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Asian Journal of Urology, 2021, 8(4): 376-390    doi: 10.1016/j.ajur.2021.05.001
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Molecular markers of systemic therapy response in urothelial carcinoma
Francesco Clapsab,Maria Carmen Mira,Homayoun Zargarcd*()
a Department of Urology, Fundacion Instituto Valenciano de Oncologia, Valencia, Spain
b Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
c Department of Urology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
d Department of Surgery, University of Melbourne, Melbourne, Victoria, Australia
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Abstract: 

Identification of reliable molecular biomarkers that can complement clinical practice represents a fascinating challenge in any cancer field. Urothelial carcinoma is a very heterogeneous disease and responses to systemic therapies, and outcomes after radical cystectomy are difficult to predict. Advances in molecular biology such as next generation sequencing and whole genome or transcriptomic analysis provide promising platforms to achieve a full understanding of the biology behind the disease and can identify emerging predictive biomarkers. Moreover, the ability to categorize patients' risk of recurrence after curative treatment, or even predict benefit from a conventional or targeted therapies, represents a compelling challenge that may reshape both selection for tailored treatment and disease monitoring. Progress has been made but currently no molecular biomarkers are used in the clinical setting to predict response to systemic agents in either neoadjuvant or adjuvant settings highlighting a relevant unmet need. Here, we aim to present the emerging role of molecular biomarkers in predicting response to systemic agents in urothelial carcinoma.

Key words:  Urothelial carcinoma    Biomarkers    Neoadjuvant chemotherapy    Adjuvant chemotherapy    Targeted therapies    Precision oncology
收稿日期:  2020-09-10      修回日期:  2021-01-07      接受日期:  2021-03-04      出版日期:  2021-10-20      发布日期:  2021-11-08      整期出版日期:  2021-10-20
引用本文:    
. [J]. Asian Journal of Urology, 2021, 8(4): 376-390.
Francesco Claps,Maria Carmen Mir,Homayoun Zargar. Molecular markers of systemic therapy response in urothelial carcinoma. Asian Journal of Urology, 2021, 8(4): 376-390.
链接本文:  
http://www.ajurology.com/CN/10.1016/j.ajur.2021.05.001  或          http://www.ajurology.com/CN/Y2021/V8/I4/376
Biomarker Cohort Source Setting Systemic therapy Summary
DDR genes alterations
ERCC2 50 Tissue NAC Cisplatin-based ERCC2 mutations correlate with pCR at RC [24].
48 Tissue NAC Cisplatin-based ERCC2 alterations confer vulnerability to cisplatin traducing in better OS [25].
32 Tissue NAC Gem-Cis Deleterious ERCC2 alterations strongly predicted pDS and superior RFS [26].
ATM 34 Tissue NAC MVAC (discovery), Gem-Cis (validation) ATM mutations predicted pCR and better OS/PFS in both sets [27].
24 Tissue NAC MVAC (discovery), Gem-Cis (validation) ATM mutations predicted better OS/DSS in both sets [28].
RB1 34 Tissue NAC MVAC (discovery), Gem-Cis (validation) RB1 mutations predicted pCR and better OS/PFS in both sets [27].
24 Tissue NAC MVAC (discovery), Gem-Cis (validation) RB1 mutations predicted better OS/DSS in both sets [28].
FANCC 34 Tissue NAC MVAC (discovery), Gem-Cis (validation) FANCC mutations predicted pCR and better OS/PFS in both sets [27].
24 Tissue NAC MVAC (discovery), Gem-Cis (validation) FANCC mutations predicted better OS/DSS in both sets [28].
Driver mutations
ERBB2 71 Tissue NAC MVAC, Gem-Cis/Car (discovery/validation) ERBB2 missense mutations predicted pCR and better CSS [33].
52 Tissue NAC Gem-Cis ERBB2 mutations were correlated with pDS [34].
FGFR3 52 Tissue NAC Gem-Cis FGFR3 mutations were correlated with pDS [34].
72 Tissue NAC Gem-Cis FGFR3 alterations were correlated with pNR and with worse RFS [36].
74 Tissue AC Gem-Cis FGFR3 alterations were associated with worse RFS [36].
PIK3Ca 52 Tissue NAC Gem-Cis PIK3Ca mutations were correlated with pDS [34].
HUS1 23 Tissue NAC Gem-Cis Amplification of HUS1 predicted pNR and worse RFS [37].
ABCA13 23 Tissue NAC Gem-Cis Amplification of ABCA13 predicted pNR and worse RFS [37].
EGFR 23 Tissue NAC Gem-Cis Amplification of EGFR predicted pNR and worse RFS [37].
FIGNL1 23 Tissue NAC Gem-Cis Amplification of FIGNL1 predicted pNR and worse RFS [37].
IKZF1 23 Tissue NAC Gem-Cis Amplification of IKZF1 predicted pNR and worse RFS [37].
Liquid biopsy
CTCs 20 Blood NAC MVAC or Gem-Cis Patients with medium/high (cut-off 10 CTCs) count showed pNR [58].
CTCs 31 Blood Metastatic MVAC Patients with favorable CTCs trend showed better PFS and OS rates [59].
ctDNA 68 Plasma NAC/AC Gem-Cis/Car; Car-Eto; Gem Dynamics of ctDNA was associated with RFS and OS but not with pDS [70].
ctDNA 17 Plasma NAC Cisplatin-based Persistence of ctDNA detection during NAC predicted disease recurrence [72].
NA Urine NAC Cisplatin-based
miRs
miR-886-3p 30 Tissue AC/metastatic MVAC or Gem-Cis miR-886-3p was correlated with CR (RECIST) and better OS [76].
miR-923 30 Tissue AC/metastatic MVAC or Gem-Cis miR-923 was correlated with CR (RECIST) and better OS [76].
miR-944 30 Tissue AC/metastatic MVAC or Gem-Cis miR-944 was correlated with CR (RECIST) and better OS [76].
miR-138 30 Tissue AC/metastatic MVAC or Gem-Cis Decreasing miR-138 increased the in vitro Cis-sensitivity [76].
miR-27a 30 Tissue AC/metastatic and in-vitro analysis MVAC or Gem-Cis miR-27a overexpression increased the in vitro Cis-sensitivity [76].
354 Tissue Cisplatin-based miR-27a increased the in vitro Cis-sensitivity through SLC7A11 axis [77].
miR-642 30 Tissue AC/metastatic MVAC or Gem-Cis miR-642 overexpression increased the in vitro Cis-sensitivity [76].
miR-101 NR Tissue In-vitro analysis Cisplatin-based miR-101 downregulation induced Cis-resistance through COX-2 axis [78].
miR-193a-3p NR Tissue In-vitro analysis and in-vivo analysis Cis, Pa, Ad, Epi miR-193a-3p promotes the multi-chemoresistance [114].
miR-203 108 Tissue AC MVAC or Gem-Cis Low miR-203 expression was correlated with worse PFS and OS [115].
miR-372 83 Tissue Metastatic MVAC or Gem-Cis High miR-372 expression was associated with worse PFS [79].
miR-21 83 Tissue Metastatic MVAC or Gem-Cis High miR-21 expression was associated with a shorter PFS [79].
miR-34a 20 Tissue NAC and in-vitro analysis Cisplatin-based or Epi Increased miR-34a expression mediated in-vitro Cis-sensitivity [116].
miR-34a overexpression resulted in increased in-vitro Epi-sensitivity [117].
miR-101-3p 89 Tissue In-vitro Gem-Cis miR-101-3p overexpression increased chemosensitivity through EZH2 [80].
Cdr1as NR Tissue In-vitro Cisplatin-based Cdr1as increased Cis-sensitivity through miR-1270/APAF1 axis [81].
  
