Integrative Statistics, Machine Learning and Artificial Intelligence Neural Network Analysis Correlated CSF1R with the Prognosis of Diffuse Large B-Cell Lymphoma

Tumor-associated macrophages (TAMs) of the immune microenvironment play an important role in Diffuse Large B-cell Lymphoma (DLBCL) pathogenesis. This research aimed to characterize expression macrophage colony-stimulating factor 1 receptor (CSF1R) at gene and protein level correlation with survival. First, immunohistochemical CSF1R was analyzed a series 198 cases from Tokai University Hospital two patterns histological were found, TAMs, diffuse B-lymphocytes pattern. The clinicopathological correlations showed that + TAMs pattern associated poor progression-free survival patients, disease progression, higher MYC proto-oncogene expression, lower MDM2 BCL2 translocation, MYD88 L265P mutation. Conversely, B-cells favorable Second, also correlated 10 CSF1R-related markers including CSF1, STAT3, NFKB1, Ki67, MYC, PD-L1, TNFAIP8, IKAROS, CD163, CD68. moderately CD68, CD163 In addition, machine learning modeling predicted high accuracy using regression, generalized linear, artificial intelligence neural network (multilayer perceptron), support vector (SVM) analyses. Finally, multilayer perceptron analysis genes GEO GSE10846 DLBCL Lymphoma/Leukemia Molecular Profiling Project (LLMPP), whole set 20,683 as well immuno-oncology cancer panel 1790 genes. positively SIRPA inversely CD47. conclusion, patients series, predictive analytics is feasible strategy DLBCL.