Neurooncology

Medulloblastoma classification

Medulloblastoma classification

In the 5th edition of the WHO classification, medulloblastomas, which are representative pediatric brain tumors, are categorized into four groups: WNT, SHH-TP53 wild, SHH-TP53 mutant, and non-WNT/non-SHH, based on their molecular background. While the histopathological findings still hold importance in predicting prognosis, the histopathological classification is no longer utilized in this edition. SHH medulloblastomas are further subdivided into two groups based on the presence or absence of TP53 mutation, as their clinical characteristics and prognosis differ. Group 3 and Group 4 medulloblastomas, recognized as distinct molecular groups in clinical practice, are combined into a single group called “non-WNT/non-SHH”, because they lack specific molecular pathway activation. Furthermore, based on methylation profiling, dividing SHH medulloblastoma into four subgroups and non-WNT/non-SHH medulloblastoma into eight subgroups was proposed. Understanding the unique clinical characteristics and prognosis associated with each group is crucial. However, it is important to acknowledge that our current understanding of prognosis is based on treatment approaches guided by clinical risk factors such as postoperative residual tumor volume and the presence of metastatic disease. This molecular-based classification holds promise in guiding the development of optimal treatment strategies for patients with medulloblastoma 1).

Nomenclature

The nomenclature and classification of medulloblastomas are rapidly evolving.

Medulloblastomas, molecularly defined

Medulloblastoma, WNT-activated

Medulloblastoma, SHH-activated and TP53-wildtype

Medulloblastoma, SHH-activated and TP53-mutant

Medulloblastoma non-WNT/non-SSH

In the World Health Organization Classification of Tumors of the Central Nervous System 2021, Group 3 medulloblastoma and group 4 medulloblastomas are grouped together under Medulloblastoma non-WNT/non-SSH, which is in turn divided into 8 subgroups.

Group 3 medulloblastoma

Group 3 medulloblastoma

Group 4 medulloblastoma

Group 4 medulloblastoma.

Misclassification between groups 3 and 4 is common. To address this issue, an AI-based R package called MBMethPred was developed based on DNA methylation and gene expression profiles of 763 medulloblastoma samples to classify subgroups using machine learning and neural network models. The developed prediction models achieved a classification accuracy of over 96% for subgroup classification by using 399 CpGs as prediction biomarkers. We also assessed the prognostic relevance of prediction biomarkers using survival analysis. Furthermore, we identified subgroup-specific drivers of medulloblastoma using functional enrichment analysis, Shapley values, and gene network analysis. In particular, the genes involved in the nervous system development process have the potential to separate medulloblastoma subgroups with 99% accuracy. Notably, our analysis identified 16 genes that were specifically significant for subgroup classification, including EP300, CXCR4, WNT4, ZIC4, MEIS1, SLC8A1, NFASC, ASCL2, KIF5C, SYNGAP1, SEMA4F, ROR1, DPYSL4, ARTN, RTN4RL1, and TLX2. Our findings contribute to enhanced survival outcomes for patients with medulloblastoma. Continued research and validation efforts are needed to further refine and expand the utility of our approach in other cancer types, advancing personalized medicine in pediatric oncology 2)

Standard-Risk Medulloblastoma

Tumor Resection Rate: Patients with standard-risk medulloblastoma typically have a high rate of tumor resection. This means that during surgery, the neurosurgeon was able to remove a significant portion of the tumor from the brain. Metastasis: Standard-risk patients usually do not have evidence of metastasis, which means that the cancer cells have not spread from the primary tumor site in the cerebellum to other parts of the central nervous system (CNS) or outside the CNS.

High-Risk Medulloblastoma

Tumor Resection Rate: Patients with high-risk medulloblastoma often have a lower rate of tumor resection. This indicates that during surgery, it may have been challenging to remove the tumor completely, and some cancerous tissue might remain.

Metastasis: High-risk patients typically have evidence of metastasis. This means that the cancer cells have spread from the primary tumor site in the cerebellum to other areas within the CNS or even outside the CNS, such as the spinal cord or other parts of the body. The classification into standard-risk and high-risk categories is essential for treatment planning and prognosis assessment. Patients with standard-risk medulloblastoma may have a more favorable prognosis because of the higher likelihood of complete tumor removal and the absence of metastasis. In contrast, high-risk patients may face a more challenging treatment course and potentially a poorer prognosis due to the presence of metastasis and the difficulty in achieving complete tumor resection.

It’s important to note that treatment approaches for these two risk groups may differ, with high-risk patients typically receiving more intensive therapies to address the increased complexity and aggressiveness of their disease. Additionally, advances in molecular and genetic profiling have led to further subclassifications within medulloblastoma, providing a more nuanced understanding of the disease and guiding personalized treatment decisions.

EpiGe-App

EpiGe

The diagnosis of medulloblastoma incorporates the histologic and molecular subclassification of clinical medulloblastoma samples into wingless (WNT)-activated, sonic hedgehog (SHH)-activated, group 3 and group 4 subgroups. Accurate medulloblastoma subclassification has important prognostic and treatment implications.

Harmony alignment reveals novel MB subgroup/subtype-associated subpopulations that recapitulate neurodevelopmental processes, including photoreceptor and glutamatergic neuron-like cells in molecular subgroups GP3 and GP4, and a specific nodule-associated neuronally-differentiated subpopulation in subgroup molecular SHH. Riemondy et al. definitively chart the spectrum of MB immune cell infiltrates, which include subpopulations that recapitulate developmentally-related neuron-pruning and antigen presenting myeloid cells. MB cellular diversity matching human samples is mirrored in subgroup-specific mouse models of MB 3)

Medulloblastoma, WNT-activated

Medulloblastoma, WNT-activated

Sonic hedgehog medulloblastoma

Sonic hedgehog medulloblastoma.

Medulloblastoma, SHH-activated

Medulloblastoma, SHH-activated

Medulloblastoma, non-WNT/non-SSH

Medulloblastoma non-WNT/non-SSH

Histology

Medulloblastoma histologically defined:

Classic medulloblastoma

Desmoplastic nodular medulloblastoma

Medulloblastoma with extensive nodularity

Medulloblastoma, large cell/anaplastic

Medulloblastoma, NOS.

Localization

see Cerebellar medulloblastomas

see Cerebellopontine angle medulloblastoma

see Multifocal medulloblastoma.

Subgrouping

Immunohistochemistry (IHC)-based and nanoString-based subgrouping methodologies have been independently described as options for medulloblastoma subgrouping, however, they have not previously been directly compared. D’Arcy described the experience with nanoString-based subgrouping in a clinical setting and compare this with our IHC-based results. Study materials included FFPE tissue from 160 medulloblastomas. Clinical data and tumor histology were reviewed. Immunohistochemical-based subgrouping using β-catenin, filamin A and p53 antibodies and nanoString-based gene expression profiling was performed. The sensitivity and specificity of IHC-based subgrouping of WNT and SHH-activated medulloblastomas was 91.5% and 99.54%, respectively. Filamin A immunopositivity highly correlated with SHH/WNT-activated subgroups (sensitivity 100%, specificity 92.7%, p < 0.001). Nuclear β-catenin immunopositivity had a sensitivity of 76.2% and specificity of 99.23% for the detection of WNT-activated tumors. Approximately 23.8% of WNT cases would have been missed using an IHC-based subgrouping method alone. nanoString could confidently predict medulloblastoma subgroup in 93% of cases and could distinguish group 3/4 subgroups in 96.3% of cases. nanoString-based subgrouping allows for a more prognostically useful classification of clinical medulloblastoma samples 4).

Molecular subgrouping was performed by immunohistochemistry (IHC) for beta catenin, GAB1 and YAP1; FISH for MYC amplification, and sequencing for CTNNB1, and by NanoString Assay on the same set of MBs. A subset of cases was subjected to 850k DNA methylation array.

IHC + FISH classified MBs into 15.8% WNT, 16.8% SHH, and 67.4% non-WNT/non-SHH subgroups; with MYC amplification identified in 20.3% cases of non-WNT/non-SHH. NanoString successfully classified 91.6% MBs into 25.3% WNT, 17.2% SHH, 23% Group 3 and 34.5% Group 4. However, NanoString assay failure was seen in eight cases, all of which were > 8-years-old formalin-fixed paraffin-embedded tissue blocks. Concordant subgroup assignment was noted in 88.5% cases, while subgroup switching was seen in 11.5% cases. Both methods showed prognostic correlation. Methylation profiling performed on discordant cases revealed 1 out of 4 extra WNT identified by NanoString to be WNT, others aligned with IHC subgroups; extra SHH by NanoString turned out to be SHH by methylation.

Both IHC supplemented by FISH and NanoString are robust methods for molecular subgrouping, albeit with few disadvantages. IHC cannot differentiate between Groups 3 and 4, while NanoString cannot classify older-archived tumors, and is not available at most centres. Thus, both the methods complement each other and can be used in concert for high confidence allotment of molecular subgroups in clinical practice 5).

The maturation of medulloblastoma into a ganglion cell-rich lesion is very rare, with few well-characterized previous reports. Given the rare nature of this entity, it would be of great value to understand the process of posttreatment maturation and the genetic and treatment factors which contribute to this phenomenon 6).

Pediatric Medulloblastoma

Pediatric Medulloblastoma.

Test and Answers

In the 5th edition of the WHO classification, how are medulloblastomas categorized based on their molecular background? a) Low-risk and high-risk b) Classic and desmoplastic nodular c) WNT, SHH-TP53 wild, SHH-TP53 mutant, and non-WNT/non-SHH d) Standard-risk and high-risk

Which subgroup of medulloblastoma is characterized by activation of the WNT pathway? a) Group 3 b) SHH-activated c) WNT-activated d) Non-WNT/non-SHH

What is the significance of TP53 mutation in SHH medulloblastomas? a) It indicates a better prognosis b) It indicates a worse prognosis c) It has no impact on prognosis d) It classifies the tumor as a WNT-activated subtype

How many subgroups are non-WNT/non-SHH medulloblastomas divided into based on methylation profiling in the 5th edition of the WHO classification? a) 2 b) 4 c) 6 d) 8

What are the clinical risk factors often used for prognosis assessment in medulloblastoma? a) Molecular subgroups b) Histopathological findings c) Age and gender d) Tumor location and size

Which of the following statements is true regarding the classification of medulloblastoma? a) Histopathological classification is the primary method used in the 5th edition of the WHO classification. b) Molecular subgroups are not considered relevant for treatment planning. c) Molecular subgroups guide the development of optimal treatment strategies. d) All medulloblastomas are classified into two main subgroups: WNT and SHH-activated.

What is the main difference between standard-risk and high-risk medulloblastoma? a) The presence of TP53 mutation b) The rate of tumor resection c) The age of the patient d) The presence of metastasis

Which of the following is NOT a method used for molecular subgrouping of medulloblastoma? a) Immunohistochemistry (IHC) b) NanoString Assay c) FISH for MYC amplification d) DNA methylation analysis

What is the advantage of using NanoString Assay for molecular subgrouping of medulloblastoma? a) It can classify older-archived tumor samples. b) It has a higher success rate in classifying tumors. c) It is based on DNA methylation profiling. d) It cannot be used in clinical practice.

Which subgroup of medulloblastoma is characterized by MYC amplification in some cases? a) WNT-activated b) SHH-activated c) Group 3 d) Group 4

Answers:

c) WNT, SHH-TP53 wild, SHH-TP53 mutant, and non-WNT/non-SHH c) WNT-activated b) It indicates a worse prognosis d) 8 c) Age and gender c) Molecular subgroups guide the development of optimal treatment strategies. b) The rate of tumor resection d) DNA methylation analysis a) It can classify older-archived tumor samples. c) Group 3

References

1)

Yamaguchi S, Fujimura M. [Medulloblastoma]. No Shinkei Geka. 2023 Sep;51(5):858-866. Japanese. doi: 10.11477/mf.1436204827. PMID: 37743337.
2)

Sharif Rahmani E, Lawarde A, Lingasamy P, Moreno SV, Salumets A, Modhukur V. MBMethPred: a computational framework for the accurate classification of childhood medulloblastoma subgroups using data integration and AI-based approaches. Front Genet. 2023 Sep 7;14:1233657. doi: 10.3389/fgene.2023.1233657. PMID: 37745846; PMCID: PMC10513500.
3)

Riemondy KA, Venkataraman S, Willard N, Nellan A, Sanford B, Griesinger AM, Amani V, Mitra S, Hankinson TC, Handler MH, Sill M, Ocasio J, Weir SJ, Malawsky DS, Gershon TR, Garancher A, Wechsler-Reya RJ, Hesselberth JR, Foreman NK, Donson AM, Vibhakar R. Neoplastic and immune single cell transcriptomics define subgroup-specific intra-tumoral heterogeneity of childhood medulloblastoma. Neuro Oncol. 2021 Jun 2:noab135. doi: 10.1093/neuonc/noab135. Epub ahead of print. PMID: 34077540.
4)

D’Arcy CE, Nobre LF, Arnaldo A, Ramaswamy V, Taylor MD, Naz-Hazrati L, Hawkins CE. Immunohistochemical and nanoString-Based Subgrouping of Clinical Medulloblastoma Samples. J Neuropathol Exp Neurol. 2020 Jan 30. pii: nlaa005. doi: 10.1093/jnen/nlaa005. [Epub ahead of print] PubMed PMID: 32053195.
5)

Kaur K, Jha P, Pathak P, Suri V, Sharma MC, Garg A, Suri A, Sarkar C. Approach to molecular subgrouping of medulloblastomas: Comparison of NanoString nCounter assay versus combination of immunohistochemistry and fluorescence in-situ hybridization in resource constrained centres. J Neurooncol. 2019 May 18. doi: 10.1007/s11060-019-03187-y. [Epub ahead of print] PubMed PMID: 31104222.
6)

Mullarkey MP, Nehme G, Mohiuddin S, et al. Posttreatment Maturation of Medulloblastoma into Gangliocytoma: Report of 2 Cases [published online ahead of print, 2020 Sep 3]. Pediatr Neurosurg. 2020;1-10. doi:10.1159/000509520

Glioblastoma prognostic markers

Glioblastoma prognostic markers

Latest PubMed Glioblastoma prognostic markers related articles

Glioblastoma (GBM) is an aggressive form of brain cancer, and predicting patient outcomes is a complex task. Prognostic markers are factors or characteristics that can help healthcare professionals estimate a patient’s likely disease course and survival. In the context of glioblastoma, several prognostic markers have been studied. Here are some of them:

Age: Increasing age is a well-established negative prognostic marker in glioblastoma. Older patients often have poorer outcomes.

