PeerJ · 2020 · 36 citations · 26 references
MedicineBiostatisticsCancer BiologyGene Expression AnalysisTranscriptomicsTumor MicroenvironmentCancer BiomarkersCancer TranscriptomicsGene Expression ProfilingImmuno-oncology BiomarkersTranscriptomic ProfilingTumor Immune MicroenvironmentCancer Genomic Biomarker DiscoveryImmune Biomarkers In CancerPrognostic Expression SignaturesRna SequencingRna Sequencing (Rna-seq)Tumor Immune Cell InfiltrationTumor Microenvironment BiomarkersTumor Profiling
BACKGROUND: Prognostic genes in the tumor microenvironment play an important role in immune biological processes and the response of cancer to immunotherapy. Thus, we aimed to assess new biomarkers that are associated with immune/stromal cells in lung adenocarcinomas (LUAD) using the ESTIMATE algorithm, which also significantly affects the prognosis of cancer. METHODS: The RNA sequencing (RNA-Seq) and clinical data of LUAD were downloaded from the the Cancer Genome Atlas (TCGA ). The immune and stromal scores were calculated for each sample using the ESTIMATE algorithm. The LUAD gene chip expression profile data and the clinical data (GSE37745, GSE11969, and GSE50081) were downloaded from the Gene Expression Omnibus (GEO) for subsequent validation analysis. Differentially expressed genes were calculated between high and low score groups. Univariate Cox regression analysis was performed on differentially expressed genes (DEGs) between the two groups to obtain initial prognosis genes. These were verified by three independent LUAD cohorts from the GEO database. Multivariate Cox regression was used to identify overall survival-related DEGs. UALCAN and the Human Protein Atlas were used to analyze the mRNA /protein expression levels of the target genes. Immune cell infiltration was evaluated using the Tumor Immune Estimation Resource (TIMER) and CIBERSORT methods, and stromal cell infiltration was assessed using xCell. RESULTS: < 0.05). Of the 286 genes initially identified, nine prognosis-related genes (CSF2RB, ITK, FLT3, CD79A, CCR4, CCR6, DOK2, AMPD1, and IGJ) were validated from three separate LUAD cohorts. In addition, functional analysis of DEGs also showed that various immunoregulatory molecular pathways, including regulation of immune response and the chemokine signaling pathways, were involved. Five genes (CCR6, ITK, CCR4, DOK2, and AMPD1) were identified as independent prognostic indicators of LUAD in specific data sets. The relationship between the expression levels of these genes and immune genes was assessed. We found that CCR6 mRNA and protein expression levels of LUAD were greater than in normal tissues. We evaluated the infiltration of immune cells and stromal cells in groups with high and low levels of expression of CCR6 in the TCGA LUAD cohort. In summary, we found a series of prognosis-related genes that were associated with the LUAD tumor microenvironment.
26
Inferring tumour purity and stromal and immune cell admixture from expression data
Kosuke Yoshihara, Maria Shahmoradgoli, Emmanuel Martínez et al. · Nature Communications · 2013 · 10.7K citations · Full text
Peter Goldstraw, Kari Chansky, John Crowley et al. · Journal of Thoracic Oncology · 2016 · 4.6K citations · Full text
Profiling Tumor Infiltrating Immune Cells with CIBERSORT
Binbin Chen, Michael S. Khodadoust, Chih Long Liu et al. · Methods in molecular biology · 2018 · 4.2K citations · Full text
Medicine, Immunology, Oncology +12