Abstract A011: Gene expression signatures of effector immune cell abundance are significantly associated with recurrence risk in colon cancer
CANCER IMMUNOLOGY RESEARCH(2016)
Abstract
Background: Previous studies have suggested that immune infiltrates in colorectal cancer are of clinical importance. We now know that functional orientation, density and location of immune cells within colorectal tumors profoundly influence the clinical outcome irrespective of stage. The currently known prognostic markers are AJCC (American Joint Committee on Cancer) stage, tumor morphology, tumor molecular pathway, tumor gene signatures and tumor mutation status. The immunoscore is currently being validated in a large prospective study to enable its application in clinical practice. The cell types most frequently investigated as antitumor effector cells are tumor infiltrating lymphocytes (TILs) such as cytotoxic T cells (CTLs), natural killer (NK) cells and B cells. Through expression microarray analysis, we recently discovered three separate immune gene signatures, or metagenes, that appear to reflect the relative abundance of distinct tumor-infiltrating leukocyte populations. These metagenes, referred as the B/P (B-cell/Plasma cell), T/NK (T-cell/Natural Killer cell) and M/D (Monocyte/Dendritic cell) immune metagenes, were found to be significantly associated with the distant metastasis-free survival of breast cancer patients with highly proliferative cancer of the Basal-like, HER2-Enriched and Luminal B subtypes, in particular. Aim: Given the histopathological evidence that TIL abundance is prognostic of outcome in colorectal cancer we sought to evaluate the interaction between established clinical and pathologic factors and immune metagenes. We hypothesized that the immune gene signatures would recapitulate the known information and potentially add additional prognostic information. Methods: In a multi-institutional, meta-cohort analysis of 177 colon cancer tumor patients, gene expression profiles of colon tumor biopsies were investigated to determine the relationships between immune gene signatures and disease specific survival (DSS). In separate Cox proportional hazards regression models, B/P and TNK metagenes were both found to be associated with DSS, however M/D was not. Next, stepwise selection models were considered in which other prognostic factors (AJCC stage, grade, gender and age) and both B/P and TNK were considered for inclusion in the Cox proportional hazards regression model. In this analysis, AJCC stage was the first variable to enter the model, followed by B/P and then grade. Results: Age, gender and TNK were not significant predictors in this multivariate model. In the final multivariate model the hazard ratio for B/P was 0.746 with 95% confidence interval (0.61 to 0.91, p=0.0038) suggesting that as B/P signature increases the DSS risk decreases. These analyses support the finding that both TNK and B/P are predictive of DSS; however the impact of TNK was not an independent predictor of DSS once AJCC stage and grade were taken into account, while B/P remained an independent predictor. Further studies need to be conducted to determine whether the TNK effect would reach statistical significance in a multivariate model with a larger sample size. Conclusions: Our results suggest that the prognostic information provided by immune metagenes (B/P and TNK) will have the greatest clinical utility when used as a complement to known clinical predictors, especially AJCC stage. Citation Format: Angela Tatiana Alistar, Julia Chifman, Ralph D9Agostino, Jr., Lance D. Miller. Gene expression signatures of effector immune cell abundance are significantly associated with recurrence risk in colon cancer. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr A011.
MoreTranslated text
Key words
immune cell abundance,gene expression signatures,gene expression,recurrence risk,colon
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined