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26 pages, 14672 KiB

Open AccessArticle

Radiomics-Based Method for Predicting the Glioma Subtype as Defined by Tumor Grade, IDH Mutation, and 1p/19q Codeletion

by Yingping Li, Samy Ammari, Littisha Lawrance, Arnaud Quillent, Tarek Assi, Nathalie Lassau and Emilie Chouzenoux

Cancers 2022, 14(7), 1778; https://doi.org/10.3390/cancers14071778 - 31 Mar 2022

Cited by 20 | Viewed by 4181

Abstract

Gliomas are among the most common types of central nervous system (CNS) tumors. A prompt diagnosis of the glioma subtype is crucial to estimate the prognosis and personalize the treatment strategy. The objective of this study was to develop a radiomics pipeline based [...] Read more.

Gliomas are among the most common types of central nervous system (CNS) tumors. A prompt diagnosis of the glioma subtype is crucial to estimate the prognosis and personalize the treatment strategy. The objective of this study was to develop a radiomics pipeline based on the clinical Magnetic Resonance Imaging (MRI) scans to noninvasively predict the glioma subtype, as defined based on the tumor grade, isocitrate dehydrogenase (IDH) mutation status, and 1p/19q codeletion status. A total of 212 patients from the public retrospective The Cancer Genome Atlas Low Grade Glioma (TCGA-LGG) and The Cancer Genome Atlas Glioblastoma Multiforme (TCGA-GBM) datasets were used for the experiments and analyses. Different settings in the radiomics pipeline were investigated to improve the classification, including the Z-score normalization, the feature extraction strategy, the image filter applied to the MRI images, the introduction of clinical information, ComBat harmonization, the classifier chain strategy, etc. Based on numerous experiments, we finally reached an optimal pipeline for classifying the glioma tumors. We then tested this final radiomics pipeline on the hold-out test data with 51 randomly sampled random seeds for reliable and robust conclusions. The results showed that, after tuning the radiomics pipeline, the mean AUC improved from 0.8935 (±0.0351) to 0.9319 (±0.0386), from 0.8676 (±0.0421) to 0.9283 (±0.0333), and from 0.6473 (±0.1074) to 0.8196 (±0.0702) in the test data for predicting the tumor grade, IDH mutation, and 1p/19q codeletion status, respectively. The mean accuracy for predicting the five glioma subtypes also improved from 0.5772 (±0.0816) to 0.6716 (±0.0655). Finally, we analyzed the characteristics of the radiomic features that best distinguished the glioma grade, the IDH mutation, and the 1p/19q codeletion status, respectively. Apart from the promising prediction of the glioma subtype, this study also provides a better understanding of the radiomics model development and interpretability. The results in this paper are replicable with our python codes publicly available in github. Full article

(This article belongs to the Special Issue Biomarker in Glioblastoma)

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15 pages, 1337 KiB

Open AccessArticle

MRI Response Assessment in Glioblastoma Patients Treated with Dendritic-Cell-Based Immunotherapy

by Johanna Heugenhauser, Malik Galijasevic, Stephanie Mangesius, Georg Goebel, Johanna Buchroithner, Friedrich Erhart, Josef Pichler, Georg Widhalm, Günther Stockhammer, Sarah Iglseder, Christian F. Freyschlag, Stefan Oberndorfer, Karin Bordihn, Gord von Campe, Thomas Czech, Birgit Surböck, Tadeja Urbanic Purkart, Christine Marosi, Thomas Felzmann and Martha Nowosielski

Cancers 2022, 14(6), 1579; https://doi.org/10.3390/cancers14061579 - 20 Mar 2022

Cited by 5 | Viewed by 2867

Abstract

Introduction: In this post hoc analysis we compared various response-assessment criteria in newly diagnosed glioblastoma (GB) patients treated with tumor lysate-charged autologous dendritic cells (Audencel) and determined the differences in prediction of progression-free survival (PFS) and overall survival (OS). Methods: 76 patients enrolled [...] Read more.

