Academic Journal
Radiomics signature for dynamic monitoring of tumor inflamed microenvironment and immunotherapy response prediction
| العنوان: | Radiomics signature for dynamic monitoring of tumor inflamed microenvironment and immunotherapy response prediction |
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| المؤلفون: | Bernatowicz, Kinga, Amat, Ramon, Prior, Olivia, Frigola, Joan, Ligero, Marta, Grussu, Francesco, Zatse, Christina, Serna, Garazi, Nuciforo, Paolo, Toledo, Rodrigo, Escobar, Manel, Garralda, Elena, Felip, Enriqueta, Perez-Lopez, Raquel |
| المساهمون: | MSCA COFUND Beatiu de Pinos, Prostate Cancer Foundation, La Caixa Foundation, CRIS Cancer Foundation, FERO Foundation, the Instituto de Salud Carlos III, LaCaixa Foundation |
| المصدر: | Journal for ImmunoTherapy of Cancer ; volume 13, issue 1, page e009140 ; ISSN 2051-1426 |
| بيانات النشر: | BMJ |
| سنة النشر: | 2025 |
| الوصف: | Background The efficacy of immune checkpoint inhibitors (ICIs) depends on the tumor immune microenvironment (TIME), with a preference for a T cell-inflamed TIME. However, challenges in tissue-based assessments via biopsies have triggered the exploration of non-invasive alternatives, such as radiomics, to comprehensively evaluate TIME across diverse cancers. To address these challenges, we develop an ICI response signature by integrating radiomics with T cell-inflamed gene-expression profiles. Methods We conducted a pan-cancer investigation into the utility of radiomics for TIME assessment, including 1360 tumors from 428 patients. Leveraging contrast-enhanced CT images, we characterized TIME through RNA gene expression analysis, using the T cell-inflamed gene expression signature. Subsequently, a pan-cancer CT-radiomic signature predicting inflamed TIME (CT-TIME) was developed and externally validated. Machine learning was employed to select robust radiomic features and predict inflamed TIME. The study also integrated independent cohorts with longitudinal CT images, baseline biopsies, and comprehensive immunohistochemistry panel evaluation to assess the pan-cancer biological associations, spatiotemporal landscape and clinical utility of the CT-TIME. Results The CT-TIME signature, comprising four radiomic features linked to a T-cell inflamed microenvironment, demonstrated robust performance with AUCs (95% CI) of 0.85 (0.73 to 0.96) (training) and 0.78 (0.65 to 0.92) (external validation). CT-TIME scores exhibited positive correlations with CD3, CD8, and CD163 expression. Intrapatient analysis revealed considerable heterogeneity in TIME between tumors, which could not be assessed using biopsies. Evaluation of aggregated per-patient CT-TIME scores highlighted its promising clinical utility for dynamically assessing the immune microenvironment and predicting immunotherapy response across diverse scenarios in advanced cancer. Despite demonstrating progression disease at the first follow-up, patients within the ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.1136/jitc-2024-009140 |
| الاتاحة: | https://doi.org/10.1136/jitc-2024-009140 https://syndication.highwire.org/content/doi/10.1136/jitc-2024-009140 |
| Rights: | http://creativecommons.org/licenses/by-nc/4.0/ |
| رقم الانضمام: | edsbas.9E532AEB |
| قاعدة البيانات: | BASE |
| DOI: | 10.1136/jitc-2024-009140 |
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