Computational Tumor Infiltration Phenotypes Enable the Spatial and Genomic Analysis of Immune Infiltration in Colorectal Cancer.
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ABSTRACT:
SUBMITTER: Failmezger H
PROVIDER: S-EPMC8006941 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A substantial fraction of patients with stage I-III colorectal adenocarcinoma (CRC) experience disease relapse after surgery with curative intent. However, biomarkers for predicting the likelihood of CRC relapse have not been fully explored. Therefore, we assessed the association between tumor infiltration by a broad array of innate and adaptive immune cell types and CRC relapse risk. We implemented a discovery-validation design including a discovery dataset from Moffitt Cancer Center (MCC; Tampa, FL) and three independent validation datasets: (1) GSE41258 (2) the Molecular Epidemiology of Colorectal Cancer (MECC) study, and (3) GSE39582. Infiltration by 22 immune cell types was inferred from tumor gene expression data, and the association between immune infiltration by each cell type and relapse-free survival was assessed using Cox proportional hazards regression. Within each of the four independent cohorts, CD4+ memory activated T cell (HR: 0.93, 95% CI: 0.90-0.96; FDR = 0.0001) infiltration was associated with longer time to disease relapse, independent of stage, microsatellite instability, and adjuvant therapy. Based on our meta-analysis across the four datasets, 10 innate and adaptive immune cell types associated with disease relapse of which 2 were internally validated using multiplex immunofluorescence. Moreover, immune cell type infiltration was a better predictors of disease relapse than Consensus Molecular Subtype (CMS) and other expression-based biomarkers (Immune-AICMCC:238.1-238.9; CMS-AICMCC: 241.0). These data suggest that transcriptome-derived immune profiles are prognostic indicators of CRC relapse and quantification of both innate and adaptive immune cell types may serve as candidate biomarkers for predicting prognosis and guiding frequency and modality of disease surveillance.
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Project description:The tumor immune microenvironment (TIME) is likely an important determinant of sensitivity to immune checkpoint inhibitor (ICI) treatment. However, a comprehensive analysis covering the complexity and diversity of the TIME and its influence on ICI therapeutic efficacy is still lacking. Data from 782 samples from 10 ICI clinical trials were collected. To infer the infiltration of 22 subsets of immune cells, CIBERSORTx was applied to the bulk tumor transcriptomes. The associations between each cell fraction and the response to ICI treatment, progression-free survival (PFS) and overall survival (OS) were evaluated, modeling cellular proportions as quartiles. Activity of the interferon-γ pathway, the cytolytic activity score and the MHC score were associated with good prognosis in melanoma. Of the immune cells investigated, M1 macrophages, activated memory CD4+ T cells, T follicular helper (Tfh) cells and CD8+ T cells correlated with response and prolonged PFS and OS, while resting memory CD4+ T cells was associated with unfavorable prognosis in melanoma and urothelial cancer. Consensus clustering revealed four immune subgroups with distinct responses to ICI therapy and survival patterns. The cluster with high proportions of infiltrated CD8+ T cells, activated memory CD4+ T cells, and Tfh cells and low levels of resting memory CD4+ T cells exhibited a higher tumor mutation burden and neoantigen load in melanoma and conferred a higher probability of response and improved survival. Local systemic immune cellular differences were associated with outcomes after ICI therapy. Further investigations of the tumor-infiltrating cellular immune response will lay the foundation for achieving durable efficacy.
