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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">IJO</journal-id>
<journal-title-group>
<journal-title>International Journal of Oncology</journal-title></journal-title-group>
<issn pub-type="ppub">1019-6439</issn>
<issn pub-type="epub">1791-2423</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name></publisher></journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3892/ijo.2025.5841</article-id>
<article-id pub-id-type="publisher-id">ijo-68-02-05841</article-id>
<article-categories>
<subj-group>
<subject>Review</subject></subj-group></article-categories>
<title-group>
<article-title>Targeted therapies for urothelial carcinoma: From FGFR inhibitors to next-generation antibody-drug conjugates (Review)</article-title></title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Du</surname><given-names>Jinping</given-names></name><xref rid="af1-ijo-68-02-05841" ref-type="aff">1</xref><xref rid="af2-ijo-68-02-05841" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>Shen</surname><given-names>Hao</given-names></name><xref rid="af1-ijo-68-02-05841" ref-type="aff">1</xref><xref rid="af2-ijo-68-02-05841" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>Zeng</surname><given-names>Tongwei</given-names></name><xref rid="af1-ijo-68-02-05841" ref-type="aff">1</xref><xref rid="af2-ijo-68-02-05841" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>Liu</surname><given-names>Wei</given-names></name><xref rid="af1-ijo-68-02-05841" ref-type="aff">1</xref><xref rid="af2-ijo-68-02-05841" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Xie</surname><given-names>Yongqiang</given-names></name><xref rid="af1-ijo-68-02-05841" ref-type="aff">1</xref><xref rid="af2-ijo-68-02-05841" ref-type="aff">2</xref><xref ref-type="corresp" rid="c1-ijo-68-02-05841"/></contrib></contrib-group>
<aff id="af1-ijo-68-02-05841">
<label>1</label>Gansu University of Chinese Medicine, Lanzhou, Gansu 730000, P.R. China</aff>
<aff id="af2-ijo-68-02-05841">
<label>2</label>Department of Urology, The Third Affiliated Hospital of Gansu University of Traditional Chinese Medicine, Baiyin, Gansu 730900, P.R. China</aff>
<author-notes>
<corresp id="c1-ijo-68-02-05841">Correspondence to: Professor Yongqiang Xie, Department of Urology, The Third Affiliated Hospital of Gansu University of Traditional Chinese Medicine, 222 Silong Road, Baiyin, Gansu 730900, P.R. China, E-mail: <email>452062491@qq.com</email></corresp></author-notes>
<pub-date pub-type="collection">
<month>02</month>
<year>2026</year></pub-date>
<pub-date pub-type="epub">
<day>22</day>
<month>12</month>
<year>2025</year></pub-date>
<volume>68</volume>
<issue>2</issue>
<elocation-id>28</elocation-id>
<history>
<date date-type="received">
<day>14</day>
<month>09</month>
<year>2025</year></date>
<date date-type="accepted">
<day>06</day>
<month>11</month>
<year>2025</year></date></history>
<permissions>
<copyright-statement>Copyright: &#x000A9; 2025 Du et al.</copyright-statement>
<copyright-year>2025</copyright-year>
<license license-type="open-access">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivs License</ext-link>, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.</license-p></license></permissions>
<abstract>
<p>Treatment of urothelial carcinoma (UC), particularly in metastatic or cisplatin-ineligible patients, remains challenging because of limited durable responses to conventional chemotherapy and immune checkpoint inhibitors. Recent advances in targeted therapies, including FGFR inhibitors (for example, erdafitinib) and antibody-drug conjugates (ADCs) targeting Nectin-4 (enfortumab vedotin) and HER2 (disitamab vedotin), have reshaped treatment paradigms. FGFR3 alterations, which are present in 20-40% of patients with advanced UC, predict sensitivity to FGFR tyrosine kinase inhibitors, whereas ADCs demonstrate efficacy across biomarker-selected and unselected populations. However, clinical implementation is complicated by resistance mechanisms, such as kinase switching, phenotypic plasticity and tumor microenvironment interactions, as well as biomarker heterogeneity. The present review synthesizes current evidence on molecularly guided therapies, contrasts resistance mechanisms between FGFR inhibitors and ADCs, and evaluates strategies to overcome therapeutic limitations. By integrating translational insights and emerging preclinical data, it was aimed to provide a roadmap for optimizing biomarker-driven approaches, novel combinations and next-generation agents for the treatment of UC.</p></abstract>
<kwd-group>
<title>Key words</title>
<kwd>urothelial carcinoma</kwd>
<kwd>targeted therapy</kwd>
<kwd>fibroblast growth factor receptor inhibitors</kwd>
<kwd>antibody-drug conjugates</kwd>
<kwd>biomarkers</kwd>
<kwd>resistance mechanisms</kwd>
<kwd>precision medicine</kwd>
<kwd>therapeutic strategies</kwd></kwd-group>
<funding-group>
<award-group>
<funding-source>Baiyin City Science and Technology Plan Project</funding-source>
<award-id>2023-2-14Y</award-id></award-group>
<funding-statement>The present study was supported by Baiyin City Science and Technology Plan Project (Preclinical study of c-MET targeted therapy in bladder cancer; grant no. 2023-2-14Y).</funding-statement></funding-group></article-meta></front>
<body>
<sec sec-type="intro">
<label>1.</label>
<title>Introduction</title>
<p>Urothelial carcinoma (UC) is a neoplastic growth that originates in the urinary tract lining and extends from the renal pelvis to the urethra. It encompasses a range of histological subtypes and anatomical locations, including upper tract UC (UTUC) and primary urethral cancer (<xref rid="b1-ijo-68-02-05841" ref-type="bibr">1</xref>). UTUC accounts for 5-10% of UC cases, whereas primary urethral cancer is even rarer (<xref rid="b2-ijo-68-02-05841" ref-type="bibr">2</xref>). In the United States, it is estimated that there were 87,840 new cases of bladder cancer and 17,840 deaths in 2024, making it the fifth most common cancer in men and the fourteenth in women. The incidence rates of bladder cancer in the US are ~82.3 per 100,000 in men and 21.3 per 100,000 in women (<xref rid="b3-ijo-68-02-05841" ref-type="bibr">3</xref>). In Europe, bladder cancer ranks as the tenth most common cancer, with ~226,000 new cases and 69,000 deaths annually. The incidence rates vary across European countries, with higher rates observed in southern and eastern Europe (<xref rid="b3-ijo-68-02-05841" ref-type="bibr">3</xref>). In Asia, the incidence of UC is lower than that in Western countries, but it still poses a significant health burden, especially in rapidly industrializing regions. For instance, in China, the incidence of bladder cancer is ~13.5 per 100,000, with higher rates in urban areas (<xref rid="b3-ijo-68-02-05841" ref-type="bibr">3</xref>). However, bladder cancer remains a notable health issue in some regions, with incidence rates influenced by factors such as schistosomiasis infection. Globally, the aggressive nature and high recurrence rate of UC make it a challenging disease to manage globally.</p>
<p>Advanced UC, particularly in metastatic or cisplatin-ineligible patients, is associated with poor prognosis (<xref rid="b4-ijo-68-02-05841" ref-type="bibr">4</xref>). The 5-year survival rate for patients with advanced UC is ~10%, highlighting an urgent need for more effective treatment strategies (<xref rid="b5-ijo-68-02-05841" ref-type="bibr">5</xref>). Traditional treatment methods, such as platinum-based chemotherapy, have limitations related to achieving durable responses. For patients with advanced UC being treated with platinum-based chemotherapy, the median OS is typically less than 15 months (<xref rid="b6-ijo-68-02-05841" ref-type="bibr">6</xref>). While the use of immune checkpoint inhibitors (ICIs) has shown promise, their efficacy varies, and numerous patients eventually develop resistance (<xref rid="b7-ijo-68-02-05841" ref-type="bibr">7</xref>). A meta-analysis of 11 trials including 1,630 previously treated patients with UC revealed that the pooled objective response rate (ORR) for single targeted agents was 10.7% (95% CI: 10.7-19.6%), the disease control rate was 33.2% (95% CI: 25-41.4%), and the 1-year OS was 31% (95% CI: 23.6-39.4%) (<xref rid="b8-ijo-68-02-05841" ref-type="bibr">8</xref>). These findings underscore the critical need for novel approaches to improve patient outcomes in this patient population.</p>
<p>Over the past decade, the treatment landscape for UC has evolved significantly with the advent of targeted therapies. Erdafitinib, a fibroblast growth factor receptor (FGFR) inhibitor, and enfortumab vedotin (EV), an antibody-drug conjugates (ADCs) targeting Nectin-4, have demonstrated significant efficacy for the treatment of UC. Erdafitinib achieved a 40% ORR in a phase II trial for patients with FGFR2/3-altered UC (<xref rid="b9-ijo-68-02-05841" ref-type="bibr">9</xref>). EV showed a robust ORR of 43% in a phase I trial, even in patients whose cancer had previously progressed on ICIs (<xref rid="b10-ijo-68-02-05841" ref-type="bibr">10</xref>). These advancements mark a significant shift from traditional chemotherapy and underscore the importance of molecularly guided therapies in improving the prognosis of patients with UC. Ongoing research continues to explore the optimal sequencing of these therapies and the development of next-generation agents to further improve treatment outcomes.</p>
<p>Unlike prior reviews that have separately summarized FGFR inhibitors or ADCs, the present article integrates real-world evidence, biomarker analytics, and resistance biology into a single comparative framework. Recent literature gaps include insufficient head-to-head evaluation of FGFR inhibitors vs. ADCs sequences, limited dissection of convergent resistance pathways (for example, PI3K/AKT re-activation and TGF-&#x003B2;-mediated immune exclusion), and absence of a unified roadmap guiding biomarker-driven combination therapy. By synthesizing 2023-2025 trial data with spatial transcriptomic and urinary circulating-tumor-DNA studies, the present review offers a dynamic, systems-level perspective that links genomic alteration, tumor microenvironment (TME) phenotype, and clinical outcomes; such integration has not been previously accomplished in UC-focused commentaries. Consequently, the manuscript provides clinicians and translational researchers with an evidence-based hierarchy for selecting FGFR or ADCs-based regimens, forecasts emerging resistance mechanisms, and proposes biomarker-adaptive trial designs to accelerate precision medicine implementation.</p></sec>
<sec sec-type="other">
<label>2.</label>
<title>Molecular biology of UC</title>
<p>In recent years, with advancements in genomics and molecular biology technologies, the molecular landscape of UC has been gradually unveiled. Various molecular alterations and signaling pathways interact synergistically, driving tumor development and progression (<xref rid="b11-ijo-68-02-05841" ref-type="bibr">11</xref>). A deeper understanding of the molecular biology of UC provides a strong foundation for the development of targeted therapies. By identifying key molecular targets and pathways (<xref rid="f1-ijo-68-02-05841" ref-type="fig">Fig. 1</xref>), researchers can develop more effective therapeutic strategies to improve treatment outcomes and survival rates for patients with UC (<xref rid="b12-ijo-68-02-05841" ref-type="bibr">12</xref>).</p>
