BACKGROUND : Tumour budding and poorly differentiated clusters (PDC) represent forms of tumour invasion. We hypothesised that T-cell densities (reflecting adaptive anti-tumour immunity) might be inversely associated with tumour budding and PDC in colorectal carcinoma.
METHODS : Utilising 915 colon and rectal carcinomas in two U.S.-wide prospective cohort studies, and multiplex immunofluorescence combined with machine learning algorithms, we assessed CD3, CD4, CD8, CD45RO (PTPRC), and FOXP3 co-expression patterns in lymphocytes. Tumour budding and PDC at invasive fronts were quantified by digital pathology and image analysis using the International tumour Budding Consensus Conference criteria. Using covariate data of 4,420 incident colorectal cancer cases, inverse probability weighting (IPW) was integrated with multivariable logistic regression analysis that assessed the association of T-cell subset densities with tumour budding and PDC while adjusting for selection bias due to tissue availability and potential confounders, including microsatellite instability status.
FINDINGS : Tumour budding counts were inversely associated with density of CD3+CD8+ [lowest vs. highest: multivariable odds ratio (OR), 0.50; 95% confidence interval (CI), 0.35-0.70; Ptrend < 0.001] and CD3+CD8+CD45RO+ cells (lowest vs. highest: multivariable OR, 0.44; 95% CI, 0.31-0.63; Ptrend < 0.001) in tumour epithelial region. Tumour budding levels were associated with higher colorectal cancer-specific mortality (multivariable hazard ratio, 2.13; 95% CI, 1.57-2.89; Ptrend < 0.001) in Cox regression analysis. There were no significant associations of PDC with T-cell subsets.
INTERPRETATION : Tumour epithelial naïve and memory cytotoxic T cell densities are inversely associated with tumour budding at invasive fronts, suggesting that cytotoxic anti-tumour immunity suppresses tumour microinvasion.
Fujiyoshi Kenji, Väyrynen Juha P, Borowsky Jennifer, Papke David J, Arima Kota, Haruki Koichiro, Kishikawa Junko, Akimoto Naohiko, Ugai Tomotaka, Lau Mai Chan, Gu Simeng, Shi Shanshan, Zhao Melissa, Da Silva Annacarolina Fabiana Lucia, Twombly Tyler S, Nan Hongmei, Meyerhardt Jeffrey A, Song Mingyang, Zhang Xuehong, Wu Kana, Chan Andrew T, Fuchs Charles S, Lennerz Jochen K, Giannakis Marios, Nowak Jonathan A, Ogino Shuji
adenocarcinoma, artificial intelligence, clinical outcomes, epithelial mesenchymal transition, host-tumour interaction, molecular pathological epidemiology