scholarly journals Worse Prognosis for IDH Wild-Type Diffuse Gliomas With Larger Residual Biological Tumor Burden

2021 ◽  
Author(s):  
Hiroyuki Tatekawa ◽  
Hiroyuki Uetani ◽  
Akifumi Hagiwara ◽  
Shadfar Bahri ◽  
Catalina Raymond ◽  
...  
Keyword(s):  
Cox Regression ◽  
Tumor Grade ◽  
Tumor Burden ◽  
Wild Type ◽  
Contrast Enhanced ◽  
Treatment Naïve ◽  
Fluid Attenuated Inversion Recovery ◽  
Diffuse Gliomas ◽  
Grade Ii ◽  
Worse Prognosis

Abstract This study aimed to assess the association between biological tumor burden in pre- and post-operative status and overall survival (OS) in isocitrate dehydrogenase (IDH) wild-type gliomas, and to evaluate which volume was the best predictor of OS. Thirty-four patients with treatment-naïve IDH wild-type gliomas (grade II, 6; III, 15; IV, 13) were retrospectively included. Three pre-operative tumor regions of interest (ROIs) were segmented based on the contrast-enhanced (CE), fluid-attenuated inversion recovery (FLAIR) hyperintense, and 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) hypermetabolic regions. Resected ROIs were segmented from the post-operative images. Residual CE, FLAIR hyperintense, and FDOPA hypermetabolic ROIs were created by subtracting resected ROIs from pre-operative ROIs. Cox regression was conducted to investigate the association of OS with the volume of each ROI. Residual CE volume had a significant association with OS (hazard ratio [HR] = 1.26, P = 0.039), but this effect disappeared when controlling for tumor grade. Residual FDOPA hypermetabolic volume was significantly associated with OS (HR = 1.18, P = 0.008), even when controlling for tumor grade. FLAIR hyperintense volume showed no significant association with OS. Residual FDOPA hypermetabolic burden predicted OS for IDH wild-type gliomas, regardless of tumor grade. Furthermore, removing hypermetabolic and CE regions may improve the prognosis.

scholarly journals Worse prognosis for IDH wild-type diffuse gliomas with larger residual biological tumor burden

2021 ◽  
Author(s):  
Hiroyuki Tatekawa ◽  
Hiroyuki Uetani ◽  
Akifumi Hagiwara ◽  
Shadfar Bahri ◽  
Catalina Raymond ◽  
...  
Keyword(s):  
Tumor Burden ◽  
Wild Type ◽  
Diffuse Gliomas ◽  
Worse Prognosis

scholarly journals RUNX1 and REXO2 are associated with the heterogeneity and prognosis of IDH wild type lower grade glioma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Ji Zhang ◽  
Hua Cao
Keyword(s):  
Transcription Factor ◽  
Low Frequency ◽  
Tumor Grade ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Wild Type ◽  
Lower Grade Glioma ◽  
Cancer Genome Atlas ◽  
Worse Prognosis ◽  
Genome Atlas

AbstractBased on isocitrate dehydrogenase (IDH) alterations, lower grade glioma (LGG) is divided into IDH mutant and wild type subgroups. However, the further classification of IDH wild type LGG was unclear. Here, IDH wild type LGG patients in The Cancer Genome Atlas and Chinese Glioma Genome Atlas were divided into two sub-clusters using non-negative matrix factorization. IDH wild type LGG patients in sub-cluster2 had prolonged overall survival and low frequency of CDKN2A alterations and low immune infiltrations. Differentially expressed genes in sub-cluster1 were positively correlated with RUNX1 transcription factor. Moreover, IDH wild type LGG patients with higher stromal score or immune score were positively correlated with RUNX1 transcription factor. RUNX1 and its target gene REXO2 were up-regulated in sub-cluster1 and associated with the worse prognosis of IDH wild type LGG. RUNX1 and REXO2 were associated with the higher immune infiltrations. Furthermore, RUNX1 and REXO2 were correlated with the worse prognosis of LGG or glioma. IDH wild type LGG in sub-cluster2 was hyper-methylated. REXO2 hyper-methylation was associated with the favorable prognosis of LGG or glioma. At last, we showed that, age, tumor grade and REXO2 expression were independent prognostic factors in IDH wild type LGG.