Karnofsky Performance Score (KPS): This is a measure of a patient’s functional impairment and general well-being. A lower KPS score is associated with poorer prognosis.

Extent of Surgical Resection: The degree to which the tumor can be surgically removed is a significant prognostic factor. More extensive resection is associated with better outcomes.

O6-methylguanine-DNA Methyltransferase (MGMT) Methylation: Methylation of the MGMT gene promoter is associated with better responses to chemotherapy and improved survival.

Corticosteroid Use: The use of corticosteroids is associated with poor prognosis in glioblastoma patients.

Density of White Matter Tracts: Recent research has suggested that the density of white matter tracts in the brain near the tumor may be a prognostic marker. Lower tract density may indicate longer survival.

STAT5b: STAT5b activation is associated with poorer survival in glioblastoma patients.

SPTSSA Expression: SPTSSA expression may serve as a prognostic biomarker for glioma patients.

Lymphopenia: Baseline lymphopenia (a low lymphocyte count) is associated with worse overall survival in elderly glioblastoma patients.

c-Met and VEGFR2: Overexpression of c-Met and VEGFR2 may predict poorer responses to anti-angiogenic therapies in glioblastoma.

SII (Systemic Immune-Inflammation Index) and AGR (Albumin-to-Globulin Ratio): High SII and low AGR values are promising prognostic markers for identifying high-grade glioma (HGG) patients with poor prognoses.

ALK (Anaplastic Lymphoma Kinase): The role of ALK as a prognostic marker in glioblastoma is not well-established and remains controversial.

ATP-Binding Cassette Transporters: The activity of ATP-binding cassette transporters may impact prognosis by reducing drug penetration into tumor cells, but their use as isolated prognostic markers is not supported.

Tumor Geometry: Tumor shape and geometric heterogeneity can be used as prognostic markers. Patients with tumors exhibiting certain geometric characteristics may have better prognoses.

Neurologic Status: A proposed neurologic index may help predict poor outcomes in glioblastoma patients receiving tumor resection.

It’s important to note that glioblastoma is a complex and heterogeneous disease, and multiple factors can influence patient outcomes. Prognostic markers are used in combination to provide a more accurate prediction of prognosis. Additionally, ongoing research continues to uncover new markers and refine our understanding of glioblastoma prognosis.

Prognostic markers in glioblastoma are complex. In addition to previously recognized prognostic variables such as age and Karnofsky performance score, tumor size, total resection and proliferative index were identified as predictors of survival in a series of patients with glioblastoma multiforme 1).

Many reports on glioblastoma multiforme discuss the prognostic impact of anatomical features such as cysts, necrotic changes, extent of edema or subependymal spread of tumor cells.

The most consistent and well-described clinical prognostic factors associated with poor survival include: increasing age, poor performance status (PS), low degree of surgical resection of the tumor, and the use of corticosteroids 2) 3) 4) 5)

Salvalaggio et al. examined two Groups of Patients: The first group, called the “discovery cohort,” included 112 patients from Italy who had surgery between February 2015 and November 2020. The second group, known as the “replicative cohort,” included 70 patients from Germany who had surgery between September 2012 and November 2015.

What They Measured: The researchers were interested in something called “white matter tracts” in the patients’ brains. They measured how dense or crowded these tracts were in the area where the GBM was located.

Main Findings:

In the first group (discovery cohort), they found that the density of these white matter tracts was related to how long patients lived after surgery. When the tracts were less dense, patients tended to live longer.

This relationship between white matter tract density and survival was stronger and more consistent compared to other factors that are commonly used to predict how GBM patients will do, like age, performance status, a specific type of DNA change (O6-methylguanine-DNA methyltransferase methylation), and how much of the tumor was removed during surgery. They confirmed these findings in the second group (replicative cohort), which makes the results more reliable. Using the density of white matter tracts, they were able to predict whether a patient would have a higher or lower chance of surviving for at least 18 or 24 months after surgery with a high level of accuracy. Conclusion: This study suggests that the density of white matter tracts in the area around the GBM may be a useful predictor of how long patients with GBM will live after surgery. It could be valuable in clinical trials and medical practice to help doctors make decisions about treatment and prognosis.

In simple terms, the study found that the structure of certain brain pathways is related to how long patients with brain cancer live after surgery. This could be a helpful tool for doctors when treating these patients. 6).

STAT5b

STAT5b is frequently activated in Glioblastoma and correlates inversely with patient survival. It does not contribute to the growth and resistance of these tumors and is thus rather a potential prognostic marker than a therapeutic target in these tumors 7).

SPTSSA

SPTSSA expression might be used as a prognostic biomarker for glioma and a potential target for novel glioma therapy 8)

Lymphopenia

Baseline lymphopenia is associated with worse OS, which may be considered a prognostic biomarker for elderly glioblastoma outcome patients 9)

c-Met and VEGFR2

c-Met and VEGFR2 overexpression have a role in the development of glioblastoma early resistance and might predict poorer responses to anti-angiogenic therapies. 10)

Liang et al., demonstrated that high SII and low AGR values may serve as promising prognostic markers to identify HGG patients with poor prognosis 11).

ALK

Data on the prognostic role of ALK in Glioblastoma are very limited and remain controversial 12) 13) 14).

ATP-binding cassette transporter

The activity of ATP-binding cassette transporters severely reduces the amount of therapeutics that penetrates the tumor cells. Roy et al. hypothesized that ABC transporter expression could correlate with survival surrogates. They assessed the expression of four commonly expressed ABC transporters in GBM samples and investigated if mRNA levels could serve as a prognostic biomarker.

The expression of the four ABC transporters evaluated would not be suitable prognostic biomarkers. They believe that when estimating prognosis, the plethora of mechanisms implicated in chemoresistance should be analyzed as a multi-facetted entity rather than isolated units 15).

Geometry

Patients with tumours having small geometric heterogeneity and/or spherical rim widths had significantly better prognosis. These imaging biomarkers have a strong individual and combined prognostic value for Glioblastoma patients 16) 17).

Multi-channel MR image derived texture features, tumor shape, and volumetric features, and patient age were obtained for 163 Glioblastoma patients. In order to assess the impact of tumor shape features on OS prediction, two feature sets, with and without tumor shape features, were created. For the feature set with tumor shape features, the mean prediction error (MPE) was 14.6 days and its 95% confidence interval (CI) was 195.8 days. For the feature set excluding shape features, the MPE was 17.1 days and its 95% CI was observed to be 212.7 days. The coefficient of determination (R2) value obtained for the feature set with shape features was 0.92, while it was 0.90 for the feature set excluding shape features. Although marginal, the inclusion of shape features improves OS prediction in Glioblastoma patients. The proposed OS prediction method using regression provides good accuracy and overcomes the limitations of Glioblastoma OS classification, like choosing data-derived or pre-decided thresholds to define the OS groups. Graphical abstract Two feature sets: with and without tumor shape features were extracted from T1-weighted contrast-enhanced, T2-weighted and FLAIR MRI. These feature sets were analyzed using the Mean Prediction Error (MPE) and its 95% Confidence Interval (CI) obtained from the Bland-Altman plot, along with the coefficient of determination (R2) value to assess the impact of tumor shape features on overall survival prediction of glioblastoma multiforme patients 18).

Neurologic status

Neurologic status is one of the major prognostic factors; however, no consensus exists on a clinical index for predicting patient outcomes.

One proposed neurologic index enables significant identification of glioblastoma patients receiving tumor resection with poor outcomes, independent of other common prognostic factors. Using the index provides a preoperative predictor of prognosis in glioblastoma patients receiving tumor resection 19).

Test and Answers

What are prognostic markers used for in medicine? a) To diagnose diseases b) To predict the likely outcome of a disease in a patient c) To treat diseases d) To prevent diseases

In glioblastoma, which of the following factors were identified as predictors of survival in addition to age and performance score? a) Blood pressure and cholesterol levels b) Tumor size and total resection c) DNA mutations and tumor grade d) Blood type and genetic markers

What did Salvalaggio et al. measure in the brains of glioblastoma patients to assess prognosis? a) Blood flow b) White matter tract density c) Tumor size d) Brain volume

What was the main finding of the study conducted by Salvalaggio et al. regarding white matter tracts? a) White matter tract density was unrelated to patient survival. b) Patients with denser white matter tracts tended to live longer. c) White matter tracts were unrelated to tumor location. d) White matter tracts were unrelated to age.

Which of the following is NOT mentioned as a clinical prognostic factor associated with poor survival in glioblastoma? a) Increasing age b) Poor performance status (PS) c) Extent of surgical resection d) Use of corticosteroids

What is the potential role of STAT5b in glioblastoma? a) It contributes to tumor growth and resistance. b) It is a therapeutic target for glioblastoma. c) It is a prognostic marker. d) It has no role in glioblastoma.

What is SPTSSA expression potentially used for in glioma? a) Diagnosis b) Prognostic marker c) Treatment d) Disease prevention

What is lymphopenia considered as in elderly glioblastoma outcome patients? a) A marker of good prognosis b) A marker of disease progression c) A prognostic biomarker for poor outcome d) A diagnostic marker

What do c-Met and VEGFR2 overexpression predict in glioblastoma? a) Positive response to anti-angiogenic therapies b) Increased tumor size c) Resistance to chemotherapy d) No impact on patient outcomes

Which statement about ALK as a prognostic marker in glioblastoma is true? a) It is a well-established prognostic marker. b) Data on its prognostic role are limited and controversial. c) It is a therapeutic target for glioblastoma. d) It is not associated with patient survival.

What are prognostic markers used for in medicine? Answer: b) To predict the likely outcome of a disease in a patient

In glioblastoma, which of the following factors were identified as predictors of survival in addition to age and performance score? Answer: b) Tumor size and total resection

What did Salvalaggio et al. measure in the brains of glioblastoma patients to assess prognosis? Answer: b) White matter tract density

What was the main finding of the study conducted by Salvalaggio et al. regarding white matter tracts? Answer: b) Patients with denser white matter tracts tended to live longer.

Which of the following is NOT mentioned as a clinical prognostic factor associated with poor survival in glioblastoma? Answer: d) Use of corticosteroids

What is the potential role of STAT5b in glioblastoma? Answer: c) It is a prognostic marker.

What is SPTSSA expression potentially used for in glioma? Answer: b) Prognostic marker

What is lymphopenia considered as in elderly glioblastoma outcome patients? Answer: c) A prognostic biomarker for poor outcome

What do c-Met and VEGFR2 overexpression predict in glioblastoma? Answer: a) Positive response to anti-angiogenic therapies

Which statement about ALK as a prognostic marker in glioblastoma is true? Answer: b) Data on its prognostic role are limited and controversial.

1)

Donato V, Papaleo A, Castrichino A, Banelli E, Giangaspero F, Salvati M, Delfini R. Prognostic implication of clinical and pathologic features in patients with glioblastoma multiforme treated with concomitant radiation plus temozolomide. Tumori. 2007 May-Jun;93(3):248-56. PubMed PMID: 17679459.
2)

Gittleman H, Lim D, Kattan MW, Chakravarti A, Gilbert MR, Lassman AB, et al. An independently validated nomogram for individualized estimation of survival among patients with newly diagnosed glioblastoma: NRG Oncology RTOG 0525 and 0825. Neuro Oncol (2017) 19(5):669–77. doi: 10.1093/neuonc/now208
3)

Helseth R, Helseth E, Johannesen TB, Langberg CW, Lote K, Ronning P, et al. Overall survival, prognostic factors, and repeated surgery in a consecutive series of 516 patients with glioblastoma multiforme. Acta Neurol Scand (2010) 122(3):159–67. doi: 10.1111/j.1600-0404.2010.01350.x
4)

Gorlia T, van den Bent MJ, Hegi ME, Mirimanoff RO, Weller M, Cairncross JG, et al. Nomograms for predicting survival of patients with newly diagnosed glioblastoma: prognostic factor analysis of EORTC and NCIC trial 26981-22981/CE.3. Lancet Oncol (2008) 9(1):29–38. doi: 10.1016/S1470-2045(07)70384-4
5)

Li H, He Y, Huang L, Luo H, Zhu X. The Nomogram Model Predicting Overall Survival and Guiding Clinical Decision in Patients With Glioblastoma Based on the SEER Database. Front Oncol (2020) 10:1051:1051. doi: 10.3389/fonc.2020.01051
6)

Salvalaggio A, Pini L, Gaiola M, Velco A, Sansone G, Anglani M, Fekonja L, Chioffi F, Picht T, Thiebaut de Schotten M, Zagonel V, Lombardi G, D’Avella D, Corbetta M. White Matter Tract Density Index Prediction Model of Overall Survival in Glioblastoma. JAMA Neurol. 2023 Sep 25. doi: 10.1001/jamaneurol.2023.3284. Epub ahead of print. PMID: 37747720.
7)

