Genomic Analysis of Tumor Microenvironment Immune Types across 14 Solid Cancer Types: Immunotherapeutic Implications

Chen, Yu-Pei; Zhang, Yu; Lv, Jia; Li, Ying Qin; Wang, Ya Qin; He, Qiuming; Yang, Xiao; Sun, Ying; Mao, Yan Ping; Yun, Jing Ping; Liu, Na

doi:10.7150/thno.21471

Cited by 187 publications

(174 citation statements)

References 40 publications

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“…Therefore, high-risk patients were more likely to benefit from immune checkpoint blockade targeting PD-1 and CTLA4. This also accords with the study of Yu-Pei Chen et al 41 their study also suggest that tumors with pre-existing intratumor T cells that express high level of PD-L1 and are suppressed by PD-1/PD-L1 pathway are most likely to benefit from immune checkpoint blockade. Nevertheless, further investigations are needed to evaluate the relationship between the signature and immunotherapy.…”

Section: Discussionsupporting

confidence: 89%

Construction of immune‐related risk signature for renal papillary cell carcinoma

et al. 2018

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The kidney renal papillary cell carcinoma (KIRP) is a relatively rare type of kidney cancer. There has been no investigation to find a robust signature to predict the survival outcome of KIRP patients in the aspect of tumor immunology. In this study, 285 KIRP samples from The Cancer Genome Atlas (TCGA) were randomly divided into training and testing set. A total of 1534 immune‐related genes from The Immunology Database and Analysis Portal (ImmPort) were used as candidates to construct the signature. Using univariate Cox analysis, we evaluated the relationship between overall survival and immune‐related genes expression and found 272 immune‐related genes with predicting prognostic ability. In order to construct an efficient predictive model, the Cox proportional hazards model with an elastic‐net penalty was used and identified 23 groups after 1000 iterations. As a result, 15‐genes model showing more stable than other gene groups was chosen to construct our immune‐related risk signature. In line with our expectations, the signature can independently predict the survival outcome of KIRP patients. Patients with high‐immune risk were found correlated with advanced stage. We also found that the high‐immune risk patients with higher PBRM1 and SETD2 mutations, increasing chromosomal instability, together with the gene set enrichment analysis (GSEA) results showing intensive connection of our signature with immune pathways. In conclusion, our study constructs a robust 15‐gene signature for predicting KIRP patients’ survival outcome on the basis of tumor immune environment and may provide possible relationship between prognosis and immune‐related biological function.

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Section: Discussionsupporting

confidence: 89%

Construction of immune‐related risk signature for renal papillary cell carcinoma

et al. 2018

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“…Further studies will be needed to determine whether therapeutic drug combinations to manipulate these factors will, in turn, directly impact intratumoral immune cytolytic activity and lead to an immune-mediated anti-tumor effect. Consistent with other studies [7,27,35], we found no association between the non-synonymous TMB and the degree of intratumoral immune cytolytic activity in GBM.…”

Section: Discussionsupporting

confidence: 92%

RNA-seq for identification of therapeutically targetable determinants of immune activation in human glioblastoma

et al. 2018

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Introduction: We sought to determine which therapeutically targetable immune checkpoints, costimulatory signals, and other tumor microenvironment (TME) factors are independently associated with immune cytolytic activity (CYT), a gene expression signature of activated effector T cells, in human glioblastoma (GBM). Methods: GlioVis was accessed for RNA-seq data from The Cancer Genome Atlas (TCGA). For subjects with treatment-naïve, primary GBM, we quantified mRNA expression of 28 therapeutically targetable TME factors. CYT (geometric mean of GZMA and PRF1 expression) was calculated for each tumor. Multiple linear regression was performed to determine the relationship between the dependent variable (CYT) and mRNA expression of each of the 28 factors. Variables associated with CYT in multivariate analysis were subsequently evaluated for this association in an independent cohort of newly diagnosed GBMs from the Chinese Glioma Cooperative Group (CGCG). Results: 109 TCGA tumors were analyzed. The final multiple linear regression model included the following variables, each positively associated with CYT except VEGF-A (negative association): CSF-1 (p=0.003), CD137 (p=0.042), VEGF-A (p<0.001), CTLA4 (p=0.028), CD40 (p=0.023), GITR (p=0.020), IL6 (p=0.02), and OX40 (p<0.001). In CGCG (n=52), each of these variables remained significantly associated with CYT in univariate analysis except for VEGF-A. In multivariate analysis, only CTLA4 and CD40 remained statistically significant. Conclusions: Using multivariate modeling of RNA-seq gene expression data, we identified therapeutically targetable TME factors that are independently associated with intratumoral cytolytic T-cell activity in human GBM. As a myriad of systemic immunotherapies are now available for investigation, our results could inform rational combinations for evaluation in GBM.

