Antibody Drug Conjugates in Bladder Cancer: Current Milestones and Future Perspectives

Alameddine, Raafat; Mallea, Patrick M.; Shahab, Farhan; Zakharia, Yousef

doi:10.1007/s11864-023-01114-y

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Curr. Treat. Options in Oncol.

2023

DOI: 10.1007/s11864-023-01114-y

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Antibody Drug Conjugates in Bladder Cancer: Current Milestones and Future Perspectives

Raafat Alameddine

Patrick M. Mallea

Farhan Shahab

et al.

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Cited by 3 publications

References 84 publications

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A HER2‐targeted Antibody‐Drug Conjugate, RC48‐ADC, Exerted Promising Antitumor Efficacy and Safety with Intravesical Instillation in Preclinical Models of Bladder Cancer

Hong,

Chen,

Wang

et al. 2023

Advanced Science

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More than half of non‐muscle‐invasive bladder cancer (NMIBC) patients eventually relapse even if treated with surgery and BCG without optional bladder‐preserving therapy. This study aims to investigate the antitumor activity and safety of a HER2‐targeted antibody‐drug conjugate, RC48‐ADC, intravesical instillation for NMIBC treatment. In this preclinical study, it is revealed that human epidermal growth factor receptor 2 (HER2) expression scores of 1+, 2+, and 3+ are recorded for 16.7%, 56.2%, and 14.6% of NMIBC cases. The antitumor effect of RC48‐ADC is positively correlated with HER2 expression in bladder cancer (BCa) cell lines and organoid models. Furthermore, RC48‐ADC is revealed to exert its antitumor effect by inducing G2/M arrest and caspase‐dependent apoptosis. In an orthotopic BCa model, tumor growth is significantly inhibited by intravesical instillation of RC48‐ADC versus disitamab, monomethyl auristatin E, epirubicin, or phosphate‐buffered saline control. The potential toxicity of intravesical RC48‐ADC is also assessed by dose escalation in normal nude mice and revealed that administration of RC48‐ADC by intravesical instillation is safe within the range of effective therapeutic doses. Taken together, RC48‐ADC demonstrates promising antitumor effects and safety with intravesical administration in multiple preclinical models. These findings provide a rational for clinical trials of intravesical RC48‐ADC in NMIBC patients.

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A HER2‐targeted Antibody‐Drug Conjugate, RC48‐ADC, Exerted Promising Antitumor Efficacy and Safety with Intravesical Instillation in Preclinical Models of Bladder Cancer

Hong,

Chen,

Wang

et al. 2023

Advanced Science

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MRI‐Based Machine Learning Radiomics for Preoperative Assessment of Human Epidermal Growth Factor Receptor 2 Status in Urothelial Bladder Carcinoma

Yu,

Cai,

Gong

et al. 2024

Magnetic Resonance Imaging

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BackgroundThe human epidermal growth factor receptor 2 (HER2) has recently emerged as hotspot in targeted therapy for urothelial bladder cancer (UBC). The HER2 status is mainly identified by immunohistochemistry (IHC), preoperative and noninvasive methods for determining HER2 status in UBC remain in searching.PurposesTo investigate whether radiomics features extracted from MRI using machine learning algorithms can noninvasively evaluate the HER2 status in UBC.Study TypeRetrospective.PopulationOne hundred ninety‐five patients (age: 68.7 ± 10.5 years) with 14.3% females from January 2019 to May 2023 were divided into training (N = 156) and validation (N = 39) cohorts, and 43 patients (age: 67.1 ± 13.1 years) with 13.9% females from June 2023 to January 2024 constituted the test cohort (N = 43).Field Strength/Sequence3 T, T2‐weighted imaging (turbo spin‐echo), diffusion‐weighted imaging (breathing‐free spin echo).AssessmentThe HER2 status were assessed by IHC. Radiomics features were extracted from MRI images. Pearson correlation coefficient and the least absolute shrinkage and selection operator (LASSO) were applied for feature selection, and six machine learning models were established with optimal features to identify the HER2 status in UBC.Statistical TestsMann–Whitney U‐test, chi‐square test, LASSO algorithm, receiver operating characteristic analysis, and DeLong test.ResultsThree thousand forty‐five radiomics features were extracted from each lesion, and 22 features were retained for analysis. The Support Vector Machine model demonstrated the best performance, with an AUC of 0.929 (95% CI: 0.888–0.970) and accuracy of 0.859 in the training cohort, AUC of 0.886 (95% CI: 0.780–0.993) and accuracy of 0.846 in the validation cohort, and AUC of 0.712 (95% CI: 0.535–0.889) and accuracy of 0.744 in the test cohort.Data ConclusionMRI‐based radiomics features combining machine learning algorithm provide a promising approach to assess HER2 status in UBC noninvasively and preoperatively.Evidence Level2Technical EfficacyStage 3

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A review of the clinical efficacy of FDA-approved antibody‒drug conjugates in human cancers

Liu,

Li,

et al. 2024

Mol Cancer

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While strategies such as chemotherapy and immunotherapy have become the first-line standard therapies for patients with advanced or metastatic cancer, acquired resistance is still inevitable in most cases. The introduction of antibody‒drug conjugates (ADCs) provides a novel alternative. ADCs are a new class of anticancer drugs comprising the coupling of antitumor mAbs with cytotoxic drugs. Compared with chemotherapeutic drugs, ADCs have the advantages of good tolerance, accurate target recognition, and small effects on noncancerous cells. ADCs occupy an increasingly important position in the therapeutic field. Currently, there are 13 Food and Drug Administration (FDA)‒approved ADCs and more than 100 ADC drugs at different stages of clinical trials. This review briefly describes the efficacy and safety of FDA-approved ADCs, and discusses the related problems and challenges to provide a reference for clinical work.

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Antibody Drug Conjugates in Bladder Cancer: Current Milestones and Future Perspectives

Cited by 3 publications

References 84 publications

A HER2‐targeted Antibody‐Drug Conjugate, RC48‐ADC, Exerted Promising Antitumor Efficacy and Safety with Intravesical Instillation in Preclinical Models of Bladder Cancer

A HER2‐targeted Antibody‐Drug Conjugate, RC48‐ADC, Exerted Promising Antitumor Efficacy and Safety with Intravesical Instillation in Preclinical Models of Bladder Cancer

MRI‐Based Machine Learning Radiomics for Preoperative Assessment of Human Epidermal Growth Factor Receptor 2 Status in Urothelial Bladder Carcinoma

A review of the clinical efficacy of FDA-approved antibody‒drug conjugates in human cancers

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