Inflammation and lymphocyte infiltration are associated with shorter survival in patients with high-grade glioma

Marinari, Eliana; Allard, Mathilde; Gustave, Robin; Widmer, Valérie; Philippin, Géraldine; Merkler, Doron; Tsantoulis, Petros; Dutoit, Valérie; Dietrich, Pierre‐Yves

doi:10.1080/2162402x.2020.1779990

Cited by 31 publications

(27 citation statements)

References 59 publications

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“…This is accordant with our result that the mesenchymal GBMs were mainly classified into immunity-high. Marinari et al [47] revealed that tumor lymphocyte infiltration was an adverse prognostic factor in gliomas, consistent with our results. Overall, our unsupervised machine learning method well recaptured the immunological heterogeneity of gliomas.…”

Section: Discussionsupporting

confidence: 93%

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Immunological classification of gliomas based on immunogenomic profiling

Feng

et al. 2020

J Neuroinflammation

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Background Gliomas are heterogeneous in the tumor immune microenvironment (TIM). However, a classification of gliomas based on immunogenomic profiling remains lacking. Methods We hierarchically clustered gliomas based on the enrichment levels of 28 immune cells in the TIM in five datasets and obtained three clusters: immunity-high, immunity-medium, and immunity-low. Results Glioblastomas were mainly distributed in immunity-high and immunity-medium, while lower-grade gliomas were distributed in all the three subtypes and predominated in immunity-low. Immunity-low displayed a better survival than other subtypes, indicating a negative correlation between immune infiltration and survival prognosis in gliomas. IDH mutations had a negative correlation with glioma immunity. Immunity-high had higher tumor stemness and epithelial-mesenchymal transition scores and included more high-grade tumors than immunity-low, suggesting that elevated immunity is associated with tumor progression in gliomas. Immunity-high had higher tumor mutation burden and more frequent somatic copy number alterations, suggesting a positive association between tumor immunity and genomic instability in gliomas. Conclusions The identification of immune-specific glioma subtypes has potential clinical implications for the immunotherapy of gliomas.

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Section: Discussionsupporting

confidence: 93%

“…The immune landscape of glioma has been investigated in several recent studies [45][46][47]. For example, Thorsson et al [45] identified six immune subtypes of pan-cancer and found that the immunologically quiet subtype was mostly composed of LGG, which contained the lowest level of lymphocyte infiltration.…”

Section: Discussionmentioning

confidence: 99%

Immunological classification of gliomas based on immunogenomic profiling

Feng

et al. 2020

J Neuroinflammation

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“…In neuro-oncology, TILs have been primarily studied in glioblastoma and were shown to be associated with molecular alterations, such as NF1 and RB1 mutations, although the reported prognostic associations are still being controversially discussed. [6][7][8] Using transcriptomic approaches, immunological differences between molecular subgroups were identified in medulloblastoma (MB), ependymoma and ATRT. [9][10][11] Recently, profiling the immune microenvironment of over 6,000 primarily pediatric brain tumors (medulloblastomas, malignant rhabdoid tumors, and high-grade gliomas) using MethylCIBERSORT, Grabovska et al showed associations of particular immune cells with molecular subgroups, mutations, as well as the overall survival in these entities.…”

Section: Introductionmentioning

confidence: 99%

DIMEimmune: Robust estimation of infiltrating lymphocytes in CNS tumors from DNA methylation profiles