Introduction: In this post hoc analysis we compared various response-assessment criteria in newly diagnosed glioblastoma (GB) patients treated with tumor lysate-charged autologous dendritic cells (Audencel) and determined the differences in prediction of progression-free survival (PFS) and overall survival (OS). Methods: 76 patients enrolled in a multicenter phase II trial receiving standard of care (SOC, n = 40) or SOC + Audencel vaccine (n = 36) were included. MRI scans were evaluated using MacDonald, RANO, Vol-RANO, mRANO, Vol-mRANO and iRANO criteria. Tumor volumes (T1 contrast-enhancing as well as T2/FLAIR volumes) were calculated by semiautomatic segmentation. The Kruskal-Wallis-test was used to detect differences in PFS among the assessment criteria; for correlation analysis the Spearman test was used. Results: There was a significant difference in median PFS between mRANO (8.6 months) and Vol-mRANO (8.6 months) compared to MacDonald (4.0 months), RANO (4.2 months) and Vol-RANO (5.4 months). For the vaccination arm, median PFS by iRANO was 6.2 months. There was no difference in PFS between SOC and SOC + Audencel. The best correlation between PFS/OS was detected for mRANO (r = 0.65) and Vol-mRANO (r = 0.69, each p < 0.001). A total of 16/76 patients developed a pure T2/FLAIR progressing disease, and 4/36 patients treated with Audencel developed pseudoprogression. Conclusion: When comparing different response-assessment criteria in GB patients treated with dendritic cell-based immunotherapy, the best correlation between PFS and OS was observed for mRANO and Vol-mRANO. Interestingly, iRANO was not superior for predicting OS in patients treated with Audencel. Full article

(This article belongs to the Special Issue Biomarker in Glioblastoma)

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17 pages, 1165 KiB

Open AccessArticle

A Simple Preoperative Blood Count to Stratify Prognosis in Isocitrate Dehydrogenase-Wildtype Glioblastoma Patients Treated with Radiotherapy plus Concomitant and Adjuvant Temozolomide

by Anne Clavreul, Jean-Michel Lemée, Gwénaëlle Soulard, Audrey Rousseau and Philippe Menei

Cancers 2021, 13(22), 5778; https://doi.org/10.3390/cancers13225778 - 18 Nov 2021

Cited by 10 | Viewed by 1683

Abstract

Purpose: The survival times of glioblastoma (GB) patients after the standard therapy including safe maximal resection followed by radiotherapy plus concomitant and adjuvant temozolomide are heterogeneous. In order to define a simple, reliable method for predicting whether patients with isocitrate dehydrogenase (IDH)-wildtype GB [...] Read more.

Purpose: The survival times of glioblastoma (GB) patients after the standard therapy including safe maximal resection followed by radiotherapy plus concomitant and adjuvant temozolomide are heterogeneous. In order to define a simple, reliable method for predicting whether patients with isocitrate dehydrogenase (IDH)-wildtype GB treated with the standard therapy will be short- or long-term survivors, we analyzed the correlation of preoperative blood counts and their combined forms with progression-free survival (PFS) and overall survival (OS) in these patients. Methods: Eighty-five patients with primary IDH-wildtype GB treated with the standard therapy between 2012 and 2019 were analyzed retrospectively. Cox proportional hazards models and Kaplan–Meier analysis were used to investigate the survival function of preoperative hematological parameters. Results: Preoperative high neutrophil-to-lymphocyte ratio (NLR, >2.42), high platelet count (>236 × 10⁹/L), and low red blood cell (RBC) count (≤4.59 × 10¹²/L) were independent prognostic factors for poorer OS (p = 0.030, p = 0.030, and p = 0.004, respectively). Moreover, a high NLR was an independent prognostic factor for shorter PFS (p = 0.010). We also found that, like NLR, preoperative high derived NLR (dNLR, >1.89) was of poor prognostic value for both PFS (p = 0.002) and OS (p = 0.033). A significant correlation was observed between NLR and dNLR (r = 0.88, p < 0.001), which had a similar prognostic power for OS (NLR: AUC = 0.58; 95% CI: [0.48; 0.68]; dNLR: AUC = 0.62; 95% CI: [0.51; 0.72]). Two scores, one based on preoperative platelet and RBC counts plus NLR and the other on preoperative platelet and RBC counts plus dNLR, were found to be independent prognostic factors for PFS (p = 0.006 and p = 0.002, respectively) and OS (p < 0.001 for both scores). Conclusion: Cheap, routinely ordered, preoperative assessments of blood markers, such as NLR, dNLR, RBC, and platelet counts, can predict the survival outcomes of patients with IDH-wildtype GB treated with the standard therapy. Full article