<sec>
<title>Key molecular pathways</title>
<p>UC development and progression involve complex molecular mechanisms. Among them, the Phosphatidylinositol 3-kinase (PI3K)/Protein Kinase B(AKT)/Mammalian Target of Rapamycin (mTOR) pathway plays a significant role (<xref rid="b13-ijo-68-02-05841" ref-type="bibr">13</xref>). This pathway is frequently activated due to mutations in genes such as PIK3CA, PTEN deletion, or AKT1 mutation (<xref rid="b14-ijo-68-02-05841" ref-type="bibr">14</xref>). PI3K catalyzes the production of PIP3, which activates AKT. Activated AKT, in turn, phosphorylates mTOR, promoting cell survival, proliferation and inhibiting apoptosis (<xref rid="b14-ijo-68-02-05841" ref-type="bibr">14</xref>). Studies have shown that PIK3CA mutations are present in ~24-40% of UC cases (<xref rid="b15-ijo-68-02-05841" ref-type="bibr">15</xref>). PTEN deletion occurs in ~17-30% of cases (<xref rid="b16-ijo-68-02-05841" ref-type="bibr">16</xref>). Activation of this pathway contributes to UC progression and chemoresistance. For example, in a particular study, PTEN-deficient mice were more prone to developing UC and displayed more aggressive tumor characteristics, such as increased proliferation rates and higher metastatic potential (<xref rid="b17-ijo-68-02-05841" ref-type="bibr">17</xref>).</p>
<p>The Receptor Tyrosine Kinase (RTK)/Rat Sarcoma (RAS)/V-Raf Murine Sarcoma Viral Oncogene Homolog (RAF)/Mitogen-Activated Protein Kinase Kinase (MEK)/Extracellular Signal-Regulated Kinase (ERK) pathway is another critical signaling pathway (<xref rid="b18-ijo-68-02-05841" ref-type="bibr">18</xref>). Abnormal activation of this pathway can be caused by mutations in FGFR, RAS, or BRAF genes. FGFR gene alterations, including mutations, fusions and amplifications, can lead to ligand-independent receptor activation, subsequently activating downstream signaling pathways (<xref rid="b19-ijo-68-02-05841" ref-type="bibr">19</xref>). RAS mutations are found in ~15-30% of UC cases, and BRAF mutations occur in ~5-10% of cases (<xref rid="b20-ijo-68-02-05841" ref-type="bibr">20</xref>). Activation of this pathway promotes cell proliferation, differentiation and angiogenesis. For example, a study by Zhou <italic>et al</italic> (<xref rid="b21-ijo-68-02-05841" ref-type="bibr">21</xref>) demonstrated that mutations in this pathway are associated with tumor progression and poor prognosis in patient with UC.</p>
<p>The Tumor Protein 53 (TP53) gene mutation pathway is also crucial in UC. TP53 is a tumor suppressor gene, and its encoded protein plays a pivotal role in cell cycle regulation, DNA repair and apoptosis (<xref rid="b22-ijo-68-02-05841" ref-type="bibr">22</xref>). TP53 mutations are detected in ~40-50% of UC cases. Mutations in this gene lead to loss of its normal function, enabling cells with DNA damage to continue proliferating, thereby promoting tumor development and progression (<xref rid="b22-ijo-68-02-05841" ref-type="bibr">22</xref>). Ecke <italic>et al</italic> (<xref rid="b23-ijo-68-02-05841" ref-type="bibr">23</xref>) revealed that TP53 mutations are associated with higher tumor grade and stage in UC and are linked to poor patient prognosis.</p></sec>
<sec>
<title>FGFR alterations</title>
<p>FGFR gene alterations are prevalent in UC. FGFR family includes FGFR1-4. Among them, FGFR3 alterations are the most common in UC, occurring in ~10-30% of cases (<xref rid="b24-ijo-68-02-05841" ref-type="bibr">24</xref>). FGFR3 gene mutations primarily involve point mutations in the tyrosine kinase domain, such as R248C, S249C and Y373C mutations, which lead to receptor constitutive activation (<xref rid="b25-ijo-68-02-05841" ref-type="bibr">25</xref>). FGFR3 gene fusions, such as FGFR3-TACC3 fusions, can also result in abnormal receptor activation. FGFR gene amplifications can increase receptor expression levels, thereby enhancing downstream signaling pathway activation (<xref rid="b26-ijo-68-02-05841" ref-type="bibr">26</xref>). These alterations contribute to tumor cell proliferation and progression. For example, Liu <italic>et al</italic> (<xref rid="b26-ijo-68-02-05841" ref-type="bibr">26</xref>) showed that FGFR3 mutations are associated with tumor recurrence and progression in non-muscle-invasive bladder cancer. FGFR3 alterations are more common in non-muscle-invasive UC, with a detection rate of ~15-20%, while in muscle-invasive UC, the detection rate is ~5-10%. FGFR2 alterations are relatively rare in UC but are also involved in tumor progression.</p></sec>
<sec>
<title>Other molecular targets</title>
<p>In addition to the aforementioned molecular pathways and FGFR alterations, other molecular targets also play important roles in UC. TROP2 is a transmembrane glycoprotein that is highly expressed in UC and other solid tumors. Its overexpression is associated with tumor aggressiveness and poor prognosis (<xref rid="b27-ijo-68-02-05841" ref-type="bibr">27</xref>). Sacituzumab govitecan, a TROP2-targeted ADCs, has demonstrated significant efficacy in the treatment of metastatic UC (<xref rid="b28-ijo-68-02-05841" ref-type="bibr">28</xref>). Nectin-4 is another molecule highly expressed in UC. EV, an ADCs targeting Nectin-4, has shown remarkable therapeutic effects in locally advanced or metastatic UC (<xref rid="b29-ijo-68-02-05841" ref-type="bibr">29</xref>). HER-2 is overexpressed in a subset of patients with UC. Trastuzumab deruxtecan, a HER-2-targeted ADCs, has shown promising efficacy in HER-2-overexpressing UC (<xref rid="b30-ijo-68-02-05841" ref-type="bibr">30</xref>). The expression levels of these molecular targets are closely related to tumor biology and patient prognosis.</p></sec></sec>
<sec sec-type="other">
<label>3.</label>
<title>FGFR pathway-directed therapies: Foundations and clinical implementation</title>
<p>The increasing understanding of FGFR pathway dysregulation in UC has driven the development of targeted therapies. The molecular basis of FGFR abnormalities in UC are addressed in the present section, the clinical data of FGFR inhibitors such as erdafitinib and infigratinib are reviewed, and resistance mechanisms are discussed, aiming to guide optimal use of FGFR-targeted strategies in clinical practice (<xref rid="f2-ijo-68-02-05841" ref-type="fig">Fig. 2</xref>).</p>
<sec>
<title>Molecular basis of FGFR dysregulation in UC</title>
<p>Dysregulation of the FGFR signaling pathway through amplifications, mutations and gene fusions has been implicated in UC (<xref rid="b31-ijo-68-02-05841" ref-type="bibr">31</xref>). FGFR signaling plays crucial roles in tumor cell proliferation, angiogenesis, migration and survival (<xref rid="b32-ijo-68-02-05841" ref-type="bibr">32</xref>) (<xref rid="tI-ijo-68-02-05841" ref-type="table">Table I</xref>). FGFR pathway dysregulation is a hallmark of UC, primarily driven by genetic alterations in FGFR3 and, less frequently, FGFR2. These aberrations include activating mutations, gene fusions and amplifications, which constitutively activate downstream signaling cascades such as RAS/MAPK and PI3K/AKT, promoting tumor proliferation and survival (<xref rid="b33-ijo-68-02-05841" ref-type="bibr">33</xref>,<xref rid="b34-ijo-68-02-05841" ref-type="bibr">34</xref>).</p>
<p>Comprehensive genomic profiling of 295 advanced UC cases revealed FGFR3 alterations in 15% of tumors, predominantly point mutations (for example, S249C, R248C and Y375C) and fusions (for example, FGFR3-TACC3) (<xref rid="b33-ijo-68-02-05841" ref-type="bibr">33</xref>). In muscle-invasive UC, FGFR3 mutations occur in 20% of cases, often co-occurring with TP53 mutations, suggesting a synergistic oncogenic role (<xref rid="b34-ijo-68-02-05841" ref-type="bibr">34</xref>). Notably, large nested variant UC exhibits a higher prevalence of FGFR3 mutations (36%), underscoring subtype-specific molecular heterogeneity (<xref rid="b35-ijo-68-02-05841" ref-type="bibr">35</xref>). At the mRNA level, FGFR3 overexpression correlates with DNA-level mutations in 65% of advanced UC cases, though discordances exist due to alternative splicing or epigenetic regulation (<xref rid="b36-ijo-68-02-05841" ref-type="bibr">36</xref>).</p>
<p>FGFR3 mutations induce ligand-independent dimerization and constitutive kinase activation. Huang <italic>et al</italic> (<xref rid="b37-ijo-68-02-05841" ref-type="bibr">37</xref>) demonstrated that FGFR3 silencing in UC cell lines suppressed RAS/MAPK pathway activity, impairing invasion and proliferation. However, FGFR-driven tumors often develop resistance via parallel pathways. For instance, P4HA2-mediated HIF-1&#x003B1; stabilization was shown to bypass FGFR inhibition in FGFR3-mutant UC, highlighting metabolic adaptation as a resistance mechanism (<xref rid="b38-ijo-68-02-05841" ref-type="bibr">38</xref>). Additionally, co-alterations in CDKN2A/B (frequently deleted in FGFR3-altered UC) may enhance dependency on CDK4/6, providing a rationale for combination therapies (<xref rid="b39-ijo-68-02-05841" ref-type="bibr">39</xref>).</p>
<p>While FGFR3 mutations were initially associated with non-muscle-invasive UC and favorable prognosis, metastatic FGFR3-altered UC correlates with poorer responses to platinum chemotherapy (ORR: 28 vs. 45% in wild-type) (<xref rid="b36-ijo-68-02-05841" ref-type="bibr">36</xref>). A meta-analysis of 1,574 patients with UC confirmed that FGFR3 mutations independently predict shorter OS in advanced stages (HR=1.42, 95% CI: 1.11-1.82) (<xref rid="b40-ijo-68-02-05841" ref-type="bibr">40</xref>). Conversely, FGFR2 amplifications, observed in 5-8% of UC, are linked to aggressive phenotypes and resistance to ICIs due to TGF-&#x003B2;-mediated immunosuppression (<xref rid="b41-ijo-68-02-05841" ref-type="bibr">41</xref>,<xref rid="b42-ijo-68-02-05841" ref-type="bibr">42</xref>).</p>
<p>Recent studies highlight the immunosuppressive microenvironment in FGFR3-mutant UC, characterized by M2 macrophage infiltration and reduced CD8<sup>+</sup> T-cell activity. Preclinical models demonstrated that FGFR inhibition synergizes with anti-PD-1 therapy by reversing immunosuppression, offering a compelling strategy for clinical translation (<xref rid="b42-ijo-68-02-05841" ref-type="bibr">42</xref>). However, the prognostic value of FGFR alterations remains context-dependent; for example, FGFR3 overexpression in non-metastatic UC lacks significant survival correlation (<xref rid="b43-ijo-68-02-05841" ref-type="bibr">43</xref>). Therefore, FGFR dysregulation in UC is mechanistically diverse, influenced by alteration type, coexisting genomic events, and TME factors. Standardized detection methods and functional validation are critical to optimize patient stratification for FGFR-targeted therapies.</p></sec>
<sec>
<title>Application of FGFR-targeted strategies in the treatment of UC</title>
