Deviations of the immune cell landscape between healthy liver and hepatocellular carcinoma

Rohr-Udilova, Nataliya; Klinglmüller, Florian; Schulte‐Hermann, Rolf; Stift, Judith; Herac, Merima; Salzmann, Martina; Finotello, Francesca; Timelthaler, Gerald; Oberhuber, Georg; Pinter, Matthias; Reiberger, Thomas; Jensen‐Jarolim, Erika; Eferl, Robert; Trauner, Michael

doi:10.1038/s41598-018-24437-5

Cited by 154 publications

(161 citation statements)

References 38 publications

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“…27 Because CIBERSORT is superior to other methods, it has received increasing attention and has been successfully used to assess the composition of immune cells in liver and breast cancer. 28,29 We utilized CIBERSORT to assess the composition of 22 immune cells in the TCGA and GEO LUAD cohorts.…”

Section: The Evaluation Of Immune Cells In Luadmentioning

confidence: 99%

Systematic construction and validation of an immune prognostic model for lung adenocarcinoma

Luo

Lei

Zhang

et al. 2019

J Cellular Molecular Medi

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Lung adenocarcinoma (LUAD), the most common non-small-cell lung cancer, is characterized by a dense lymphocytic infiltrate, which indicates that the immune system plays an active role in the development and growth of this cancer. However, no investigations to date have proposed robust models for predicting survival outcome for patients with LUAD in terms of tumour immunology. A total of 761 LUAD patients were included in this study, in which the database of The Cancer Genome Atlas (TCGA) was utilized for discovery, and the Gene Expression Omnibus (GEO) database was utilized for validation. Bioinformatics analysis and R language tools were utilized to construct an immune prognostic model and annotate biological functions.Lung adenocarcinoma showed a weakened immune phenotype compared with adjacent normal tissues. Immune-related gene sets were profiled, an immune prognostic model based on 2 immune genes (ANLN and F2) was developed with the TCGA database to distinguish cases as having a low or high risk of unfavourable prognosis, and the model was verified with the GEO database. The model was prognostically significant in stratified cohorts, including stage I-II, stage III-IV and epidermal growth factor receptor (EGFR) mutant subsets, and was considered to be an independent prognostic factor for LUAD. Furthermore, the low-and high-risk groups showed marked differences in tumour-infiltrating leucocytes, tumour mutation burden, aneuploidy and PD-L1 expression. In conclusion, an immune prognostic model was proposed for LUAD that is capable of independently identifying patients at high risk for poor survival, suggesting a relationship between local immune status and prognosis. K E Y W O R D Sbiomarkers, immune prognostic model, immunology, lung adenocarcinoma, overall survival

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Section: The Evaluation Of Immune Cells In Luadmentioning

confidence: 99%

Systematic construction and validation of an immune prognostic model for lung adenocarcinoma

Luo

Lei

Zhang

et al. 2019

J Cellular Molecular Medi

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“…This deconvolution algorithm based on gene expression data quantifies the cellular composition of immune response and has greatly expanded the potential of the genomic database. Due to the superiority of CIBERSORT over other methods, it has received increasing attention and it has been successfully used to evaluate the composition of immune cells in breast, lung and liver cancer …”

Section: Introductionmentioning

confidence: 99%

“…Due to the superiority of CIBERSORT over other methods, it has received increasing attention and it has been successfully used to evaluate the composition of immune cells in breast, lung and liver cancer. 25,28,29 In this study, CIBERSORT was applied to assess the relative proportions of 22 TIIC, presenting a comprehensive immune cell landscape of RCC. We further revealed relationships between the composition of TIIC and molecular subtypes, tumor stages, and survival in RCC; moreover, we explored the association between TIIC and recurrent genomic alterations.…”

Section: Introductionmentioning

confidence: 99%

Immune infiltration in renal cell carcinoma

et al. 2019

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Immune infiltration of tumors is closely associated with clinical outcome in renal cell carcinoma ( RCC ). Tumor‐infiltrating immune cells ( TIIC s) regulate cancer progression and are appealing therapeutic targets. The purpose of this study was to determine the composition of TIIC s in RCC and further reveal the independent prognostic values of TIIC s. CIBERSORT , an established algorithm, was applied to estimate the proportions of 22 immune cell types based on gene expression profiles of 891 tumors. Cox regression was used to evaluate the association of TIIC s and immune checkpoint modulators with overall survival ( OS ). We found that CD 8+ T cells were associated with prolonged OS (hazard ratio [ HR ] = 0.09, 95% confidence interval [ CI ].01‐.53; P = 0.03) in chromophobe carcinoma ( KICH ). A higher proportion of regulatory T cells was associated with a worse outcome ( HR = 1.59, 95% CI 1.23‐.06; P < 0.01) in renal clear cell carcinoma ( KIRC ). In renal papillary cell carcinoma ( KIRP ), M1 macrophages were associated with a favorable outcome ( HR = .43, 95% CI .25‐.72; P < 0.01), while M2 macrophages indicated a worse outcome ( HR = 2.55, 95% CI 1.45‐4.47; P < 0.01). Moreover, the immunomodulator molecules CTLA 4 and LAG 3 were associated with a poor prognosis in KIRC , and IDO 1 and PD ‐L2 were associated with a poor prognosis in KIRP . This study indicates TIIC s are important determinants of prognosis in RCC meanwhile reveals potential targets and biomarkers for immunotherapy development.

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“…To assess cell density tissue arrays as shown in (Rohr-Udilova et al, 2018) , 2018). Negatively stained cells were considered for further morphometric analysis.…”

Section: Cell Density Measurementmentioning

confidence: 99%

“…Fig. S5B-C)(Rohr-Udilova et al, 2018). Cell density, or cells per field, is an indirect, reciprocal readout for cell size and thus ploidy.…”

mentioning

confidence: 98%

PIDDosome-induced p53-activation for ploidy restriction facilitates hepatocarcinogenesis

Sladky

Knapp

Szabó

et al. 2020

Preprint

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Polyploidization frequently precedes tumorigenesis but also occurs during normal development in several tissues. Hepatocyte ploidy is controlled by the PIDDosome during development and regeneration. The PIDDosome multi-protein complex is activated by supernumerary centrosomes to induce p53 and restrict proliferation of polyploid cells, otherwise prone for chromosomal instability.PIDDosome-deficiency in the liver results in drastically increased polyploidy. To investigate PIDDosome-induced p53-activation in the pathogenesis of liver cancer, we chemically induced hepatocellular carcinoma (HCC) in mice. Strikingly, PIDDosome-deficiency reduced tumor number and burden, despite the inability to activate p53 in polyploid cells. Liver tumors arise primarily from cells with low ploidy, indicating an intrinsic pro-tumorigenic effect of PIDDosome-mediated ploidy restriction. These data suggest that hyperpolyploidization caused by PIDDosome-deficiency protects from HCC. Moreover, high tumor cell density, as a surrogate marker of low ploidy, predicts of survival of HCC patients receiving liver transplantation. Together, we show that the PIDDosome is a potential therapeutic target to manipulate hepatocyte polyploidization for HCC prevention and tumor cell density serves as a novel prognostic marker for recurrence free survival in HCC patients.

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Deviations of the immune cell landscape between healthy liver and hepatocellular carcinoma

Cited by 154 publications

References 38 publications

Systematic construction and validation of an immune prognostic model for lung adenocarcinoma

Systematic construction and validation of an immune prognostic model for lung adenocarcinoma

Immune infiltration in renal cell carcinoma

PIDDosome-induced p53-activation for ploidy restriction facilitates hepatocarcinogenesis

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