Analysis of IDH mutation, 1p/19q deletion, and PTEN loss delineates prognosis in clinical low-grade diffuse gliomas

Brain tumors, such as low grade gliomas (LGG), are molecularly classified which require the surgical collection of tissue samples. The pre-surgical or non-operative identification of LGG molecular type could improve patient counseling and treatment decisions. However, radiographic approaches to LGG molecular classification are currently lacking, as clinicians are unable to reliably predict LGG molecular type using magnetic resonance imaging (MRI) studies. Machine learning approaches may improve the prediction of LGG molecular classification through MRI, however, the development of these techniques requires large annotated data sets. Merging clinical data from different hospitals to increase case numbers is needed, but the use of different scanners and settings can affect the results and simply combining them into a large dataset often have a significant negative impact on performance. This calls for efficient domain adaption methods. Despite some previous studies on domain adaptations, mapping MR images from different datasets to a common domain without affecting subtitle molecular-biomarker information has not been reported yet. In this paper, we propose an effective domain adaptation method based on Cycle Generative Adversarial Network (CycleGAN). The dataset is further enlarged by augmenting more MRIs using another GAN approach. Further, to tackle the issue of brain tumor segmentation that requires time and anatomical expertise to put exact boundary around the tumor, we have used a tight bounding box as a strategy. Finally, an efficient deep feature learning method, multi-stream convolutional autoencoder (CAE) and feature fusion, is proposed for the prediction of molecular subtypes (1p/19q-codeletion and IDH mutation). The experiments were conducted on a total of 161 patients consisting of FLAIR and T1 weighted with contrast enhanced (T1ce) MRIs from two different institutions in the USA and France. The proposed scheme is shown to achieve the test accuracy of 74 . 81 % on 1p/19q codeletion and 81 . 19 % on IDH mutation, with marked improvement over the results obtained without domain mapping. This approach is also shown to have comparable performance to several state-of-the-art methods.

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P04.14 Loss of oligodendroglial features at recurrence in five diffuse low-grade glioma patients treated with repeated surgery

Neuro-Oncology ◽

10.1093/neuonc/noz126.109 ◽

2019 ◽

Vol 21 (Supplement_3) ◽

pp. iii31-iii32

Author(s):

A Darlix ◽

H Duffau ◽

V Rigau ◽

C Gozé

Keyword(s):

Tumor Volume ◽

Biological Data ◽

Low Grade ◽

Idh Mutation ◽

Genetic Analyses ◽

Continuous Growth ◽

1P19q Codeletion ◽

Tert Promoter ◽

Second Surgery ◽

Repeated Surgery

Abstract BACKGROUND Diffuse low-grade gliomas (DLGG) are characterized by a continuous growth and an unavoidable anaplastic transformation. IDH mutation and 1p19q codeletion have been integrated to the 2016 WHO classification to define the oligodendroglioma entity. Whenever feasible, neurosurgical resection is the first treatment option. At recurrence, a second surgical resection is proposed in selected cases. The consistency of molecular patterns (IDH mutation, 1p19q codeletion) at recurrence has been poorly studied in DLGG. MATERIAL AND METHODS We conducted a retrospective study on consecutive DLGG patients treated at our institution with repeated surgery (2006–2017). Clinical and biological data were collected for both the initial and subsequent surgery. Additional immunohistochemistry (including tumor morphology, ATRX and p53) and genetic analyses (TERT promoter mutation, CIC mutation, CGHa) were also performed on tumors with joint loss of IDH mutation and of 1p19q codeletion at recurrence. RESULTS A total of 71 patients were identified. Analyses were carried out on 56 patients (molecular data missing: n=15). Nine patients (16.1%) presented with a loss of their IDH mutation at second surgery. Five of them (8.9%) had an additional loss of their 1p19q codeletion. These five cases (3 men, median age 36.6 years) were all treated with surgery as the first oncological treatment. The first surgery revealed in all cases tumors with morphological oligodendroglial features, IDH mutation and 1p19q codeletion. Further molecular analysis strengthened the diagnosis of oligodendroglioma (TERT promoter and CIC mutations, no ATRX loss, no expression of p53). Four patients were followed-up after the first surgery; one patient received Temozolomide 14 months later due to FLAIR tumor volume growth. Because of the regrowth of the residual FLAIR tumor volume, a second surgery was performed in all patients, after a median time of 38.9 months. The morphological oligodendroglial features were lost, and the genetic analyses revealed in all cases no IDH mutation, no 1p19q codeletion, no ATRX loss and no expression of p53. No evidence of anaplasia was found histologically or by CGHa analysis in these recurrent tumors. CONCLUSION We describe five DLGG patients with a shared histo-molecular evolution characterized by the loss of the initial IDH mutation and of oligodendroglial features at second surgery. While rare, this possible evolution must be acknowledged as it can impact the subsequent therapeutic strategy. This observation is the first of a loss of founder alterations in DLGG genesis (i.e. IDH mutation and 1p19q codeletion); the involved mechanism likely differs from the previously described oligoclonal selection caused by spontaneous tumor genetic drift and/or pressure of chemotherapy, and could be linked with the Darwinian selection of a subpopulation of tumor cells after the first surgery.

