors have been evaluated for their predictive value in the context of muscle-invasive bladder cancer [14]. Specifically, patients with pure urothelial carcinoma have ~11 times more chance to experience pathological complete response post-neoadjuvant therapy (NAT) compared to tumors with histological variants or mixed tumors. While pure urothelial carcinoma constitutes ~70% of cases of bladder cancer, the remaining cases are histologic variants or have mixed histological features [15]. This intratumor heterogeneity is a significant hurdle to any clinical decision-making involving best choice of treatment for patients with UBC [16].

    Recent technological advances have allowed for efficient deep molecular profiling of bladder cancer tumors to support prediction of clinical outcomes and responses to therapy [17][18][19]. Transcriptomic profiling of biopsy and cystectomy specimens has, for instance, revealed distinct molecular subtypes of bladder cancer [18][20][21][22][23]. Similar to histology, molecular classification reveals important tumor heterogeneity with co-existence of luminal and basal subtypes within the same tumor in ~30% of cases [24][25]. However, while studies agree on gene expression signatures that identify each molecular subtype, they have shown conflicting results with regards to prediction of response to chemotherapy. Two recent studies, including one meta-analysis of 16 transcriptomic datasets, showed no significant difference in response rates to chemotherapy between tumor subtypes [20][21]. Overall, these findings collectively support the fact that UBC is a multifactorial disease whose genomic, transcriptomic, and epigenomic diversity represent a significant challenge in treatment decision-making. Additionally, the high cost of such molecular analyses and the relatively long turn-around time for data collection and downstream bioinformatic interrogation are further obstacles for personalized medicine applications [20][21]. These limitations underscore the need to develop additional biological resources that can improve patient stratification and better predict response to chemotherapy.

    3. Preclinical 2D and Patient-Derived Xenograft Models Bring Value to Drug Discovery but Have Limited Bedside Applications

    The increasingly recognized complexity and heterogeneity of bladder cancer has posed a major challenge to predicting treatment response. New tumor models generated from patient’s tumor specimens, such as primary cell lines and patient-derived xenografts, have gained attention for preclinical drug testing. Conventional two-dimensional (2D) culture of urothelial carcinoma (UC) cells [26] has traditionally been used for prediction of chemotherapeutic efficacy [27]. Over the years, a large number of bladder cancer cell lines has been established, recapitulating genomic and phenotypic heterogeneity of bladder cancer [28]. However, the majority of bladder cancer cell lines have been established from muscle-invasive and metastatic bladder cancer. While non-muscle invasive bladder cancer is the most common form of urothelial carcinoma, establishment of primary cell lines has not been successful [28][29]. Although 2D cell lines can expand rapidly and offer the possibility for high-throughput drug screening, they do not faithfully reproduce the 3-dimensional nature and cellular diversity of native bladder cancer. Compounding this, cancer-derived 2D cell lines typically exhibit genetic drift after multiple passages [30]. These limiting factors likely contribute to failure in predicting in vivo drug response in cancer patients using only 2D cell lines.

    Patient-derived xenografts (PDX) is an approach whereby patient tumor fragments are implanted into immunocompromised mice to generate tumors that recapitulate genomic and phenotypical features of a patient’s original tumor [31][32]. PDX have value in both better understanding tumor biology and evaluating the efficacy of FDA-approved anticancer therapies or novel targeted treatments [33]. Although PDX models present an exciting opportunity for improving predictive value of preclinical studies, there are several hurdles to their translation into the clinic. The lack of an immune system in the immunocompromised host makes PDX models inadequate for modeling immune response and testing immunotherapies. Further, engraftment rates tend to positively correlate with tumor grade, meaning that low-grade patient tumors may not lead to a high yield of viable mouse tumors [34][35]. Finally, engrafted tumors can take several months to grow. This is a critical drawback for their application in translational medicine as, in the neoadjuvant setting, treatment is usually initiated within 3-4 weeks from the time of diagnosis. An ideal tumor model would combine the rapid growth and high-throughput potential of 2D models with the faithful recapitulation of host tumor microenvironment provided by PDX platforms.

