Abstract
BackgroundThe tumor microenvironment (TME) plays an important role in the occurrence and development of gastric cancer (GC) and is widely used to assess the treatment outcomes of GC patients. Immunohistochemistry (IHC) and gene sequencing are the main analysis methods for the TME but are limited due to the subjectivity of observers, the high cost of equipment and the need for professional analysts.MethodsThe ImmunoScore (IS) was developed in the TCGA cohort and validated in GEO cohorts. The Radiomic ImmunoScore (RIS) was developed in the TCGA cohort and validated in the Nanfang cohort. A nomogram was developed and validated in the Nanfang cohort based on RIS and clinical features.ResultsFor IS, the area under the curves (AUCs) were 0.798 for 2-year overall survival (OS) and 0.873 for 4-year overall survival. For RIS, in the TCGA cohort, the AUCs distinguishing High-IS or Low-IS and predicting prognosis were 0.85 and 0.81, respectively; in the Nanfang cohort, the AUC predicting prognosis was 0.72. The nomogram performed better than the TNM staging system according to the ROC curve (all P < 0.01). Patients with TNM stage II and III in the High-nomogram group were more likely to benefit from adjuvant chemotherapy than Low-nomogram group patients.ConclusionsThe RIS and the nomogram can be used to assess the TME, prognosis and adjuvant chemotherapy benefit of GC patients after radical gastrectomy and are valuable additions to the current TNM staging system. High-nomogram GC patients may benefit more from adjuvant chemotherapy than Low-nomogram GC patients.
Highlights
The tumor-node-metastasis (TNM) staging system is widely used in the classification of cancer; is based on the primary tumor (T), regional nodes (N) and metastasis (M); and helps in choosing surgery, chemotherapy, etc
We developed an support vector machines (SVMs) model to analyze the relationship between gene expression and CT images based on a The Cancer Genome Atlas (TCGA) cohort, aiming to learn the immune microenvironment from CT images
We collected and analyzed their clinical characteristics, which were summarized in Table 1: 44 patients in the TCGA cohort [38 (86.4%) were male, 6 (13.6%) were female and the mean age was 64.73 ± 9.33 years], 300 patients in the GSE62254 cohort [199 (66.3%) were male, 101 (33.7%) were female and the mean age was 61.94 ± 11.36 years], 192 patients in the GSE15459 cohort [123 (65.1%) were male, 69 (34.9%) were female and the mean age was 64.37 ± 13.24 years], 400 patients in the Nanfang Hospital cohort [276 (69.0%) were male, 124 (31.0%) were female and the mean age was 56.04 ± 10.87 years]
Summary
The tumor-node-metastasis (TNM) staging system is widely used in the classification of cancer; is based on the primary tumor (T), regional nodes (N) and metastasis (M); and helps in choosing surgery, chemotherapy, etc. Recent studies have shown that the TNM staging system does not perfectly predict the prognosis of gastric cancer (GC) patients [1] Specific analysis of an individual’s tumor microenvironment and targeted selection of therapy regimens based on the assessment will be considerably helpful for patients. The tumor microenvironment (TME) plays an important role in the occurrence and development of gastric cancer (GC) and is widely used to assess the treatment outcomes of GC patients. Immunohistochemistry (IHC) and gene sequencing are the main analysis methods for the TME but are limited due to the subjectivity of observers, the high cost of equipment and the need for professional analysts
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