scholarly journals The Role of Extent of Resection in IDH1 Wild-Type or Mutant Low-Grade Gliomas

Neurosurgery ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. 808-814 ◽  
Author(s):  
Toral Patel ◽  
Evan D Bander ◽  
Rachael A Venn ◽  
Tiffany Powell ◽  
Gustav Young-Min Cederquist ◽  
...  
Keyword(s):  
Cox Regression ◽  
Extent Of Resection ◽  
World Health ◽  
Low Grade ◽  
Wild Type ◽  
Who Grade ◽  
Cox Regression Analysis ◽  
Low Grade Gliomas ◽  
Grade Ii ◽  
The Impact

Abstract BACKGROUND Maximizing extent of resection (EOR) improves outcomes in adults with World Health Organization (WHO) grade II low-grade gliomas (LGG). However, recent studies demonstrate that LGGs bearing a mutation in the isocitrate dehydrogenase 1 (IDH1) gene are a distinct molecular and clinical entity. It remains unclear whether maximizing EOR confers an equivalent clinical benefit in IDH mutated (mtIDH) and IDH wild-type (wtIDH) LGGs. OBJECTIVE To assess the impact of EOR on malignant progression-free survival (MPFS) and overall survival (OS) in mtIDH and wtIDH LGGs. METHODS We performed a retrospective review of 74 patients with WHO grade II gliomas and known IDH mutational status undergoing resection at a single institution. EOR was assessed with quantitative 3-dimensional volumetric analysis. The effect of predictor variables on MPFS and OS was analyzed with Cox regression models and the Kaplan–Meier method. RESULTS Fifty-two (70%) mtIDH patients and 22 (30%) wtIDH patients were included. Median preoperative tumor volume was 37.4 cm3; median EOR of 57.6% was achieved. Univariate Cox regression analysis confirmed EOR as a prognostic factor for the entire cohort. However, stratifying by IDH status demonstrates that greater EOR independently prolonged MPFS and OS for wtIDH patients (hazard ratio [HR] = 0.002 [95% confidence interval {CI} 0.000-0.074] and HR = 0.001 [95% CI 0.00-0.108], respectively), but not for mtIDH patients (HR = 0.84 [95% CI 0.17-4.13] and HR = 2.99 [95% CI 0.15-61.66], respectively). CONCLUSION Increasing EOR confers oncologic and survival benefits in IDH1 wtLGGs, but the impact on IDH1 mtLGGs requires further study.

scholarly journals Factors Associated With Dysfunction of Glymphatic System in Patients With Glioma

2021 ◽  
Vol 11 ◽  
Author(s):  
Cheng Hong Toh ◽  
Tiing Yee Siow
Keyword(s):  
Brain Edema ◽  
Diffusion Tensor ◽  
Tumor Grade ◽  
Wild Type ◽  
Mutation Status ◽  
Factors Associated ◽  
Edema Volume ◽  
Peritumoral Brain Edema ◽  
Grade Ii ◽  
The Alps