    This entry is adapted from 10.3390/cancers13030422

    References

    1. Chamie, K.; Litwin, M.S.; Bassett, J.C.; Daskivich, T.J.; Lai, J.; Hanley, J.M.; Konety, B.R.; Saigal, C.S. Recurrence of high-risk bladder cancer: A population-based analysis. Cancer 2013, 119, 3219–3227, doi:10.1002/cncr.28147.
    2. Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer statistics, 2019. CA Cancer J. Clin. 2019, 69, 7–34, doi:10.3322/caac.21551.
    3. Kamat, A.M.; Hahn, N.M.; Efstathiou, J.A.; Lerner, S.P.; Malmström, P.U.; Choi, W.; Guo, C.C.; Lotan, Y.; Kassouf, W. Bladder cancer. Lancet 2016, 388, 2796–2810, doi:10.1016/s0140-6736(16)30512-8.
    4. Neoadjuvant chemotherapy in invasive bladder cancer: Update of a systematic review and meta-analysis of individual patient data advanced bladder cancer (ABC) meta-analysis collaboration. Urol. 2005, 48, 202–205; discussion 205–206, doi:10.1016/j.eururo.2005.04.006.
    5. Peyton, C.C.; Tang, D.; Reich, R.R.; Azizi, M.; Chipollini, J.; Pow-Sang, J.M.; Manley, B.; Spiess, P.E.; Poch, M.A.; Sexton, W.J.; et al. Downstaging and Survival Outcomes Associated With Neoadjuvant Chemotherapy Regimens Among Patients Treated With Cystectomy for Muscle-Invasive Bladder Cancer. JAMA Oncol. 2018, 4, 1535–1542, doi:10.1001/jamaoncol.2018.3542.
    6. Gao, J.; Navai, N.; Alhalabi, O.; Siefker-Radtke, A.; Campbell, M.T.; Tidwell, R.S.; Guo, C.C.; Kamat, A.M.; Matin, S.F.; Araujo, J.C.; et al. Neoadjuvant PD-L1 plus CTLA-4 blockade in patients with cisplatin-ineligible operable high-risk urothelial carcinoma. Med. 2020, 26, 1845–1851, doi:10.1038/s41591-020-1086-y.
    7. Powles, T.; Kockx, M.; Rodriguez-Vida, A.; Duran, I.; Crabb, S.J.; Van Der Heijden, M.S.; Szabados, B.; Pous, A.F.; Gravis, G.; Herranz, U.A.; et al. Clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial. Med. 2019, 25, 1706–1714, doi:10.1038/s41591-019-0628-7.
    8. Necchi, A.; Anichini, A.; Raggi, D.; Briganti, A.; Massa, S.; Lucianò, R.; Colecchia, M.; Giannatempo, P.; Mortarini, R.; Bianchi, M.; et al. Pembrolizumab as Neoadjuvant Therapy Before Radical Cystectomy in Patients With Muscle-Invasive Urothelial Bladder Carcinoma (PURE-01): An Open-Label, Single-Arm, Phase II Study. Clin. Oncol. 2018, 36, 3353–3360, doi:10.1200/jco.18.01148.
    9. Thompson, R.H.; Boorjian, S.A.; Kim, S.P.; Cheville, J.C.; Thapa, P.; Tarrel, R.; Dronca, R.; Costello, B.; Frank, I. Eligibility for neoadjuvant/adjuvant cisplatin-based chemotherapy among radical cystectomy patients. BJU Int. 2014, 113, E17-21, doi:10.1111/bju.12274.
    10. Bhindi, B.; Frank, I.; Mason, R.J.; Tarrell, R.F.; Thapa, P.; Cheville, J.C.; Costello, B.A.; Pagliaro, L.C.; Karnes, R.J.; Thompson, R.H.; et al. Oncologic Outcomes for Patients with Residual Cancer at Cystectomy Following Neoadjuvant Chemotherapy: A Pathologic Stage-matched Analysis. Urol. 2017, 72, 660–664, doi:10.1016/j.eururo.2017.05.016.
    11. Mazza, P.; Moran, G.W.; Li, G.; Robins, D.J.; Matulay, J.T.; Herr, H.W.; Decastro, G.J.; McKiernan, J.M.; Anderson, C.B. Conservative Management Following Complete Clinical Response to Neoadjuvant Chemotherapy of Muscle Invasive Bladder Cancer: Contemporary Outcomes of a Multi-Institutional Cohort Study. Urol. 2018, 200, 1005–1013, doi:10.1016/j.juro.2018.05.078.