et al. 2021

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The interaction of CNS tumors with infiltrating lymphocytes plays an important role in their initiation and progression and might be related to therapeutic responses. Gene expression-based methods have been successfully used to characterize the tumor microenvironment. However, methylation data are now increasingly used for molecular diagnostics and there are currently only few methods to infer information about the microenvironment from this data type. Using an approach based on differential methylation and principal component analysis, we developed DIMEimmune (Differential Methylation Analysis for Immune Cell Estimation) to estimate CD4 + and CD8 + T cell abundance as well as tumor-infiltrating lymphocytes (TILs) scores from bulk methylation data. Well-established approaches based on gene expression data and immunohistochemistry-based lymphocyte counts were used as benchmarks. The comparison of DIMEimmune to the previously published MethylCIBERSORT and MeTIL algorithms showed an improved correlation with both gene expression-based and immunohistological results across different brain tumor types. Further, we applied our method to large datasets of glioma, medulloblastoma, atypical teratoid/rhabdoid tumors (ATRTs) and ependymoma. High-grade gliomas showed higher scores of tumor-infiltrating lymphocytes than lower-grade gliomas. There were overall only few tumorinfiltrating lymphocytes in medulloblastoma subgroups. ATRTs were highly infiltrated by lymphocytes, most prominently in the MYC subgroup. DIMEimmune-based estimates of TILs were a significant prognostic factor in the overall cohort of gliomas and medulloblastomas, but not within methylation-based diagnostic subgroups. To conclude, DIMEimmune allows for robust estimates of TIL abundance and might contribute to establishing them as a prognostic or predictive factor in future studies of CNS tumors.

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“…[2][3][4] Many lines of evidence have demonstrated that cancer patients with systemic inflammation are characterized by inadequate antitumor responses and unfavorable outcomes compared with those patients without systemic inflammation. [4][5][6][7][8][9][10][11][12][13] In addition to systemic inflammation, the nutritional status of cancer patients is another aspect that can affect antitumor treatment efficacy. Several nutritional indexes, such as the prognostic nutritional index (PNI), nutritional risk index (NRI), and controlling nutritional status (CONUT) score, have been closely correlated with treatment-related complications, therapeutic responses, and clinical outcomes in various cancer types, including NPC.…”

Section: Introductionmentioning

confidence: 99%

A Scoring System Based on Nutritional and Inflammatory Parameters to Predict the Efficacy of First-Line Chemotherapy and Survival Outcomes for De Novo Metastatic Nasopharyngeal Carcinoma

Li¹,

Hua²,

Lv³

et al. 2021

JIR

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Purpose We aimed to develop a simple scoring system based on baseline inflammatory and nutritional parameters to predict the efficacy of first-line chemotherapy and survival outcomes for de novo metastatic nasopharyngeal carcinoma (mNPC). Patients and Methods We retrospectively collected ten candidate inflammatory and nutritional parameters from de novo mNPC patients who received platinum-based first-line chemotherapy treatment. We examined the effects of these ten candidate variables on progression-free survival (PFS) using the Cox regression model. We built a risk-scoring system based on the regression coefficients associated with the identified independent prognostic factors. The predictive accuracy of the scoring system was evaluated and independently validated. Results A total of 460 patients were analyzed. Four independent prognostic factors were identified in a training cohort and were used to construct the scoring system, including nutritional risk index, C-reactive protein level, alkaline phosphatase level, and lactate dehydrogenase level. Based on the score obtained from the scoring system, we stratified patients into three prognostic subgroups (low: 0–1 point, intermediate: 2–3 points, and high: 4 points) associated with significantly different disease control rates (94.7% vs. 92.5% vs. 66.0%, respectively) and survival outcomes (3-year PFS: 55.8% vs. 29.1% vs. 11.9%, respectively). The scoring system had a good performance for the prediction of short-term disease control (area under the receiver operating characteristic curve [AUC]: 0.701) and long-term survival outcomes (time-dependent AUC for 5-year PFS: 0.713). The results were internally validated using an independent cohort (AUC for predicting disease control: 0.697; time-dependent AUC for 5-year PFS: 0.713). Conclusion We developed and validated a clinically useful risk-scoring system that could predict the efficacy of first-line chemotherapy and survival outcomes in de novo mNPC patients. This system may help clinicians to design personalized treatment strategies.

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Inflammation and lymphocyte infiltration are associated with shorter survival in patients with high-grade glioma

Cited by 31 publications

References 59 publications

Immunological classification of gliomas based on immunogenomic profiling

Immunological classification of gliomas based on immunogenomic profiling

DIMEimmune: Robust estimation of infiltrating lymphocytes in CNS tumors from DNA methylation profiles

A Scoring System Based on Nutritional and Inflammatory Parameters to Predict the Efficacy of First-Line Chemotherapy and Survival Outcomes for De Novo Metastatic Nasopharyngeal Carcinoma

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