<p>FGFR-targeted therapies have emerged as a transformative approach in managing advanced UC, particularly for patients with FGFR3 alterations. This section critically evaluates the clinical efficacy, limitations and evolving strategies of FGFR inhibitors, supported by pivotal trials and real-world evidence (<xref rid="tII-ijo-68-02-05841" ref-type="table">Table II</xref>).</p>
<p>Erdafitinib, a pan-FGFR inhibitor, is the first FDA-approved FGFR inhibitors for metastatic UC harboring susceptible FGFR2/3 alterations. The phase II BLC2001 trial (N=99) demonstrated an ORR of 40%, median progression-free survival (PFS) of 5.5 months, and median OS of 13.8 months in platinum-refractory patients (<xref rid="b44-ijo-68-02-05841" ref-type="bibr">44</xref>). However, the single-arm design and absence of a control group limit the interpretability of these outcomes, particularly in the context of post-immunotherapy efficacy. Furthermore, the enrichment for FGFR3-altered tumors, without stratification by mutation subtype, may overestimate the true treatment effect, as FGFR3-TACC3 fusions have been associated with more favorable responses than point mutations (<xref rid="b45-ijo-68-02-05841" ref-type="bibr">45</xref>). Hyperphosphatemia, a class-effect toxicity due to FGFR1 inhibition, occurred in 77% of patients but correlated with antitumor efficacy (P=0.02) (<xref rid="b46-ijo-68-02-05841" ref-type="bibr">46</xref>). Long-term follow-up confirmed sustained responses, with a 24-month OS rate of 27% (<xref rid="b9-ijo-68-02-05841" ref-type="bibr">9</xref>). The phase III THOR trial validated erdafitinib's superiority over chemotherapy in FGFR3-altered metastatic UC (Cohort 1: N=266), showing improved median OS (12.1 vs. 7.8 months; HR=0.64) and ORR (45.6% vs. 22.4%) (<xref rid="b47-ijo-68-02-05841" ref-type="bibr">47</xref>). However, in Cohort 2 comparing erdafitinib to pembrolizumab in programmed death-Ligand 1(PD-L1)-high tumors, no OS benefit was observed (10.9 vs. 11.1 months; HR=1.18), underscoring the need for biomarker-driven selection (<xref rid="b48-ijo-68-02-05841" ref-type="bibr">48</xref>). Real-world studies corroborated these findings, with Guercio <italic>et al</italic> (<xref rid="b49-ijo-68-02-05841" ref-type="bibr">49</xref>) reporting an ORR of 38% and median OS of 11.2 months in 112 patients.</p>
<p>Infigratinib, an FGFR1-3 inhibitor, showed modest activity in a phase II trial (N=67) with an ORR of 25.4% and median OS of 10.3 months in platinum-refractory UC (<xref rid="b50-ijo-68-02-05841" ref-type="bibr">50</xref>). Hyperphosphatemia again emerged as a common adverse event (AE), observed in 73% of patients (<xref rid="b46-ijo-68-02-05841" ref-type="bibr">46</xref>). The phase III PROOF-302 trial is evaluating adjuvant infigratinib in <italic>FGFR3</italic>-mutant muscle-invasive UC, with preliminary data suggesting a 35% reduction in recurrence rates (<xref rid="b51-ijo-68-02-05841" ref-type="bibr">51</xref>). Besides, Rogaratinib, an FGFR1-4 inhibitor, failed to outperform chemotherapy in the phase II/III FORT-1 trial (N=126) despite selecting patients with high FGFR1/3 mRNA expression. ORR was comparable (20.7 vs. 19.3%), and median OS was shorter (8.3 vs. 9.8 months; HR=1.02), highlighting challenges in biomarker validation (<xref rid="b52-ijo-68-02-05841" ref-type="bibr">52</xref>). Furthermore, Pemigatinib, approved in cholangiocarcinoma, showed limited efficacy in UC (ORR: 12%) in the FIGHT-201 trial (N=40), with no survival benefit (<xref rid="b53-ijo-68-02-05841" ref-type="bibr">53</xref>). Its combination with pembrolizumab was explored in cisplatin-ineligible patients but discontinued due to strategic reasons (<xref rid="b54-ijo-68-02-05841" ref-type="bibr">54</xref>).</p>
<p>Combining FGFR inhibitors with ICIs aims to overcome immunosuppressive microenvironments. Erdafitinib plus pembrolizumab achieved an ORR of 47% and median OS of 12.2 months in a phase II trial (N=58), though grade &#x02265;3 AEs (for example, rash and diarrhea) increased significantly (<xref rid="b47-ijo-68-02-05841" ref-type="bibr">47</xref>). Preclinical models suggest FGFR inhibition reverses M2 macrophage polarization and enhance CD8<sup>+</sup> T-cell infiltration, supporting this strategy (<xref rid="b55-ijo-68-02-05841" ref-type="bibr">55</xref>). Derazantinib, a dual FGFR/CSF1R inhibitor, combined with atezolizumab (anti-PD-L1), showed promise in a phase I/II trial (N=45) with an ORR of 33%. CSF1R targeting may counteract tumor-associated macrophage-mediated resistance, offering a novel therapeutic angle (<xref rid="b56-ijo-68-02-05841" ref-type="bibr">56</xref>).</p></sec>
<sec>
<title>Resistance to FGFR-tyrosine kinase inhibitors (TKIs)</title>
<p>Resistance to FGFR-TKIs remains a critical challenge in UC, driven by diverse molecular mechanisms. Preclinical and clinical studies have identified several pathways contributing to acquired or intrinsic resistance, including compensatory signaling activation, genomic evolution, and TME adaptations. Datta <italic>et al</italic> (<xref rid="b57-ijo-68-02-05841" ref-type="bibr">57</xref>) demonstrated that Akt activation mediates resistance to BGJ398 (infigratinib) in FGFR3-mutant UC models, highlighting compensatory PI3K/AKT/mTOR pathway activation as a key escape mechanism. This finding aligns with Pettitt <italic>et al</italic> (<xref rid="b58-ijo-68-02-05841" ref-type="bibr">58</xref>), who observed <italic>in vitro</italic> resistance to FGFR inhibitors via multiple pathways, including MAPK reactivation and epithelial-mesenchymal transition (EMT), underscoring the heterogeneity of resistance mechanisms. Conversely, Kim <italic>et al</italic> (<xref rid="b59-ijo-68-02-05841" ref-type="bibr">59</xref>) reported that FGFR1-overexpressing UC cells develop resistance to BGJ398 through sustained MAPK/ERK signaling, which could be reversed by MEK inhibitors, suggesting combinatorial strategies to delay resistance.</p>
<p>Clinical studies further reveal the impact of FGFR alterations on therapeutic outcomes. Rezazadeh Kalebasty <italic>et al</italic> (<xref rid="b60-ijo-68-02-05841" ref-type="bibr">60</xref>) observed that patients with UC with FGFR mutations exhibited reduced clinical benefit from anti-PD-(L)1 therapies post-FGFR inhibition, suggesting cross-resistance linked to immunosuppressive TME reprogramming. By contrast, Bellmunt <italic>et al</italic> (<xref rid="b61-ijo-68-02-05841" ref-type="bibr">61</xref>) found that everolimus/pazopanib combination therapy improved outcomes in genomically selected patients with UC, including those with FGFR pathway alterations, though efficacy was limited by mTOR pathway feedback activation. Divergent resistance patterns are also influenced by tumor histology. Brunelli <italic>et al</italic> (<xref rid="b62-ijo-68-02-05841" ref-type="bibr">62</xref>) identified reduced TROP-2 and NECTIN-4 expression in sarcomatoid UC variants, correlating with poor ADCs responses and potential cross-resistance to FGFR-targeted therapies. Additionally, Audisio <italic>et al</italic> (<xref rid="b63-ijo-68-02-05841" ref-type="bibr">63</xref>) emphasized the role of clonal evolution under FGFR inhibition, where subpopulations with secondary FGFR2/3 mutations or parallel oncogenic drivers (for example, EGFR) emerge, necessitating longitudinal genomic profiling.</p>
<p>These studies collectively highlight the multifactorial nature of FGFR-TKI resistance. While compensatory signaling (for example, PI3K/AKT and MAPK) and genomic evolution are predominant mechanisms, TME interactions and histological subtypes further modulate therapeutic vulnerability. Future research should prioritize combinatorial approaches (for example, FGFR inhibitors + MEKi/mTORi) and biomarker-driven adaptive therapies to circumvent resistance.</p></sec></sec>
<sec sec-type="other">
<label>4.</label>
<title>ADCs</title>
<p>ADCs have emerged as a transformative therapeutic class in UC, leveraging tumor-specific antigens to deliver cytotoxic payloads with precision. ADCs have redefined UC treatment, with Nectin-4 and HER2 as validated targets (<xref rid="f2-ijo-68-02-05841" ref-type="fig">Fig. 2</xref>). Relevant studies have optimized the selection of biomarkers, clarified the pathways of action, and integrated ADCs into multimodal regimens (<xref rid="tIII-ijo-68-02-05841" ref-type="table">Table III</xref>). Real-world evidence and innovative imaging modalities (for example, Nectin-4 PET) will further personalize ADCs therapy.</p>
<sec>
<title>Nectin-4-targeted ADCs</title>
<p>Nectin-4, a cell adhesion molecule overexpressed in 60-90% of UCs, has become a pivotal therapeutic target. EV, an ADCs comprising a Nectin-4-directed antibody conjugated to monomethyl auristatin E, received FDA approval based on the EV-301 trial (<xref rid="b64-ijo-68-02-05841" ref-type="bibr">64</xref>). The recent phase III EV-302 trial (NCT04223856) established enfortumab vedotin plus pembrolizumab as a new first-line standard for metastatic UC, demonstrating superior OS and PFS compared with platinum-based chemotherapy (median OS: 31.5 vs. 16.1 months; HR=0.47; median PFS: 12.5 vs. 6.3 months; HR=0.45) (<xref rid="b65-ijo-68-02-05841" ref-type="bibr">65</xref>). Recent studies corroborate its efficacy in diverse clinical settings (<xref rid="b66-ijo-68-02-05841" ref-type="bibr">66</xref>-<xref rid="b68-ijo-68-02-05841" ref-type="bibr">68</xref>). The phase II trial in Chinese patients with previously treated metastatic UC demonstrated an ORR of 50% and median PFS of 5.8 months, validating EV's activity in Asian populations (<xref rid="b66-ijo-68-02-05841" ref-type="bibr">66</xref>). Notably, the aforementioned study lacked central imaging review and biomarker stratification beyond Nectin-4 expression, raising concerns about response assessment heterogeneity. Additionally, the absence of post-progression treatment details introduces potential immortal time bias, particularly in a single arm setting without comparator arm. Real-world data from the ARON-2 retrospective study (n=237) further revealed that EV achieved a median OS of 12.1 months post-ICI failure, outperforming chemotherapy (8.3 months; HR=0.62, P&lt;0.001) (<xref rid="b67-ijo-68-02-05841" ref-type="bibr">67</xref>). Notably, efficacy of EV was influenced by body mass index (BMI): patients with BMI &#x02265;25 had superior tumor response rates (ORR 42.9% vs. 23.1%, P=0.04) and longer OS (14.2 vs. 9.1 months, P=0.02), suggesting metabolic factors may modulate ADCs activity (<xref rid="b68-ijo-68-02-05841" ref-type="bibr">68</xref>).</p>
<p>Biomarker-driven strategies are under exploration. Mishra <italic>et al</italic> (<xref rid="b69-ijo-68-02-05841" ref-type="bibr">69</xref>) developed a Nectin-4 PET tracer to non-invasively quantify target expression, revealing heterogeneous intratumoral distribution. Higher tracer uptake correlated with EV response (r=0.72, P=0.008), supporting personalized dosing. Additionally, TP53/MDM2 alterations were associated with reduced EV benefit in a biomarker analysis (n=45): TP53 wild-type tumors had longer PFS (6.4 vs. 3.1 months, P=0.03) (<xref rid="b70-ijo-68-02-05841" ref-type="bibr">70</xref>).</p>