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Project description:BackgroundThe anti-epidermal growth factor receptor (EGFR) antibody introduces adaptable variations to the transcriptome and triggers tumor immune infiltration, resulting in colorectal cancer (CRC) treatment resistance. We intended to identify genes that play essential roles in cetuximab resistance and tumor immune cell infiltration.MethodsA cetuximab-resistant CACO2 cellular model was established, and its transcriptome variations were detected by microarray. Meanwhile, public data from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) database were downloaded. Integrated bioinformatics analysis was applied to detect differentially expressed genes (DEGs) between the cetuximab-resistant and the cetuximab-sensitive groups. Then, we investigated correlations between DEGs and immune cell infiltration. The DEGs from bioinformatics analysis were further validated in vitro and in clinical samples.ResultsWe identified 732 upregulated and 1259 downregulated DEGs in the induced cellular model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, along with Gene Set Enrichment Analysis and Gene Set Variation Analysis, indicated the functions of the DEGs. Together with GSE59857 and GSE5841, 12 common DEGs (SATB-2, AKR1B10, ADH1A, ADH1C, MYB, ATP10B, CDX-2, FAR2, EPHB2, SLC26A3, ORP-1, VAV3) were identified and their predictive values of cetuximab treatment were validated in GSE56386. In online Genomics of Drug Sensitivity in Cancer (GDSC) database, nine of twelve DEGs were recognized in the protein-protein (PPI) network. Based on the transcriptome profiles of CRC samples in TCGA and using Tumor Immune Estimation Resource Version 2.0, we bioinformatically determined that SATB-2, ORP-1, MYB, and CDX-2 expressions were associated with intensive infiltration of B cell, CD4+ T cell, CD8+ T cell and macrophage, which was then validated the correlation in clinical samples by immunohistochemistry. We found that SATB-2, ORP-1, MYB, and CDX-2 were downregulated in vitro with cetuximab treatment. Clinically, patients with advanced CRC and high ORP-1 expression exhibited a longer progression-free survival time when they were treated with anti-EGFR therapy than those with low ORP-1 expression.ConclusionsSATB-2, ORP-1, MYB, and CDX-2 were related to cetuximab sensitivity as well as enhanced tumor immune cell infiltration in patients with CRC.
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Project description:The RNA 5-methylcytosine (m5C) modification has been demonstrated to be an important epigenetic regulator and to impact colorectal cancer (CRC) progression. However, the potential roles of m5C modification in immune cell infiltration in the CRC tumor microenvironment (TME) remain unknown. The m5C modification phenotypes were comprehensively evaluated based on 14 m5C regulators in a meta-CRC cohort of 1792 patients and systematically correlated with the m5C modification phenotypes, immune cell infiltration characteristics and known biological processes. The m5Cscore model was constructed by principal component analysis (PCA) algorithms to quantify the m5C modification phenotypes of individual CRC samples and was used to predict the immunotherapy response. We identified three m5C modification phenotypes associated with distinct clinical outcomes and biological processes among the 1792 meta-CRC patients. Three phenotypes with a highly consistent TME landscape and characteristics were revealed: immune excluded, immune desert and immune inflammation. The meta-CRC patients were divided into high and low m5Cscore subgroups based on the m5Cscore. The m5Cscore was confirmed to have a negative correlation with infiltrating immune cells and PD-L1 expression and a positive correlation with tumor mutation burden (TMB), mutation rate and microsatellite instability (MSI) score. Moreover, patients in the low m5Cscore group had better immunotherapy responses and significant durable survival benefits in independent anti-PD-1/L1 immunotherapy cohorts for the immune checkpoint inhibitor (ICI) therapeutic strategy. This study revealed that m5C modification plays a crucial role in TME composition and complexity. Comprehensive evaluation of the m5C modification phenotypes of individual patients will enhance our understanding of TME characteristics and promote the application of more appropriate and personalized treatment strategies.
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Project description:OBJECTIVES:Analysis of tumor immune infiltration has been suggested to outperform tumor, node, metastasis staging in predicting clinical course of colorectal cancer (CRC). Infiltration by cells expressing OX40, a member of the tumor necrosis factor receptor family, or CD16, expressed by natural killer cells, monocytes, and dendritic cells, has been associated with favorable prognosis in patients with CRC. We hypothesized that assessment of CRC infiltration by both OX40+ and CD16+ cells might result in enhanced prognostic significance. METHODS:Colorectal cancer infiltration by OX40 and CD16 expressing cells was investigated in 441 primary CRCs using tissue microarrays and specific antibodies, by immunohistochemistry. Patients' survival was evaluated by Kaplan-Meier and log-rank tests. Multivariate Cox regression analysis, hazard ratios, and 95% confidence intervals were also used to evaluate prognostic significance of OX40+ and CD16+ cell infiltration. RESULTS:Colorectal cancer infiltration by OX40+ and CD16+ cells was subclassified into 4 groups with high or low infiltration levels in all possible combinations. High levels of infiltration by both OX40+ and CD16+ cells were associated with lower pT stage, absence of peritumoral lymphocytic (PTL) inflammation, and a positive prognostic impact. Patients bearing tumors with high infiltration by CD16+ and OX40+ cells were also characterized by significantly longer overall survival, as compared with the other groups. These results were confirmed by analyzing an independent validation cohort. CONCLUSIONS:Combined infiltration by OX40+ and CD16+ immune cells is an independent favorable prognostic marker in CRC. The prognostic value of CD16+ immune cell infiltration is significantly improved by the combined analysis with OX40+ cell infiltration.