    12. Robins, D.; Matulay, J.; Lipsky, M.; Meyer, A.; Ghandour, R.; DeCastro, G.; Anderson, C.; Drake, C.; Benson, M.; McKiernan, J.M. Outcomes Following Clinical Complete Response to Neoadjuvant Chemotherapy for Muscle-invasive Urothelial Carcinoma of the Bladder in Patients Refusing Radical Cystectomy. Urology 2018, 111, 116–121, doi:10.1016/j.urology.2017.09.003.
    13. Pokuri, V.K.; Syed, J.R.; Yang, Z.; Field, E.P.; Cyriac, S.; Pili, R.; Levine, E.G.; Azabdaftari, G.; Trump, D.L.; Guru, K.; et al. Predictors of Complete Pathologic Response (pT0) to Neoadjuvant Chemotherapy in Muscle-invasive Bladder Carcinoma. Genitourin. Cancer 2016, 14, e59–65, doi:10.1016/j.clgc.2015.09.013.
    14. Humphrey, P.A.; Moch, H.; Cubilla, A.L.; Ulbright, T.M.; Reuter, V.E. The 2016 WHO Classification of Tumours of the Urinary System and Male Genital Organs-Part B: Prostate and Bladder Tumours. Urol. 2016, 70, 106–119, doi:10.1016/j.eururo.2016.02.028.
    15. Naspro, R.; Finati, M.; Roscigno, M.; Pellucchi, F.; La Croce, G.; Sodano, M.; Manica, M.; Chinaglia, D.; Da Pozzo, L.F. The impact of histological variants on outcomes after open radical cystectomy for muscle-invasive urothelial bladder cancer: Results from a single tertiary referral centre. World J. Urol. 2020, 10.1007/s00345-020-03364-z, doi:10.1007/s00345-020-03364-z.
    16. Kamoun, A.; de Reyniès, A.; Allory, Y.; Sjödahl, G.; Robertson, A.G.; Seiler, R.; Hoadley, K.A.; Groeneveld, C.S.; Al-Ahmadie, H.; Choi, W.; et al. A Consensus Molecular Classification of Muscle-invasive Bladder Cancer. Urol. 2020, 77, 420–433, doi:10.1016/j.eururo.2019.09.006.
    17. Robertson, A.G.; Kim, J.; Al-Ahmadie, H.; Bellmunt, J.; Guo, G.; Cherniack, A.D.; Hinoue, T.; Laird, P.W.; Hoadley, K.A.; Akbani, R.; et al. Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. Cell 2017, 171, 540-556.e525, doi:10.1016/j.cell.2017.09.007.
    18. Batista da Costa, J.; Gibb, E.A.; Bivalacqua, T.J.; Liu, Y.; Oo, H.Z.; Miyamoto, D.T.; Alshalalfa, M.; Davicioni, E.; Wright, J.; Dall'Era, M.A.; et al. Molecular Characterization of Neuroendocrine-like Bladder Cancer. Cancer Res. 2019, 25, 3908–3920, doi:10.1158/1078-0432.Ccr-18-3558.
    19. Seiler, R.; Ashab, H.A.D.; Erho, N.; van Rhijn, B.W.G.; Winters, B.; Douglas, J.; Van Kessel, K.E.; Fransen van de Putte, E.E.; Sommerlad, M.; Wang, N.Q.; et al. Impact of Molecular Subtypes in Muscle-invasive Bladder Cancer on Predicting Response and Survival after Neoadjuvant Chemotherapy. Urol. 2017, 72, 544–554, doi:10.1016/j.eururo.2017.03.030.
    20. Network, C.G.A.R. Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 2014, 507, 315–322, doi:10.1038/nature12965.
    21. Necchi, A.; Raggi, D.; Gallina, A.; Ross, J.S.; Farè, E.; Giannatempo, P.; Marandino, L.; Colecchia, M.; Lucianò, R.; Bianchi, M.; et al. Impact of Molecular Subtyping and Immune Infiltration on Pathological Response and Outcome Following Neoadjuvant Pembrolizumab in Muscle-invasive Bladder Cancer. Urol. 2020, 77, 701–710, doi:10.1016/j.eururo.2020.02.028.
    22. Choi, W.; Porten, S.; Kim, S.; Willis, D.; Plimack, E.R.; Hoffman-Censits, J.; Roth, B.; Cheng, T.; Tran, M.; Lee, I.L.; et al. Identification of distinct basal and luminal subtypes of muscle-invasive bladder cancer with different sensitivities to frontline chemotherapy. Cancer Cell. 2014, 25, 152–165, doi:10.1016/j.ccr.2014.01.009.
    23. Warrick, J.I.; Sjödahl, G.; Kaag, M.; Raman, J.D.; Merrill, S.; Shuman, L.; Chen, G.; Walter, V.; DeGraff, D.J. Intratumoral Heterogeneity of Bladder Cancer by Molecular Subtypes and Histologic Variants. Urol. 2019, 75, 18–22, doi:10.1016/j.eururo.2018.09.003.