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Molecular Alterations in Pediatric Low-Grade Gliomas That Led to Death

Journal of Neuropathology & Experimental Neurology ◽

10.1093/jnen/nlab097 ◽

2021 ◽

Author(s):

Jared T Ahrendsen ◽

Claire Sinai ◽

David M Meredith ◽

Seth W Malinowski ◽

Tabitha M Cooney ◽

...

Keyword(s):

Braf V600e ◽

Molecular Characteristics ◽

Low Grade ◽

Diffuse Astrocytoma ◽

Term Survival ◽

Pten Loss ◽

Low Grade Gliomas ◽

Molecular Alterations ◽

Idh1 R132h ◽

Poor Outcomes

Abstract Pediatric low-grade gliomas (PLGGs) have excellent long-term survival, but death can occasionally occur. We reviewed all PLGG-related deaths between 1975 and 2019 at our institution: 48 patients were identified; clinical data and histology were reviewed; targeted exome sequencing was performed on available material. The median age at diagnosis was 5.2 years (0.4–23.4 years), at death was 13.0 years (1.9–43.2 years), and the overall survival was 7.2 years (0.0–33.3 years). Tumors were located throughout CNS, but predominantly in the diencephalon. Diagnoses included low-grade glioma, not otherwise specified (n = 25), pilocytic astrocytoma (n = 15), diffuse astrocytoma (n = 3), ganglioglioma (n = 3), and pilomyxoid astrocytoma (n = 2). Recurrence occurred in 42/48 cases, whereas progression occurred in 10. The cause of death was direct tumor involvement in 31/48 cases. Recurrent drivers included KIAA1549-BRAF (n = 13), BRAF(V600E) (n = 3), NF1 mutation (n = 3), EGFR mutation (n = 3), and FGFR1-TACC1 fusion (n = 2). Single cases were identified with IDH1(R132H), FGFR1(K656E), FGFR1 ITD, FGFR3 gain, PDGFRA amplification, and mismatch repair alteration. CDKN2A/B, CDKN2C, and PTEN loss was recurrent. Patients who received only chemotherapy had worse survival compared with patients who received radiation and chemotherapy. This study demonstrates that PLGG that led to death have diverse molecular characteristics. Location and co-occurring molecular alterations with malignant potential can predict poor outcomes.

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Classification of Brain Tumor IDH Status using MRI and Deep Learning

10.1101/757344 ◽

2019 ◽

Author(s):

Sahil Nalawade ◽

Gowtham Murugesan ◽

Maryam Vejdani-Jahromi ◽

Ryan A. Fisicaro ◽

Chandan Ganesh Bangalore Yogananda ◽

...

Keyword(s):

Deep Learning ◽

Classification Accuracy ◽

Test Accuracy ◽

Low Grade ◽

Idh Mutation ◽

Validation Data ◽

Mutation Status ◽

Radiologic Imaging ◽

Address Data

AbstractIsocitrate dehydrogenase (IDH) mutation status is an important marker in glioma diagnosis and therapy. We propose a novel automated pipeline for predicting IDH status noninvasively using deep learning and T2-weighted (T2w) MR images with minimal preprocessing (N4 bias correction and normalization to zero mean and unit variance). T2w MRI and genomic data were obtained from The Cancer Imaging Archive dataset (TCIA) for 260 subjects (120 High grade and 140 Low grade gliomas). A fully automated 2D densely connected model was trained to classify IDH mutation status on 208 subjects and tested on another held-out set of 52 subjects, using 5-fold cross validation. Data leakage was avoided by ensuring subject separation during the slice-wise randomization. Mean classification accuracy of 90.5% was achieved for each axial slice in predicting the three classes of no tumor, IDH mutated and IDH wild-type. Test accuracy of 83.8% was achieved in predicting IDH mutation status for individual subjects on the test dataset of 52 subjects. We demonstrate a deep learning method to predict IDH mutation status using T2w MRI alone. Radiologic imaging studies using deep learning methods must address data leakage (subject duplication) in the randomization process to avoid upward bias in the reported classification accuracy.

