Immune cell infiltration as a biomarker for the diagnosis and prognosis of stage I–III colon cancer

• Published in: Cancer Immunology, Immunotherapy Immunotherapy, 2019-03, Vol.68 (3), p.433-442
• Main Authors: Zhou, Rui, Zhang, Jingwen, Zeng, Dongqiang, Sun, Huiying, Rong, Xiaoxiang, Shi, Min, Bin, Jianping, Liao, Yulin, Liao, Wangjun
• Format: Article
• Language: English
• Subjects: Adult; Aged; Aged, 80 and over; Biomarkers, Tumor; Cancer Research; Colon cancer; Colonic Neoplasms - diagnosis; Colonic Neoplasms - immunology; Colonic Neoplasms - mortality; Colonic Neoplasms - pathology; Colorectal cancer; Diagnosis; DNA microarrays; Female; Humans; Immunology; Lymphocytes, Tumor-Infiltrating - immunology; Male; Medical prognosis; Medicine; Medicine & Public Health; Metastases; Microsatellite Instability; Middle Aged; Neoplasm Staging; Nomograms; Oncology; Original; Original Article; Prognosis; Ribonucleic acid; RNA; Tumors
• ISSN: 0340-7004; 1432-0851
• DOI: 10.1007/s00262-018-2289-7

Tumour-infiltrating immune cells are a source of important prognostic information for patients with resectable colon cancer. We developed a novel immune model based on systematic assessments of the immune landscape inferred from bulk tumor transcriptomes of stage I–III colon cancer patients. The “Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT)” algorithm was used to estimate the fraction of 22 immune cell types from six microarray public datasets. The random forest method and least absolute shrinkage and selection operator model were then used to establish immunoscores for diagnosis and prognosis. By comparing immune cell compositions in samples of 870 colon cancer patients and 70 normal controls, we constructed a diagnostic model, designated the diagnostic immune risk score (dIRS), that showed high specificity and sensitivity in both the training [area under the curve (AUC) = 0.98, p