Molecular markers of systemic therapy response in urothelial carcinoma

doi:10.1016/j.ajur.2021.05.001

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 Claps^a,b,Maria Carmen Mir^a,Homayoun Zargar^c,d,*(

)

^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

Received: 10 September 2020 Available online: 20 October 2021

Corresponding Authors: Homayoun Zargar E-mail: homi.zargar@gmail.com

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Francesco Claps,Maria Carmen Mir,Homayoun Zargar. Molecular markers of systemic therapy response in urothelial carcinoma[J]. Asian Journal of Urology, 2021, 8(4): 376-390.

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http://www.ajurology.com/EN/10.1016/j.ajur.2021.05.001 OR http://www.ajurology.com/EN/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].
ATM	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].
RB1	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].
FANCC	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].
ERBB2	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].
ctDNA	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].
miR-27a	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	20	Tissue	NAC and in-vitro analysis	Cisplatin-based or Epi	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].

Emerging predictive molecular biomarkers of response to systemic therapies in urothelial carcinoma.

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