Prediction of overall survival and response to immune checkpoint inhibitors: An immune-related signature for gastric cancer

CD36-BATF2\MYB Axis Predicts Anti-PD-1 Immunotherapy Response in Gastric Cancer

Despite the utilization of anti-PD-1 therapy in gastric cancer (GC), the absence of a reliable predictive biomarker continues to pose a challenge. In this study, we utilized bioinformatic analysis and immunohistochemistry to develop a prediction model for activated CD4+ memory T cells, considering both mRNA and protein levels. An elevation of activated CD4+ memory T cells in GC was noted, which exhibited a strong association with the patients' overall survival. By utilizing WGCNA and DEG analysis, we discovered that BATF2, MYB, and CD36 are genes that exhibit differential expression and are linked to activated CD4+ memory T cells. Afterwards, a forecast model was built utilizing Stepwise regression and immunohistochemistry relying on the three genes. The model's high-risk score showed significant associations with a suppressive immune microenvironment. Moreover, our model exhibited encouraging prognostic value and superior performance in predicting response to immune checkpoint blockade therapy compared with the conventional CD8+PD-L1 model. In terms of mechanism, CD36 could function as a receptor upstream that identifies Helicobacter pylori and fatty acids. This recognition then results in the reduction of the BATF2-MYB protein complex and subsequent alterations in the transcription of genes associated with classical T cell activation. As a result, the activation state of CD4+ memory T cells is ultimately suppressed. The CD36-BATF2/MYB signature serves as a robust predictor of anti-PD-1 immunotherapy response in GC.

Immune gene signatures as prognostic criteria for cancer patients

Recently, the possibility of using immune gene signatures (IGSs) has been considered as a novel prognostic tool for numerous cancer types. State-of-the-art methods of genomic, transcriptomic, and protein analysis have allowed the identification of a number of immune signatures correlated to disease outcome. The major adaptive and innate immune components are the T lymphocytes and macrophages, respectively. Herein, we collected essential data on IGSs consisting of subsets of T cells and tumor-associated macrophages and indicating cancer patient outcomes. We discuss factors that can introduce errors in the recognition of immune cell types and explain why the significance of immune signatures can be interpreted with uncertainty. The unidirectional functions of cell types should be entirely addressed in the signatures constructed by the combination of innate and adaptive immune cells. The state of the antitumor immune response is the key basis for IGSs and should be considered in gene signature construction. We also analyzed immune signatures for the prediction of immunotherapy response. Finally, we attempted to explain the present-day limitations in the use of immune signatures as robust criteria for prognosis.

Identification and Validation of the Immune Regulator CXCR4 as a Novel Promising Target for Gastric Cancer

Immune checkpoint blockade has attracted a lot of attention in the treatment of human malignant tumors. We are trying to establish a prognostic model of gastric cancer (GC) based on the expression profile of immunoregulatory factor-related genes. Based on the TCGA database, we identified 234 differentially expressed immunoregulatory factors. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) conducted enrichment analysis to clarify the biological functions of differential expression of immunoregulatory factors. STRING database predicted the interaction network between 234 differently expressed immune regulatory factors. The expression of 11 immunoregulatory factors was significantly related to the overall survival of gastric cancer patients. Univariate Cox regression analysis, Kaplan–Meier analysis and multivariate Cox regression analysis found that immunomodulatory factors were involved in the progression of gastric cancer and promising biomarkers for predicting prognosis. Among them, CXCR4 was related to the low survival of GC patients and a key immunomodulatory factor in GC. Based on TCGA data, the high expression of CXCR4 in GC was positively correlated with the advanced stage and grade of gastric cancer and related to poor prognosis. Univariate analysis and multivariate analysis indicated that CXCR4 was an independent prognostic indicator for TCGA gastric cancer patients. In vitro functional studies had shown that CXCR4 promoted the proliferation, migration, and invasion of gastric cancer cells. In summary, this study has determined the prognostic value of 11 immunomodulatory factors in gastric cancer. CXCR4 is an independent prognostic indicator for gastric cancer patients, which may help to improve the individualized prognostic prediction of GC and provide candidates for the diagnosis and treatment of GC.