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Transcriptional characterization of immunological infiltrates and their relation with glioblastoma patients overall survival.

ABSTRACT: Introduction: Several cell populations from the peripheral immune system interact to create a complex immunologic status during glioblastoma growth and response to therapy. The aim of this study was to integrate the impact of different immune cell populations present in glioblastoma tumor microenvironment on overall survival. Methodology: Gene expression and clinical data were generated by The Cancer Genome Atlas and previously reported meta-signatures representing cells of the immune system were used. The relationship between meta-signatures was evaluated through Pearson's correlation analyses. Survival analyses were performed through Kaplan-Meier plots and Cox regression model. Results and discussion: Meta-signatures corresponding to infiltrating immune cells with immunosuppressive roles, such as macrophages, NK and NK T cells, MDSCs and Tregs, correlated with poorer patient prognosis. Meta-signatures related to CD8+ T cells predicted improved survival only in patients with low immunosuppressive meta-signatures. By clustering the meta-signatures we found that the cluster containing high meta-signatures of macrophages, MDSCs and Tregs demonstrated the worst prognosis. Conclusion: Integrating the information provided by transcriptional signatures of immunological aspects is fundamental in understanding the impact of the immune system on patient survival. We found a predictive impact on survival with positive role for CD8 and negative roles for macrophages, MDSC, Tregs, NK and NK-T in glioblastoma patients. Understanding these regulatory and stimulatory factors of patients' immune system is essential to delineate an effective strategy to increase the anti-tumor immune response and to generate potential clinical benefits.

SUBMITTER: Pereira MB

PROVIDER: S-EPMC5980418 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Transcriptional characterization of immunological infiltrates and their relation with glioblastoma patients overall survival.

Pereira Mariana Brutschin MB Barros Luciana Rodrigues Carvalho LRC Bracco Paula A PA Vigo Alvaro A Boroni Mariana M Bonamino Martín Hernán MH Lenz Guido G

Oncoimmunology 20180212 6

<b>Introduction</b>: Several cell populations from the peripheral immune system interact to create a complex immunologic status during glioblastoma growth and response to therapy. The aim of this study was to integrate the impact of different immune cell populations present in glioblastoma tumor microenvironment on overall survival. <b>Methodology</b>: Gene expression and clinical data were generated by The Cancer Genome Atlas and previously reported meta-signatures representing cells of the imm ...[more]

PMID: 29872555

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Project description:tumor-infiltrating lymphocytes are prognostic in many human cancers. However, the prognostic value of lymphocytes infiltrating glioblastoma (GBM), and roles in tumor control or progression are unclear. We hypothesized that B and T cell density, and markers of their activity, proliferation, differentiation, or function, would have favorable prognostic significance for patients with GBM. initial resection specimens from 77 patients with IDH1/2 wild type GBM who received standard-of-care treatment were evaluated with multiplex immunofluorescence histology (mIFH), for the distribution, density, differentiation, and proliferation of T cells and B cells, as well as for the presence of tertiary lymphoid structures (TLS), and IFNγ expression. Immune infiltrates were evaluated for associations with overall survival (OS) by univariate and multivariate Cox proportional hazards modeling. in univariate analyses, improved OS was associated with high densities of proliferating (Ki67+) CD8+ cells (HR 0.36, p = 0.001) and CD20+ cells (HR 0.51, p = 0.008), as well as CD8+Tbet+ cells (HR 0.46, p = 0.004), and RORγt+ cells (HR 0.56, p = 0.04). Conversely, IFNγ intensity was associated with diminished OS (HR 0.59, p = 0.036). In multivariable analyses, adjusting for clinical variables, including age, resection extent, Karnofsky Performance Status (KPS), and MGMT methylation status, improved OS was associated with high densities of proliferating (Ki67+) CD8+ cells (HR 0.15, p < 0.001), and higher ratios of CD8+ cells to CD4+ cells (HR 0.31, p = 0.005). Diminished OS was associated with increases in patient age (HR 1.21, p = 0.005) and higher mean intensities of IFNγ (HR 2.13, p = 0.027). intratumoral densities of proliferating CD8 T cells and higher CD8/CD4 ratios are independent predictors of OS in patients with GBM. Paradoxically, higher mean intensities of IFNγ in the tumors were associated with shorter OS. These findings suggest that survival may be enhanced by increasing proliferation of tumor-reactive CD8+ T cells and that approaches may be needed to promote CD8+ T cell dominance in GBM, and to interfere with the immunoregulatory effects of IFNγ in the tumor microenvironment.

Project description:IntroductionGlioblastoma (GBM) is one of the most frequent primary intracranial malignancies, with limited treatment options and poor overall survival rates. Alternated glucose metabolism is a key metabolic feature of tumour cells, including GBM cells. However, due to high cellular heterogeneity, accurately predicting the prognosis of GBM patients using a single biomarker is difficult. Therefore, identifying a novel glucose metabolism-related biomarker signature is important and may contribute to accurate prognosis prediction for GBM patients.MethodsIn this research, we performed gene set enrichment analysis and profiled four glucose metabolism-related gene sets containing 327 genes related to biological processes. Univariate and multivariate Cox regression analyses were specifically completed to identify genes to build a specific risk signature, and we identified ten mRNAs (B4GALT7, CHST12, G6PC2, GALE, IL13RA1, LDHB, SPAG4, STC1, TGFBI, and TPBG) within the Cox proportional hazards regression model for GBM.ResultsDepending on this glucose metabolism-related gene signature, we divided patients into high-risk (with poor outcomes) and low-risk (with satisfactory outcomes) subgroups. The results of the multivariate Cox regression analysis demonstrated that the prognostic potential of this ten-gene signature is independent of clinical variables. Furthermore, we used two other GBM databases (Chinese Glioma Genome Atlas (CGGA) and REMBRANDT) to validate this model. In the functional analysis results, the risk signature was associated with almost every step of cancer progression, such as adhesion, proliferation, angiogenesis, drug resistance, and even an immune-suppressed microenvironment. Moreover, we found that IL31RA expression was significantly different between the high-risk and low-risk subgroups.ConclusionThe 10 glucose metabolism-related gene risk signatures could serve as an independent prognostic factor for GBM patients and might be valuable for the clinical management of GBM patients. The differential gene IL31RA may be a potential treatment target in GBM.

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Transcriptional characterization of immunological infiltrates and their relation with glioblastoma patients overall survival.

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Transcriptional characterization of immunological infiltrates and their relation with glioblastoma patients overall survival.

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