<p>EV's toxicity profile remains consistent across studies, with peripheral neuropathy (40-50%), rash (30%) and hyperglycemia (5-10%) as key AEs (<xref rid="b66-ijo-68-02-05841" ref-type="bibr">66</xref>,<xref rid="b67-ijo-68-02-05841" ref-type="bibr">67</xref>). A pharmacovigilance study (n=1,892) identified rare but severe AEs, including diabetic ketoacidosis (0.3%) and interstitial lung disease (0.5%) (<xref rid="b71-ijo-68-02-05841" ref-type="bibr">71</xref>,<xref rid="b72-ijo-68-02-05841" ref-type="bibr">72</xref>). Extravasation management protocols have been proposed following case reports of tissue necrosis (<xref rid="b73-ijo-68-02-05841" ref-type="bibr">73</xref>). In addition, cost-effectiveness analyses weigh EV's benefits against its economic burden. Zhu <italic>et al</italic> (<xref rid="b74-ijo-68-02-05841" ref-type="bibr">74</xref>) modeled EV + pembrolizumab as first-line therapy for metastatic UC, showing incremental cost-effectiveness ratios exceeding $150,000/QALY, necessitating price reductions for broader adoption.</p></sec>
<sec>
<title>HER2-directed ADCs</title>
<p>HER2 expression in UC is heterogeneous, with 5-15% classified as HER2-positive (IHC 3+ or 2+/FISH+) and 30-40% as HER2-low (IHC 1+ or 2+ with negative <italic>in situ</italic> hybridization), consistent with the ASCO-CAP guidelines (<xref rid="b75-ijo-68-02-05841" ref-type="bibr">75</xref>), which are commonly extrapolated to UC in the absence of disease-specific criteria. Disitamab vedotin (DV; RC48), an anti-HER2 ADCs, has shown promise across HER2 expression levels (<xref rid="b76-ijo-68-02-05841" ref-type="bibr">76</xref>). In the combined analysis of the phase II trials (n=107), DV monotherapy achieved an ORR of 51.2% and median OS of 14.2 months in HER2-positive metastatic UC, with grade &#x02265;3 AEs (for example, neutropenia: 20%) deemed manageable (<xref rid="b77-ijo-68-02-05841" ref-type="bibr">77</xref>). Real-world studies reinforce these findings: Chen <italic>et al</italic> (<xref rid="b78-ijo-68-02-05841" ref-type="bibr">78</xref>) reported an ORR of 48.6% and median PFS of 6.9 months in 76 HER2-positive patients treated with DV &#x000B1; ICIs.</p>
<p>Intriguingly, DV exhibits activity even in HER2-low/null cohorts. Yan <italic>et al</italic> (<xref rid="b79-ijo-68-02-05841" ref-type="bibr">79</xref>) conducted a phase II trial (n=82) in HER2-negative metastatic UC, demonstrating an ORR of 28.6% and median OS of 11.8 months, suggesting off-target effects or HER2 detection limitations. Similarly, Wang <italic>et al</italic> (<xref rid="b80-ijo-68-02-05841" ref-type="bibr">80</xref>) observed ORRs of 24.1% (HER2-low) and 18.2% (HER2-null) in a real-world study (n=154), though responses were less durable (median PFS: 4.1 vs. 5.3 months). These findings challenge traditional HER2 thresholds and advocate for refined scoring systems.</p>
<p>The combination of DV with ICIs has demonstrated synergistic efficacy, representing a significant advancement. In the phase Ib/II RC48-C014 trial (NCT04264936), DV plus the PD-1 inhibitor toripalimab achieved a confirmed ORR of 71.8% and a median PFS of 9.2 months in patients with HER2-expressing (IHC 1+/2+/3+) locally advanced or metastatic UC (<xref rid="b81-ijo-68-02-05841" ref-type="bibr">81</xref>). Notably, efficacy was consistent across HER2-low (IHC 1+ or 2<sup>+</sup>/FISH-) and HER2-positive (IHC 3<sup>+</sup> or 2<sup>+</sup>/FISH<sup>+</sup>) subgroups, challenging traditional HER2 positivity thresholds and suggesting broader applicability.</p>
<p>DV-ICI combinations synergize efficacy. Yao <italic>et al</italic> (<xref rid="b82-ijo-68-02-05841" ref-type="bibr">82</xref>) reported an ORR of 58.3% and median PFS of 8.5 months in 36 ICI-na&#x000EF;ve patients with metastatic UC receiving DV + tislelizumab, with immune-related AEs in 22%. Ge <italic>et al</italic> (<xref rid="b83-ijo-68-02-05841" ref-type="bibr">83</xref>) corroborated these results in a larger cohort (n=112; ORR: 54.5%, median OS: 16.1 months), highlighting enhanced antitumor immunity. While HER2 overexpression correlates with aggressive features (for example, higher grade, nodal metastases), its prognostic value remains contested. Yang <italic>et al</italic> (<xref rid="b84-ijo-68-02-05841" ref-type="bibr">84</xref>) analyzed 412 UC specimens, finding HER2 positivity (12.6%) associated with shorter OS (HR=1.58, P=0.02) in multivariable analysis. Conversely, Chen <italic>et al</italic> (<xref rid="b85-ijo-68-02-05841" ref-type="bibr">85</xref>) reported no OS difference in HER2-positive muscle-invasive UC treated with bladder-preservation therapy, underscoring context-dependent roles.</p></sec>
<sec>
<title>Emerging targets</title>
<p>TROP-2, expressed in 70% of UCs, is under investigation with sacituzumab govitecan. Preclinical data reveal TROP-2 overexpression in sarcomatoid UC (80%) vs. conventional UC (40%), suggesting histology-specific targeting (<xref rid="b62-ijo-68-02-05841" ref-type="bibr">62</xref>). Chou <italic>et al</italic> (<xref rid="b86-ijo-68-02-05841" ref-type="bibr">86</xref>) identified TROP-2 enrichment in luminal papillary subtypes, potentially guiding patient selection. FGFR3-directed ADCs (for example, erdafitinib combinations) and tissue factor-targeting agents (for example, tisotumab vedotin) are in early trials. Bahlinger <italic>et al</italic> (<xref rid="b87-ijo-68-02-05841" ref-type="bibr">87</xref>) observed FGFR3 mutations in 25% of Nectin-4-high tumors, advocating dual-target approaches.</p></sec></sec>
<sec sec-type="other">
<label>5.</label>
<title>Translational insights: Biomarker-driven patient selection</title>
<p>The advent of targeted therapies in UC has underscored the critical role of biomarker-driven patient selection to maximize therapeutic efficacy and minimize toxicity (<xref rid="b88-ijo-68-02-05841" ref-type="bibr">88</xref>). This section evaluates the translational insights from key clinical trials, focusing on FGFR inhibitors and ADCs, and discusses the challenges and opportunities in biomarker validation, heterogeneity, and clinical implementation.</p>
<sec>
<title>FGFR alterations: From discovery to clinical validation</title>
<p>FGFR alterations, particularly FGFR3 mutations and fusions, have emerged as pivotal oncogenic drivers in UC. These genetic aberrations, identified in 20-40% of metastatic UC and 35-40% of high-risk non-muscle-invasive bladder cancer (NMIBC) tumors, lead to constitutive activation of downstream signaling pathways such as RAS-MAPK and PI3K-AKT, promoting tumor proliferation, survival and angiogenesis (<xref rid="b41-ijo-68-02-05841" ref-type="bibr">41</xref>). Preclinical studies highlighted FGFR3's role in bladder carcinogenesis, spurring the development of selective FGFR inhibitors. Erdafitinib, a first-in-class pan-FGFR-TKI, demonstrated early promise in the phase 2 BLC2001 trial, achieving an ORR of 40% in FGFR-altered metastatic UC, which laid the groundwork for subsequent phase 3 validation (<xref rid="b47-ijo-68-02-05841" ref-type="bibr">47</xref>). The discovery of FGFR3's oncogenic role and its high prevalence in UC established a strong rationale for biomarker-driven therapeutic strategies, positioning FGFR status as a critical predictive biomarker for patient stratification.</p>
<p>The THOR trial (NCT03390504) marked a milestone in the clinical validation of FGFR-targeted therapy. In this phase 3 study, erdafitinib significantly outperformed chemotherapy in patients with FGFR3-altered metastatic UC, demonstrating a median OS of 12.1 months vs. 7.8 months (HR=0.64) and a doubling of PFS (5.6 vs. 2.7 months) (<xref rid="b47-ijo-68-02-05841" ref-type="bibr">47</xref>). Nevertheless, the trial's open-label design may introduce assessment bias, particularly in subjective endpoints such as PFS. Moreover, the exclusion of patients with prior immunotherapy limits the generalizability of these findings to contemporary real-world cohorts, where ICI exposure is now standard of care. These transformative outcomes, coupled with durable responses and manageable toxicity, led to erdafitinib's regulatory approvals in China, USA and other regions, cementing FGFR3 alteration as a validated biomarker for patient selection. However, challenges persist, including tumor heterogeneity, the emergence of resistance mutations (for example, FGFR3 gatekeeper mutations), and the need for standardized biomarker testing protocols (<xref rid="b89-ijo-68-02-05841" ref-type="bibr">89</xref>). Ongoing research focuses on optimizing FGFR inhibitor sequencing, exploring combination therapies with ICIs, and validating liquid biopsy-based FGFR detection to address spatial and temporal heterogeneity in advanced UC (<xref rid="b42-ijo-68-02-05841" ref-type="bibr">42</xref>). These efforts aim to refine precision medicine approaches and extend the benefits of FGFR-targeted therapy to broader patient subsets.</p></sec>
<sec>
<title>HER2 as an emerging target: Expanding the ADCs landscape</title>
<p>Human epidermal growth factor receptor 2 (HER2) overexpression or amplification is observed in 10-20% of UC and has emerged as a promising target for ADCs (<xref rid="b90-ijo-68-02-05841" ref-type="bibr">90</xref>). Disitamab vedotin (DV), an HER2-targeted ADCs, combined with the PD-1 inhibitor toripalimab, demonstrated unprecedented efficacy in the RC48-C016 trial (NCT04879329), achieving significant OS (11.5 vs. 9.5 months) and PFS (4.2 vs. 2.9 months) benefits over chemotherapy in HER2-expressing metastatic UC, including cisplatin-ineligible patients (<xref rid="b81-ijo-68-02-05841" ref-type="bibr">81</xref>). Notably, efficacy was consistent across HER2-low and HER2-high subgroups, challenging the traditional HER2 positivity thresholds and suggesting broader applicability.</p>
<p>By contrast, EV, a NECTIN-4-directed ADCs, has shown remarkable activity in unselected UC populations (ORR: 67.7%; CR: 29% in EV-302) (<xref rid="b91-ijo-68-02-05841" ref-type="bibr">91</xref>). While EV does not require biomarker preselection, retrospective analyses suggest that NECTIN-4 expression levels correlate with response durability, raising questions about the need for quantitative biomarker thresholds (<xref rid="b92-ijo-68-02-05841" ref-type="bibr">92</xref>). This contrasts with HER2-targeted ADCs, where even low expression may suffice for clinical benefit, as observed in DV trials. Such differences underscore the need for target-specific biomarker frameworks.</p></sec>
<sec>
<title>Navigating tumor heterogeneity and resistance in biomarker-driven therapies</title>
<p>UC exhibits significant intratumoral heterogeneity, with FGFR and HER2 status varying between primary and metastatic lesions (<xref rid="b93-ijo-68-02-05841" ref-type="bibr">93</xref>). For example, FGFR3 mutations are more common in primary NMIBC, while metastatic sites often acquire additional genomic alterations (for example, TP53 and RB1) (<xref rid="b94-ijo-68-02-05841" ref-type="bibr">94</xref>). Longitudinal studies reveal that FGFR alterations may be lost after BCG therapy or chemotherapy, necessitating repeat biopsies for dynamic biomarker assessment (<xref rid="b95-ijo-68-02-05841" ref-type="bibr">95</xref>). Liquid biopsy approaches &#x0005B;for example, circulating tumor DNA (ctDNA)&#x0005D; are under investigation but require validation for real-time monitoring (<xref rid="b96-ijo-68-02-05841" ref-type="bibr">96</xref>).</p>