Dubois N, Berendsen S, Tan K, Schoysmans L, Spliet W, Seute T, Bours V, Robe PA. STAT5b is a marker of poor prognosis, rather than a therapeutic target in glioblastomas. Int J Oncol. 2022 Oct;61(4):124. doi: 10.3892/ijo.2022.5414. Epub 2022 Sep 7. PMID: 36069226.
8)

Wang Z, Ge X, Shi J, Lu B, Zhang X, Huang J. SPTSSA Is a Prognostic Marker for Glioblastoma Associated with Tumor-Infiltrating Immune Cells and Oxidative Stress. Oxid Med Cell Longev. 2022 Aug 24;2022:6711085. doi: 10.1155/2022/6711085. PMID: 36062185; PMCID: PMC9434331.
9)

Song AJ, Ding K, Alnahhas I, Laperriere NJ, Perry J, Mason WP, Winch C, O’Callaghan CJ, Menten JJ, Brandes AA, Phillips C, Fay MF, Nishikawa R, Osoba D, Cairncross JG, Roa W, Wick W, Shi W. Impact of lymphopenia on survival for elderly patients with glioblastoma: A secondary analysis of the CCTG CE.6 (EORTC 26062-22061, TROG03.01) randomized clinical trial. Neurooncol Adv. 2021 Oct 15;3(1):vdab153. doi: 10.1093/noajnl/vdab153. Erratum in: Neurooncol Adv. 2022 Jan 27;4(1):vdac011. PMID: 34765975; PMCID: PMC8577525.
10)

Carvalho B, Lopes JM, Silva R, Peixoto J, Leitão D, Soares P, Fernandes AC, Linhares P, Vaz R, Lima J. The role of c-Met and VEGFR2 in glioblastoma resistance to bevacizumab. Sci Rep. 2021 Mar 16;11(1):6067. doi: 10.1038/s41598-021-85385-1. PMID: 33727583.
11)

Liang R, Li J, Tang X, Liu Y. The prognostic role of preoperative systemic immune-inflammation index and albumin/globulin ratio in patients with newly diagnosed high-grade glioma. Clin Neurol Neurosurg. 2019 Jun 24;184:105397. doi: 10.1016/j.clineuro.2019.105397. [Epub ahead of print] PubMed PMID: 31306893.
12)

Elsers D, Temerik DF, Attia AM, Hadia A, Hussien MT. Prognostic role of ALK-1 and h-TERT expression in glioblastoma multiforme: correlation with ALK gene alterations. J Pathol Transl Med. 2021;55:212–224.
13)

Karagkounis G, Stranjalis G, Argyrakos T, et al. Anaplastic lymphoma kinase expression and gene alterations in glioblastoma: correlations with clinical outcome. J Clin Pathol. 2017;70:593–9.
14)

Franceschi E, De Biase D, Di Nunno V, et al. The clinical and prognostic role of ALK in glioblastoma. Pathol Res Pract. 2021;221:153447.
15)

Roy LO, Lemelin M, Blanchette M, Poirier MB, Aldakhil S, Fortin D. Expression of ABCB1, ABCC1 and 3 and ABCG2 in glioblastoma and their relevance in relation to clinical survival surrogates. J Neurooncol. 2022 Nov 7. doi: 10.1007/s11060-022-04179-1. Epub ahead of print. PMID: 36342588.
16)

Pérez-Beteta J, Martínez-González A, Molina D, Amo-Salas M, Luque B, Arregui E, Calvo M, Borrás JM, López C, Claramonte M, Barcia JA, Iglesias L, Avecillas J, Albillo D, Navarro M, Villanueva JM, Paniagua JC, Martino J, Velásquez C, Asenjo B, Benavides M, Herruzo I, Delgado MD, Del Valle A, Falkov A, Schucht P, Arana E, Pérez-Romasanta L, Pérez-García VM. Glioblastoma: does the pre-treatment geometry matter? A postcontrast T1 MRI-based study. Eur Radiol. 2017 Mar;27(3):1096-1104. doi: 10.1007/s00330-016-4453-9. PubMed PMID: 27329522.
17)

Molina D, Pérez-Beteta J, Luque B, Arregui E, Calvo M, Borrás JM, López C, Martino J, Velasquez C, Asenjo B, Benavides M, Herruzo I, Martínez-González A, Pérez-Romasanta L, Arana E, Pérez-García VM. Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival. Br J Radiol. 2016 Jun 20:20160242. [Epub ahead of print] PubMed PMID: 27319577.
18)

Sanghani P, Ang BT, King NKK, Ren H. Regression based overall survival prediction of glioblastoma multiforme patients using a single discovery cohort of multi-institutional multi-channel MR images. Med Biol Eng Comput. 2019 May 18. doi: 10.1007/s11517-019-01986-z. [Epub ahead of print] PubMed PMID: 31104273.
19)

Liang HK, Wang CW, Tseng HM, Huang CY, Lan KH, Chen YH, You SL, Cheng JC, Cheng AL, Kuo SH. Preoperative prognostic neurologic index for glioblastoma patients receiving tumor resection. Ann Surg Oncol. 2014 Nov;21(12):3992-8. doi:10.1245/s10434-014-3793-4. Epub 2014 May 23. PubMed PMID: 24854491.

Magnetic resonance image-guided laser interstitial thermal therapy for glioblastoma

Magnetic resonance image-guided laser interstitial thermal therapy for glioblastoma

see Glioblastoma treatment.

see Magnetic resonance image-guided laser interstitial thermal therapy for intracranial tumor.

Magnetic Resonance Image-Guided Laser Interstitial Thermal Therapy (MRg-LITT) is an innovative and minimally invasive medical procedure used in the treatment of certain brain tumors, including glioblastoma.

Here’s an overview of how MRg-LITT works for glioblastoma:

Patient Selection: MRg-LITT is typically considered for patients who have glioblastoma that is difficult to access with traditional surgical methods or for patients who are not candidates for open surgery due to various reasons, such as the tumor’s location within critical brain regions.

Imaging and Planning: Before the procedure, high-resolution magnetic resonance imaging (MRI) scans are used to precisely locate and map the tumor. These images are used to plan the laser treatment.

Laser Ablation: During the MRg-LITT procedure, the patient is typically awake under local anesthesia. A small incision is made in the skull, and a thin, flexible laser probe is inserted into the brain. The laser probe has an optical fiber that delivers laser energy directly to the tumor.

Real-Time MRI Guidance: The critical aspect of MRg-LITT is real-time MRI guidance. As the laser is activated, MRI scans are continuously performed to monitor the temperature changes and precisely control the heat distribution within the tumor and surrounding healthy tissue. This real-time feedback ensures that the tumor is effectively heated and destroyed while minimizing damage to healthy brain tissue.

Treatment Monitoring: The MRI images provide immediate feedback to the medical team, allowing them to adjust the laser’s power and position as needed to optimize tumor ablation.

Thermal Ablation: The laser heats and destroys the tumor cells through thermal ablation, effectively killing the cancerous tissue. The procedure is carefully monitored to ensure the entire tumor is treated.

Post-Procedure Care: After the laser ablation, the probe is removed, and the incision is closed. Patients typically stay in the hospital for a short period for observation and recovery.

MRg-LITT offers several advantages for the treatment of glioblastoma:

Minimally Invasive: It involves a smaller incision compared to traditional open surgery, leading to reduced trauma and a shorter recovery time. Precise Targeting: Real-time MRI guidance allows for highly precise targeting and monitoring of the tumor, minimizing damage to healthy brain tissue. Outpatient Potential: In some cases, MRg-LITT can be performed on an outpatient basis or with shorter hospital stays. Reduced Risk: It may be suitable for patients with tumors in challenging or critical brain areas. However, it’s important to note that MRg-LITT is not suitable for all cases of glioblastoma. Patient eligibility and the choice of treatment method depend on various factors, including tumor size, location, and the patient’s overall health. Treatment decisions are typically made in consultation with a multidisciplinary team of medical professionals, including neurosurgeons, oncologists, and radiologists. Additionally, the long-term effectiveness of MRg-LITT for glioblastoma is an area of ongoing research and clinical trials.

Case series

50 GBM patients treated with LITT, with regard to safety, efficacy, and outcomes.

Kamath et al. performed a retrospective descriptive study of patients with histologically proven GBM who underwent LITT. Data collected included demographics, tumor location and volume, tumor genetic markers, treatment volume, perioperative complications, and long-term follow-up data.

They performed 58 LITT treatments for GBM in 54 patients over 5.5 yr. Forty-one were recurrent tumors while 17 were frontline treatments. Forty GBMs were lobar in location, while 18 were in deep structures (thalamus, insula, corpus callosum). Average tumor volume was 12.5 ± 13.4 cm3. The average percentage of tumors treated with the yellow thermal damage threshold (TDT) line (dose equivalent of 43°C for 2 min) was 93.3% ± 10.6%, and with the blue TDT line (dose equivalent of 43°C for 10 min) was 88.0% ± 14.2%. There were 7 perioperative complications (12%) and 2 mortalities (3.4%). Median overall survival after LITT for the total cohort was 11.5 mo, and median progression-free survival was 6.6 mo.

LITT appears to be a safe and effective treatment for GBM in properly selected patients 1).

A study included patients with de novo or recurrent glioblastoma of the corpus callosum (n = 15). The mean patient age was 54.7 yr. The mean pretreatment Karnofsky Performance Scale score was 80.7 and there was no significant difference between subgroups. The mean tumor volume was 18.7 cm3. Hemiparesis occurred in 26.6% of patients. Complications were more frequent in patients with tumors >15 cm3 (RR 6.1, P = .009) and were associated with a 32% decrease in survival postLITT. Median progression-free survival, survival postLITT, and overall survival were 3.4, 7.2, and 18.2 mo, respectively.

LITT is a safe and effective treatment for glioblastoma of the corpus callosum and provides survival benefits comparable to subtotal surgical resection with adjuvant chemoradiation. LITT-associated complications are related to tumor volume and can be nearly eliminated by limiting the procedure to tumors of 15 cm3 or less 2).

A 51-year-old male presented after a fall with progressive dizziness, ataxia, and worsening headaches with a small, frontal ring-enhancing lesion. After clinical and radiographic progression, the patient underwent a stereotactic biopsy, confirming an IDH-WT World Health Organization Grade IV Glioblastoma, followed by LITT. The patient was subsequently started on adjuvant temozolomide, and 60 Gy fractionated – radiotherapy to the post-LITT tumor volume. After 3 months, surgical debulking was conducted due to perilesional vasogenic edema and cognitive decline, with H&E staining demonstrating perivascular lymphocytic infiltration. Postoperative serial imaging over 3 years showed no evidence of tumor recurrence. The patient is currently alive 9 years after diagnosis. Multiplex immunofluorescence imaging of pre-LITT and post-LITT biopsies showed increased CD8 and activated macrophage infiltration and programmed death ligand 1 expression. This is the first depiction of the in-situ immune response to LITT and the first human clinical presentation of increased CD8 infiltration and programmed death ligand 1 expression in post-LITT tissue. The findings point to LITT as a treatment approach with the potential for long-term delay of recurrence and improving response to immunotherapy 3)

Test

Magnetic Resonance Image-Guided Laser Interstitial Thermal Therapy (MRg-LITT)

What is MRg-LITT primarily used for? a. Treating lung cancer b. Treating glioblastoma c. Treating breast cancer d. Treating skin disorders

Why is MRg-LITT considered for glioblastoma patients? a. It is less expensive than traditional surgery. b. It involves a larger incision than traditional surgery. c. It is suitable for all cases of glioblastoma. d. It is considered when traditional surgery is challenging or not an option.

What is the first step in the MRg-LITT procedure? a. Administering chemotherapy b. Conducting a stereotactic biopsy c. Performing a CT scan d. Using high-resolution MRI scans for tumor mapping

During the MRg-LITT procedure, what delivers laser energy directly to the tumor? a. A scalpel b. A robotic arm c. An optical fiber in a laser probe d. A radiation beam

What is the critical aspect of MRg-LITT that ensures precise treatment and minimal damage to healthy tissue? a. Real-time MRI guidance b. Post-operative care c. Chemotherapy administration d. Surgical incision size

How is the laser energy used during MRg-LITT to treat the tumor? a. It cools down the tumor. b. It freezes the tumor. c. It heats and destroys the tumor cells through thermal ablation. d. It directly removes the tumor.

What is one of the advantages of MRg-LITT for glioblastoma treatment? a. Longer hospital stays b. Increased trauma compared to traditional surgery c. Outpatient potential d. Risk reduction for all patients

What factors determine patient eligibility and the choice of treatment method for MRg-LITT? a. The patient’s hair color b. The patient’s blood type c. Tumor size, location, and overall health d. The patient’s age and gender

What is the primary focus of the case series study mentioned? a. The history of MRg-LITT b. The benefits of chemotherapy c. The safety and outcomes of MRg-LITT in GBM patients d. The development of new surgical instruments

According to the study by Kamath et al., what percentage of patients experienced perioperative complications related to MRg-LITT? a. 0% b. 3.4% c. 12% d. 26.6%

Answers:

b. Treating glioblastoma d. It is considered when traditional surgery is challenging or not an option. d. Using high-resolution MRI scans for tumor mapping c. An optical fiber in a laser probe a. Real-time MRI guidance c. It heats and destroys the tumor cells through thermal ablation. c. Outpatient potential c. Tumor size, location, and overall health c. The safety and outcomes of MRg-LITT in GBM patients c. 12%

1)

Kamath AA, Friedman DD, Akbari SHA, Kim AH, Tao Y, Luo J, Leuthardt EC. Glioblastoma Treated With Magnetic Resonance Imaging-Guided Laser Interstitial Thermal Therapy: Safety, Efficacy, and Outcomes. Neurosurgery. 2019 Apr 1;84(4):836-843. doi: 10.1093/neuros/nyy375. PMID: 30137606; PMCID: PMC6425465.
2)

Beaumont TL, Mohammadi AM, Kim AH, Barnett GH, Leuthardt EC. Magnetic Resonance Imaging-Guided Laser Interstitial Thermal Therapy for Glioblastoma of the Corpus Callosum. Neurosurgery. 2018 Sep 1;83(3):556-565. doi: 10.1093/neuros/nyx518. PMID: 29438526; PMCID: PMC6939409.
3)

Chandar JS, Bhatia S, Ingle S, Mendez Valdez MJ, Maric D, Seetharam D, Desgraves JF, Govindarajan V, Daggubati L, Merenzon M, Morell A, Luther E, Saad AG, Komotar RJ, Ivan ME, Shah AH. Laser Interstitial Thermal Therapy Induces Robust Local Immune Response for Newly Diagnosed Glioblastoma with Long-term Survival and Disease Control. J Immunother. 2023 Sep 19. doi: 10.1097/CJI.0000000000000485. Epub ahead of print. PMID: 37727953.

