Comparative analysis of tertiary lymphoid structures for predicting survival of colorectal cancer: a whole-slide images-based study
Year: 2024
Type: article
Study design: Observational Study
Abstract: Background Tertiary lymphoid structures (TLS) are major components in the immune microenvironment, correlating with a favorable prognosis in colorectal cancer. However, the methods used to define and characterize TLS were not united, hindering its clinical application. This study aims to seek a more stable method to characterize TLS and clarify their prognostic value in larger multicenter cohorts. Methods A total of 1609 patients from four hospitals and The Cancer Genome Atlas database were analyzed. We quantified the number and maximum length of TLS along the invasive margin of tumor using hematoxylin and eosin-stained whole-slide images (WSIs). Additionally, the length of the invasive margin was determined to calculate the TLS density. The prognostic value of TLS for overall survival was evaluated. In addition, we examined the association between TLS density and immune cell infiltration using immunohistochemistry-stained WSIs. The performance for predicting overall survival was measured using hazard ratios (HR) with 95% confidence intervals (CI). Results Among the three TLS quantification methods, TLS density has the strongest discriminative performance. Survival analysis indicated that higher TLS density correlated with better overall survival [HR for high vs. low 0.57 (95% CI 0.42–0.78) in the primary cohort; 0.49 (0.35–0.69) in the validation cohort; 0.35 (0.18–0.67) in TCGA cohort]. A high TLS density was associated with a high level of CD3+ T cell infiltration. Conclusions Based on this comparative multicenter analysis, TLS density was identified as a simple, robust, and effective immune prognostic index for colorectal cancer.
Source: Precision Clinical Medicine
Institutions: Key Laboratory of Guangdong Province, Guangdong Academy of Medical Sciences, Guangdong Provincial People's Hospital, Southern Medical University, Shanghai Medical College of Fudan University, Fudan University, Fudan University Shanghai Cancer Center, The Affiliated Yongchuan Hospital of Chongqing Medical University, Kunming Medical University, Zhengzhou University, First Affiliated Hospital of Zhengzhou University, Sun Yat-sen University Cancer Center, Shanxi Medical University, Sixth Affiliated Hospital of Sun Yat-sen University
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,000
Awards: G1665940170, G7407931452, G7834753781
OpenAlex ID: W4403526086