Biomarker Cohort Source Setting Systemic therapy Summary
IHC
PD-L1/PD-1 1213 Tissue Metastatic Atezolizumab+Gem-Cis/Car - High PD-L1 expression correlated with better PFS [118].
1837 Tissue Metastatic ICIs - Patients who progressed after first-line Cisplatin-based therapy had better OS and PFS when PD-L1/PD-1 was positive [92].
Liquid Biopsy
ctDNA 29 Plasma Metastatic Durvalumab (discovery/validation) - On-treatment reduction in ctDNA VAF may be a useful predictor of OS/PFS benefit [105].
ctDNA 50 Plasma NAC Gem-Cis - Patients with metastatic relapse had significantly higher ctDNA levels compared with disease-free patients [71].
10 Plasma Metastatic Atezolizumab, Car-Eto, Gem-Cis, Vin
  
Biomarker Cohort Source Setting Systemic therapy Summary
FGFR3 67 Tissue Metastatic Infigratinib - Infigratinib is active in patients with FGFR3 alterations resulting in both reductions in tumor volume and stabilization of disease (RECIST) [107].
FGFR1-3 52 Tissue Metastatic Rogaratinib - Rogaratinib is active in patients selected by overexpression of FGFR1-3 mRNA achieving an objective response (RECIST) [109].
FGFR2-3 99 Tissue Metastatic Erdafitinib - In patients with prespecified FGFR alterations erdafitinib was associated with an objective tumor response (RECIST) [110].
  
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