Test your knowledge about BCL2L13 and its potential role in glioblastoma

Certainly, here's a quiz to test your knowledge about BCL2L13 and its potential role in glioblastoma:

What is BCL2L13's role within the BCL-2 protein family?
a) Promotion of apoptosis
b) Inhibition of apoptosis
c) Regulation of cell division
d) Promotion of cell growth

What does BCL2L13 stand for?
a) B-cell leukemia/lymphoma 2-like protein 13
b) Bcl-rambo
c) Bcl2-L-13
d) All of the above

In the context of glioblastoma, what is the primary function of BCL2L13?
a) Promotion of tumor growth
b) Inhibition of mitophagy
c) Regulation of apoptosis
d) Promotion of mitochondrial fission and mitophagy

How does BCL2L13 potentially impact glioblastoma cell behavior?
a) By inhibiting cell invasion
b) By promoting programmed cell death
c) By enhancing cell proliferation and invasion
d) By regulating DNA repair mechanisms

In a study by Wang et al., what was the main finding regarding BCL2L13 in glioblastoma?
a) BCL2L13 is downregulated in GBM.
b) BCL2L13 has no significant impact on GBM cells.
c) BCL2L13 is upregulated in GBM and promotes mitophagy through DNM1L-mediated mitochondrial fission.
d) BCL2L13 is unrelated to GBM progression.

What is DNM1L's role in the context of BCL2L13 and glioblastoma?
a) It inhibits BCL2L13 expression.
b) It promotes apoptosis.
c) It mediates mitochondrial fission and mitophagy.
d) It has no connection to glioblastoma.

Why is understanding the role of BCL2L13 in glioblastoma important?
a) Because it is a well-established target for glioblastoma treatment.
b) Because it plays a role in DNA repair.
c) Because it can potentially be a molecular target for therapy.
d) Because it is a commonly mutated gene in glioblastoma.

Answers

Glioblastoma survival

Glioblastoma survival

Advances in glioblastoma diagnosis and glioblastoma surgery mean that radical resections can be performed even in eloquent brain areas. However, patients not indicated for resection will experience a major reduction in life expectancy. Patients who underwent stereotactic biopsy and received some form of oncological treatment experienced slightly increased overall survival relative to patients with a natural disease course. Patients with favorable clinical factors reacted better to treatment 1)

Overall survival

Glioblastoma overall survival.

Glioblastoma patients who were readmitted within 30 days had significantly shorter survival than nonreadmitted patients. Future studies that attempt to decrease readmissions and evaluate the impact of reducing readmissions on patient outcomes are needed 2).

Despite advances in treatment, the median patient survival is 12 to 15 months 3).

Glioblastoma progression

Glioblastoma progression.

1)

Halaj M, Kalita O, Tuckova L, Hrabalek L, Dolezel M, Vrbkova J. Life expectancy in glioblastoma patients who had undergone stereotactic biopsy: a retrospective single-center study. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2023 Jul 10. doi: 10.5507/bp.2023.030. Epub ahead of print. PMID: 37431620.
2)

Nuño M, Ly D, Ortega A, Sarmiento JM, Mukherjee D, Black KL, Patil CG. Does 30-Day Readmission Affect Long-term Outcome Among Glioblastoma Patients? Neurosurgery. 2014 Feb;74(2):196-205. doi: 10.1227/NEU.0000000000000243. PubMed PMID: 24176955.
3)

DeAngelis LM. Brain tumors. N Engl J Med. 2001;344(2):114–123.

Craniopharyngioma endoscopic endonasal approach

Craniopharyngioma endoscopic endonasal approach

Latest Craniopharyngioma endoscopic endonasal approach PubMed-related Articles

Indications

Craniopharyngioma endoscopic endonasal approach Indications.

Systematic reviews

The endoscopic endonasal approach (EEA) for craniopharyngiomas has proven to be a safe option for extensive tumor resection, with minimal or no manipulation of the optic nerves and excellent visualization of the superior hypophyseal artery branches when compared to the Transcranial Approach (TCA). However, there is an ongoing debate regarding the criteria for selecting different approaches. To explore the current results of EEA and discuss its role in the management of craniopharyngiomas, Figueredo et al. performed MEDLINE, Embase, and LILACS searches from 2012 to 2022. Baseline characteristics, the extent of resection, and clinical outcomes were evaluated. Statistical analysis was performed through an X2 and Fisher exact test, and a comparison between quantitative variables through a Kruskal-Wallis and verified with post hoc Bonferroni. The tumor volume was similar in both groups (EEA 11.92 cm3, -TCA 13.23 cm3). The mean follow-up in months was 39.9 for EEA and 43.94 for TCA, p = 0.76). The EEA group presented a higher visual improvement rate (41.96% vs. 25% for TCA, p < 0.0001, OR 7.7). Permanent DI was less frequent with EEA (29.20% vs. 67.40% for TCA, p < 0.0001, OR 0.2). CSF Leaks occurred more frequently with EEA (9.94% vs. 0.70% for TCA, p < 0.0001, OR 15.8). Recurrence rates were lower in the EEA group (EEA 15.50% vs. for TCA 21.20%, p = 0.04, OR 0.7). The results demonstrate that, in selected cases, EEA for resection of craniopharyngiomas is associated with better results regarding visual preservation and extent of tumor resection. Postoperative cerebrospinal fluid fistula rates associated with EEA have improved compared to the historical series. The decision-making process should consider each person’s characteristics; however, it is noticeable that recent data regarding EEA justify its widespread application as a first-line approach in centers of excellence for skull base surgery 1).

Qiao et al., conducted a systematic review and meta-analysis. They conducted a comprehensive search of PubMed to identify relevant studies. Pituitary, hypothalamus functions and recurrence were used as outcome measures. A total of 39 cohort studies involving 3079 adult patients were included in the comparison. Among these studies, 752 patients across 17 studies underwent endoscopic transsphenoidal resection, and 2327 patients across 23 studies underwent transcranial resection. More patients in the endoscopic group (75.7%) had visual symptoms and endocrine symptoms (60.2%) than did patients in the transcranial group (67.0%, p = 0.038 and 42.0%, p = 0.016). There was no significant difference in hypopituitarism and pan-hypopituitarism after surgery between the two groups: 72.2% and 43.7% of the patients in endoscopic group compared to 80.7% and 48.3% in the transcranial group (p = 0.140 and p = 0.713). We observed same proportions of transient and permanent diabetes insipidus in both groups. Similar recurrence was observed in both groups (p = 0.131). Pooled analysis showed that neither weight gain (p = 0.406) nor memory impairment (p = 0.995) differed between the two groups. Meta-regression analysis revealed that gross total resection contributed to the heterogeneity of recurrence proportion (p < 0.001). They observed similar proportions of endocrine outcomes and recurrence in both endoscopic and transcranial groups. More recurrences were observed in studies with lower proportions of gross total resection 2).

Komotar et al performed a systematic review of the available published reports after endoscope-assisted endonasal approaches and compared their results with transsphenoidal purely microscope-based or transcranial microscope-based techniques.

The endoscopic endonasal approach is a safe and effective alternative for the treatment of certain craniopharyngiomas. Larger lesions with more lateral extension may be more suitable for an open approach, and further follow-up is needed to assess the long-term efficacy of this minimal access approach 3)

Nowadays, an endoscopic endonasal approach (EEA) provides an “easier” way for CPs resection allowing a direct route to the tumor with direct visualization of the surrounding structures, diminishing inadvertent injuries, and providing a better outcome for the patient 4).

Historically, aggressive surgical resection was the treatment goal to minimize the risk of tumor recurrence via open transcranial midline, anterolateral, and lateral approaches, but could lead to clinical sequela of visual, endocrine, and hypothalamic dysfunction. However, recent advances in the endoscopic endonasal approach over the last decade have mostly supplanted transcranial surgery as the optimal surgical approach for these tumors. With viable options for adjuvant radiation therapy, targeted medical treatment, and alternative minimally invasive surgical approaches, the management paradigm for craniopharyngiomas has shifted from aggressive open resection to more minimally invasive but maximally safe resection, emphasizing quality of life issues, particularly in regards to visual, endocrine, and hypothalamic function. 5).

Craniopharyngioma surgery has evolved over the last two decades. Traditional transcranial microsurgical approaches were the only option until the advent of the endoscopic endonasal approach 6).

The endoscopic endonasal approach for craniopharyngiomas is increasingly used as an alternative to microsurgical transsphenoidal or transcranial approaches. It is a step forward in treatment, providing improved resection rates and better visual outcome. Especially in retrochiasmatic tumors, this approach provides better lesion access and reduces the degree of manipulations of the optic apparatus. The panoramic view offered by endoscopy and the use of angulated optics allows the removal of lesions extending far into the third ventricle avoiding microsurgical brain splitting. Intensive training is required to perform this surgery 7).

The highest priority of current surgical craniopharyngioma treatment is to maximize tumor removal without compromising the patients’ long-term functional outcome. Surgical damage to the hypothalamus may be avoided or at least ameliorated with a precise knowledge regarding the type of adherence for each case.

Endoscopic endonasal approach, has been shown to achieve higher rates of hypothalamic preservation regardless of the degree of involvement by tumor 8) 9).

Extended endoscopic transsphenoidal approach have gained interest. Surgeons have advocated for both approaches, and at present there is no consensus whether one approach is superior to the other.

With the widespread use of endoscopes in endonasal surgery, the endoscopic transtuberculum transplanum approach have been proposed as an alternative surgical route for removal of different types of suprasellar tumors, including solid craniopharyngiomas in patients with normal pituitary function and small sella.

As part of a minimally disruptive treatment paradigm, the extended endoscopic transsphenoidal approach has the potential to improve rates of resection, improve postoperative visual recovery, and minimize surgical morbidity 10).

Corridors

The endoscopic endonasal approach has become a valid surgical technique for the management of craniopharyngiomas. It provides an excellent corridor to infra- and supradiaphragmatic midline craniopharyngiomas, including the management of lesions extending into the third ventricle chamber. Even though indications for this approach are rigorously lesion based, the data confirm its effectiveness in a large patient series 11).

The endoscopic endonasal approach offers advantages in the management of craniopharyngiomas that historically have been approached via the transsphenoidal approach (i.e., purely intrasellar or intra-suprasellar infradiaphragmatic, preferably cystic lesions in patients with panhypopituitarism).

Use of the extended endoscopic endonasal approach overcomes the limits of the transsphenoidal route to the sella enabling the management of different purely suprasellar and retrosellar cystic/solid craniopharyngiomas, regardless of the sellar size or pituitary function 12).

They provide acceptable results comparable to those for traditional craniotomies. Endoscopic endonasal surgery is not limited to adults and actually shows higher resection rates in the pediatric population 13).

Infrachiasmatic corridor

Infrachiasmatic corridor

Complications

Craniopharyngioma endoscopic endonasal approach complications.

Case series

see Craniopharyngioma endoscopic endonasal approach case series.