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PATH-26. EVALUATING THE DISTRIBUTION AND PROGNOSIS OF IMMUNE CELL SIGNATURES OF THE TUMOR MICRO-ENVIRONMENT IN DIFFUSE GLIOMAS

Neuro-Oncology ◽

10.1093/neuonc/noab196.478 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi120-vi120

Author(s):

Bharati Mehani ◽

Saleembhasha Asanigari ◽

Hye-Jung Chung ◽

Kenneth Aldape

Keyword(s):

Gene Expression ◽

Single Cell ◽

Immune Cell ◽

Tumor Grade ◽

Cell Types ◽

Idh Mutation ◽

Mutation Status ◽

Cluster Analyses ◽

Diffuse Gliomas ◽

Cell Expression

Abstract The tumor micro-environment (TME) plays an important role in the biology of cancer, including gliomas. Single cell studies have highlighted the role of specific TME components in gliomas, and the methods to deconvolve bulk profiling data may serve to complement these studies on clinically annotated tumors. In this study, we estimated cell type proportions in 3 large glioma datasets (TCGA, CGGA-325, CGGA-693) using CIBERSORTx. Using a signature matrix comprising 22 immune cell types, we identified IDH mutation status-specific immune cell distributions and found that the proportions of 10 cell types were significantly different between IDHmut and IDHwt tumors across the 3 datasets. Looking further within IDHmut tumors, we found that monocytes were enriched in 1p/19q non-co-deleted tumors across the 3 glioma datasets, consistent with prior single cell studies. We then examined estimated gene expression among immune cell types relative to IDH mutation status and found clear separation of gene expression in 15 of 22 cell types in all 3 datasets. When we applied these 22 gene expression signatures in each tumor sample onto cluster-of-cluster analyses to identify tumor groups with distinct immune signature patterns, we found that samples were distributed largely according to the IDH status in all 3 datasets, confirming that immune cell expression is distinct based on IDH status. Among IDH-specific groups, cluster-of-cluster analyses showed that immune cell-based cluster groups had distinct survival outcomes, and that IDHwt samples were distributed significantly based on tumor grades as well as based on EGFR overexpression. Among IDHmut tumors, the distributions of tumor grade and 1p/19q co-deletion status were significantly different in the immune-based clusters in 2 of the 3 datasets examined. Overall, these results highlight the biological and clinical significance of the immune cell environment in gliomas, including distinctions based on IDH mutation status as well as prognosis within IDH-specific groups.

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Low grade glioma patients with IDH mutation and 1p19q codeletion: What to do after surgery?

Annals of Oncology ◽

10.1093/annonc/mdx366.003 ◽

2017 ◽

Vol 28 ◽

pp. v110

Author(s):

E. Franceschi ◽

A. Mura ◽

A. Mandrioli ◽

S. Minichillo ◽

A. Tosoni ◽

...

Keyword(s):

Low Grade Glioma ◽

Low Grade ◽

Idh Mutation ◽

1P19q Codeletion

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P10.21 2-hydroxyglutarate as a biomarker for IDH mutation in low grade gliomas

Neuro-Oncology ◽

10.1093/neuonc/nox036.339 ◽

2017 ◽

Vol 19 (suppl_3) ◽

pp. iii89-iii90

Author(s):

R. Nejad ◽

H. Sim ◽

K. Aldape ◽

W. Mason ◽

M. Bernstein ◽

...

Keyword(s):

Low Grade ◽

Idh Mutation ◽

Low Grade Gliomas

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WP1-18 Risk factors and patterns of recurrence of low grade glioma: a systematic review

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2019-abn.19 ◽

2019 ◽

Vol 90 (3) ◽

pp. e6.3-e6

Author(s):

V Narbad ◽

JP Lavrador ◽

A Elhag ◽

S Acharya ◽

J Hanrahan ◽

...

