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Identification of immune cell infiltration landscape for predicting prognosis of colorectal cancer.
BACKGROUND: The tumor microenvironment plays an essential role in the therapeutic response to immunotherapy. It is necessary to identify immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits. This study aimed to evaluate the ICI score as an effective prognostic biomarker for immune response.
METHODS: The cell-type identification by estimating relative subsets of RNA transcripts and the estimation of stromal and immune cells in malignant tumors using expression methods were used to analyse ICI landscapes in 161 colorectal cancer (CRC) samples with patients' clinical and prognostic data, RNA sequencing data, and whole-exome sequencing data from the Sixth Affiliated Hospital, Sun Yat-sen University (Guangzhou, China). Statistical analysis and data processing were conducted to calculate ICI scores, and to analyse the prognosis of CRC patients with different ICI scores and other features. A similar analysis with RNA sequencing and clinical data of colon adenocarcinoma (COAD) samples from The Cancer Genome Atlas (TCGA) database was conducted to confirm the correctness of the findings.
RESULTS: The high-ICI score group with a better prognosis (hazard ratio [HR], 2.19; 95% confidence interval [CI], 1.03-4.64; log-rank test, P = 0.036) was characterized by the increased tumor mutational burden and interleukin-17 (IL-17) signaling pathway. Significant differences in the prognosis and the expression levels of immune checkpoints and chemokine marker genes were found between the two ICI score groups. For COAD samples from TCGA, the results also showed a significant difference in patients' prognosis between the two ICI score groups (HR, 1.72; 95% CI, 1.00-2.96; log-rank test, P = 0.047).
CONCLUSIONS: Tumor heterogeneity induced differences in identifying ICI subtypes of CRC patients. The ICI score may serve as an effective biomarker for predicting prognosis, help identify new therapeutic markers for CRC, and develop novel effective immune checkpoint blockade therapies.
METHODS: The cell-type identification by estimating relative subsets of RNA transcripts and the estimation of stromal and immune cells in malignant tumors using expression methods were used to analyse ICI landscapes in 161 colorectal cancer (CRC) samples with patients' clinical and prognostic data, RNA sequencing data, and whole-exome sequencing data from the Sixth Affiliated Hospital, Sun Yat-sen University (Guangzhou, China). Statistical analysis and data processing were conducted to calculate ICI scores, and to analyse the prognosis of CRC patients with different ICI scores and other features. A similar analysis with RNA sequencing and clinical data of colon adenocarcinoma (COAD) samples from The Cancer Genome Atlas (TCGA) database was conducted to confirm the correctness of the findings.
RESULTS: The high-ICI score group with a better prognosis (hazard ratio [HR], 2.19; 95% confidence interval [CI], 1.03-4.64; log-rank test, P = 0.036) was characterized by the increased tumor mutational burden and interleukin-17 (IL-17) signaling pathway. Significant differences in the prognosis and the expression levels of immune checkpoints and chemokine marker genes were found between the two ICI score groups. For COAD samples from TCGA, the results also showed a significant difference in patients' prognosis between the two ICI score groups (HR, 1.72; 95% CI, 1.00-2.96; log-rank test, P = 0.047).
CONCLUSIONS: Tumor heterogeneity induced differences in identifying ICI subtypes of CRC patients. The ICI score may serve as an effective biomarker for predicting prognosis, help identify new therapeutic markers for CRC, and develop novel effective immune checkpoint blockade therapies.
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