References

1)

Figueredo LF, Martínez AL, Suarez-Meade P, Marenco-Hillembrand L, Salazar AF, Pabon D, Guzmán J, Murguiondo-Perez R, Hallak H, Godo A, Sandoval-Garcia C, Ordoñez-Rubiano EG, Donaldson A, Chaichana KL, Peris-Celda M, Bendok BR, Samson SL, Quinones-Hinojosa A, Almeida JP. Current Role of Endoscopic Endonasal Approach for Craniopharyngiomas: A 10-Year Systematic Review and Meta-Analysis Comparison with the Open Transcranial Approach. Brain Sci. 2023 May 23;13(6):842. doi: 10.3390/brainsci13060842. PMID: 37371322.
2)

Qiao N. Endocrine outcomes of endoscopic versus transcranial resection of craniopharyngiomas: A system review and meta-analysis. Clin Neurol Neurosurg. 2018 Apr 7;169:107-115. doi: 10.1016/j.clineuro.2018.04.009. [Epub ahead of print] Review. PubMed PMID: 29655011.
3)

Komotar RJ, Starke RM, Raper DM, Anand VK, Schwartz TH. Endoscopic endonasal compared with microscopic transsphenoidal and open transcranial resection of craniopharyngiomas. World Neurosurg. 2012 Feb;77(2):329-41. doi: 10.1016/j.wneu.2011.07.011. Epub 2011 Nov 1. Review. PubMed PMID: 22501020.
4)

Aragón-Arreola JF, Marian-Magaña R, Villalobos-Diaz R, López-Valencia G, Jimenez-Molina TM, Moncada-Habib JT, Sangrador-Deitos MV, Gómez-Amador JL. Endoscopic Endonasal Approach in Craniopharyngiomas: Representative Cases and Technical Nuances for the Young Neurosurgeon. Brain Sci. 2023 Apr 28;13(5):735. doi: 10.3390/brainsci13050735. PMID: 37239207; PMCID: PMC10216292.
5)

Hong CS, Omay SB. The Role of Surgical Approaches in the Multi-Modal Management of Adult Craniopharyngiomas. Curr Oncol. 2022 Feb 24;29(3):1408-1421. doi: 10.3390/curroncol29030118. PMID: 35323318; PMCID: PMC8947636.
6)

Fong RP, Babu CS, Schwartz TH. Endoscopic endonasal approach for craniopharyngiomas. J Neurosurg Sci. 2021 Apr;65(2):133-139. doi: 10.23736/S0390-5616.21.05097-9. PMID: 33890754.
7)

Baldauf J, Hosemann W, Schroeder HW. Endoscopic Endonasal Approach for Craniopharyngiomas. Neurosurg Clin N Am. 2015 Jul;26(3):363-75. doi: 10.1016/j.nec.2015.03.013. Epub 2015 May 26. PMID: 26141356.
8)

Tan TSE, Patel L, Gopal-Kothandapani JS, Ehtisham S, Ikazoboh EC, Hayward R, et al: The neuroendocrine sequelae of paediatric craniopharyngioma: a 40-year meta-data analysis of 185 cases from three UK centres. Eur J Endocrinol 176:359–369, 2017
9)

Yokoi H, Kodama S, Kogashiwa Y, Matsumoto Y, Ohkura Y, Nakagawa T, et al: An endoscopic endonasal approach for early-stage olfactory neuroblastoma: an evaluation of 2 cases with minireview of literature. Case Rep Otolaryngol 2015:541026, 2015
10)

Zacharia BE, Amine M, Anand V, Schwartz TH. Endoscopic Endonasal Management of Craniopharyngioma. Otolaryngol Clin North Am. 2016 Feb;49(1):201-12. doi: 10.1016/j.otc.2015.09.013. Review. PubMed PMID: 26614838.
11)

Cavallo LM, Frank G, Cappabianca P, Solari D, Mazzatenta D, Villa A, Zoli M, D’Enza AI, Esposito F, Pasquini E. The endoscopic endonasal approach for the management of craniopharyngiomas: a series of 103 patients. J Neurosurg. 2014 May 2. [Epub ahead of print] PubMed PMID: 24785324.
12)

Cavallo LM, Solari D, Esposito F, Villa A, Minniti G, Cappabianca P. The Role of the Endoscopic Endonasal Route in the Management of Craniopharyngiomas. World Neurosurg. 2014 Dec;82(6S):S32-S40. doi: 10.1016/j.wneu.2014.07.023. Review. PubMed PMID: 25496633.
13)

Koutourousiou M, Gardner PA, Fernandez-Miranda JC, Tyler-Kabara EC, Wang EW, Snyderman CH. Endoscopic endonasal surgery for craniopharyngiomas: surgical outcome in 64 patients. J Neurosurg. 2013 Nov;119(5):1194-207. doi: 10.3171/2013.6.JNS122259. Epub 2013 Aug 2. PubMed PMID: 23909243.

Vorasidenib

Vorasidenib

Vorasidenib (AG-881) is an orally available, brain-penetrant second-generation dual mutant isocitrate dehydrogenases 1 and 2 (mIDH1/2) inhibitor. Vorasidenib (AG-881) exhibits nanomolar inhibition of (D)-2-hydroxyglutarate (D-2-HG), and the IC50 ranges of 0.04~22 nM against IDH1 R132C, IDH1 R132G, IDH1 R132H and IDH1 R132S and 7~14 nM against IDH2 R140Q and 130 nM against IDH2 R172K

In a double-blind, phase 3 trial, Mellinghoff et al. randomly assigned patients with residual or recurrent grade 2 IDH-mutant glioma who had undergone no previous treatment other than surgery to receive either oral vorasidenib (40 mg once daily) or matched placebo in 28-day cycles. The primary endpoint was imaging-based progression-free survival according to a blinded assessment by an independent review committee. The key secondary endpoint was the time for the next anticancer intervention. Crossover to vorasidenib from placebo was permitted on confirmation of imaging-based disease progression. Safety was also assessed.

A total of 331 patients were assigned to receive vorasidenib (168 patients) or placebo (163 patients). At a median follow-up of 14.2 months, 226 patients (68.3%) were continuing to receive vorasidenib or a placebo. Progression-free survival was significantly improved in the vorasidenib group as compared with the placebo group (median progression-free survival, 27.7 months vs. 11.1 months; hazard ratio for disease progression or death, 0.39; 95% confidence interval [CI], 0.27 to 0.56; P<0.001). The time to the next intervention was significantly improved in the vorasidenib group as compared with the placebo group (hazard ratio, 0.26; 95% CI, 0.15 to 0.43; P<0.001). Adverse events of grade 3 or higher occurred in 22.8% of the patients who received vorasidenib and in 13.5% of those who received a placebo. An increased alanine aminotransferase level of grade 3 or higher occurred in 9.6% of the patients who received vorasidenib and in no patients who received placebo

In patients with grade 2 IDH-mutant glioma, vorasidenib significantly improved progression-free survival and delayed the time to the next intervention. (Funded by Servier; INDIGO ClinicalTrials.gov number, NCT04164901.). 1)

According to the phase III INDIGO trial, vorasidenib, an IDH1/2 inhibitor, significantly benefited adults with IDH1/2-mutant low-grade gliomas, reducing progression risk and delaying the need for chemoradiotherapy. Meanwhile, in a pediatric low-grade glioma cohort of FIREFLY-1, a phase II trial, robust responses to the type II pan-RAF inhibitor tovorafenib were seen 2)

Vorasidenib and ivosidenib inhibit mutant forms of isocitrate dehydrogenase (mIDH) and have shown preliminary clinical activity against mIDH glioma. We evaluated both agents in a perioperative phase 1 trial to explore the mechanism of action in recurrent low-grade glioma (IGG) and select a molecule for phase 3 testing. Primary end-point was concentration of D-2-hydroxyglutarate (2-HG), the metabolic product of mIDH enzymes, measured in tumor tissue from 49 patients with mIDH1-R132H nonenhancing gliomas following randomized treatment with vorasidenib (50 mg or 10 mg once daily, q.d.), ivosidenib (500 mg q.d. or 250 mg twice daily) or no treatment before surgery. Tumor 2-HG concentrations were reduced by 92.6% (95% credible interval (CrI), 76.1-97.6) and 91.1% (95% CrI, 72.0-97.0) in patients treated with vorasidenib 50 mg q.d. and ivosidenib 500 mg q.d., respectively. Both agents were well tolerated and follow-up is ongoing. In exploratory analyses, 2-HG reduction was associated with increased DNA 5-hydroxymethylcytosine, reversal of ‘proneural’ and ‘stemness’ gene expression signatures, decreased tumor cell proliferation and immune cell activation. Vorasidenib, which showed brain penetrance and more consistent 2-HG suppression than ivosidenib, was advanced to phase 3 testing in patients with mIDH LGGs. Funded by Agios Pharmaceuticals, Inc. and Servier Pharmaceuticals LLC; ClinicalTrials.gov number NCT03343197 3)

computational drug repurposing strategies were employed to identify potent mIDH1- specific inhibitors from the 11,808 small molecules listed in the DrugBank repository.

Methods: Tanimoto coefficient (Tc) calculations were initially used to retrieve compounds with structurally similar scaffolds to ivosidenib. The resultant compounds were then subjected to molecular docking to discriminate the binders from the non-binders. The binding affinities and pharmacokinetic properties of the screened compounds were examined using prime Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) and QikProp algorithm, respectively. The conformational stability of these molecules was validated using 100 ns molecular dynamics simulation.

Results: Together, these processes led to the identification of three-hit molecules, namely DB12001, DB08026, and DB03346, as potential inhibitors of the mIDH1 protein. Of note, the binding free energy calculations and MD simulation studies emphasized the greater binding affinity and structural stability of the hit compounds towards the mIDH1 protein.

Conclusion: The collective evidence from our study indicates the activity of DB12001 against recurrent glioblastoma, which, in turn, highlights the accuracy of our adapted strategy. Hence, we hypothesize that the identified lead molecules could be translated for the development of mIDH1 inhibitors in the near future 4)

Vorasidenib (AG-881) has recently been reported as a promising dual inhibitor of mutant isocitrate dehydrogenase 1 and 2 with the ability to penetrate the blood-brain barrier towards the treatment of low-grade glioma. In order to combat drug resistance and toxicity levels, this compelled us to further investigate this substance as a basis for the creation of potential selective inhibitors of mutant isocitrate dehydrogenases 1 and 2.

Methods: By employing a wide range of computational techniques, binding moieties of AG-881 that contributed towards its selective binding to isocitrate dehydrogenase enzymes 1 and 2 were identified and subsequently used to generate pharmacophore models for the screening of potential inhibitor drugs that were further assessed by their pharmacokinetics and physicochemical properties.

Results: AG-881 was identified as the most favorable candidate for isocitrate dehydrogenase enzyme 1, exhibiting a binding free energy of -28.69 kcal/mol. ZINC93978407 was the most favorable candidatefor isocitrate dehydrogenase enzyme 2, displaying a strong binding free energy of -27.10 kcal/mol. ZINC9449923 and ZINC93978407 towards isocitrate dehydrogenase enzyme 1 and 2 showed good protein structural stability with a low radius of gyration values relative to AG-881.

Conclusion: We investigated that ZINC9449923 of isocitrate dehydrogenase enzyme 1 and ZINC 93978407 of isocitrate dehydrogenase enzyme 2 could serve as promising candidates for the treatment of lower-grade glioma as they cross the blood-brain barrier, and present with lower toxicity levels relative to AG-881 5)

conducted a multicenter, open-label, phase I, dose-escalation study of vorasidenib in 93 patients with mutant IDH1/2 (mIDH1/2) solid tumors, including 52 patients with glioma that had recurred or progressed following standard therapy. Vorasidenib was administered orally, once daily, in 28-day cycles until progression or unacceptable toxicity. Enrollment is complete; this trial is registered with ClinicalTrials.gov, NCT02481154.

Results: Vorasidenib showed a favorable safety profile in the glioma cohort. Dose-limiting toxicities of elevated transaminases occurred at doses ≥100 mg and were reversible. The protocol-defined objective response rate per Response Assessment in Neuro-Oncology criteria for LGG in patients with nonenhancing glioma was 18% (one partial response, three minor responses). The median progression-free survival was 36.8 months [95% confidence interval (CI), 11.2-40.8] for patients with nonenhancing glioma and 3.6 months (95% CI, 1.8-6.5) for patients with enhancing glioma. Exploratory evaluation of tumor volumes in patients with nonenhancing glioma showed sustained tumor shrinkage in multiple patients.

Conclusions: Vorasidenib was well tolerated and showed preliminary antitumor activity in patients with recurrent or progressive nonenhancing mIDH LGG 6).

A analysis proved that the dual-targeting ability of AG-881 is mediated by Val255/Val294 within the binding pockets of both mIDH1 and mIDH2 which are shown to elicit a strong intermolecular interaction, thus favoring binding affinity. The structural orientations of AG-881 within the respective hydrophobic pockets allowed favorable interactions with binding site residues which accounted for its high binding free energy of -28.69 kcal/mol and -19.89 kcal/mol towards mIDH1 and mIDH2, respectively. Interestingly, upon binding, AG-881 was found to trigger systemic alterations of mIDH1 and mIDH2 characterized by restricted residue flexibility and a reduction in exposure of residues to the solvent surface area. As a result of these structural alterations, crucial interactions of the mutant enzymes were inhibited, a phenomenon that results in a suppression of the production of oncogenic stimulator 2-HG. Findings therefore provide thorough structural and dynamic insights associated with the dual inhibitory activity of AG-881 towards glioma therapy 7)

Mutations in isocitrate dehydrogenase 1 (IDH1mut) are reported in 70-90% of low-grade gliomas and secondary glioblastomas. IDH1mut catalyzes the reduction of α-ketoglutarate (α-KG) to 2-hydroxyglutarate (2-HG), an oncometabolite which drives tumorigenesis. Inhibition of IDH1mut is therefore an emerging therapeutic approach, and inhibitors such as AG-120 and AG-881 have shown promising results in phase 1 and 2 clinical studies. However, detection of response to these therapies prior to changes in tumor growth can be challenging. The goal of this study was to identify non-invasive clinically translatable metabolic imaging biomarkers of IDH1mut inhibition that can serve to assess response. Methods: IDH1mut inhibition was confirmed using an enzyme assay and 1H- and 13C- magnetic resonance spectroscopy (MRS) were used to investigate the metabolic effects of AG-120 and AG-881 on two genetically engineered IDH1mut-expressing cell lines, NHAIDH1mut and U87IDH1mut. Results:1H-MRS indicated a significant decrease in steady-state 2-HG following treatment, as expected. This was accompanied by a significant 1H-MRS-detectable increase in glutamate. However, other metabolites previously linked to 2-HG were not altered. 13C-MRS also showed that the steady-state changes in glutamate were associated with a modulation in the flux of glutamine to both glutamate and 2-HG. Finally, hyperpolarized 13C-MRS was used to show that the flux of α-KG to both glutamate and 2-HG was modulated by treatment. Conclusion: In this study, we identified potential 1H- and 13C-MRS-detectable biomarkers of response to IDH1mut inhibition in gliomas. Although further studies are needed to evaluate the utility of these biomarkers in vivo, we expect that in addition to a 1H-MRS-detectable drop in 2-HG, a 1H-MRS-detectable increase in glutamate, as well as a hyperpolarized 13C-MRS-detectable change in [1-13C] α-KG flux, could serve as metabolic imaging biomarkers of response to treatment 8)