(This article belongs to the Special Issue Biomarker in Glioblastoma)

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8 pages, 772 KiB

Open AccessArticle

Newly Diagnosed IDH-Wildtype Glioblastoma and Temporal Muscle Thickness: A Multicenter Analysis

by Tim Wende, Johannes Kasper, Gordian Prasse, Änne Glass, Thomas Kriesen, Thomas M. Freiman, Jürgen Meixensberger and Christian Henker

Cancers 2021, 13(22), 5610; https://doi.org/10.3390/cancers13225610 - 10 Nov 2021

Cited by 10 | Viewed by 1424

Abstract

Background: Reduced temporal muscle thickness (TMT) has been discussed as a prognostic marker in IDH-wildtype glioblastoma. This retrospective multicenter study was designed to investigate whether TMT is an independent prognostic marker in newly diagnosed glioblastoma. Methods: TMT was retrospectively measured in 335 patients [...] Read more.

Background: Reduced temporal muscle thickness (TMT) has been discussed as a prognostic marker in IDH-wildtype glioblastoma. This retrospective multicenter study was designed to investigate whether TMT is an independent prognostic marker in newly diagnosed glioblastoma. Methods: TMT was retrospectively measured in 335 patients with newly diagnosed glioblastoma between 1 January 2014 and 31 December 2019 at the University Hospitals of Leipzig and Rostock. The cohort was dichotomized by TMT and tested for association with overall survival (OS) after 12 months by multivariate proportional hazard calculation. Results: TMT of 7.0 mm or more was associated with increased OS (46.3 ± 3.9% versus 36.6 ± 3.9%, p > 0.001). However, the sub-groups showed significant epidemiological differences. In multivariate proportional hazard calculation, patient age (HR 1.01; p = 0.004), MGMT promoter status (HR 0.76; p = 0.002), EOR (HR 0.61), adjuvant irradiation (HR 0.24) and adjuvant chemotherapy (HR 0.40; all p < 0.001) were independent prognostic markers for OS. However, KPS (HR 1.00, p = 0.31), BMI (HR 0.98, p = 0.11) and TMT (HR 1.06; p = 0.07) were not significantly associated with OS. Conclusion: TMT has not appeared as a statistically independent prognostic marker in this cohort of patients with newly diagnosed IDH-wildtype glioblastoma. Full article

(This article belongs to the Special Issue Biomarker in Glioblastoma)

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22 pages, 4827 KiB

Open AccessArticle

Integrative Metabolomics Reveals Deep Tissue and Systemic Metabolic Remodeling in Glioblastoma

by Vianney Gilard, Justine Ferey, Florent Marguet, Maxime Fontanilles, Franklin Ducatez, Carine Pilon, Céline Lesueur, Tony Pereira, Carole Basset, Isabelle Schmitz-Afonso, Frédéric Di Fioré, Annie Laquerrière, Carlos Afonso, Stéphane Derrey, Stéphane Marret, Soumeya Bekri and Abdellah Tebani

Cancers 2021, 13(20), 5157; https://doi.org/10.3390/cancers13205157 - 14 Oct 2021

Cited by 9 | Viewed by 2607

Abstract

(1) Background: Glioblastoma is the most common malignant brain tumor in adults. Its etiology remains unknown in most cases. Glioblastoma pathogenesis consists of a progressive infiltration of the white matter by tumoral cells leading to progressive neurological deficit, epilepsy, and/or intracranial hypertension. The [...] Read more.

