The paratumoral immune cell signature reveals the potential for the implementation of immunotherapy in esophageal carcinoma patients

Střížová, Zuzana; Snajdauf, Martin; Stakheev, Dmitry; Taborska, Pavla; Vachtenheim, J; Biskup, Justyna; Lischke, Robert; Bartůňková, Jiřina; Smrž, Daniel

doi:10.1007/s00432-020-03258-y

Cited by 15 publications

(11 citation statements)

References 45 publications

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“…Pembrolizumab was proposed as an antineoplastic protocol for ESCA patients positive for PD-L1 [27]. However, identifying patients who are suitable for immunotherapy remains a critical issue [28]. Our findings suggested ICI scores as valid prognostic markers and predictors for evaluating immunotherapy response in ESCA patients.…”

Section: Discussionmentioning

confidence: 73%

Characterization of the Immune Infiltration Landscape and Identification of Prognostic Biomarkers for Esophageal Cancer

et al. 2022

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Immunotherapy is an effective treatment for esophageal cancer (ESCA) patients. However, there are no dependable markers for predicting prognosis and immunotherapy responses in ESCA. Our study aims to explore immune gene prognostic models and markers in ESCA as well as predictors for immunotherapy. The expression profiles of ESCA were obtained from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and International Cancer Genome Consortium (ICGC) databases. Cox regression analysis was performed to construct an immune gene prognostic model. ESCA was grouped into three immune cell infiltration (ICI) clusters by CIBERSORT algorithm. The immunotherapy response of patients in different ICI score clusters was also compared. The copy number variations, somatic mutations, and single nucleotide polymorphisms were analyzed. Enrichment analyses were also performed. An immune gene prognostic model was successfully constructed. The ICI score may be used as a predictor independent of tumor mutation burden. Enrichment analyses showed that the differentially expressed genes were mostly enriched in microvillus and the KRAS and IL6/JAK/STAT3 pathways. The top eight genes with the highest mutation frequencies in ESCA were identified and all related to the prognosis of ESCA patients. Our study established an effective immune gene prognostic model and identified markers for predicting the prognosis and immunotherapy response of ESCA patients.

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Section: Discussionmentioning

confidence: 73%

Characterization of the Immune Infiltration Landscape and Identification of Prognostic Biomarkers for Esophageal Cancer

et al. 2022

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“…It has been reported that TNFSF15 promotes the co-activation of T cells, 16 the maturation of DC cells, 25 and the enhancement of the toxicity of NK cells. 26 Considering that various types of cells in tumors can express DR3, 54 , 55 it cannot at this stage of the investigation be definitely excluded that, in response to TNFSF15, signals from other cells in the tumor microenvironment are involved indirectly in the promotion of macrophage polarization toward the M1 phenotype.…”

Section: Discussionmentioning

confidence: 99%

TNFSF15 facilitates differentiation and polarization of macrophages toward M1 phenotype to inhibit tumor growth

et al. 2022

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Macrophages of the M2 phenotype in malignant tumors significantly aid tumor progression and metastasis, as opposed to the M1 phenotype that exhibits anti-cancer characteristics. Raising the ratio of M1/M2 is thus a promising strategy to ameliorate the tumor immunomicroenvironment toward cancer inhibition. We report here that tumor necrosis factor superfamily-15 (TNFSF15), a cytokine with anti-angiogenic activities, is able to facilitate the differentiation and polarization of macrophages toward M1 phenotype. We found that tumors formed in mice by Lewis lung carcinoma (LLC) cells artificially overexpressing TNFSF15 exhibited retarded growth. The tumors displayed a greater percentage of M1 macrophages than those formed by mock-transfected LLC cells. Treatment of mouse macrophage RAW264.7 cells with recombinant TNFSF15 led to augmentation of the phagocytic and pro-apoptotic capacity of the macrophages against cancer cells. Mechanistically, TNFSF15 activated STAT1/3 in bone marrow cells and MAPK, Akt and STAT1/3 in naive macrophages. Additionally, TNFSF15 activated STAT1/3 but inactivated STAT6 in M2 macrophages. Modulations of these signals gave rise to a reposition of macrophage phenotypes toward M1. The ability of TNFSF15 to promote macrophage differentiation and polarization toward M1 suggests that this unique cytokine may have a utility in the reconstruction of the immunomicroenvironment in favor of tumor suppression.

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“…Wang et al found that an "infiltrated-excluded" or "cole" tumor immune microenvironment is predictive of poor response and low-dose metformin reprograms the TME in ESCC [17]. Research by Strizova et al showed that FasR + NK cells, CD4 + , and CD8 + T cells infiltrated lymph nodes at the lowest levels and that the FasR + DR3 + CD4 + T cells were enhanced in esophageal cancer [18]. These compartmental proportions correlated with tumor stage and tumor grade suggested new possibilities for personalized immunotherapy for patients.…”

Section: Discussionmentioning

confidence: 99%

Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of esophageal squamous cell carcinoma

Liu

et al. 2021

BMC Med Genomics

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Background As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC). Methods ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC. Results Based on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function. Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis. Kaplan–Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. The risk score was negatively correlated with plasma cells, while positively correlated with the proportions of activated CD4 memory T cells, M1 Macrophages and M2 Macrophages (p < 0.001 for each comparison). Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group. Conclusions Our study provided a comprehensive understanding of the TME in ESCC patients. The establishment of the risk model is valuable for the early identification of high-risk patients to facilitate individualized treatment and improve the possibility of immunotherapy response.

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The paratumoral immune cell signature reveals the potential for the implementation of immunotherapy in esophageal carcinoma patients

Cited by 15 publications

References 45 publications

Characterization of the Immune Infiltration Landscape and Identification of Prognostic Biomarkers for Esophageal Cancer

Characterization of the Immune Infiltration Landscape and Identification of Prognostic Biomarkers for Esophageal Cancer

TNFSF15 facilitates differentiation and polarization of macrophages toward M1 phenotype to inhibit tumor growth

Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of esophageal squamous cell carcinoma

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