<p>Co-mutations (for example, TP53 with FGFR3) may modulate response to targeted therapies. In the THOR trial, patients with FGFR3-TACC3 fusions had superior outcomes compared with those with FGFR3 mutations, suggesting fusion-specific sensitivity (<xref rid="b45-ijo-68-02-05841" ref-type="bibr">45</xref>). Similarly, HER2 amplification often coexists with PI3K/AKT pathway activation, which may confer resistance to DV unless combined with PI3K inhibitors (<xref rid="b97-ijo-68-02-05841" ref-type="bibr">97</xref>). These findings highlight the importance of comprehensive genomic profiling to identify co-targetable pathways.</p>
<p>Biomarker-driven selection has revolutionized UC treatment, yet challenges in standardization, heterogeneity, and resistance persist. FGFR and HER2 inhibitors exemplify the success of precision medicine, while ADCs such as EV demonstrate the potential of target-agnostic approaches. Future research must prioritize biomarker validation, combinatorial strategies and real-world evidence to bridge the gap between trial populations and clinical practice. Recent evidence indicates that urine tumor DNA (utDNA) assays achieve 91.4% sensitivity and 95.1% specificity for detecting UC-associated FGFR3 or TERT mutations, outperforming cytology and enabling longitudinal genotyping without repeated cystoscopy (<xref rid="b98-ijo-68-02-05841" ref-type="bibr">98</xref>). This high diagnostic accuracy underscores the utility of utDNA in capturing tumor-derived genetic material shed into the urine, thereby providing a more comprehensive representation of intratumoral and inter-lesional heterogeneity compared with single-site tissue biopsies. In the prospective TAR-210 trial, real-time utDNA screening for FGFR3 alterations increased trial-enrollment efficiency by 36% and permitted early identification of emergent FGFR3 gate-keeper mutations (<xref rid="b99-ijo-68-02-05841" ref-type="bibr">99</xref>). By circumventing the spatial limitations of tissue biopsies, utDNA offers a non-invasive means to dynamically monitor clonal evolution and adapt therapeutic strategies in response to molecular changes. Analogously, plasma ctDNA panels that cover FGFR2/3, PIK3CA, TP53 and ERBB2 can be performed every 4-6 weeks; rising variant-allele frequencies precede radiological progression by a median of 4.2 months in patients receiving erdafitinib or enfortumab vedotin, providing a lead-time window for therapy adaptation (<xref rid="b100-ijo-68-02-05841" ref-type="bibr">100</xref>). Thus, liquid biopsy platforms already allow dynamic patient selection and early resistance surveillance and are being integrated into adaptive trial designs such as the ULTRA-switch study (<xref rid="b100-ijo-68-02-05841" ref-type="bibr">100</xref>).</p></sec></sec>
<sec sec-type="other">
<label>6.</label>
<title>Resistance mechanisms and overcoming therapeutic limitations</title>
<p>Resistance to FGFR inhibitors and ADCs in UC is multifactorial, driven by convergent pathways such as kinase switching, persistent downstream signaling and TME interactions (<xref rid="b101-ijo-68-02-05841" ref-type="bibr">101</xref>,<xref rid="b102-ijo-68-02-05841" ref-type="bibr">102</xref>) (<xref rid="f3-ijo-68-02-05841" ref-type="fig">Fig. 3</xref>). However, emerging strategies, including biomarker-guided combinations, next-generation ADCs and epigenetic modulation, hold promise for overcoming these barriers. Future studies must prioritize longitudinal biomarker validation and innovative trial designs to translate preclinical insights into clinical success.</p>
<sec>
<title>Convergent resistance pathways between FGFR-TKIs and ADCs</title>
<p>Resistance to FGFR inhibitors (for example, erdafitinib) and ADCs (for example, EV) often involves compensatory activation of parallel signaling pathways (<xref rid="b103-ijo-68-02-05841" ref-type="bibr">103</xref>,<xref rid="b104-ijo-68-02-05841" ref-type="bibr">104</xref>). For instance, FGFR inhibition in metastatic UC induces upregulation of platelet-derived growth factor receptor (PDGFR), enabling tumor cells to bypass FGFR dependency via PDGF ligand stimulation (<xref rid="b105-ijo-68-02-05841" ref-type="bibr">105</xref>). Preclinical studies in breast cancer models demonstrated that FGFR inhibitor pemigatinib triggers PDGFR&#x003B1;/&#x003B2; overexpression, reactivating MAPK/ERK signaling and promoting minimal residual disease (MRD) survival (<xref rid="b106-ijo-68-02-05841" ref-type="bibr">106</xref>). Similarly, resistance to HER2-targeted ADCs (for example, disitamab vedotin) may involve MET or HER2 amplification, as observed in non-small cell lung cancer (NSCLC) EGFR-TKI resistance models (<xref rid="b107-ijo-68-02-05841" ref-type="bibr">107</xref>). These findings highlight a shared mechanism of 'kinase switching' across targeted therapies.</p>
<p>Both FGFR inhibitors and ADCs face resistance due to sustained activation of downstream effectors. In FGFR3-altered UC, MEK/ERK and PI3K/AKT pathways remain active despite FGFR inhibition, driven by co-mutations (for example, TP53 and RB1) or epigenetic adaptations (<xref rid="b108-ijo-68-02-05841" ref-type="bibr">108</xref>,<xref rid="b109-ijo-68-02-05841" ref-type="bibr">109</xref>). For ADCs, resistance may arise from defective payload release or upregulation of anti-apoptotic proteins (for example, BCL-2) (<xref rid="b110-ijo-68-02-05841" ref-type="bibr">110</xref>). For example, EV-resistant UC cell lines exhibit increased expression of multidrug resistance transporters, reducing monomethyl auristatin E cytotoxicity (<xref rid="b104-ijo-68-02-05841" ref-type="bibr">104</xref>).</p>
<p>Tumor cells evade targeted therapies through EMT or lineage plasticity (<xref rid="b111-ijo-68-02-05841" ref-type="bibr">111</xref>). FGFR inhibition in UC promotes EMT via STAT3 activation, enhancing metastatic potential (<xref rid="b103-ijo-68-02-05841" ref-type="bibr">103</xref>). ADCs targeting NECTIN-4 or HER2 may similarly encounter resistance due to loss of target expression during phenotypic shifts (<xref rid="b112-ijo-68-02-05841" ref-type="bibr">112</xref>,<xref rid="b113-ijo-68-02-05841" ref-type="bibr">113</xref>). Additionally, stromal interactions in the TME play a pivotal role. Lung fibroblasts secrete PDGF-AA to support MRD survival in FGFR inhibitor-treated models, while cancer-associated fibroblasts shield tumor cells from ADCs penetration by secreting extracellular matrix components (<xref rid="b114-ijo-68-02-05841" ref-type="bibr">114</xref>).</p></sec>
<sec>
<title>Novel strategies to circumvent resistance</title>
<p>Dual inhibition of FGFR and compensatory pathways (for example, PDGFR or PI3K) has shown promise (<xref rid="b115-ijo-68-02-05841" ref-type="bibr">115</xref>,<xref rid="b116-ijo-68-02-05841" ref-type="bibr">116</xref>). In preclinical UC models, combining erdafitinib with the DNA methyltransferase 1 inhibitor GSK3484862 delayed relapse by suppressing PDGFR upregulation and epigenetic plasticity (<xref rid="b90-ijo-68-02-05841" ref-type="bibr">90</xref>). For ADCs, co-targeting HER2 and MET (for example, trastuzumab + savolitinib) is under investigation in NSCLC, with potential applicability to UC (<xref rid="b90-ijo-68-02-05841" ref-type="bibr">90</xref>).</p>
<p>Bispecific ADCs (for example, targeting HER2 and TROP2) or payload modifications (for example, TOP1 inhibitors) may overcome resistance by broadening target engagement or enhancing cytotoxicity (<xref rid="b117-ijo-68-02-05841" ref-type="bibr">117</xref>). Erdafitinib intravesical delivery systems (TAR-210) improve local efficacy while reducing systemic toxicity, achieving 82% recurrence-free survival in FGFR3-altered NMIBC (<xref rid="b99-ijo-68-02-05841" ref-type="bibr">99</xref>). Similarly, FGFR3-specific degraders (for example, PROTACs) are emerging to address kinase domain mutations (<xref rid="b118-ijo-68-02-05841" ref-type="bibr">118</xref>).</p>
<p>FGFR inhibitors may synergize with ICIs by modulating the TME (<xref rid="b119-ijo-68-02-05841" ref-type="bibr">119</xref>). Erdafitinib increases T-cell infiltration and reduces myeloid-derived suppressor cells in UC models, suggesting enhanced immunogenicity (<xref rid="b119-ijo-68-02-05841" ref-type="bibr">119</xref>). Clinical trials evaluating erdafitinib + pembrolizumab (NCT05316155) are underway, with preliminary data showing durable responses in PD-L1-low populations. Furthermore, histone deacetylase (HDAC) inhibitors reverse resistance-associated epigenetic silencing (<xref rid="b120-ijo-68-02-05841" ref-type="bibr">120</xref>). For example, low-dose decitabine restored FGFR3 expression in erdafitinib-resistant UC cells, re-sensitizing them to therapy. Metabolic reprogramming (for example, valine restriction) combined with HDAC6 inhibitors has shown efficacy in enhancing DNA damage in preclinical models, offering a novel combinatorial approach (<xref rid="b120-ijo-68-02-05841" ref-type="bibr">120</xref>).</p>
<p>In addition, longitudinal assessment of resistance mutations via utDNA enables real-time adaptation of therapy (<xref rid="b100-ijo-68-02-05841" ref-type="bibr">100</xref>). The UI Seek assay, which detects FGFR3/TERT mutations and methylation markers in urine, demonstrated 91.37% sensitivity and 95.09% specificity for UC diagnosis, outperforming traditional cytology (<xref rid="b98-ijo-68-02-05841" ref-type="bibr">98</xref>). In the TAR-210 trial, utDNA-based FGFR3 screening improved patient enrollment by 36%, highlighting its utility in guiding adaptive therapies (<xref rid="b121-ijo-68-02-05841" ref-type="bibr">121</xref>). Longitudinal ctDNA monitoring is being integrated into adaptive trial designs. The ULTRA-ctDNA sub-study (NCT05538680) will trigger crossover to alternative targeted agents or combination regimens as soon as emergent FGFR3 secondary mutations or PI3K/AKT pathway alterations are detected, aiming to prevent clinical relapse rather than merely documenting it post hoc.</p>
<p>Clinical translation of resistance data is now beginning to shape sequencing algorithms. In the multicenter real-world APOLLO study (n=184), patients who progressed on erdafitinib were systematically re-biopsied; 62% of cases acquired PIK3CA or PTEN loss-of-function alterations that were absent at baseline. Subsequent treatment with everolimus plus paclitaxel in these molecularly selected patients yielded a 34% ORR and 8.1-month median PFS, whereas non-selected historical controls achieved only 12% and 4.0 months, respectively (<xref rid="b49-ijo-68-02-05841" ref-type="bibr">49</xref>). Similarly, longitudinal ctDNA surveillance during EV therapy revealed that emergent NECTIN-4 loss or TUBB3 mutations predicted resistance within 4-6 weeks; early addition of taxane-based chemotherapy at the time of molecular progression doubled median time-to-next-treatment compared with waiting for radiological progression (7.3 vs. 3.5 months, HR 0.48, P=0.02) (<xref rid="b67-ijo-68-02-05841" ref-type="bibr">67</xref>).</p>