ObjectivesRodent experiments have provided some insights into the changes of glymphatic function associated with glioma growth. The diffusion tensor image analysis along the perivascular space (DTI-ALPS) method offers an opportunity for the noninvasive investigation of the glymphatic system in patients with glioma. We aimed to investigate the factors associated with glymphatic function changes in patients with glioma.Materials and MethodsA total of 201 glioma patients (mean age = 47.4 years, 116 men; 86 grade II, 52 grade III, and 63 grade IV) who had preoperative diffusion tensor imaging for calculation of the ALPS index were retrospectively included. Information collected from each patient included sex, age, tumor grade, isocitrate dehydrogenase 1 (IDH1) mutation status, peritumoral brain edema volume, tumor volume, and ALPS index. Group differences in the ALPS index according to sex, tumor grade, and IDH1 mutation status were assessed using analysis of covariance with age adjustment. Linear regression analyses were performed to identify the factors associated with the ALPS index.ResultsGroup comparisons revealed that the ALPS index of grade II/III gliomas was significantly higher than that of grade IV gliomas (p < 0.001). The ALPS index of IDH1 mutant gliomas was significantly higher than that of IDH1 wild-type gliomas (p < 0.001). On multivariable linear regression analysis, IDH1 mutation (β = 0.308, p < 0.001) and peritumoral brain edema volume (β = −0.353, p < 0.001) were the two independent factors associated with the ALPS index.ConclusionIDH1 wild-type gliomas and gliomas with larger peritumoral brain edema volumes were associated with a lower ALPS index, which may reflect impaired glymphatic function.

scholarly journals TERT promoter mutation confers favorable prognosis regardless of 1p/19q status in adult diffuse gliomas with IDH1/2 mutations

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Hideyuki Arita ◽  
Yuko Matsushita ◽  
Ryunosuke Machida ◽  
Kai Yamasaki ◽  
Nobuhiro Hata ◽  
...  
Keyword(s):  
Cox Regression ◽  
Hazard Ratio ◽  
Prognostic Impact ◽  
Promoter Mutation ◽  
Who Grade ◽  
Favorable Prognosis ◽  
Diffuse Gliomas ◽  
Grade Ii ◽  
Promoter Mutations ◽  
The Impact

AbstractTERT promoter mutations are commonly associated with 1p/19q codeletion in IDH-mutated gliomas. However, whether these mutations have an impact on patient survival independent of 1p/19q codeletion is unknown. In this study, we investigated the impact of TERT promoter mutations on survival in IDH-mutated glioma cases. Detailed clinical information and molecular status data were collected for a cohort of 560 adult patients with IDH-mutated gliomas. Among these patients, 279 had both TERT promoter mutation and 1p/19q codeletion, while 30 had either TERT promoter mutation (n = 24) or 1p/19q codeletion (n = 6) alone. A univariable Cox proportional hazard analysis for survival using clinical and genetic factors indicated that a Karnofsky performance status score (KPS) of 90 or 100, WHO grade II or III, TERT promoter mutation, 1p/19q codeletion, radiation therapy, and extent of resection (90–100%) were associated with favorable prognosis (p < 0.05). A multivariable Cox regression model revealed that TERT promoter mutation had a significantly favorable prognostic impact (hazard ratio = 0.421, p = 0.049), while 1p/19q codeletion did not have a significant impact (hazard ratio = 0.648, p = 0.349). Analyses incorporating patient clinical and genetic information were further conducted to identify subgroups showing the favorable prognostic impact of TERT promoter mutation. Among the grade II-III glioma patients with a KPS score of 90 or 100, those with IDH-TERT co-mutation and intact 1p/19q (n = 17) showed significantly longer survival than those with IDH mutation, wild-type TERT, and intact 1p/19q (n = 185) (5-year overall survival, 94% and 77%, respectively; p = 0.032). Our results demonstrate that TERT promoter mutation predicts favorable prognosis independent of 1p/19q codeletion in IDH-mutated gliomas. Combined with its adverse effect on survival among IDH-wild glioma cases, the bivalent prognostic impact of TERT promoter mutation may help further refine the molecular diagnosis and prognostication of diffuse gliomas.

scholarly journals Better  efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist’s reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images

2020 ◽  
Author(s):  
Sha-Sha Zhao ◽  
Xiu-Long Feng ◽  
Yu-Chuan Hu ◽  
Yu Han ◽  
Qiang Tian ◽  
...  
Keyword(s):  
Machine Learning ◽  
Inversion Recovery ◽  
World Health ◽  
Diagnostic Efficacy ◽  
Who Grade ◽  
Superior Efficacy ◽  
Contrast Enhanced ◽  
Fluid Attenuated Inversion Recovery ◽  
T1 Contrast ◽  
Grade Ii

