Malignant Glioma with Neuronal Marker Expression : A Clinicopathological Study of 18 Cases

Kim, Hong Rye; Lee, Jae Jun; Lee, Jung-Il; Nam, Do Hyun; Suh, Yeon‐Lim; Seol, Ho Jun

doi:10.3340/jkns.2016.59.1.44

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…Mitosis and proliferative activity are reliable methods to determine the biological behaviour of tumours; therefore, studies continue to focus on relevant biological biomarkers for different tumour types. Currently, gene methylations are considered biomarkers in glial tumours [10]. In our study, we evaluated survivin and Ki-67 as potential indicators and performed comparative analysis to determine whether one was superior to the other in terms of distinguishing glial tumour grades.…”

Section: Resultsmentioning

confidence: 99%

A comparative histopathological and immunohistochemical study of Survivin and Ki-67 proteins in glial tumours

Topyalin

Budak

Özbay

et al. 2019

Biotechnology & Biotechnological Equipment

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Survivin is a bifunctional protein which regulates cell division and inhibits apoptosis. Survivin is a member of the inhibitor of apoptosis protein (IAP) family. Expression of survivin has been shown to be responsible for apoptosis and resistance to ionizing radiation. The aim of the present study was to investigate the association between À31 G/C promoter polymorphism, survivin protein and glial tumour grading, and to compare survivin versus Ki-67 as a marker. In this study, DNA was isolated from paraffin-embedded sections of 29 patients diagnosed with glial tumours. Survivin gene promoter À31 G/C polymorphism was investigated using PCR-RFLP. For the analysis, 10 mm sections were stained with survivin protein and Ki-67 antibody. Immunohistochemical staining was performed. Survivin showed a positive correlation with Ki-67 (r ¼ 0.604; p ¼ 0.001). The tumour grades correlated with survivin; however, the relationship was not statistically significant (r ¼ 0.345; p> 0.05). We found a significant correlation between tumour grades and Ki-67 (r ¼ 0.663; p < 0.01), suggesting that Ki-67 is a more sensitive marker compared to survivin.

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Section: Resultsmentioning

confidence: 99%

A comparative histopathological and immunohistochemical study of Survivin and Ki-67 proteins in glial tumours

Topyalin

Budak

Özbay

et al. 2019

Biotechnology & Biotechnological Equipment

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“…This observation is consistent with a recent study based on genomic variations 31 . Neuronal marker expression has been reported in malignant (grade III/IV) gliomas other than classical anaplastic gangliogliomas 32,33 . In our cohort, tumors expressing canonical neuronal markers like neurofilament (NEFL, NEFM, and NEFH) and synaptophysin (SYP) were significantly localized within the expression space of oligodendrogliomas (q-value < 0.015, Supplementary Fig.…”

Section: Identification Of Cancer-associated Genes Inmentioning

confidence: 99%

Identification of relevant genetic alterations in cancer using topological data analysis

et al. 2020

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Large-scale cancer genomic studies enable the systematic identification of mutations that lead to the genesis and progression of tumors, uncovering the underlying molecular mechanisms and potential therapies. While some such mutations are recurrently found in many tumors, many others exist solely within a few samples, precluding detection by conventional recurrence-based statistical approaches. Integrated analysis of somatic mutations and RNA expression data across 12 tumor types reveals that mutations of cancer genes are usually accompanied by substantial changes in expression. We use topological data analysis to leverage this observation and uncover 38 elusive candidate cancer-associated genes, including inactivating mutations of the metalloproteinase ADAMTS12 in lung adenocarcinoma. We show that ADAMTS12 −/− mice have a five-fold increase in the susceptibility to develop lung tumors, confirming the role of ADAMTS12 as a tumor suppressor gene. Our results demonstrate that data integration through topological techniques can increase our ability to identify previously unreported cancer-related alterations.

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Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

et al. 2023

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Background Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher’s exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage (http://www.wang-lab-hkust.com:3838/TMZEP). Conclusions We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs.

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Malignant Glioma with Neuronal Marker Expression : A Clinicopathological Study of 18 Cases

Cited by 3 publications

References 22 publications

A comparative histopathological and immunohistochemical study of Survivin and Ki-67 proteins in glial tumours

A comparative histopathological and immunohistochemical study of Survivin and Ki-67 proteins in glial tumours

Identification of relevant genetic alterations in cancer using topological data analysis

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

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