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Project description:The immune infiltration of patients with gastric cancer (GC) is closely associated with clinical prognosis. However, previous studies failed to explain the different subsets of immune cells involved in immune responses and diverse functions. The present study aimed to uncover the differences in immunophenotypes in a tumor microenvironment (TME) between adjacent and tumor tissues and to explore their therapeutic targets. In our study, the relative proportion of immune cells in 229 GC tumor samples and 22 paired matched tissues was evaluated with a Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) algorithm. The correlation between immune cell infiltration and clinical information was analyzed. The proportion of 22 immune cell subsets was assessed to determine the correlation between each immune cell type and clinical features. Three molecular subtypes were identified with 'CancerSubtypes' R-package. Functional enrichment was analyzed in each subtype. The profiles of immune infiltration in the GC cohort from The Cancer Genome Atlas (TCGA) varied significantly between the 22 paired tissues. TNM stage was associated with M1 macrophages and eosinophils. Follicular helper T cells were activated at the late stage. Monocytes were associated with radiation therapy. Three clustering processes were obtained via the 'CancerSubtypes' R-package. Each cancer subtype had a specific molecular classification and subtype-specific characterization. These findings showed that the CIBERSOFT algorithm could be used to detect differences in the composition of immune-infiltrating cells in GC samples, and these differences might be an important driver of GC progression and treatment response.
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Project description:ImportanceWhy some triple-negative breast cancers (TNBCs) have high and others have low immune cell infiltration is unknown. Understanding how immune surveillance shapes the cancer genome could help in the selection of patients and the development of more effective immunotherapy strategies.ObjectiveTo examine the association between genomic metrics and the extent of immune infiltration in TNBCs.Design, setting, and participantsThis study, performed from June 1, 2015, through January 31, 2017, used DNA and RNA sequencing data and messenger RNA expression results from The Cancer Genome Atlas (TCGA) breast cancer data set (n = 1215) to calculate previously described immune metagene expression values and histologic lymphocyte counts to quantify immune infiltration and assign prognostic categories to TNBCs. It used the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data set as an independent validation cohort. The study compared clonal heterogeneity, somatic total mutational load, neoantigen load, and somatic copy number alteration levels between immune-rich TNBC cohorts with good prognosis and immune-poor TNBC cohorts with poor prognosis. The study also compared the distribution of mutations in 119 canonical cancer genes.Main outcomes and measuresCorrelation between immune prognostic category and genomic metrics of the cancer.ResultsThis study of 193 TNBC samples with patient survival information found an inverse association between clonal heterogeneity and immune metagene expression (? = ?0.395, P = 2 ×?10?8). The study also found an inverse association between immune metagene expression and somatic copy number alteration levels (? = ?0.484, P = 2 ×?10?10). Lymphocyte-rich TNBCs with good prognosis had significantly lower mutation and neoantigen counts than did lymphocyte-poor TNBCs with poor prognosis. The robustness of the study results was confirmed by using various immune metagenes in the same TCGA data set and in the independent METABRIC data set.Conclusions and relevanceThis study suggests that immune-rich TNBCs may be under an immune surveillance that continuously eliminates many immunogenic clones, resulting in lower clonal heterogeneity. These cancers may also represent the subset of TNBCs that could derive benefit from immune checkpoint inhibitor therapy to tilt the balance in favor of the immune system.
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