Abstract Abstract Background: The medical imaging to differentiate World Health Organization (WHO) grade II (ODG2) from III (ODG3) oligodendrogliomas still remains a challenge. We investigated whether combination of machine leaning with radiomics from conventional T1 contrast-enhanced (T1CE) and fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) offered superior efficacy. Methods: Thirty-six patients with histologically confirmed ODGs underwent T1CE and 33 of them underwent FLAIR MR examination before any intervention from January 2015 to July 2017 were retrospectively recruited in the current study. The volume of interest (VOI) covering the whole tumor enhancement were manually drawn on the T1CE and FLAIR slice by slice using ITK-SNAP and a total of 1072 features were extracted from the VOI using 3-D slicer software. Random forest (RF) algorithm was applied to differentiate ODG2 from ODG3 and the efficacy was tested with 5-fold cross validation. The diagnostic efficacy of radiomics-based machine learning and radiologist’s assessment were also compared. Results: Nineteen ODG2 and 17 ODG3 were included in this study and ODG3 tended to present with prominent necrosis and nodular/ring-like enhancement (P < 0.05). The AUC, ACC, sensitivity, and specificity of radiomics were 0.798, 0.735, 0.672, 0.789 for T1CE, 0.774, 0.689, 0.700, 0.683 for FLAIR, as well as 0.861, 0.781, 0.778, 0.783 for the combination, respectively. The AUCs of radiologists 1, 2 and 3 were 0.700, 0.687, and 0.714, respectively. The efficacy of machine learning based on radiomics was superior to the radiologists' assessment. Conclusions: Machine-learning based on radiomics of T1CE and FLAIR offered superior efficacy to that of radiologists in differentiating ODG2 from ODG3.

scholarly journals Better  efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist’s reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images

2020 ◽  
Author(s):  
Sha-Sha Zhao ◽  
Xiu-Long Feng ◽  
Yu-Chuan Hu ◽  
Yu Han ◽  
Qiang Tian ◽  
...  
Keyword(s):  
Machine Learning ◽  
Inversion Recovery ◽  
World Health ◽  
Diagnostic Efficacy ◽  
Who Grade ◽  
Superior Efficacy ◽  
Contrast Enhanced ◽  
Fluid Attenuated Inversion Recovery ◽  
T1 Contrast ◽  
Grade Ii

Abstract Background: The medical imaging to differentiate World Health Organization (WHO) grade II (ODG2) from III (ODG3) oligodendrogliomas still remains a challenge. We investigated whether combination of machine leaning with radiomics from conventional T1 contrast-enhanced (T1CE) and fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) offered superior efficacy. Methods: Thirty-six patients with histologically confirmed ODGs underwent T1CE and 33 of them underwent FLAIR MR examination before any intervention from January 2015 to July 2017 were retrospectively recruited in the current study. The volume of interest (VOI) covering the whole tumor enhancement were manually drawn on the T1CE and FLAIR slice by slice using ITK-SNAP and a total of 1072 features were extracted from the VOI using 3-D slicer software. Random forest (RF) algorithm was applied to differentiate ODG2 from ODG3 and the efficacy was tested with 5-fold cross validation. The diagnostic efficacy of radiomics-based machine learning and radiologist’s assessment were also compared. Results: Nineteen ODG2 and 17 ODG3 were included in this study and ODG3 tended to present with prominent necrosis and nodular/ring-like enhancement (P < 0.05). The AUC, ACC, sensitivity, and specificity of radiomics were 0.798, 0.735, 0.672, 0.789 for T1CE, 0.774, 0.689, 0.700, 0.683 for FLAIR, as well as 0.861, 0.781, 0.778, 0.783 for the combination, respectively. The AUCs of radiologists 1, 2 and 3 were 0.700, 0.687, and 0.714, respectively. The efficacy of machine learning based on radiomics was superior to the radiologists' assessment. Conclusions: Machine-learning based on radiomics of T1CE and FLAIR offered superior efficacy to that of radiologists in differentiating ODG2 from ODG3.

