Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts
Abstract Advanced bladder cancer patients show very variable responses to immune checkpoint inhibitors (ICIs) and effective strategies to predict response are still lacking. Here we integrate mutation and gene expression data from 707 advanced bladder cancer patients treated with anti-PD-1/anti-PD-L...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-56462-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849723980047450112 |
|---|---|
| author | Lilian Marie Boll Sergio Vázquez Montes de Oca Marta E. Camarena Robert Castelo Joaquim Bellmunt Júlia Perera-Bel M. Mar Albà |
| author_facet | Lilian Marie Boll Sergio Vázquez Montes de Oca Marta E. Camarena Robert Castelo Joaquim Bellmunt Júlia Perera-Bel M. Mar Albà |
| author_sort | Lilian Marie Boll |
| collection | DOAJ |
| description | Abstract Advanced bladder cancer patients show very variable responses to immune checkpoint inhibitors (ICIs) and effective strategies to predict response are still lacking. Here we integrate mutation and gene expression data from 707 advanced bladder cancer patients treated with anti-PD-1/anti-PD-L1 to build highly accurate predictive models. We find that, in addition to tumor mutational burden (TMB), enrichment in the APOBEC mutational signature, and the abundance of pro-inflammatory macrophages, are major factors associated with the response. Paradoxically, patients with high immune infiltration do not show an overall better response. We show that this can be explained by the activation of immune suppressive mechanisms in a large portion of these patients. In the case of non-immune-infiltrated cancer subtypes, we uncover specific variables likely to be involved in the response. Our findings provide information for advancing precision medicine in patients with advanced bladder cancer treated with immunotherapy. |
| format | Article |
| id | doaj-art-de643bae1db5451f80ea886473b900ba |
| institution | DOAJ |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-de643bae1db5451f80ea886473b900ba2025-08-20T03:10:52ZengNature PortfolioNature Communications2041-17232025-02-0116111510.1038/s41467-025-56462-0Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohortsLilian Marie Boll0Sergio Vázquez Montes de Oca1Marta E. Camarena2Robert Castelo3Joaquim Bellmunt4Júlia Perera-Bel5M. Mar Albà6Hospital del Mar Research Institute (HMRIB)Hospital del Mar Research Institute (HMRIB)Hospital del Mar Research Institute (HMRIB)Department of Medicine and Life Sciences, Universitat Pompeu Fabra (UPF)Hospital del Mar Research Institute (HMRIB)Hospital del Mar Research Institute (HMRIB)Hospital del Mar Research Institute (HMRIB)Abstract Advanced bladder cancer patients show very variable responses to immune checkpoint inhibitors (ICIs) and effective strategies to predict response are still lacking. Here we integrate mutation and gene expression data from 707 advanced bladder cancer patients treated with anti-PD-1/anti-PD-L1 to build highly accurate predictive models. We find that, in addition to tumor mutational burden (TMB), enrichment in the APOBEC mutational signature, and the abundance of pro-inflammatory macrophages, are major factors associated with the response. Paradoxically, patients with high immune infiltration do not show an overall better response. We show that this can be explained by the activation of immune suppressive mechanisms in a large portion of these patients. In the case of non-immune-infiltrated cancer subtypes, we uncover specific variables likely to be involved in the response. Our findings provide information for advancing precision medicine in patients with advanced bladder cancer treated with immunotherapy.https://doi.org/10.1038/s41467-025-56462-0 |
| spellingShingle | Lilian Marie Boll Sergio Vázquez Montes de Oca Marta E. Camarena Robert Castelo Joaquim Bellmunt Júlia Perera-Bel M. Mar Albà Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts Nature Communications |
| title | Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts |
| title_full | Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts |
| title_fullStr | Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts |
| title_full_unstemmed | Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts |
| title_short | Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts |
| title_sort | predicting immunotherapy response of advanced bladder cancer through a meta analysis of six independent cohorts |
| url | https://doi.org/10.1038/s41467-025-56462-0 |
| work_keys_str_mv | AT lilianmarieboll predictingimmunotherapyresponseofadvancedbladdercancerthroughametaanalysisofsixindependentcohorts AT sergiovazquezmontesdeoca predictingimmunotherapyresponseofadvancedbladdercancerthroughametaanalysisofsixindependentcohorts AT martaecamarena predictingimmunotherapyresponseofadvancedbladdercancerthroughametaanalysisofsixindependentcohorts AT robertcastelo predictingimmunotherapyresponseofadvancedbladdercancerthroughametaanalysisofsixindependentcohorts AT joaquimbellmunt predictingimmunotherapyresponseofadvancedbladdercancerthroughametaanalysisofsixindependentcohorts AT juliapererabel predictingimmunotherapyresponseofadvancedbladdercancerthroughametaanalysisofsixindependentcohorts AT mmaralba predictingimmunotherapyresponseofadvancedbladdercancerthroughametaanalysisofsixindependentcohorts |