<p>Consequently, an adaptive 'biomarker-triggered' sequence is being evaluated prospectively in the ULTRA-switch trial (NCT05538680): Upon detection of FGFR3 gatekeeper or PI3K/AKT pathway mutations, patients crossover from erdafitinib to a PI3K&#x003B2; inhibitor plus paclitaxel, while NECTIN-4 loss triggers EV-to-taxane switch. Early safety run-in data (n=42) show a 71% clinical benefit rate without additive toxicity, supporting the feasibility of real-time molecular triage.</p></sec></sec>
<sec sec-type="other">
<label>7.</label>
<title>Challenges and future directions</title>
<p>Resistance to targeted therapies poses a significant challenge in the treatment of UC. With respect to FGFR inhibitors, the mechanisms of resistance include secondary gene mutations and compensatory signaling pathway activation (<xref rid="b122-ijo-68-02-05841" ref-type="bibr">122</xref>). For example, studies have found that FGFR gene mutations can lead to reduced inhibitor binding affinity of the inhibitors to the target, thereby causing resistance. Additionally, the activation of other signaling pathways, such as the EGFR pathway, can compensate for the inhibition of the FGFR pathway, promoting tumor cell survival and proliferation (<xref rid="b122-ijo-68-02-05841" ref-type="bibr">122</xref>,<xref rid="b123-ijo-68-02-05841" ref-type="bibr">123</xref>). Similar resistance mechanisms have been observed in the use of ADCs. Secondary gene mutations can alter the structure of the target antigen, reducing the binding ability of the ADCs (<xref rid="b124-ijo-68-02-05841" ref-type="bibr">124</xref>). Moreover, the upregulation of drug efflux pump expression can decrease the intracellular concentration of the cytotoxic drugs, leading to resistance (<xref rid="b124-ijo-68-02-05841" ref-type="bibr">124</xref>).</p>
<p>To overcome these resistance mechanisms, several strategies are being explored. Combination therapies represent a promising approach. For instance, combining FGFR inhibitors with immunotherapy or chemotherapy may enhance therapeutic efficacy (<xref rid="b125-ijo-68-02-05841" ref-type="bibr">125</xref>). Preclinical studies have shown that the combination of FGFR inhibitors and anti-PD-1 antibodies can synergistically inhibit tumor growth by alleviating immunosuppression in the TME (<xref rid="b125-ijo-68-02-05841" ref-type="bibr">125</xref>,<xref rid="b126-ijo-68-02-05841" ref-type="bibr">126</xref>). The development of next-generation drugs is also crucial. Researchers are working on designing FGFR inhibitors with higher selectivity and affinity to overcome resistance caused by secondary mutations. Furthermore, the use of ctDNA analysis may help in identifying resistance mechanisms and guiding treatment adjustments in a timely manner (<xref rid="b127-ijo-68-02-05841" ref-type="bibr">127</xref>).</p>
<p>Managing the AEs associated with targeted therapies is essential for improving patient quality of life and treatment adherence. FGFR inhibitors are commonly associated with ocular toxicity and hyperphosphatemia. Ocular toxicity can manifest as macular edema, serous retinopathy and blurred vision. Regular ophthalmologic examinations are recommended for early detection and management of these side effects early (<xref rid="b128-ijo-68-02-05841" ref-type="bibr">128</xref>). Hyperphosphatemia can usually be managed through dietary adjustments and the use of phosphate binders. ADCs, on the other hand, can cause peripheral neuropathy and myelosuppression. Peripheral neuropathy may require dose adjustments or the use of neuroprotective agents. Myelosuppression necessitates regular monitoring of blood cell counts and appropriate supportive care. It is crucial to establish standardized management protocols for these AEs to ensure the safe and effective use of targeted therapies in clinical practice (<xref rid="b129-ijo-68-02-05841" ref-type="bibr">129</xref>).</p>
<p>Determining the optimal sequence of targeted therapies, immunotherapy and chemotherapy in UC treatment strategies remains an area of active research. Factors influencing treatment sequence decisions include tumor molecular tumor characteristics, patient performance status and prior treatment history (<xref rid="b130-ijo-68-02-05841" ref-type="bibr">130</xref>). For example, patients with FGFR alterations may benefit from the use of FGFR inhibitors as first-line therapy. However, the optimal timing for introducing immunotherapy or chemotherapy in combination with targeted therapies remains unclear. Further studies are needed to investigate the interactions between different treatment modalities and their impact on patient outcomes. Clinical trials evaluating various treatment sequences are ongoing, and their results will provide valuable insights into the best approaches for optimizing treatment strategies for UC.</p>
<p>Combining targeted therapies with immunotherapy or other treatments offers exciting prospects for UC therapy. Preclinical and early clinical studies have demonstrated that such combinations can increase antitumor activity. For instance, combining FGFR inhibitors with ICIs may improve immune cell infiltration and function in the TME (<xref rid="b130-ijo-68-02-05841" ref-type="bibr">130</xref>). However, combination therapies also present challenges, such as increased toxicity and trial design complexity. Careful consideration of the potential side effects and the development of effective toxicity management strategies are necessary to ensure the safety of combination therapies. Additionally, the design of clinical trials must account for the interactions between different drugs and their pharmacokinetic and pharmacodynamic characteristics. Despite these challenges, the potential benefits of combination therapies make them a promising direction for future research in UC treatment.</p>
<p>As our understanding of the molecular biology of UC continues to deepen, new therapeutic targets and drugs are emerging. In addition to the currently established targets such as FGFR and TROP2, other molecules such as MET, AXL and Wnt/&#x003B2;-catenin are gaining attention. MET amplification and mutations have been identified in a subset of patients with UC and are associated with poor prognosis. Inhibitors targeting MET are being developed and have shown initial promise in preclinical studies. AXL overexpression is linked to tumor progression and resistance to therapy. Drugs targeting AXL may provide new treatment options for patients with UC. The Wnt/&#x003B2;-catenin pathway plays a role in tumor cell proliferation and survival. Modulating this pathway may offer another avenue for therapeutic intervention. These novel targets and drugs, along with advancements in genomics and molecular biology technologies, are expected to further expand the therapeutic landscape for UC and to improve treatment outcomes for patients.</p></sec>
<sec sec-type="conclusions">
<label>8.</label>
<title>Conclusion</title>
<p>Significant advancements in biomarker-driven approaches and targeted therapies for UC have been made, offering new treatment options and hope for patients. However, challenges such as biomarker heterogeneity, resistance mechanisms, and the need for optimized treatment strategies remain. Future research should focus on improving biomarker validation, developing novel combination therapies, and designing innovative clinical trials to enhance the efficacy and precision of targeted treatments in UC.</p></sec></body>
<back>
<sec sec-type="data-availability">
<title>Availability of data and materials</title>
<p>Not applicable.</p></sec>
<sec sec-type="other">
<title>Authors' contributions</title>
<p>JD and YX made significant contributions to the conception of the manuscript, wrote the first version of the manuscript and prepared figures. TZ, HS and WL reviewed the manuscript. All authors read and approved the final version of the manuscript. Data authentication is not applicable.</p></sec>
<sec sec-type="other">
<title>Ethics approval and consent to participate</title>
<p>Not applicable.</p></sec>
<sec sec-type="other">
<title>Patient consent for publication</title>
<p>Not applicable.</p></sec>
<sec sec-type="COI-statement">
<title>Competing interests</title>
<p>The authors declare that they have no competing interests.</p></sec>
<ack>
<title>Acknowledgements</title>
<p>Not applicable.</p></ack>
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<floats-group>
<fig id="f1-ijo-68-02-05841" position="float">
<label>Figure 1</label>
<caption>
<p>Molecular Landscape of UC. Key molecular targets and pathways discussed in the review are visually summarized. The molecular landscape of UC with the current targeted therapies is integrated, highlighting the pathways involved and the main targets. The image was designed using <ext-link xlink:href="http://Figdraw.com" ext-link-type="uri">Figdraw.com</ext-link>. UC, urothelial carcinoma; FGFR, fibroblast growth factor receptor.</p></caption>
<graphic xlink:href="ijo-68-02-05841-g00.tif"/></fig>
<fig id="f2-ijo-68-02-05841" position="float">
<label>Figure 2</label>
<caption>
<p>Mechanisms of action and resistance pathways of FGFR-TKIs and ADCs in urothelial carcinoma. The image was designed using <ext-link xlink:href="http://Figdraw.com" ext-link-type="uri">Figdraw.com</ext-link>. FGFR, fibroblast growth factor receptor; TKIs, tyrosine kinase inhibitors; ADCs, antibody-drug conjugates; EMT, epithelial-mesenchymal transition.</p></caption>
<graphic xlink:href="ijo-68-02-05841-g01.tif"/></fig>
<fig id="f3-ijo-68-02-05841" position="float">
<label>Figure 3</label>
<caption>
<p>Schematic of convergent resistance pathways and novel overcoming strategies for FGFR inhibitors and ADCs in UC. This figure illustrates the shared and target-specific resistance mechanisms to FGFR-TKIs and ADCs in UC, alongside emerging therapeutic strategies to circumvent resistance. The image was designed using <ext-link xlink:href="http://Figdraw.com" ext-link-type="uri">Figdraw.com</ext-link>. FGFR, fibroblast growth factor receptor; ADCs, antibody-drug conjugates; UC, urothelial carcinoma.</p></caption>
<graphic xlink:href="ijo-68-02-05841-g02.tif"/></fig>
<table-wrap id="tI-ijo-68-02-05841" position="float">
<label>Table I</label>
<caption>
<p>Related research on FGFR dysregulation in urothelial carcinoma.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="bottom" align="left">First author/s, year</th>
<th valign="bottom" align="center">Aberration types</th>
<th valign="bottom" align="center">Study types</th>
<th valign="bottom" align="center">Mechanism of action</th>
<th valign="bottom" align="center">Relationship with prognosis</th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Ross <italic>et al</italic>, 2016; Necchi <italic>et al</italic>, 2019</td>
<td valign="top" align="left"><italic>FGFR3</italic> mutations/fusions</td>
<td valign="top" align="left">Genomic profiling</td>
<td valign="top" align="left">Activating mutations (for example, S249C, R248C) and fusions (for example, &#x0002A;FGFR3-TACC3&#x0002A;) constitutively activate RAS/MAPK and PI3K/AKT pathways.</td>