scholarly journals Better efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist’s reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery imagines

2019 ◽  
Author(s):  
Sha-Sha Zhao ◽  
Xiu-Long Feng ◽  
Yu-Chuan Hu ◽  
Yu Han ◽  
Qiang Tian ◽  
...  
Keyword(s):  
Machine Learning ◽  
Inversion Recovery ◽  
World Health ◽  
Diagnostic Efficacy ◽  
Who Grade ◽  
Superior Efficacy ◽  
Contrast Enhanced ◽  
Fluid Attenuated Inversion Recovery ◽  
T1 Contrast ◽  
Grade Ii

Abstract Background: The medical imaging to differentiate World Health Organization (WHO) grade II (ODG2) from III (ODG3) oligodendrogliomas still remains a challenge. We investigated whether combination of machine leaning with radiomics from conventional T1 contrast-enhanced (T1CE) and fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) offered superior efficacy. Methods: Thirty-six patients with histologically confirmed ODGs underwent T1CE and 33 of them underwent FLAIR MR examination before any intervention from January 2015 to July 2017 were retrospectively recruited in the current study. The volume of interest (VOI) covering the whole tumor enhancement were manually drawn on the T1CE and FLAIR slice by slice using ITK-SNAP and a total of 1072 features were extracted from the VOI using 3-D slicer software. Random forest (RF) algorithm was applied to differentiate ODG2 from ODG3 and the efficacy was tested with 5-fold cross validation. The diagnostic efficacy of radiomics-based machine learning and radiologist’s assessment were also compared. Results: Nineteen ODG2 and 17 ODG3 were included in this study and ODG3 tended to present with prominent necrosis and nodular/ring-like enhancement (P < 0.05). The AUC, ACC, sensitivity, and specificity of radiomics were 0.798, 0.735, 0.672, 0.789 for T1CE, 0.774, 0.689, 0.700, 0.683 for FLAIR, as well as 0.861, 0.781, 0.778, 0.783 for the combination, respectively. The AUCs of radiologists 1, 2 and 3 were 0.700, 0.687, and 0.714, respectively. The efficacy of machine learning based on radiomics was superior to the radiologists' assessment. Conclusions: Machine-learning based on radiomics of T1CE and FLAIR offered superior efficacy to that of radiologists in differentiating ODG2 from ODG3.

IDH1 status and survival benefit from surgical resection of enhancing and nonenhancing tumor in malignant astrocytomas.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 2019-2019 ◽  
Author(s):  
Daniel P. Cahill ◽  
Jason Beiko ◽  
Dima Suki ◽  
Sujit S. Prabhu ◽  
Jeffrey Weinberg ◽  
...  
Keyword(s):  
Surgical Resection ◽  
Survival Benefit ◽  
Tumor Grade ◽  
Tumor Burden ◽  
Prognostic Impact ◽  
Karnofsky Performance Score ◽  
Wild Type ◽  
Who Grade ◽  
Malignant Astrocytomas ◽  
Astrocytic Gliomas