1)

Mellinghoff IK, van den Bent MJ, Blumenthal DT, Touat M, Peters KB, Clarke J, Mendez J, Yust-Katz S, Welsh L, Mason WP, Ducray F, Umemura Y, Nabors B, Holdhoff M, Hottinger AF, Arakawa Y, Sepulveda JM, Wick W, Soffietti R, Perry JR, Giglio P, de la Fuente M, Maher EA, Schoenfeld S, Zhao D, Pandya SS, Steelman L, Hassan I, Wen PY, Cloughesy TF. Vorasidenib in IDH1- or IDH2-Mutant Low-Grade Glioma. N Engl J Med. 2023 Jun 4. doi: 10.1056/NEJMoa2304194. Epub ahead of print. PMID: 37272516.
2)

Targeted Options for Glioma Looking Good. Cancer Discov. 2023 Jun 5:OF1. doi: 10.1158/2159-8290.CD-ND2023-0004. Epub ahead of print. PMID: 37276325.
3)

Mellinghoff IK, Lu M, Wen PY, Taylor JW, Maher EA, Arrillaga-Romany I, Peters KB, Ellingson BM, Rosenblum MK, Chun S, Le K, Tassinari A, Choe S, Toubouti Y, Schoenfeld S, Pandya SS, Hassan I, Steelman L, Clarke JL, Cloughesy TF. Vorasidenib and ivosidenib in IDH1-mutant low-grade glioma: a randomized, perioperative phase 1 trial. Nat Med. 2023 Mar;29(3):615-622. doi: 10.1038/s41591-022-02141-2. Epub 2023 Feb 23. PMID: 36823302.
4)

Murali P, Karuppasamy R. Imidazole and Biphenyl Derivatives as Anti-cancer Agents for Glioma Therapeutics: Computational Drug Repurposing Strategy. Anticancer Agents Med Chem. 2023;23(9):1085-1101. doi: 10.2174/1871520623666230125090815. PMID: 36698225.
5)

Poonan P, Peters XQ, Soliman MES, Alahmdi MI, Abo-Dya NE. Pharmacophore-based Identification of Potential Mutant Isocitrate Dehydrogenases I/2 Inhibitors: An Explorative Avenue in Cancer Drug Design. Anticancer Agents Med Chem. 2023;23(8):953-966. doi: 10.2174/1871520623666221129163001. PMID: 36453510.
6)

Mellinghoff IK, Penas-Prado M, Peters KB, Burris HA 3rd, Maher EA, Janku F, Cote GM, de la Fuente MI, Clarke JL, Ellingson BM, Chun S, Young RJ, Liu H, Choe S, Lu M, Le K, Hassan I, Steelman L, Pandya SS, Cloughesy TF, Wen PY. Vorasidenib, a Dual Inhibitor of Mutant IDH1/2, in Recurrent or Progressive Glioma; Results of a First-in-Human Phase I Trial. Clin Cancer Res. 2021 Aug 15;27(16):4491-4499. doi: 10.1158/1078-0432.CCR-21-0611. Epub 2021 Jun 2. PMID: 34078652; PMCID: PMC8364866.
7)

Poonan P, Agoni C, Soliman MES. Dual-Knockout of Mutant Isocitrate Dehydrogenase 1 and 2 Subtypes Towards Glioma Therapy: Structural Mechanistic Insights on the Role of Vorasidenib. Chem Biodivers. 2021 May 12. doi: 10.1002/cbdv.202100110. Epub ahead of print. PMID: 33982420.
8)

Molloy AR, Najac C, Viswanath P, Lakhani A, Subramani E, Batsios G, Radoul M, Gillespie AM, Pieper RO, Ronen SM. MR-detectable metabolic biomarkers of response to mutant IDH inhibition in low-grade glioma. Theranostics. 2020 Jul 9;10(19):8757-8770. doi: 10.7150/thno.47317. PMID: 32754276; PMCID: PMC7392019.

Glioma biomarker

Glioma biomarker

1p/19q co-deletion.

ATRX.

BRAF.

CDKN2A.

Chromosome 7 Gain and Chromosome 10 Loss

EGFR

H3F3A.

H3K27M

IDH1 and IDH2.

MAPK Pathway

MGMT

MN1

MYB.

TERT.

TP53.

see Glioblastoma biomarker.

Diffuse gliomas exhibits different molecular and genetic profiles with a wide range of heterogeneity and prognosis. Recently, molecular parameters including ATRX gene mutation, P53, and IDH mutation status or absence or presence of 1p/19q co-deletion have become a crucial part of diffuse glioma diagnosis. Shabanzadeh Nejabad et al. tried to analyze the routine practice of the above-mentioned molecular markers focusing on the IHC method in cases of adult diffuse gliomas to evaluate their utility in the integrated diagnosis of adult diffuse gliomas. Totally, 134 cases of adult diffuse glioma were evaluated. Using the IHC method, 33,12, and 12 cases of IDH mutant Astrocytoma grade 2, 3, 4, and 45 cases of glioblastoma, IDH wild type, were molecularly diagnosed. By adding the FISH study for 1p/19q co-deletion, 9 and 8 cases of oligodendroglioma grades 2 and 3 also were included. Two IDH mutant cases were negative for IDH1 in IHC but revealed a positive mutation in further molecular testing. Finally, we were not able to incorporate a complete integrated diagnosis in 16/134(11.94%) of cases. The main molecularly unclassified group was histologically high-grade diffuse glial tumors in patients less than 55 years old and negative IDH1 immunostaining. P53 was positive in 23/33 grade 2, 4/12 grade 3, and 7/12 grade 4 astrocytomas, respectively. Four out of 45 glioblastomas showed positive immunostain, and all oligodendrogliomas were negative. In conclusion, a panel of IHC markers for IDH1 R132H, P53, and ATRX significantly improves the molecular classification of adult diffuse gliomas in daily practice and can be used as a tool to select limited cases for co-deletion testing in the low resources area 1).

Nakae et al., previously investigated IDH1/2 and TP53 mutations via Sanger sequencing for adult supratentorial gliomas and reported that PCR-based sequence analysis classified gliomas into three genetic subgroups that have a strong association with patient prognosis: IDH mutant gliomas without TP53 mutations, IDH and TP53 mutant gliomas, and IDH-wildtype gliomas. Furthermore, this analysis had a strong association with patient prognosis. To predict genetic subgroups prior to initial surgery, we retrospectively investigated preoperative radiological data using CT and MRI, including MR spectroscopy (MRS), and evaluated positive 5-aminolevulinic acid (5-ALA) fluorescence as an intraoperative factor. We subsequently compared these factors to differentiate each genetic subgroup. Multiple factors such as age at diagnosis, tumor location, gadolinium enhancement, 5-ALA fluorescence, and several tumor metabolites according to MRS, such as myo-inositol (myo-inositol/total choline) or lipid20, were statistically significant factors for differentiating IDH mutant and wild type, suggesting that these two subtypes have totally distinct characteristics. In contrast, only calcification, laterality, and lipid13 (lipid13/total Choline) were statistically significant parameters for differentiating TP53 wild-type and mutant in IDH mutant gliomas. In this study, we detected several pre- and intraoperative factors that enabled us to predict genetic subgroups for adult supratentorial gliomas and clarified that lipid13 quantified by MRS is the key tumor metabolite that differentiates TP53 wild-type and mutant in IDH mutant gliomas. These results suggested that each genetic subtype in gliomas selects the distinct lipid synthesis pathways in the process of tumorigenesis 2).

Glioma grading and classification, today based on histological features, is not always easy to interpret and diagnosis partly relies on the personal experience of the neuropathologists. The most important feature of the classification is the aimed correlation between tumor grade and prognosis. However, in the clinical reality, large variations exist in the survival of patients concerning both glioblastomas and low-grade gliomas. Thus, there is a need for biomarkers for a more reliable classification of glioma tumors as well as for prognosis.

Sorting and grading of glial tumors by the WHO grade classification provide clinicians with guidance as to the predicted course of the disease and choice of treatment. Nonetheless, histologically identical tumors may have very different outcome and response to treatment. Molecular biomarkers that carry both diagnostic and prognostic information add useful tools to traditional classification by redefining tumor subtypes within each WHO category. Therefore, molecular markers have become an integral part of tumor assessment in modern neurooncology and biomarker status now guides clinical decisions in some subtypes of gliomas. The routine assessment of IDH status improves histological diagnostic accuracy by differentiating diffuse glioma from reactive gliosis. It carries a favorable prognostic implication for all glial tumors and it is predictive for chemotherapeutic response in anaplastic oligodendrogliomas with 1p/19q co-deletion chromosomes. Glial tumors that contain chromosomal codeletion of 1p/19q are defined as tumors of oligodendroglial lineage and have favorable prognosis. MGMT promoter methylation is a favorable prognostic marker in astrocytic high-grade gliomas and it is predictive for chemotherapeutic response in anaplastic gliomas with wild-type IDH1/2 and in elderly glioblastoma 3).

The growing awareness that histologically indistinguishable tumors can be divided into more precise and biologically relevant subgroups has demanded a more global routine approach to biomarker assessment. These considerations have begun to intersect with the decreasing costs and availability of genome-wide analysis tools and, thus, incorporation into routine practice 4).

The Metabolomics profiling of glioma tissue as well as serum may be a valuable tool in the search for latent biomarkers for future characterization of malignant glioma 5).

In a article, Li et al. from Nanjing provided an overview of how Long non-coding RNAs (lncRNAs) regulate cellular processes in glioma, enumerated the lncRNAs that may act as glioma biomarkers, and showed their potential clinical implications 6).

see also Glioma diagnosis.

Glioma shed extracellular vesicles (EVs), which invade the surrounding tissue and circulate within both the cerebrospinal fluid and the systemic circulation. These tumor-derived EVs and their content serve as an attractive source of biomarkers.

In a review, Hochberg et al., discuss the current state of the art of biomarkers for glioma with emphasis on their EV derivation 7).

A study identified an 18-cytokine signature for distinguishing glioma sera from normal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology 8).

Shi et al., from Hangzhou, Department of Neurosurgery, Changhai Hospital, Second Military Medical University, Shanghai. Department of Neurosurgery, Huai’an Second People’s Hospital, The Affiliated Huai’an Hospital of Xuzhou Medical University, Huai’an, China, extracted data sets from the Gene Expression Omnibus data set by using “glioma” as the keyword. Then, a coexpression module was constructed with the help of Weighted Gene Coexpression Network Analysis software. Besides, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the genes in these modules. As a result, the critical modules and target genes were identified. Eight coexpression modules were constructed using the 4,000 genes with a high expression value of the total 141 glioma samples. The result of the analysis of the interaction among these modules showed that there was a high scale independence degree among them. The GO and KEGG enrichment analyses showed that there was a significant difference in the enriched terms and degree among these eight modules, and module 5 was identified as the most important module. Besides, the pathways it was enriched in, hsa04510: Focal adhesion and hsa04610: Complement and coagulation cascades, were determined as the most important pathways. In summary, module 5 and the pathways it was enriched in, hsa04510: Focal adhesion and has 04610: Complement and coagulation cascades, have the potential to serve as glioma biomarkers 9).

Eckel-Passow et al., defined five glioma molecular groups with the use of three alterations: mutations in the telomerase reverse transcriptase TERT promoter, mutations in IDH, and codeletion of chromosome arms 1p19q (1p/19q co-deletion). They tested the hypothesis that within groups based on these features, tumors would have similar clinical variables, acquired somatic alterations, and germline variants.

They scored tumors as negative or positive for each of these markers in 1087 gliomas and compared acquired alterations and patient characteristics among the five primary molecular groups. Using 11,590 controls, they assessed associations between these groups and known glioma germline variants.

Among 615 grade II or III gliomas, 29% had all three alterations (i.e., were triple-positive), 5% had TERT and IDH mutations, 45% had only IDH mutations, 7% were triple-negative, and 10% had only TERT mutations; 5% had other combinations. Among 472 grade IV gliomas, less than 1% were triple-positive, 2% had TERT and IDH mutations, 7% had only IDH mutations, 17% were triple-negative, and 74% had only TERT mutations. The mean age at diagnosis was lowest (37 years) among patients who had gliomas with only IDH mutations and was highest (59 years) among patients who had gliomas with only TERT mutations. The molecular groups were independently associated with overall survival among patients with grade II or III gliomas but not among patients with grade IV gliomas. The molecular groups were associated with specific germline variants.

Gliomas were classified into five principal groups on the basis of three tumor markers. The groups had different ages at onset, overall survival, and associations with germline variants, which implies that they are characterized by distinct mechanisms of pathogenesis 10).

Long non-coding RNA in glioma

see Long non-coding RNA in glioma.

