Predicting Complete Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer
Abstract
:Simple Summary
Abstract
1. Introduction
2. Neoadjuvant Chemotherapy in Urothelial Cell Bladder Cancer
3. Pathologic Complete Response and Overall Survival
4. Potential Predictors of Complete Response to Neoadjuvant Chemotherapy
5. Clinical Staging
6. Primary Versus Secondary Muscle-Invasive Bladder Cancer
7. Impact of Neoadjuvant Chemotherapy Regimen on Complete Response
8. Assessment of Complete Response following Neoadjuvant Chemotherapy
9. Molecular Subtypes of Muscle-Invasive Bladder Cancer
10. Tumor Genomics and Gene Expression Profiles
11. Circulating Tumor DNA
12. Radiomics
13. Future Directions
Author Contributions
Funding
Conflicts of Interest
References
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Author | Biomarker Evaluated | Prediction of CR |
---|---|---|
O’Donnell, P.H. et al. [34] | Nine germline single nucleotide polymorphisms | Polymorphisms in RARS and GALNTL4 significant in discovery cohort, but not significant in validation cohort |
Font, A. et al. [35] | KRT5/6, KRT14, GATA3, and FOXA1 | Increased CR in patients with BASQ-like tumors |
Nassif, E.F. et al. [36] | Immunoscore | High Immunoscore associated with increased CR |
Jutte, H. et al. [37] | KRT20, KRT5, ESR1, ERBB2 mRNA expression | Elevated expression of KRT20, ERBB2 and ESR1 associate with CR |
Koskinen, I. et al. [38] | Clinical features, Ki-67, p53, HER-2, and EGFR | No significant association with CR noted |
Ornstein, M.C. et al. [39] | Peripheral circulating myeloid derived suppressor cells | Decreased levels of peripheral circulating myeloid derived suppressor cells associated with CR |
Bazargani, S.T. et al. [40] | Serum CA-125, CA 19-9, and CEA | Increased downstaging noted in patients with normalized serum markers after NAC |
Author | Imaging Modality | Model | Prediction of CR |
---|---|---|---|
Choi, S.J. et al. [43] | CT | Imaging based model including tumor shape, clinical stage and tumor size | Training cohort: AUC 0.85 (95% CI, 0.78–0.93) Validation cohort: AUC 0.75 (95% CI, 0.60–0.86) |
Choi, S.J. et al. [44] | CT | Bladder wall thickening and enhancement characteristics noted on urothelial phase | Reader 1: AUC 0.85 (95% CI, 0.76–0.93) Reader 2: AUC 0.85 (95% CI) |
Ahmed, S.A. et al. [45] | MRI | Dynamic and diffusion weighted MRI | Reader 1: AUC 0.981 Reader 2: AUC 0.971 |
Soubra, A. et al. [46] | FDG-PET/CT | Change in maximum SUV on FDG-PET/CT | Sensitivity for CR 75% Negative Predictive Value for CR 89% |
Cha, K.H. et al. [47] | CT | Decision support system utilizing deep-learning neural networks and radiomics | AUC improved with support system compared to clinician alone |
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Miyagi, H.; Kwenda, E.; Ramnaraign, B.H.; Chatzkel, J.A.; Brisbane, W.G.; O’Malley, P.; Crispen, P.L. Predicting Complete Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer. Cancers 2023, 15, 168. https://doi.org/10.3390/cancers15010168
Miyagi H, Kwenda E, Ramnaraign BH, Chatzkel JA, Brisbane WG, O’Malley P, Crispen PL. Predicting Complete Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer. Cancers. 2023; 15(1):168. https://doi.org/10.3390/cancers15010168
Chicago/Turabian StyleMiyagi, Hiroko, Elizabeth Kwenda, Brian H. Ramnaraign, Jonathan A. Chatzkel, Wayne G. Brisbane, Padraic O’Malley, and Paul L. Crispen. 2023. "Predicting Complete Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer" Cancers 15, no. 1: 168. https://doi.org/10.3390/cancers15010168