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Tp53 Mutation ◽

Methylation Status ◽

Low Grade Glioma ◽

Low Grade ◽

Diffuse Glioma ◽

Idh Mutation ◽

Mgmt Methylation ◽

Inclusion Criteria

ObjectivesTo review the risk factors and patterns of progression/recurrence of low grade glioma (LGG).DesignSystematic review of the published literature.SubjectsInclusion criteria were peer reviewed publications of cohort studies of recurrent/progressive LGG. Studies of wider populations were included if relevant LGG data could be analysed separately.MethodsMedline and Cochrane databases were searched using MeSH and non-MeSH terms, including ‘glioma’, ‘astrocytoma’, ‘oligoastrocytoma’, ‘diffuse glioma’, ‘oligodendroglioma’, ‘low grade’ and ‘disease recurrence’ by two independent reviewers.ResultsOverall, 917 studies were screened, of which 57 studies met the inclusion criteria. The most frequently described risk factor for recurrent LGG was suboptimal extent of resection (EOR) of the initial tumour (in 20 studies); recurrence was also associated with the patient’s age (2), tumour location (4), neurological status (3), tumour volume (6), bihemispherical tumour (3) and astrocytic histology (6). IDH mutation was associated with recurrence in 1 out of 3 studies, but TP53 mutation (2 of 4) and MGMT methylation status (4) were not. Malignant transformation was associated with TP53 mutations (3), IDH mutation (1) and EOR (1). Favourable progression free survival (PFS) and/or overall survival (OS) were associated with greater EOR (16), oligodendroglioma histology (2 of 4), initial KPS (3) and the use of adjuvant therapies (9 of 14). IDH mutation was associated with improved PFS and OS (3 of 4). TP53 mutation improved PFS in 1 of 3 studies. MGMT methylation and 1 p/19q codeletion may predict treatment response but their effects on survival are unclear.ConclusionsAstrocytoma histology, IDH and TP53 mutation statuses and surgical treatment (EOR) are essential in determining the time to recurrence or progression in LGG.

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Low grade glioma patients with IDH mutation and 1p19q codeletion: To treat or not to treat?

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.2017 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 2017-2017 ◽

Cited By ~ 1

Author(s):

Enrico Franceschi ◽

Dario De Biase ◽

Alexandro Paccapelo ◽

Antonella Mura ◽

Alicia Tosoni ◽

...

Keyword(s):

Extent Of Resection ◽

Low Grade ◽

Incomplete Resection ◽

Idh Mutation ◽

1P19q Codeletion ◽

Formalin Fixed Paraffin ◽

Formalin Fixed Paraffin Embedded ◽

Surgical Treatments

2017 Background: Molecular characterization of low grade gliomas (LGG) is essential for diagnosis and treatment of these diseases. LGG patients (pts) with IDH mutation and 1p19q codeletion (codel) are characterized by a median OS (mOS) longer than 10 years. Thus, the role of treatments and side effects should be carefully evaluated. Methods: We evaluated LGG pts from our data warehouse (n=679 pts) who received surgery and had sufficient tissue to assess biomarkers characterization. Pts with gliomatosis were excluded. IDH1/2 assessment was performed on formalin-fixed paraffin-embedded samples by qPCR. In wild type cases we performed NGS. 1p/19 codel analysis was performed by FISH. Results: 93 consecutive LGG with IDH mutation and codel were included. The median follow up (FU) was 96.1 months. Mean age was 40 yrs (range: 25-66); 8 pts (8.6%) underwent biopsy, 61 pts (65.6%) partial resection, 24 pts (25.8%) complete resection. 84 pts (90.3%) were considered high risk using RTOG criteria (>40 years and/or incomplete resection). Fifty pts (53.7%) received only FU, 17 pts (18.3%) received chemotherapy (CT), 18 pts (19.4%) received radiotherapy (RT), 8 pts (8.6%) received RT + CT. Median PFS (mPFS) was 59.6 months (95%CI: 41.8-77.4) and was significantly longer in pts who received postsurgical treatments (79.5 months, 95%CI: 66.4-92.7) than pts who received FU (46.3 months, 95%CI: 36.0-56.5; P=0.001). mPFS was 50.8 months (95%CI: 17.4-84.3), 103.6 months (95%CI: 11.7-195.6) and 120.2 months (95%CI: 40.5-199.8) in pts treated with CT alone, RT alone and RT + CT, respectively. Multivariate analysis showed that receiving a post-surgical treatment (P<0.001), and the extent of resection (P=0.043) were significantly correlated with PFS. Conclusions: Our study evaluated the role of treatments in LGG pts assessed with NGS and FISH. Post-surgical treatments are crucial to extend PFS in pts with IDH mutation and codel. The choice of post-surgical treatments seems to have a role, being CT alone less effective than RT and RT+CT. Longer FU is needed to provide information about OS.

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