References

1)

Shabanzadeh Nejabad Z, Mabroukzadeh Kavari H, Saffar H, Tavangar SM, Sefidbakht S, Khoshnevisan A, Zare-Mirzaie A, Vasei M, Jafari E, Yaghmaii M, Saffar H. Practice of IDH1, ATRX, and P53 Immunohistochemistry in Integrated Diagnosis of Adult Diffuse Gliomas: Single Center Study. Appl Immunohistochem Mol Morphol. 2023 Jun 6. doi: 10.1097/PAI.0000000000001135. Epub ahead of print. PMID: 37278280.
2)

Nakae S, Murayama K, Sasaki H, Kumon M, Nishiyama Y, Ohba S, Adachi K, Nagahisa S, Hayashi T, Inamasu J, Abe M, Hasegawa M, Hirose Y. Prediction of genetic subgroups in adult supra tentorial gliomas by pre- and intraoperative parameters. J Neurooncol. 2016 Nov 11. [Epub ahead of print] PubMed PMID: 27837434.
3)

Siegal T. Clinical Relevance of Prognostic and Predictive Molecular Markers in Gliomas. Adv Tech Stand Neurosurg. 2016;43:91-108. doi: 10.1007/978-3-319-21359-0_4. PubMed PMID: 26508407.
4)

Diamandis P, Aldape KD. Insights From Molecular Profiling of Adult Glioma. J Clin Oncol. 2017 Jul 20;35(21):2386-2393. doi: 10.1200/JCO.2017.73.9516. Epub 2017 Jun 22. Review. PubMed PMID: 28640696.
5)

Mörén L, Bergenheim AT, Ghasimi S, Brännström T, Johansson M, Antti H. Metabolomic Screening of Tumor Tissue and Serum in Glioma Patients Reveals Diagnostic and Prognostic Information. Metabolites. 2015 Sep 15;5(3):502-520. PubMed PMID: 26389964.
6)

Li J, Zhu Y, Wang H, Ji X. Targeting Long non-coding RNA in Glioma: A Pathway Perspective. Mol Ther Nucleic Acids. 2018 Oct 2;13:431-441. doi: 10.1016/j.omtn.2018.09.023. [Epub ahead of print] Review. PubMed PMID: 30388617.
7)

Hochberg FH, Atai NA, Gonda D, Hughes MS, Mawejje B, Balaj L, Carter RS. Glioma diagnostics and biomarkers: an ongoing challenge in the field of medicine and science. Expert Rev Mol Diagn. 2014 May;14(4):439-52. doi: 10.1586/14737159.2014.905202. Review. PubMed PMID: 24746164; PubMed Central PMCID: PMC5451266.
8)

Nijaguna MB, Patil V, Hegde AS, Chandramouli BA, Arivazhagan A, Santosh V, Somasundaram K. An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals. PLoS One. 2015 Sep 21;10(9):e0137524. doi: 10.1371/journal.pone.0137524. eCollection 2015. PubMed PMID: 26390214.
9)

Shi T, Chen J, Li J, Yang BY, Zhang QL. Identification of key gene modules and pathways of human glioma through coexpression network. J Cell Physiol. 2018 Aug 1. doi: 10.1002/jcp.27059. [Epub ahead of print] PubMed PMID: 30067869.
10)

Eckel-Passow JE, Lachance DH, Molinaro AM, Walsh KM, Decker PA, Sicotte H, Pekmezci M, Rice T, Kosel ML, Smirnov IV, Sarkar G, Caron AA, Kollmeyer TM, Praska CE, Chada AR, Halder C, Hansen HM, McCoy LS, Bracci PM, Marshall R, Zheng S, Reis GF, Pico AR, O’Neill BP, Buckner JC, Giannini C, Huse JT, Perry A, Tihan T, Berger MS, Chang SM, Prados MD, Wiemels J, Wiencke JK, Wrensch MR, Jenkins RB. Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors. N Engl J Med. 2015 Jun 25;372(26):2499-508. doi: 10.1056/NEJMoa1407279. Epub 2015 Jun 10. PubMed PMID: 26061753; PubMed Central PMCID: PMC4489704.

Craniopharyngioma (CP)

Craniopharyngioma (CP)

A craniopharyngioma (CP) is an embryonic malformation of the sellar region and parasellar region.

Its relation to Rathke’s cleft cyst (RCC) is controversial, and both lesions have been hypothesized to lie on a continuum of ectodermal cystic lesions of the sellar region.

Jakob Erdheim (1874-1937) was a Viennese pathologist who identified and defined a category of pituitary tumors known as craniopharyngiomas. He named these lesions “hypophyseal duct tumors” (Hypophysenganggeschwülste), a term denoting their presumed origin from cell remnants of the hypophyseal duct, the embryological structure through which Rathke’s pouch migrates to form part of the pituitary gland. He described the two histological varieties of these lesions as the adamantinomatous and the squamous-papillary types. He also classified the different topographies of craniopharyngiomas along the hypothalamus-pituitary axis. Finally, he provided the first substantial evidence for the functional role of the hypothalamus in the regulation of metabolism and sexual functions. Erdheim’s monograph on hypophyseal duct tumors elicited interest in the clinical effects and diagnosis of pituitary tumors. It certainly contributed to the development of pituitary surgery and neuroendocrinology. Erdheim’s work was greatly influenced by the philosophy and methods of research introduced to the Medical School of Vienna by the prominent pathologist Carl Rokitansky. Routine practice of autopsies in all patients dying at the Vienna Municipal Hospital (Allgemeines Krankenhaus), as well as the preservation of rare pathological specimens in a huge collection stored at the Pathological-Anatomical Museum, represented decisive policies for Erdheim’s definition of a new category of epithelial hypophyseal growths. Because of the generalized use of the term craniopharyngioma, which replaced Erdheim’s original denomination, his seminal work on hypophyseal duct tumors is only referenced in passing in most articles and monographs on this tumor.

Jakob Erdheim should be recognized as the true father of craniopharyngiomas 1).

Epidemiology

Craniopharyngioma epidemiology.

Origin

Its relation to Rathke’s cleft cyst (RCC) is controversial, and both lesions have been hypothesized to lie on a continuum of cystic ectodermal lesions of the sellar region.

It grows close to the optic nerve, hypothalamus and pituitary gland.

Craniopharyngiomas frequently grow from remnants of the Rathke pouch, which is located on the cisternal surface of the hypothalamic region. These lesions can also extend elsewhere in the infundibulohypophyseal axis.

These tumors can also grow from the infundibulum or tuber cinereum on the floor of the third ventricle, developing exclusively into the third ventricle.

Classification

Craniopharyngioma Classification.

Molecular and genetic markers

Genetic and immunological markers show variable expression in different types of Craniopharyngioma. BRAF is implicated in tumorigenesis in papillary Craniopharyngioma (pCP), whereas CTNNB1 and EGFR are often overexpressed in adamantinomatous Craniopharyngioma (aCP) and VEGF is overexpressed in aCP and Craniopharyngioma recurrence. Targeted treatment modalities inhibiting thesepathways can shrink or halt progression of CP. In addition, Epidermal growth factor receptor tyrosine kinase inhibitors may sensitize tumors to radiation therapy. These – drugs show promise in medical management and neoadjuvant therapy for CP. Immunotherapy, including anti-interleukin 6 (IL-6) drugs and interferon treatment, are also effective in managing tumor growth. Ongoing – clinical trials in CP are limited but are testing BRAF/MET inhibitors and IL-6 monoclonal antibodies.

Genetic and immunological markers show variable expression in different subtypes of CP. Several current molecular treatments have shown some success in the management of this disease. Additional clinical trials and targeted therapies will be important to improve CP patient outcomes 2).

Craniopharyngioma Natural History

Craniopharyngioma natural history.

Clinical Features

see Craniopharyngioma Clinical Features.

Diagnosis

see Craniopharyngioma Diagnosis.

Differential diagnosis

Rathke’s cleft cyst.

ependymoma, pilocytic astrocytoma, choroid plexus papilloma (CPP), craniopharyngioma, primitive neuroectodermal tumor (PNET), choroid plexus carcinoma (CPC), immature teratoma, atypical teratoid rhabdoid tumor (AT/RT), anaplastic astrocytoma, and gangliocytoma.

Compared with craniopharyngiomas, sellar gliomas presented with a significantly lower ratio of visual disturbances, growth hormone deficiencies, lesion cystic changes, and calcification. Sellar gliomas had significantly greater effects on the patients’ mentality and anatomical brain stem involvement 3).

Co-occurrence

Simultaneous sellar-suprasellar craniopharyngioma and intramural clival chordoma, successfully treated by a single staged, extended, fully endoscopic endonasal approach, which required no following adjuvant therapy is reported 4).

Treatment

see Craniopharyngioma treatment

Outcome

see Craniopharyngioma outcome

Books

Craniopharyngioma: Surgical Treatment.

10 Selected Works

Craniopharyngioma Selected Works.

Case series

see Craniopharyngioma case series.

Case reports

see Craniopharyngioma case reports.

Videos

Craniopharyngioma Videos

1)

Pascual JM, Rosdolsky M, Prieto R, Strauβ S, Winter E, Ulrich W. Jakob Erdheim (1874-1937): father of hypophyseal-duct tumors (craniopharyngiomas). Virchows Arch. 2015 Jun 19. [Epub ahead of print] PubMed PMID: 26089144.
2)

Reyes M, Taghvaei M, Yu S, Sathe A, Collopy S, Prashant GN, Evans JJ, Karsy M. Targeted Therapy in the Management of Modern Craniopharyngiomas. Front Biosci (Landmark Ed). 2022 Apr 20;27(4):136. doi: 10.31083/j.fbl2704136. PMID: 35468695.
3)

Deng S, Li Y, Guan Y, Xu S, Chen J, Zhao G. Gliomas in the Sellar Turcica Region: A Retrospective Study Including Adult Cases and Comparison with Craniopharyngioma. Eur Neurol. 2014 Dec 18;73(3-4):135-143. [Epub ahead of print] PubMed PMID: 25531372.
4)

Iacoangeli M, Rienzo AD, Colasanti R, Scarpelli M, Gladi M, Alvaro L, Nocchi N, Scerrati M. A rare case of chordoma and craniopharyngioma treated by an endoscopic endonasal, transtubercular transclival approach. Turk Neurosurg.2014;24(1):86-9. doi: 10.5137/1019-5149.JTN.7237-12.0. PubMed PMID: 24535799.

Glioblastoma immunotherapy

Glioblastoma immunotherapy

Immunotherapy has shown promising success in a variety of solid tumor types, but efficacy in glioblastoma is yet to be demonstrated. Barriers to the success of immunotherapy in glioblastoma include a heterogeneous tumor cell population, a highly immunosuppressive microenvironment, and the blood-brain barrier, to name a few. Several immunotherapeutic approaches are actively being investigated and developed to overcome these limitations 1)

Immunotherapy approaches include the use of checkpoint inhibitors, chimeric antigen receptor (CAR) T-Cell therapy, vaccine-based approaches, viral vector therapies, and cytokine-based treatment 2)

Future strategies to ameliorate the efficacy of immunotherapy and facilitate clinical translation will be provided to address the unmet medical needs of GBM 3).

With the success of immunotherapy in other aggressive cancers such as advanced melanoma and advanced non-small cell lung cancer, glioblastoma has been brought to the forefront of immunotherapy research 4).

Immunotherapy, has become a promising strategy with the ability to penetrate the blood-brain barrier since the pioneering discovery of lymphatics in the central nervous system.

The anti-tumoral contribution of Gamma delta T cells depends on their activation and differentiation into effectors. This depends on different molecules and membrane receptors, which conditions their physiology. Belghali et al. aimed to determine the phenotypic characteristics of γδT cells in glioblastoma (Glioblastoma) according to five layers of membrane receptors.

Among ten Glioblastoma cases initially enrolled, five of them who had been confirmed by pathological examination and ten healthy controls underwent phenotyping of peripheral γδT cells by flow cytometry, using the following staining: αβTCR, γδTCR, CD3, CD4, CD8, CD16, CD25, CD27, CD28, CD45, CD45RA, CD56, NKG2D, CD272(BTLA) and CD279(PD-1).

Compared to controls, the results showed no significant change in the number of γδT cells. However, they noted a decrease of double-negative (CD4- CD8- ) Tγδ cells and an increase of naive γδT cells, a lack of CD25 expression, a decrease of the expression of CD279, and a remarkable, but not significant increase in the expression of the CD27 and CD28 costimulation markers. Among γδT cell subsets, the number of Vδ2 decreased in Glioblastoma and showed no significant difference in the expression of CD16, CD56, and NKG2D. In contrast, the number of Vδ1 increased in Glioblastoma with overexpression of CD16, CD56, and NKG2D.

The results showed that γδT cells are prone to adopt a pro-inflammatory profile in the Glioblastoma’s context, which suggests that they might be a potential tool to consider in T cell-based glioblastoma immunotherapy. However, this requires additional investigation on a larger sample size 5).

A limited number of phase III trials have been completed for checkpoint inhibitor, vaccine, as well as gene therapies, and have been unable to show improvement in survival outcomes. Nevertheless, these trials have also shown these strategies to be safe and promising with further adaptations. Further large-scale studies for chimeric antigen receptors T cell therapies and viral therapies are anticipated. Many current trials are broadening the number of antigens targeted and modulating the microtumor microenvironment to abrogate early mechanisms of resistance. Future Glioblastoma treatment will also likely require synergistic effects by combination regimens 6).

As the pioneer and the main effector cells of immunotherapy, T cells play a key role in tumor immunotherapy.

For glioblastoma, immunotherapy has not been as effective 7) , the T cells in Glioblastoma microenvironment are inhibited by the highly immunosuppressive environment of Glioblastoma, (cold tumor microenvironment) posing huge challenges to T cell-based Glioblastoma immunotherapy 8) 9) 10).

As these tumors do not attract and activate immune cells, approaches based on educating immune cells on killing tumor cells, utilized in “hot” immuno-activating cancers, have not been successful in brain tumor clinical trials. In this context, the use of immune-stimulatory approaches, like therapy with oncolytic viruses (OV), is promising 11)

Xu et al. detailed the management of gliomas and previous studies assessing different immunotherapies in gliomas, despite the fact that the associated clinical trials have not been completed yet. Moreover, several drugs that have undergone clinical trials are listed as novel strategies for future application; however, these clinical trials have indicated limited efficacy in glioma. Therefore, additional studies are warranted to evaluate novel therapeutic approaches in glioma treatment 12).

