膀胱癌患者 TIL（肿瘤浸润淋巴细胞）无创成像与生存及 BCG 免疫治疗反应的相关性：多中心队列研究

Tumour-infiltrating lymphocytes (TILs) are strongly correlated with the prognosis and immunotherapy response in bladder cancer. The TIL status is typically assessed through microscopy as part of tissue pathology. Here, the authors developed Rad-TIL model, a novel radiomics model, to predict TIL status in patients with bladder cancer. MATERIAL AND METHODS: The authors enrolled 1089 patients with bladder cancer and developed the Rad-TIL model by using a machine-learning method based on computed tomography (CT) images. The authors applied a radiogenomics cohort to reveal the key pathways underlying the Rad-TIL model. Finally, the authors used an independent treatment cohort to evaluate the predictive efficacy of the Rad-TIL model for Bacillus Calmette-Gu rin (BCG) immunotherapy.

The authors developed the Rad-TIL model by integrating tumoral and peritumoral features on CT images and obtained areas under the receiver operating characteristic curves of 0.844 and 0.816 in the internal and external validation cohorts, respectively. Patients were stratified into two groups based on the predicted radiomics score of TILs (RSTIL). RSTIL exhibited prognostic significance for both overall and cancer-specific survival in each cohort (hazard ratios: 2.27-3.15, all P<0.05). Radiogenomics analysis revealed a significant association of RSTIL with immunoregulatory pathways and immune checkpoint molecules (all P<0.05). Notably, BCG immunotherapy response rates were significantly higher in high-RSTIL patients than in low-RSTIL patients (P=0.007).

The Rad-TIL model, a noninvasive method for assessing TIL status, can predict clinical outcomes and BCG immunotherapy response in patients with bladder cancer.