To the Editor:Lung adenocarcinoma(LUAD)with a high degree of malignancy is the most common histological subtype of lung cancer,and the leading cause of cancerrelated death in the world.[1]Tumor immune microenvironment...To the Editor:Lung adenocarcinoma(LUAD)with a high degree of malignancy is the most common histological subtype of lung cancer,and the leading cause of cancerrelated death in the world.[1]Tumor immune microenvironment is mainly composed of infiltrating immune and stromal cells,which have an important influence on the prognosis of LUAD patients.[2]In recent years,rapid advances in high-throughput sequencing technology have profoundly changed our understanding of tumor research.It uses a large amount of public clinical data to help researchers more effectively to study the characteristics of tumors and improve our ability to diagnose,treat,and prevent cancer.The purpose of this study was to use the estimation of stromal and immune cells in malignant tumor tissues using expression data(ESTIMATE)algorithm to calculate the immune and stromal scores of LUAD patients from The Cancer Genome Atlas(TCGA)database,explore the correlation between the scores and the survival of LUAD patients,and identify differentially expressed genes(DEGs)based on the immune/stromal scores.In addition,we also judged the prognostic value of DEGs and further studied their potential molecular functions.展开更多
基金This work was supported by grants from the Institutional Fundamental Research Funds(No.2018PT32033)the Ministry of Education Innovation Team Development Project(No.IRT-17R10)the Beijing Hope Run Special Fund of Cancer Foundation of China(No.LC2019B15).
文摘To the Editor:Lung adenocarcinoma(LUAD)with a high degree of malignancy is the most common histological subtype of lung cancer,and the leading cause of cancerrelated death in the world.[1]Tumor immune microenvironment is mainly composed of infiltrating immune and stromal cells,which have an important influence on the prognosis of LUAD patients.[2]In recent years,rapid advances in high-throughput sequencing technology have profoundly changed our understanding of tumor research.It uses a large amount of public clinical data to help researchers more effectively to study the characteristics of tumors and improve our ability to diagnose,treat,and prevent cancer.The purpose of this study was to use the estimation of stromal and immune cells in malignant tumor tissues using expression data(ESTIMATE)algorithm to calculate the immune and stromal scores of LUAD patients from The Cancer Genome Atlas(TCGA)database,explore the correlation between the scores and the survival of LUAD patients,and identify differentially expressed genes(DEGs)based on the immune/stromal scores.In addition,we also judged the prognostic value of DEGs and further studied their potential molecular functions.