2019 Background: The value of maximal safe resection for malignant astrocytic gliomas (AA, WHO Grade III anaplastic astrocytoma and GBM, WHO Grade IV glioblastoma) has sometimes been controversial, because of confounding between measures of surgical resection and other prognostic factors. IDH1 gene mutations are associated with improved survival in glioma patients, and are thought to identify tumors with a distinct molecular evolutionary origin. We sought to determine the prognostic impact of surgical resection on survival after controlling for IDH1 status in malignant astrocytomas. Methods: Clinical parameters including preoperative and postoperative MRI-based tumor volume were recorded prospectively on 407 malignant astrocytoma patients – AA (n=157) and GBM (n=250). IDH1 status was assessed by sequencing and R132H-specific immunohistochemistry. Results: The measures of surgical resection associated with longer survival differed between IDH1 wild-type and mutant tumors. In multivariate analyses of IDH1 wild-type tumors (controlling for age, Karnofsky performance score, tumor location, and tumor grade), residual postoperative enhancement was associated with a median survival of 9.9 mo vs. 17.4 mo with no enhancement (HR=1.73, 95% CI, 1.19-2.52, p=.004). Residual non-enhancing disease, however, was not associated with survival (scored as continuous volumetric cc, 95% CI 0.99-1.01, p=.608). These results are consistent with prior studies of GBM, which are largely IDH1 wild-type lesions (Lacroix et al., J Neurosurg 95:190-8, 2001). In contrast, in IDH1 mutant tumors, both residual enhancing (HR=7.93, 95%CI 1.14-55.22, p=.037) and non-enhancing (HR=1.03, 95% CI 1.01-1.05, p=.005) postoperative tumor burden were associated with worse survival. Conclusions: These data suggest surgical resection in malignant astrocytic gliomas may be individualized based on IDH1 genotype. IDH1 mutant tumors have a better baseline overall prognosis, therefore more aggressive surgery and tolerance of temporary peri-operative neurologic deficits can be weighed in an attempt to gain the additional survival benefit that appears to be associated with reducing non-enhancing tumor burden.

Co-existance of KRAS and LKB1 mutation as predictor of resistance to Erlotinib: Customized next-generation sequencing (NGS) of TAILOR trial.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e20631-e20631
Author(s):  
Eliana Rulli ◽  
Mara Serena Serafini ◽  
Mirko Marabese ◽  
Elisa Caiola ◽  
Gabriella Sozzi ◽  
...  
Keyword(s):  
Predictive Value ◽  
Kras Mutation ◽  
Cox Regression ◽  
Cell Metabolism ◽  
Future Research ◽  
Wild Type ◽  
Cox Regression Analysis ◽  
Mutational Status ◽  
Key Factor ◽  
Worse Prognosis

e20631 Background: The prognostic and predictive value of KRAS mutation in advanced NSCLC is still debatable. In TAILOR (NCT00637910) trial EGFR wild-type patients were randomized to receive 2nd line erlotinib versus docetaxel, and no interaction was detected according to KRAS mutational status. Recent evidences indicate that the concurrent mutation of KRAS and LKB1 (key factor for cell metabolism) may be associated with worse prognosis. Methods: Availableformalin-fixed embeddedtissue samples with annotated clinical data from TAILOR were gathered. Customized deep sequencing (Ion proton Technology) of 111 genes most frequently associated with cancer, was performed; 5% of frequency was used to identify mutations. Association between genes and clinical features was performed with non-parametric tests; Cox regression analysis was used to assess the prognostic and predictive value of LKB1. Results: 123 out of 222 (55%) randomized patients had available tissue and were successfully sequenced. 42/123 (34%) patients had a KRAS mutation. KRAS and LKB1 mutations were found in 11/42 (26%) KRAS patients, while only 6 patients had a LKB1 mutation without KRAS. The presence of a concurrent KRAS-LKB1 mutation did not adversely influence progression-free (PFS) or overall (OS) survival [hazard ratio (HR) PFS 1.08, 95% confidence interval (CI) 0.57-2.05, P = 0.81; OS 1.09, 95% CI 0.56-2.14, P = 0.78]. Patients receiving docetaxel experienced longer survival regardless of the KRAS-LKB1 mutational status (mutated KRAS-LKB1 HR 0.42, 95% CI 0.08-2.29; wild-type KRAS-LKB1 HR 1.16, 95% CI 0.72-1.87, P = 0.55; interaction P = 0.10). Conclusions: Although the significant attrition and the limited number, these data generate the hypothesis that the concurrent mutation of KRAS and LKB1 may potentially be associated with resistance to erlotinib. Overall, the coexistence of mutation in KRAS and LKB1 is not associated with worse prognosis in NSCLC. For these patients refractory to EGFR targeting, metabolic strategies represent a future research opportunity.

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