A study evaluating a prognostic signature derived from integrating tumor budding, lymphocyte infiltration, and their spatial relationship has found that the method could more accurately stratify patients with stage II colorectal cancer at high risk for disease-specific death compared with traditional methods of clinical staging. The study results can serve as a base for future studies on the prognostic significance of the interplay between different cell types within a patient’s heterogeneous and heterotypic tumor microenvironment. The study by Nearchou et al was published in Cancer Immunology Research.
Surgical resection without the use of adjuvant treatment improves long-term disease-free survival in most stage II colorectal cancer cases. However, studies show that 20% of patients experience disease-specific death.
The researchers analyzed data from a training cohort of 114 patients with stage II colorectal cancer who underwent surgical resection in hospitals in Edinburgh between 2002 and 2003. The researchers validated their method in two independent cohorts (56 patients from Edinburgh in cohort 1 and 62 patients from the National Defense Medical College Hospital in Japan in cohort 2, respectively).
Multiplexed immunofluorescence and automated image analysis were used for the quantification of CD3-positive and CD8-positive T cells and tumor buds across whole-slide images of the three independent cohorts. Machine learning algorithms were used for feature selection and prognostic risk model development.
High numbers of tumor buds (hazard ratio [HR] = 5.899, 95% confidence interval [CI] = 1.875–18.55), low CD3-positive T-cell density (HR = 9.964, 95% CI = 3.156–31.46), and low mean number of CD3-positive, CD8-positive T cells within 50 µm of tumor buds (HR = 8.907, 95% CI = 2.834–28.0) were associated with reduced disease-specific survival. A prognostic signature—derived from integrating tumor buds, lymphocyte infiltration, and their spatial relationship—identified a more significant cohort stratification (HR = 18.75, 95% CI = 6.46–54.43) than tumor buds, Immunoscore, or pT stage. This was confirmed in two independent validation cohorts (HR = 12.27, 95% CI = 3.524–42.73; HR = 15.61, 95% CI = 4.692–51.91.
“The investigation of the spatial relationship between lymphocytes and tumor buds within the tumor microenvironment improves accuracy of prognosis of patients with stage II colorectal cancer through an automated image analysis and machine learning workflow,” concluded the researchers.
“Tumor node metastasis staging was not prognostically significant in our second validation cohort, reflecting the heterogeneous nature of stage II colorectal cancer and highlighting the need for more precise prognostic scoring systems to be translated into the clinic,” said Ines P. Nearchou, a PhD student at the University of St. Andrews School of Medicine in North Haugh, Scotland, and lead author of this study. “We found that our combinatorial method was superior to the current prognostic staging systems in defining stage II colorectal cancer patient prognosis. After further validation in larger studies, this index could be translated into routine clinical classification of stage II colorectal cancer as well as other solid tumor types, thus providing a more precise prognosis with the ultimate goal of improving patient care.”
Dr. Nearchou is the corresponding author of this study.
Disclosure: Funding for this study was provided by Medical Research Scotland and Indica Labs, Inc. The study authors' full disclosures can be found at cancerimmunolres.aacrjournals.org.