    24. Thomsen, M.B.H.; Nordentoft, I.; Lamy, P.; Vang, S.; Reinert, L.; Mapendano, C.K.; Høyer, S.; Ørntoft, T.F.; Jensen, J.B.; Dyrskjøt, L. Comprehensive multiregional analysis of molecular heterogeneity in bladder cancer. Rep. 2017, 7, 11702, doi:10.1038/s41598-017-11291-0.
    25. Moret, R.; Hellmers, L.; Zhang, X.; Gills, J.; Hite, N.; Klinger, A.; Maresh, G.A.; Canter, D.; Bardot, S.; Margolin, D.A.; et al. Patient-derived Orthotopic Xenograft Models for Human Urothelial Cell Carcinoma and Colorectal Cancer Tumor Growth and Spontaneous Metastasis. Vis. Exp. 2019, 10.3791/59223, doi:10.3791/59223.
    26. Hutterer, G.C. Special Issue on Molecular Research Efforts in Urothelial Carcinoma: Summary of Included Topics. J. Mol. Sci. 2019, 20, doi:10.3390/ijms20153790.
    27. Nickerson, M.L.; Witte, N.; Im, K.M.; Turan, S.; Owens, C.; Misner, K.; Tsang, S.X.; Cai, Z.; Wu, S.; Dean, M.; et al. Molecular analysis of urothelial cancer cell lines for modeling tumor biology and drug response. Oncogene 2017, 36, 35–46, doi:10.1038/onc.2016.172.
    28. Zuiverloon, T.C.M.; de Jong, F.C.; Costello, J.C.; Theodorescu, D. Systematic Review: Characteristics and Preclinical Uses of Bladder Cancer Cell Lines. Bladder Cancer 2018, 4, 169–183, doi:10.3233/blc-180167.
    29. Earl, J.; Rico, D.; Carrillo-de-Santa-Pau, E.; Rodríguez-Santiago, B.; Méndez-Pertuz, M.; Auer, H.; Gómez, G.; Grossman, H.B.; Pisano, D.G.; Schulz, W.A.; et al. The UBC-40 Urothelial Bladder Cancer cell line index: A genomic resource for functional studies. BMC Genom. 2015, 16, 403, doi:10.1186/s12864-015-1450-3.
    30. Siracusano, S.; Rizzetto, R.; Porcaro, A.B. Bladder cancer genomics. Urologia 2020, 87, 49–56, doi:10.1177/0391560319899011.
    31. Kim, K.; Hu, W.; Audenet, F.; Almassi, N.; Hanrahan, A.J.; Murray, K.; Bagrodia, A.; Wong, N.; Clinton, T.N.; Dason, S.; et al. Modeling biological and genetic diversity in upper tract urothelial carcinoma with patient derived xenografts. Commun. 2020, 11, 1975, doi:10.1038/s41467-020-15885-7.
    32. Zeng, S.X.; Zhu, Y.; Ma, A.H.; Yu, W.; Zhang, H.; Lin, T.Y.; Shi, W.; Tepper, C.G.; Henderson, P.T.; Airhart, S.; et al. The Phosphatidylinositol 3-Kinase Pathway as a Potential Therapeutic Target in Bladder Cancer. Cancer Res. 2017, 23, 6580–6591, doi:10.1158/1078-0432.Ccr-17-0033.
    33. Ambrosini, Y.M.; Park, Y.; Jergens, A.E.; Shin, W.; Min, S.; Atherly, T.; Borcherding, D.C.; Jang, J.; Allenspach, K.; Mochel, J.P.; et al. Recapitulation of the accessible interface of biopsy-derived canine intestinal organoids to study epithelial-luminal interactions. PLoS ONE 2020, 15, e0231423, doi:10.1371/journal.pone.0231423.
    34. Abe, T.; Tada, M.; Shinohara, N.; Okada, F.; Itoh, T.; Hamada, J.; Harabayashi, T.; Chen, Q.; Moriuchi, T.; Nonomura, K. Establishment and characterization of human urothelial cancer xenografts in severe combined immunodeficient mice. J. Urol. 2006, 13, 47–57, doi:10.1111/j.1442-2042.2006.01220.x.
    35. Bernardo, C.; Costa, C.; Amaro, T.; Gonçalves, M.; Lopes, P.; Freitas, R.; Gärtner, F.; Amado, F.; Ferreira, J.A.; Santos, L. Patient-derived sialyl-Tn-positive invasive bladder cancer xenografts in nude mice: An exploratory model study. Anticancer Res. 2014, 34, 735–744.
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