(1) Background: Glioblastoma is the most common malignant brain tumor in adults. Its etiology remains unknown in most cases. Glioblastoma pathogenesis consists of a progressive infiltration of the white matter by tumoral cells leading to progressive neurological deficit, epilepsy, and/or intracranial hypertension. The mean survival is between 15 to 17 months. Given this aggressive prognosis, there is an urgent need for a better understanding of the underlying mechanisms of glioblastoma to unveil new diagnostic strategies and therapeutic targets through a deeper understanding of its biology. (2) Methods: To systematically address this issue, we performed targeted and untargeted metabolomics-based investigations on both tissue and plasma samples from patients with glioblastoma. (3) Results: This study revealed 176 differentially expressed lipids and metabolites, 148 in plasma and 28 in tissue samples. Main biochemical classes include phospholipids, acylcarnitines, sphingomyelins, and triacylglycerols. Functional analyses revealed deep metabolic remodeling in glioblastoma lipids and energy substrates, which unveils the major role of lipids in tumor progression by modulating its own environment. (4) Conclusions: Overall, our study demonstrates in situ and systemic metabolic rewiring in glioblastoma that could shed light on its underlying biological plasticity and progression to inform diagnosis and/or therapeutic strategies. Full article

(This article belongs to the Special Issue Biomarker in Glioblastoma)

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17 pages, 3057 KiB

Open AccessArticle

Paliperidone Inhibits Glioblastoma Growth in Mouse Brain Tumor Model and Reduces PD-L1 Expression

by Yu-Shu Liu, Bor-Ren Huang, Ching-Ju Lin, Ching-Kai Shen, Sheng-Wei Lai, Chao-Wei Chen, Hui-Jung Lin, Chia-Huei Lin, Yun-Chen Hsieh and Dah-Yuu Lu

Cancers 2021, 13(17), 4357; https://doi.org/10.3390/cancers13174357 - 28 Aug 2021

Cited by 9 | Viewed by 2753

Abstract

A previous study from our group reported that monocyte adhesion to glioblastoma (GBM) promoted tumor growth and invasion activity and increased tumor-associated macrophages (TAMs) proliferation and inflammatory mediator secretion as well. The present study showed that prescribed psychotropic medicine paliperidone reduced GBM growth [...] Read more.

A previous study from our group reported that monocyte adhesion to glioblastoma (GBM) promoted tumor growth and invasion activity and increased tumor-associated macrophages (TAMs) proliferation and inflammatory mediator secretion as well. The present study showed that prescribed psychotropic medicine paliperidone reduced GBM growth and immune checkpoint protein programmed death ligand (PD-L)1 expression and increased survival in an intracranial xenograft mouse model. An analysis of the database of patients with glioma showed that the levels of PD-L1 and dopamine receptor D (DRD)2 were higher in the GBM group than in the low grade astrocytoma and non-tumor groups. In addition, GFP expressing GBM (GBM-GFP) cells co-cultured with monocytes-differentiated macrophage enhanced PD-L1 expression in GBM cells. The enhancement of PD-L1 in GBM was antagonized by paliperidone and risperidone as well as DRD2 selective inhibitor L741426. The expression of CD206 (M2 phenotype marker) was observed to be markedly increased in bone marrow-derived macrophages (BMDMs) co-cultured with GBM. Importantly, treatment with paliperidone effectively decreased CD206 and also dramatically increased CD80 (M1 phenotype marker) in BMDMs. We have previously established a PD-L1 GBM-GFP cell line that stably expresses PD-L1. Experiments showed that the expressions of CD206 was increased and CD80 was mildly decreased in the BMDMs co-cultured with PD-L1 GBM-GFP cells. On the other hands, knockdown of DRD2 expression in GBM cells dramatically decreased the expression of CD206 but markedly increased CD80 expressions in BMDMs. The present study suggests that DRD2 may be involved in regulating the PD-L1 expression in GBM and the microenvironment of GBM. Our results provide a valuable therapeutic strategy and indicate that treatments combining DRD2 antagonist paliperidone with standard immunotherapy may be beneficial for GBM treatment. Full article

(This article belongs to the Special Issue Biomarker in Glioblastoma)