Earlier forms of immune-based platforms have now given way to more current approaches, including chimeric antigen receptor T-cells, personalized neoantigen vaccines, oncolytic viruses, and checkpoint blockade 13).

Critical to mapping a path forward will be the systematic characterization of the immunobiology of glioblastoma utilizing currently available, state of the art technologies. Therapeutic approaches aimed at driving effector immune cells into the glioblastoma microenvironment as well as overcoming immunosuppressive myeloid cells, physical factors, and cytokines, as well as limiting the potentially detrimental, iatrogenic impact of dexamethasone, will likely be required for the potential of anti-tumor immune responses to be realized for glioblastoma 14).

Patients with glioblastoma (Glioblastoma) exhibit a complex state of immunodeficiency involving multiple mechanisms of local, regional, and systemic immune suppression and tolerance. These pathways are now being identified and their relative contributions explored. Delineating how these pathways are interrelated is paramount to effectively implementing immunotherapy for Glioblastoma 15).

Progress in the development of these therapies for glioblastoma has been slow due to the lack of immunogenic antigen targets that are expressed uniformly and selectively by gliomas.

Trials have revealed promising trends in overall survival and progression free survival for patients with glioblastoma, and have paved the way for ongoing randomized controlled trials 16) 17)

Some clinical trials are reaching phase III. Significant progress has been made in unraveling the molecular and genetic heterogeneity of glioblastoma multiforme and its implications to disease prognosis. There is now consensus related to the critical need to incorporate tumor heterogeneity into the design of therapeutic approaches. Recent data also indicates that an efficacious treatment strategy will need to be combinatorial and personalized to the tumor genetic signature 18).

A recurrent theme of this work is that immunotherapy is not a one-size-fits-all solution. Rather, dynamic, tumor-specific interactions within the tumor microenvironment continually shape the immunologic balance between tumor elimination and escape. High-grade gliomas are a particularly fascinating example. These aggressive, universally fatal tumors are highly resistant to radiation and chemotherapy and inevitably recur after surgical resection. Located in the immune-privileged central nervous system, high-grade gliomas also employ an array of defenses that serve as direct impediments to immune attack. Despite these challenges, vaccines have shown activity against high-grade gliomas and anecdotal, preclinical, and early clinical data bolster the notion that durable remission is possible with immunotherapy. Realizing this potential, however, will require an approach tailored to the unique aspects of glioma biology 19).

Clinical experiences with active specific immunotherapy demonstrate feasibility, safety and most importantly, but incompletely understood, prolonged long-term survival in a fraction of the patients. In relapsed patients, Van Gool et al developed an immunotherapy schedule and categorized patients into clinically defined risk profiles. He learned how to combine immunotherapy with standard multimodal treatment strategies for newly diagnosed glioblastoma multiforme patients. The developmental program allows further improvements related to newest scientific insights. Finally, he developed a mode of care within academic centers to organize cell therapy for experimental clinical trials in a large number of patients 20).

Immunostimulating oligodeoxynucleotides containing unmethylated cytosine–guanosine motifs (CpG-ODN) have shown a promising efficacy in several cancer models when injected locally. A previous phase II study of CpG-ODN in patients with Glioblastoma recurrence (Glioblastoma) has suggested some activity and has shown a limited toxicity. This multicentre single-blinded randomised phase II trial was designed to study the efficacy of a local treatment by CpG-ODN in patients with de novo glioblastomas.

Patients with a newly diagnosed glioblastoma underwent large surgical resection and CpG-ODN was randomly administrated locally around the surgical cavity. The patients were then treated according to standard of care (SOC) with radiotherapy and temozolomide. The primary objective was 2-year survival. Secondary outcomes were progression free survival (PFS), and tolerance.

Eighty-one (81) patients were randomly assigned to receive CpG-ODN plus SOC (39 patients) or SOC (42 patients). The 2-year overall survival was 31% (19%; 49%) in the CpG-ODN arm and 26% (16%; 44%) in the SOC arm. The median PFS was 9 months in the CpG-ODN arm and 8.5 months in the SOC arm. The incidence of adverse events was similar in both arms; although fever and post-operative haematoma were more frequent in the CpG-ODN arm.

Local immunotherapy with CpG-ODN injected into the surgical cavity after tumour removal and followed by SOC, although well tolerated, does not improve survival of patients with newly diagnosed Glioblastoma 21).

Epidermal growth factor receptor 3 (EGFRvIII) is present in approximately one-third of glioblastoma (Glioblastoma) patients. It is never found in normal tissues; therefore, it represents a candidate target for glioblastoma immunotherapy. PEPvIII, a peptide sequence from EGFRvIII, was designed to represent a target of glioma and is presented by MHC I/II complexes. Dendritic cells (DCs) have great potential to sensitize CD4+ T and CD8+ T cells to precisely target and eradicate Glioblastoma.

Li et al. show that PEPvIII could be loaded by DCs and presented to T lymphocytes, especially PEPvIII-specific CTLs, to precisely kill U87-EGFRvIII cells. In addition to inhibiting proliferation and inducing the apoptosis of U87-EGFRvIII cells, miR-326 also reduced the expression of TGF-β1 in the tumour environment, resulting in improved efficacy of T cell activation and killing via suppressing the SMO/Gli2 axis, which at least partially reversed the immunosuppressive environment. Furthermore, combining the EGFRvIII-DC vaccine with miR-326 was more effective in killing U87-EGFRvIII cells compared with the administration of either one alone. This finding suggested that a DC-based vaccine combined with miR-326 may induce more powerful anti-tumour immunity against Glioblastoma cells that express a relevant antigen, which provides a promising approach for Glioblastoma immunotherapy 22).

Reviews

Yuan et al. provided an overview of the basic knowledge underlying immune targeting and promising immunotherapeutic strategies including CAR T cells, oncolytic viruses, cancer vaccines, and checkpoint blockade inhibitors that have been recently investigated in glioblastoma. Current clinical trials and previous clinical trial findings are discussed, shedding light on novel strategies to overcome various limitations and challenges 23).

Rui Y, Green JJ. Overcoming delivery barriers in immunotherapy for glioblastoma. Drug Deliv Transl Res. 2021 May 30. doi: 10.1007/s13346-021-01008-2. Epub ahead of print. PMID: 34053034.

Glioblastoma Immune Checkpoint Inhibitor Therapy

Glioblastoma Immune Checkpoint Inhibitor Therapy

Glioblastoma CAR-T cell therapy

Glioblastoma CAR-T cell therapy

1)

Zaidi SE, Moelker E, Singh K, Mohan A, Salgado MA, Essibayi MA, Hotchkiss K, Shen S, Lee W, Sampson J, Khasraw M. Novel Immunotherapeutic Approaches for the Treatment of Glioblastoma. BioDrugs. 2023 May 31. doi: 10.1007/s40259-023-00598-2. Epub ahead of print. PMID: 37256535.
2)

Sener U, Ruff MW, Campian JL. Immunotherapy in Glioblastoma: Current Approaches and Future Perspectives. Int J Mol Sci. 2022 Jun 24;23(13):7046. doi: 10.3390/ijms23137046. PMID: 35806051; PMCID: PMC9266573.
3)

Bausart M, Préat V, Malfanti A. Immunotherapy for glioblastoma: the promise of combination strategies. J Exp Clin Cancer Res. 2022 Jan 25;41(1):35. doi: 10.1186/s13046-022-02251-2. PMID: 35078492; PMCID: PMC8787896.
4)

Yu MW, Quail DF. Immunotherapy for Glioblastoma: Current Progress and Challenges. Front Immunol. 2021 May 13;12:676301. doi: 10.3389/fimmu.2021.676301. Erratum in: Front Immunol. 2021 Oct 07;12:782687. PMID: 34054867; PMCID: PMC8158294.
5)

Belghali MY, El Moumou L, Hazime R, Brahimi M, El Marrakchi M, Belaid HA, Benali SA, Khouchani M, Ba-M’hamed S, Admou B. Phenotypic characterization of human peripheral γδT-Cell subsets in glioblastoma. Microbiol Immunol. 2022 Jun 19. doi: 10.1111/1348-0421.13016. Epub ahead of print. PMID: 35718749.
6)

Zhang M, Choi J, Lim M. Advances in Immunotherapies for Gliomas. Curr Neurol Neurosci Rep. 2022 Feb 2. doi: 10.1007/s11910-022-01176-9. Epub ahead of print. PMID: 35107784.
7)

Bovenberg MS, Degeling MH, Tannous BA. Cell-based immunotherapy against gliomas: from bench to bedside. Mol Ther. 2013 Jul;21(7):1297-305. doi: 10.1038/mt.2013.80. Epub 2013 May 7. PMID: 23648695; PMCID: PMC3702108.
8)

Wang H, Zhou H, Xu J, Lu Y, Ji X, Yao Y, Chao H, Zhang J, Zhang X, Yao S, Wu Y, Wan J. Different T-cell subsets in glioblastoma multiforme and targeted immunotherapy. Cancer Lett. 2020 Oct 3:S0304-3835(20)30498-5. doi: 10.1016/j.canlet.2020.09.028. Epub ahead of print. PMID: 33022290.
9)

Lim M., Xia Y., Bettegowda C., Weller M. Current state of immunotherapy for glioblastoma. Nat. Rev. Clin. Oncol. 2018;15:422–442. doi: 10.1038/s41571-018-0003-5.
10)

Reardon D.A., Wucherpfennig K., Chiocca E.A. Immunotherapy for glioblastoma: On the sidelines or in the game? Discov. Med. 2017;24:201–208.
11)

Iorgulescu JB, Reardon DA, Chiocca EA, Wu CJ. Immunotherapy for glioblastoma: going viral. Nat Med. 2018 Aug;24(8):1094-1096. doi: 10.1038/s41591-018-0142-3. PMID: 30082860; PMCID: PMC6443579.
12)

Xu S, Tang L, Li X, Fan F, Liu Z. Immunotherapy for glioma: current management and future application. Cancer Lett. 2020 Feb 7. pii: S0304-3835(20)30056-2. doi: 10.1016/j.canlet.2020.02.002. [Epub ahead of print] PubMed PMID: 32044356.
13)

Fecci PE, Sampson JH. The current state of immunotherapy for gliomas: an eye toward the future. J Neurosurg. 2019 Sep 1;131(3):657-666. doi: 10.3171/2019.5.JNS181762. Review. PubMed PMID: 31473668.
14)

Reardon DA, Wucherpfennig K, Chiocca EA. Immunotherapy for glioblastoma: on the sidelines or in the game? Discov Med. 2017 Nov;24(133):201-208. PubMed PMID: 29278673.
15)

Jackson CM, Lim M. Immunotherapy for glioblastoma: playing chess, not checkers. Clin Cancer Res. 2018 Apr 24. pii: clincanres.0491.2018. doi: 10.1158/1078-0432.CCR-18-0491. [Epub ahead of print] PubMed PMID: 29691293.
16)

Thomas AA, Fisher JL, Ernstoff MS, Fadul CE. Vaccine-based immunotherapy for glioblastoma. CNS Oncol. 2013 Jul;2(4):331-49. doi: 10.2217/cns.13.29. PubMed PMID: 25054578.
17)

Agrawal NS, Miller R Jr, Lal R, Mahanti H, Dixon-Mah YN, DeCandio ML, Vandergrift WA 3rd, Varma AK, Patel SJ, Banik NL, Lindhorst SM, Giglio P, Das A. Current Studies of Immunotherapy on Glioblastoma. J Neurol Neurosurg. 2014 Apr 5;1(1). pii: 21000104. PubMed PMID: 25346943.
18)

Kamran N, Calinescu A, Candolfi M, Chandran M, Mineharu Y, Assad AS, Koschmann C, Nunez F, Lowenstein P, Castro M. Recent advances and future of immunotherapy for glioblastoma. Expert Opin Biol Ther. 2016 Jul 13. [Epub ahead of print] PubMed PMID: 27411023.
19)

Jackson CM, Lim M, Drake CG. Immunotherapy for Brain Cancer: Recent Progress and Future Promise. Clin Cancer Res. 2014 Apr 25. [Epub ahead of print] PubMed PMID: 24771646.
20)

Van Gool SW. Brain Tumor Immunotherapy: What have We Learned so Far? Front Oncol. 2015 Jun 17;5:98. eCollection 2015. Review. PubMed PMID: 26137448.
21)

Ursu R, Carpentier A, Metellus P, Lubrano V, Laigle-Donadey F, Capelle L, Guyotat J, Langlois O, Bauchet L, Desseaux K, Tibi A, Chinot O, Lambert J, Carpentier AF. Intracerebral injection of CpG oligonucleotide for patients with de novo glioblastoma-A phase II multicentric, randomised study. Eur J Cancer. 2017 Jan 28;73:30-37. doi: 10.1016/j.ejca.2016.12.003. [Epub ahead of print] PubMed PMID: 28142059.
22)

Li J, Wang F, Wang G, Sun Y, Cai J, Liu X, Zhang J, Lu X, Li Y, Chen M, Chen L, Jiang C. Combination epidermal growth factor receptor variant III peptide-pulsed dendritic cell vaccine with miR-326 results in enhanced killing on EGFRvIII-positive cells. Oncotarget. 2017 Feb 17. doi: 10.18632/oncotarget.15445. [Epub ahead of print] PubMed PMID: 28412740.
23)

Yuan B, Wang G, Tang X, Tong A, Zhou L. Immunotherapy of glioblastoma: recent advances and future prospects. Hum Vaccin Immunother. 2022 Mar 28:1-16. doi: 10.1080/21645515.2022.2055417. Epub ahead of print. PMID: 35344682.