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“…Different lung cancer subtypes have a different biologic background and tissue characteristics . Subsequent genomic analysis indicated that TMIT was associated with mutation and neoantigen numbers in LAC but not in SCC . Based on the IHC analysis, some study reported that PD‐L1 expression was related to a longer or a shorter survival of NSCLC patients, or was even not correlated with their survival .…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, according to the expression of PD‐L1 on tumor cells and tumor‐infiltrating lymphocytes (TILs), TMIT classification has been recently proposed by Teng et al, including TMIT I adaptive immune resistance (PD‐L1 positive and high TIL), TMIT II immune ignorance (PD‐L1 negative and low TIL), TMIT III intrinsic induction (PD‐L1 positive and low TIL), and TMIT IV immune tolerance (PD‐L1 negative and high TIL). Several studies based on database analysis have revealed that the proposed classification of TMIT subtypes is important to tailor optimal immunotherapeutic strategies . Nevertheless, the pathological characterizations of TMIT based on both the expression of PD‐L1 on tumor cells and the spatial distribution of TIL especially in LAC and SCC remain unknown.…”

Section: Introductionmentioning

confidence: 99%

The landscape of immune microenvironment in lung adenocarcinoma and squamous cell carcinoma based on PD‐L1 expression and tumor‐infiltrating lymphocytes

et al. 2019

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Aims The aim of this study was to investigate the tumor microenvironment immune types (TMIT) based on tumor cell programmed cell death ligand 1 (PD‐L1) expression and tumor‐infiltrating lymphocytes (TILs) distribution and whether distinct TMIT subtypes (TMIT I, PD‐L1high/TILhigh; TMIT II, PD‐L1low/TILlow; TMIT III, PD‐L1high/TILlow; and TMIT IV, PD‐L1low/TILhigh) differentially affect clinical outcomes of patients with lung adenocarcinoma (LAC) and squamous cell carcinoma (SCC). Methods and results Immunohistochemistry (IHC) was applied to evaluate the expression of PD‐L1 and the spatial distribution of programmed cell death 1 (PD‐1) and CD8 TILs on the surgically resected specimens from 205 cases of LAC and 149 cases of SCC. PD‐1 and CD8 TILs were more frequently distributed in SCC than those in LAC, regardless of their infiltrating in the tumor islets or stroma. The density of TILs was a poor prognostic factor in LAC but a favorable one in SCC. PD‐L1 levels and its clinical prognostic significance differed in LAC vs SCC. LAC patients with TMIT III and SCC patients with TMIT I had the longest survival, respectively (P = .0197 and .0049). Moreover, TMIT stratification based on tumor cell PD‐L1 expression and stromal CD8+ TILs could be considered as an independent prognostic factor of SCC patients' survival as determined by both univariate and multivariate analysis. Conclusion Our study indicates that different type of TMIT provides its specific microenvironment with diverse impact on survival of LAC and SCC patients and highlights the importance of the integrative assessment of PD‐L1 status and TILs' spatial distribution to predict patients' prognosis.

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Genomic Analysis of Tumor Microenvironment Immune Types across 14 Solid Cancer Types: Immunotherapeutic Implications

Cited by 187 publications

References 40 publications

Construction of immune‐related risk signature for renal papillary cell carcinoma

Construction of immune‐related risk signature for renal papillary cell carcinoma

RNA-seq for identification of therapeutically targetable determinants of immune activation in human glioblastoma

The landscape of immune microenvironment in lung adenocarcinoma and squamous cell carcinoma based on PD‐L1 expression and tumor‐infiltrating lymphocytes

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