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25 pages, 9144 KiB

Open AccessArticle

PLEK2, RRM2, GCSH: A Novel WWOX-Dependent Biomarker Triad of Glioblastoma at the Crossroads of Cytoskeleton Reorganization and Metabolism Alterations

by Żaneta Kałuzińska, Damian Kołat, Andrzej K. Bednarek and Elżbieta Płuciennik

Cancers 2021, 13(12), 2955; https://doi.org/10.3390/cancers13122955 - 12 Jun 2021

Cited by 10 | Viewed by 3580

Abstract

Glioblastoma is one of the deadliest human cancers. Its malignancy depends on cytoskeleton reorganization, which is related to, e.g., epithelial-to-mesenchymal transition and metastasis. The malignant phenotype of glioblastoma is also affected by the WWOX gene, which is lost in nearly a quarter of [...] Read more.

Glioblastoma is one of the deadliest human cancers. Its malignancy depends on cytoskeleton reorganization, which is related to, e.g., epithelial-to-mesenchymal transition and metastasis. The malignant phenotype of glioblastoma is also affected by the WWOX gene, which is lost in nearly a quarter of gliomas. Although the role of WWOX in the cytoskeleton rearrangement has been found in neural progenitor cells, its function as a modulator of cytoskeleton in gliomas was not investigated. Therefore, this study aimed to investigate the role of WWOX and its collaborators in cytoskeleton dynamics of glioblastoma. Methodology on RNA-seq data integrated the use of databases, bioinformatics tools, web-based platforms, and machine learning algorithm, and the obtained results were validated through microarray data. PLEK2, RRM2, and GCSH were the most relevant WWOX-dependent genes that could serve as novel biomarkers. Other genes important in the context of cytoskeleton (BMP4, CCL11, CUX2, DUSP7, FAM92B, GRIN2B, HOXA1, HOXA10, KIF20A, NF2, SPOCK1, TTR, UHRF1, and WT1), metabolism (MTHFD2), or correlation with WWOX (COL3A1, KIF20A, RNF141, and RXRG) were also discovered. For the first time, we propose that changes in WWOX expression dictate a myriad of alterations that affect both glioblastoma cytoskeleton and metabolism, rendering new therapeutic possibilities. Full article

(This article belongs to the Special Issue Biomarker in Glioblastoma)

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9 pages, 1050 KiB

Open AccessArticle

An AI-Powered Blood Test to Detect Cancer Using NanoDSF

by Philipp O. Tsvetkov, Rémi Eyraud, Stéphane Ayache, Anton A. Bougaev, Soazig Malesinski, Hamed Benazha, Svetlana Gorokhova, Christophe Buffat, Caroline Dehais, Marc Sanson, Franck Bielle, Dominique Figarella Branger, Olivier Chinot, Emeline Tabouret and François Devred

Cancers 2021, 13(6), 1294; https://doi.org/10.3390/cancers13061294 - 15 Mar 2021

Cited by 9 | Viewed by 11020

Abstract

Glioblastoma is the most frequent and aggressive primary brain tumor. Its diagnosis is based on resection or biopsy that could be especially difficult and dangerous in the case of deep location or patient comorbidities. Monitoring disease evolution and progression also requires repeated biopsies [...] Read more.

Glioblastoma is the most frequent and aggressive primary brain tumor. Its diagnosis is based on resection or biopsy that could be especially difficult and dangerous in the case of deep location or patient comorbidities. Monitoring disease evolution and progression also requires repeated biopsies that are often not feasible. Therefore, there is an urgent need to develop biomarkers to diagnose and follow glioblastoma evolution in a minimally invasive way. In the present study, we described a novel cancer detection method based on plasma denaturation profiles obtained by a non-conventional use of differential scanning fluorimetry. Using blood samples from 84 glioma patients and 63 healthy controls, we showed that their denaturation profiles can be automatically distinguished with the help of machine learning algorithms with 92% accuracy. Proposed high throughput workflow can be applied to any type of cancer and could become a powerful pan-cancer diagnostic and monitoring tool requiring only a simple blood test. Full article

(This article belongs to the Special Issue Biomarker in Glioblastoma)

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