Abstract
The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clear. It is of great significance to discern mUC patients who could benefit from ICI therapy in clinical practice. In this study, we performed machine learning method and selected 10 prognostic genes for constructing the immunotherapy response nomogram for mUC patients. The calibration plot suggested that the nomogram had an optimal agreement with actual observations when predicting the 1- and 1.5-year survival probabilities. The prognostic nomogram had a favorable discrimination of overall survival of mUC patients, with area under the curve values of 0.815, 0.752, and 0.805 for ICI response (ICIR) prediction in the training cohort, testing cohort, and combined cohort, respectively. A further decision curve analysis showed that the prognostic nomogram was superior to either mutation burden or neoantigen burden for overall survival prediction when the threshold probability was >0.35. The immune infiltrate analysis indicated that the low ICIR-Score values in mUC patients were significantly related to CD8+ T cell infiltration and immune checkpoint-associated signatures. We also identified differentially mutated genes, which could act as driver genes and regulate the response to ICI therapy. In conclusion, we developed and validated an immunotherapy-responsive nomogram for mUC patients, which could be conveniently used for the estimate of ICI response and the prediction of overall survival probability for mUC patients.
Highlights
Urothelial carcinoma is one of the most aggressive malignancies, with an estimated 81,400 new cases and 17,980 deaths in the United States in 2020 [1]
By performing machine learning and nomogram methods, we aimed to create a nomogram model to predict the immune checkpoint inhibitors (ICIs) response and the overall survival (OS) of metastatic urothelial carcinoma (mUC) patients treated with ICI therapy, which could aid in decision-making in clinical practice
We designed and validated a gene signaturebased nomogram that was associated with ICI response and could predict the OS of mUC patients treated with ICI therapy
Summary
Urothelial carcinoma is one of the most aggressive malignancies, with an estimated 81,400 new cases and 17,980 deaths in the United States in 2020 [1]. Up to 10–15% of initially diagnosed patients have metastatic urothelial carcinoma (mUC), with a 5-year survival possibility of 5% worldwide [2, 3]. Cisplatin-based combination chemotherapy is identified as the standard first-line therapy for mUC patients [4]. More than 60% of mUC patients are not suitable for cisplatin treatment [5] due to their poor performance status or other comorbidities, including renal dysfunction, hearing loss, and heart failure [6]. There remain tremendous practical demands for the development of optimal treatments for these patients. Developments in immune checkpoint inhibitor (ICI) therapy targeting programmed cell death 1 (PD-1) and PD-1 ligand (PD-L1) have revolutionized the management of mUC [3, 7]
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