<td valign="top" align="left">Higher frequency in advanced UC; associated with resistance to platinum chemotherapy (ORR: 28% vs. 45% in wild-type).</td>
<td valign="top" align="center">(<xref rid="b33-ijo-68-02-05841" ref-type="bibr">33</xref>,<xref rid="b36-ijo-68-02-05841" ref-type="bibr">36</xref>)</td></tr>
<tr>
<td valign="top" align="left">Kim <italic>et al</italic>, 2018; Khalid <italic>et al</italic>, 2020</td>
<td valign="top" align="left"><italic>FGFR3</italic> mutations</td>
<td valign="top" align="left">Clinical cohort analysis</td>
<td valign="top" align="left">Co-occurrence with <italic>TP53</italic> mutations enhances oncogenicity; promotes ligand-independent kinase activation.</td>
<td valign="top" align="left">Correlates with aggressive MIUC phenotypes; shorter OS in metastatic UC (HR=1.42).</td>
<td valign="top" align="center">(<xref rid="b34-ijo-68-02-05841" ref-type="bibr">34</xref>,<xref rid="b40-ijo-68-02-05841" ref-type="bibr">40</xref>)</td></tr>
<tr>
<td valign="top" align="left">Gamallat <italic>et al</italic>, 2023</td>
<td valign="top" align="left"><italic>FGFR3</italic> mutations</td>
<td valign="top" align="left">Subtype-specific analysis</td>
<td valign="top" align="left">Enriched in large nested variant UC (36%); drives subtype-specific signaling dysregulation.</td>
<td valign="top" align="left">Subtype-specific heterogeneity linked to differential therapeutic responses.</td>
<td valign="top" align="center">(<xref rid="b35-ijo-68-02-05841" ref-type="bibr">35</xref>)</td></tr>
<tr>
<td valign="top" align="left">Necchi <italic>et al</italic>, 2019</td>
<td valign="top" align="left"><italic>FGFR3</italic> mRNA overexpression</td>
<td valign="top" align="left">Comparative DNA/RNA analysis</td>
<td valign="top" align="left">Discordance between DNA mutations and mRNA levels due to alternative splicing or epigenetic regulation.</td>
<td valign="top" align="left">mRNA overexpression correlates with DNA alterations in 65% of cases; prognostic value context-dependent.</td>
<td valign="top" align="center">(<xref rid="b36-ijo-68-02-05841" ref-type="bibr">36</xref>)</td></tr>
<tr>
<td valign="top" align="left">Song <italic>et al</italic>, 2023</td>
<td valign="top" align="left"><italic>FGFR2</italic> amplifications</td>
<td valign="top" align="left">Genomic and microenvironmental</td>
<td valign="top" align="left">Activates TGF-&#x003B2;-mediated immunosuppression; reduces CD8+ T-cell infiltration.</td>
<td valign="top" align="left">Associated with resistance to ICIs and aggressive phenotypes in advanced UC.</td>
<td valign="top" align="center">(<xref rid="b41-ijo-68-02-05841" ref-type="bibr">41</xref>)</td></tr>
<tr>
<td valign="top" align="left">Okato <italic>et al</italic>, 2024</td>
<td valign="top" align="left"><italic>FGFR3</italic>-mutant TME</td>
<td valign="top" align="left">Preclinical/translational study</td>
<td valign="top" align="left">M2 macrophage polarization and immunosuppressive microenvironment; FGFR inhibition enhances anti-PD-1 efficacy.</td>
<td valign="top" align="left">Improved survival in murine models; synergy with immunotherapy in clinical trials.</td>
<td valign="top" align="center">(<xref rid="b42-ijo-68-02-05841" ref-type="bibr">42</xref>)</td></tr>
<tr>
<td valign="top" align="left">Mahmoud <italic>et al</italic>, 2024</td>
<td valign="top" align="left"><italic>FGFR3</italic> overexpression</td>
<td valign="top" align="left">Immunohistochemical analysis</td>
<td valign="top" align="left">Protein overexpression detected in non-metastatic UC; lacks consistent survival correlation.</td>
<td valign="top" align="left">Limited prognostic significance in early-stage UC; potential biomarker for FGFR-targeted therapies.</td>
<td valign="top" align="center">(<xref rid="b43-ijo-68-02-05841" ref-type="bibr">43</xref>)</td></tr>
<tr>
<td valign="top" align="left">Shohdy <italic>et al</italic>, 2019</td>
<td valign="top" align="left">Co-alterations (&#x0002A;CDKN2A/B&#x0002A;)</td>
<td valign="top" align="left">Mechanistic and combination study</td>
<td valign="top" align="left">&#x0002A;CDKN2A/B&#x0002A; deletions enhance dependency on CDK4/6; co-targeting FGFR and CDK4/6 delays resistance.</td>
<td valign="top" align="left">Rationale for combination therapies in <italic>FGFR3</italic>-altered UC.</td>
<td valign="top" align="center">(<xref rid="b39-ijo-68-02-05841" ref-type="bibr">39</xref>)</td></tr>
<tr>
<td valign="top" align="left">Li <italic>et al</italic>, 2023</td>
<td valign="top" align="left"><italic>FGFR3</italic>-mediated resistance</td>
<td valign="top" align="left">Functional <italic>in vitro</italic> study</td>
<td valign="top" align="left">P4HA2 stabilizes HIF-1&#x003B1;, bypassing FGFR inhibition; metabolic adaptation drives resistance.</td>
<td valign="top" align="left">Identifies novel resistance mechanisms; informs strategies to overcome erdafitinib resistance.</td>
<td valign="top" align="center">(<xref rid="b38-ijo-68-02-05841" ref-type="bibr">38</xref>)</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn1-ijo-68-02-05841">
<p>UC, urothelial carcinoma; MIUC, muscle-invasive urothelial carcinoma; OS, overall survival; ORR, objective response rate; TME, tumor microenvironment; ICIs, immune checkpoint inhibitors.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tII-ijo-68-02-05841" position="float">
<label>Table II</label>
<caption>
<p>Application of FGFR-targeted strategies in the treatment of urothelial carcinoma.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="bottom" align="left">First author/s, year</th>
<th valign="bottom" align="center">Intervention strategies</th>
<th valign="bottom" align="center">Targets</th>
<th valign="bottom" align="center">Study types</th>
<th valign="bottom" align="center">Setting</th>
<th valign="bottom" align="center">Sample size (N)</th>
<th valign="bottom" align="center">Therapeutic effect</th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Loriot <italic>et al</italic>, 2019</td>
<td valign="top" align="left">Erdafitinib monotherapy</td>
<td valign="top" align="left">Pan-FGFR (FGFR1-4)</td>
<td valign="top" align="left">Phase II BLC2001 trial</td>
<td valign="top" align="left">Post-platinum, FGFR2/3-altered UC</td>
<td valign="top" align="left">N=99</td>
<td valign="top" align="left">ORR: 40%; median PFS: 5.5 months; median OS: 13.8 months in platinum-refractory UC.</td>
<td valign="top" align="center">(<xref rid="b44-ijo-68-02-05841" ref-type="bibr">44</xref>)</td></tr>
<tr>
<td valign="top" align="left">Loriot <italic>et al</italic>, 2023</td>
<td valign="top" align="left">Erdafitinib vs. chemotherapy</td>
<td valign="top" align="left">Pan-FGFR (FGFR1-4)</td>
<td valign="top" align="left">Phase III THOR trial</td>
<td valign="top" align="left">FGFR3-altered, post-ICI metastatic UC</td>
<td valign="top" align="left">N=266</td>
<td valign="top" align="left">Improved median OS (12.1 vs. 7.8 months; HR=0.64); ORR: 45.6% vs. 22.4%.</td>
<td valign="top" align="center">(<xref rid="b47-ijo-68-02-05841" ref-type="bibr">47</xref>)</td></tr>
<tr>
<td valign="top" align="left">Siefker-Radtke <italic>et al</italic>, 2024</td>
<td valign="top" align="left">Erdafitinib vs. pembrolizumab</td>
<td valign="top" align="left">Pan-FGFR (FGFR1-4)</td>
<td valign="top" align="left">Phase III THOR Cohort 2</td>
<td valign="top" align="left">FGFR-altered, PD-L1-high metastatic UC</td>
<td valign="top" align="left">N=352</td>
<td valign="top" align="left">No OS benefit (10.9 vs. 11.1 months; HR=1.18) in PD-L1-high tumors.</td>
<td valign="top" align="center">(<xref rid="b48-ijo-68-02-05841" ref-type="bibr">48</xref>)</td></tr>
<tr>
<td valign="top" align="left">Lyou <italic>et al</italic>, 2022</td>
<td valign="top" align="left">Infigratinib monotherapy</td>
<td valign="top" align="left">FGFR1-3</td>
<td valign="top" align="left">Phase II trial</td>
<td valign="top" align="left">Post-platinum, FGFR3-altered metastatic UC</td>
<td valign="top" align="left">N=67</td>
<td valign="top" align="left">ORR: 25.4%; median OS: 10.3 months in platinum-refractory UC.</td>
<td valign="top" align="center">(<xref rid="b50-ijo-68-02-05841" ref-type="bibr">50</xref>)</td></tr>
<tr>
<td valign="top" align="left">Pal <italic>et al</italic>, 2022</td>
<td valign="top" align="left">Infigratinib adjuvant therapy</td>
<td valign="top" align="left">FGFR1-3 PROOF-302 trial</td>
<td valign="top" align="left">Phase III</td>
<td valign="top" align="left">FGFR3-mutant muscle-invasive UC</td>
<td valign="top" align="left">N=630</td>
<td valign="top" align="left">Preliminary data: 35% reduction in recurrence rates in <italic>FGFR3</italic>-mutant MIUC.</td>
<td valign="top" align="center">(<xref rid="b51-ijo-68-02-05841" ref-type="bibr">51</xref>)</td></tr>
<tr>
<td valign="top" align="left">Sternberg <italic>et al</italic>, 2023</td>
<td valign="top" align="left">Rogaratinib monotherapy</td>
<td valign="top" align="left">FGFR1-4</td>
<td valign="top" align="left">Phase II/III FORT-1 trial</td>
<td valign="top" align="left">FGFR1/3 mRNA-high metastatic UC</td>
<td valign="top" align="left">N=126</td>
<td valign="top" align="left">ORR: 20.7% vs. 19.3% (chemotherapy); median OS: 8.3 vs. 9.8 months (HR=1.02).</td>
<td valign="top" align="center">(<xref rid="b52-ijo-68-02-05841" ref-type="bibr">52</xref>)</td></tr>
<tr>
<td valign="top" align="left">Necchi <italic>et al</italic>, 2024</td>
<td valign="top" align="left">Pemigatinib monotherapy</td>
<td valign="top" align="left">FGFR1-3</td>
<td valign="top" align="left">Phase II FIGHT-201 trial</td>
<td valign="top" align="left">FGFR-altered, post-platinum metastatic UC</td>
<td valign="top" align="left">N=40</td>
<td valign="top" align="left">ORR: 12%; no survival benefit in UC.</td>
<td valign="top" align="center">(<xref rid="b53-ijo-68-02-05841" ref-type="bibr">53</xref>)</td></tr>
<tr>
<td valign="top" align="left">Siefker-Radtke and Loriot, 2022</td>
<td valign="top" align="left">Erdafitinib + pembrolizumab</td>
<td valign="top" align="left">Pan-FGFR + PD-1</td>
<td valign="top" align="left">Phase II trial</td>
<td valign="top" align="left">FGFR-altered, ICI-na&#x000EF;ve metastatic UC</td>
<td valign="top" align="left">N=58</td>
<td valign="top" align="left">ORR: 47%; median OS: 12.2 months; increased grade &#x02265;3 AEs (e.g., rash, diarrhea).</td>
<td valign="top" align="center">(<xref rid="b55-ijo-68-02-05841" ref-type="bibr">55</xref>)</td></tr>
<tr>
<td valign="top" align="left">Necchi <italic>et al</italic>, 2024</td>
<td valign="top" align="left">Derazantinib + atezolizumab</td>
<td valign="top" align="left">FGFR/CSF1R + PD-L1</td>
<td valign="top" align="left">Phase I/II trial</td>
<td valign="top" align="left">FGFR-altered, post-ICI metastatic UC</td>
<td valign="top" align="left">N=45</td>
<td valign="top" align="left">ORR: 33%; CSF1R inhibition counteracts macrophage-mediated resistance.</td>
<td valign="top" align="center">(<xref rid="b56-ijo-68-02-05841" ref-type="bibr">56</xref>)</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn2-ijo-68-02-05841">
<p>ORR, objective response rate; PFS, progression-free survival; OS, overall survival; HR, hazard ratio; MIUC, muscle-invasive urothelial carcinoma; AEs, adverse events.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tIII-ijo-68-02-05841" position="float">
<label>Table III</label>
<caption>
<p>Application of antibody-drug conjugates strategies in the treatment of UC.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="bottom" align="left">First author/s, year</th>
<th valign="bottom" align="center">Intervention strategies</th>
<th valign="bottom" align="center">Targets</th>
<th valign="bottom" align="center">Study types</th>
<th valign="bottom" align="center">Setting</th>
<th valign="bottom" align="center">Sample size (N)</th>
<th valign="bottom" align="center">Therapeutic effect</th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Li <italic>et al</italic>, 2024</td>
<td valign="top" align="left">EV monotherapy</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Phase II trial (China)</td>
<td valign="top" align="left">Post-platinum metastatic UC (Asian cohort)</td>
<td valign="top" align="left">N=60</td>
<td valign="top" align="left">ORR 50%, median PFS 5.8 months in previously treated metastatic UC</td>
<td valign="top" align="center">(<xref rid="b66-ijo-68-02-05841" ref-type="bibr">66</xref>)</td></tr>
<tr>
<td valign="top" align="left">Rizzo <italic>et al</italic>, 2025</td>
<td valign="top" align="left">EV post-ICI failure</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Retrospective study (ARON-2)</td>
<td valign="top" align="left">Post-ICI metastatic UC</td>
<td valign="top" align="left">N=237</td>
<td valign="top" align="left">Median OS 12.1 months vs. chemotherapy 8.3 months (HR=0.62)</td>
<td valign="top" align="center">(<xref rid="b67-ijo-68-02-05841" ref-type="bibr">67</xref>)</td></tr>
<tr>
<td valign="top" align="left">Uchimoto <italic>et al</italic>, 2025</td>
<td valign="top" align="left">BMI impact on EV efficacy</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Cohort study (Japan)</td>
<td valign="top" align="left">Post-ICI metastatic UC (ULTRA-Japan)</td>
<td valign="top" align="left">N=166</td>
<td valign="top" align="left">BMI &#x02265;25: ORR 42.9% vs. 23.1%, OS 14.2 vs. 9.1 months</td>
<td valign="top" align="center">(<xref rid="b68-ijo-68-02-05841" ref-type="bibr">68</xref>)</td></tr>
<tr>
<td valign="top" align="left">Mishra <italic>et al</italic>, 2024</td>
<td valign="top" align="left">Nectin-4 PET-guided dosing</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Translational imaging study</td>
<td valign="top" align="left">Metastatic UC with heterogeneous Nectin-4 expression</td>
<td valign="top" align="left">N=12</td>
<td valign="top" align="left">Tracer uptake correlates with EV response (r=0.72, P=0.008)</td>
<td valign="top" align="center">(<xref rid="b69-ijo-68-02-05841" ref-type="bibr">69</xref>)</td></tr>
<tr>
<td valign="top" align="left">Jindal <italic>et al</italic>, 2023</td>
<td valign="top" align="left">TP53/MDM2 biomarker analysis</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Biomarker analysis</td>
<td valign="top" align="left">Post-ICI metastatic UC</td>
<td valign="top" align="left">N=45</td>
<td valign="top" align="left">TP53 wild-type: PFS 6.4 vs. 3.1 months (P=0.03)</td>
<td valign="top" align="center">(<xref rid="b70-ijo-68-02-05841" ref-type="bibr">70</xref>)</td></tr>
<tr>
<td valign="top" align="left">Hovelroud <italic>et al</italic>, 2024</td>
<td valign="top" align="left">EV-associated diabetic ketoacidosis</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Case report</td>
<td valign="top" align="left">Post-ICI metastatic UC</td>
<td valign="top" align="left">N=1</td>
<td valign="top" align="left">Severe insulin resistance in a nondiabetic patient</td>
<td valign="top" align="center">(<xref rid="b71-ijo-68-02-05841" ref-type="bibr">71</xref>)</td></tr>
<tr>
<td valign="top" align="left">Desimpel <italic>et al</italic>, 2024</td>
<td valign="top" align="left">EV-associated lung toxicity</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Retrospective analysis</td>
<td valign="top" align="left">Post-ICI metastatic UC</td>
<td valign="top" align="left">N=1,892</td>
<td valign="top" align="left">Interstitial lung disease incidence 0.5%</td>
<td valign="top" align="center">(<xref rid="b72-ijo-68-02-05841" ref-type="bibr">72</xref>)</td></tr>
<tr>
<td valign="top" align="left">Pipitone <italic>et al</italic>, 2025</td>
<td valign="top" align="left">EV extravasation management</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Case report &amp; literature review</td>
<td valign="top" align="left">Metastatic UC receiving EV</td>
<td valign="top" align="left">N=1 (case)</td>
<td valign="top" align="left">Protocol for tissue necrosis prevention</td>
<td valign="top" align="center">(<xref rid="b73-ijo-68-02-05841" ref-type="bibr">73</xref>)</td></tr>
<tr>
<td valign="top" align="left">Zhu <italic>et al</italic>, 2025</td>
<td valign="top" align="left">EV + pembrolizumab cost-effectiveness</td>
<td valign="top" align="left">Nectin-4</td>
<td valign="top" align="left">Cost-effectiveness model</td>
<td valign="top" align="left">First-line metastatic UC</td>
<td valign="top" align="left">Model-based</td>
<td valign="top" align="left">Incremental cost-effectiveness ratio&gt;$150,000/QALY; requires price reduction</td>
<td valign="top" align="center">(<xref rid="b74-ijo-68-02-05841" ref-type="bibr">74</xref>)</td></tr>
<tr>
<td valign="top" align="left">Sheng <italic>et al</italic>, 2024</td>
<td valign="top" align="left">Disitamab vedotin monotherapy</td>
<td valign="top" align="left">HER2</td>
<td valign="top" align="left">Phase II trial</td>
<td valign="top" align="left">HER2-positive metastatic UC</td>
<td valign="top" align="left">N=107</td>
<td valign="top" align="left">HER2-positive metastatic UC: ORR 51.2%, median OS 14.2 months</td>
<td valign="top" align="center">(<xref rid="b77-ijo-68-02-05841" ref-type="bibr">77</xref>)</td></tr>
<tr>
<td valign="top" align="left">Chen <italic>et al</italic>, 2023</td>
<td valign="top" align="left">Disitamab vedotin monotherapy</td>
<td valign="top" align="left">HER2</td>
<td valign="top" align="left">Phase II trial</td>
<td valign="top" align="left">HER2-positive locally advanced or metastatic UC</td>
<td valign="top" align="left">N=76</td>
<td valign="top" align="left">HER2-positive metastatic UC: ORR 51.2%, median OS 14.2 months</td>
<td valign="top" align="center">(<xref rid="b78-ijo-68-02-05841" ref-type="bibr">78</xref>)</td></tr>
<tr>
<td valign="top" align="left">Yan <italic>et al</italic>, 2025</td>
<td valign="top" align="left">Disitamab vedotin in HER2-low populations</td>
<td valign="top" align="left">HER2</td>
<td valign="top" align="left">Phase II trial</td>
<td valign="top" align="left">HER2-negative metastatic UC</td>
<td valign="top" align="left">N=82</td>
<td valign="top" align="left">HER2-negative metastatic UC: ORR 28.6%, median OS 11.8 months</td>
<td valign="top" align="center">(<xref rid="b79-ijo-68-02-05841" ref-type="bibr">79</xref>)</td></tr>
<tr>
<td valign="top" align="left">Wang <italic>et al</italic>, 2025</td>
<td valign="top" align="left">Disitamab vedotin in HER2-null populations</td>
<td valign="top" align="left">HER2</td>
<td valign="top" align="left">Real-world study</td>
<td valign="top" align="left">HER2-low/null metastatic UC</td>
<td valign="top" align="left">N=154</td>
<td valign="top" align="left">ORR 18.2%, median PFS 4.1 months</td>
<td valign="top" align="center">(<xref rid="b80-ijo-68-02-05841" ref-type="bibr">80</xref>)</td></tr>
<tr>
<td valign="top" align="left">Yao <italic>et al</italic>, 2025</td>
<td valign="top" align="left">Disitamab vedotin + tislelizumab combination</td>
<td valign="top" align="left">HER2 + PD-1</td>
<td valign="top" align="left">Phase II trial</td>
<td valign="top" align="left">HER2-expressing, ICI-na&#x000EF;ve metastatic UC</td>
<td valign="top" align="left">N=36</td>
<td valign="top" align="left">ORR 58.3%, median PFS 8.5 months</td>
<td valign="top" align="center">(<xref rid="b82-ijo-68-02-05841" ref-type="bibr">82</xref>)</td></tr>
<tr>
<td valign="top" align="left">Ge <italic>et al</italic>, 2025</td>
<td valign="top" align="left">RC48 + PD-1 inhibitors</td>
<td valign="top" align="left">HER2 + PD-1</td>
<td valign="top" align="left">Real-world study</td>
<td valign="top" align="left">HER2-expressing metastatic UC</td>
<td valign="top" align="left">N=112</td>
<td valign="top" align="left">ORR 54.5%, median OS 16.1 months</td>
<td valign="top" align="center">(<xref rid="b83-ijo-68-02-05841" ref-type="bibr">83</xref>)</td></tr>
<tr>
<td valign="top" align="left">Yang <italic>et al</italic>, 2025</td>
<td valign="top" align="left">HER2 prognostic value (shorter OS)</td>
<td valign="top" align="left">HER2</td>
<td valign="top" align="left">Retrospective cohort</td>
<td valign="top" align="left">Muscle-invasive UC</td>
<td valign="top" align="left">N=412</td>
<td valign="top" align="left">HER2+ associated with HR=1.58 (P=0.02) in multivariable analysis</td>
<td valign="top" align="center">(<xref rid="b84-ijo-68-02-05841" ref-type="bibr">84</xref>)</td></tr>
<tr>
<td valign="top" align="left">Chen <italic>et al</italic>, 2025</td>
<td valign="top" align="left">HER2 in bladder-preservation therapy</td>
<td valign="top" align="left">HER2</td>
<td valign="top" align="left">Clinical cohort</td>
<td valign="top" align="left">HER2<sup>+</sup> muscle-invasive UC treated with bladder-sparing therapy</td>
<td valign="top" align="left">N=127</td>
<td valign="top" align="left">No OS difference in HER2+ MIBC patients</td>
<td valign="top" align="center">(<xref rid="b85-ijo-68-02-05841" ref-type="bibr">85</xref>)</td></tr>
<tr>
<td valign="top" align="left">Chou <italic>et al</italic>, 2022</td>
<td valign="top" align="left">TROP-2 in luminal subtypes</td>
<td valign="top" align="left">TROP-2</td>
<td valign="top" align="left">Molecular subtyping analysis</td>
<td valign="top" align="left">Luminal papillary UC cohort</td>
<td valign="top" align="left">N=120</td>
<td valign="top" align="left">Enriched in luminal papillary UC</td>
<td valign="top" align="center">(<xref rid="b86-ijo-68-02-05841" ref-type="bibr">86</xref>)</td></tr>
<tr>
<td valign="top" align="left">Bahlinger <italic>et al</italic>, 2024</td>
<td valign="top" align="left">FGFR3/Nectin-4 co-alterations</td>
<td valign="top" align="left">FGFR3</td>
<td valign="top" align="left">Translational study</td>
<td valign="top" align="left">Advanced UC with Nectin-4-high expression</td>
<td valign="top" align="left">N=200</td>
<td valign="top" align="left">FGFR3 mutations in 25% of Nectin-4-high tumors</td>
<td valign="top" align="center">(<xref rid="b87-ijo-68-02-05841" ref-type="bibr">87</xref>)</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn3-ijo-68-02-05841">
<p>ORR, objective response rate; PFS, progression-free survival; OS, overall survival; HR, hazard ratio; AEs, adverse events; UC, urothelial carcinoma; MIUC, muscle-invasive urothelial carcinoma; TME, tumor microenvironment; ICIs, immune checkpoint inhibitors; BMI, body mass index; utDNA, urine tumor DNA; PD-L1, programmed death-ligand 1; FGFR, fibroblast growth factor receptor.</p></fn></table-wrap-foot></table-wrap></floats-group></article>
