Evidence-based Treatment for Low-grade Glioma

Semmel, D.; Ware, Courtney; Kim, Jung Young; Peters, Katherine B.

doi:10.1016/j.soncn.2018.10.008

Cited by 7 publications

(6 citation statements)

References 30 publications

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“…The grade 2 glioma is the main type of low-grade glioma (LGG). Symptoms of LGG vary depending on the location and size of the tumor, mainly due to the mass effect [ 6 ]. Seizure is the most common clinical symptom, occurring in more than 90% of LGG patients at some stage of the disease, mostly in the frontal lobe of patients with oligodendroglioma [ 7 ].…”

Section: Discussionmentioning

confidence: 99%

A Model for Predicting Clinical Prognosis in Patients with WHO Grade 2 Glioma

Gao

Zhou

Wang

et al. 2022

Journal of Oncology

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Objectives. Although patients with grade 2 glioma have a relatively better prognosis and longer survival than those with high-grade glioma, there are still a number of patients with disappointing outcomes. In order to accurately predict the prognosis of patients, relevant risk factors were included in the analysis to establish a clinical prediction model so as to provide a basis for clinically individualized treatment. Methods. A retrospective study was conducted in patients diagnosed with grade 2 glioma. Data including clinical features, pathological type, molecular classification, neuroimaging examination, treatment, and survival were collected. The data sets were randomly assigned, with 80% of the data used for model building and 20% for validation. Cox proportional hazard regression analysis was used to construct the model using important risk factors and present it in the form of a nomogram. The nomogram was evaluated a using C-index and calibration chart. Results. A total of 160 patients were enrolled in this analysis, including 128 in the training group and 32 in the validation group. In the training group, eight important risk factors including preoperative KPS, the first presenting symptom, the extent of resection, the gross tumor size, 1p19q, IDH, radiotherapy, and chemotherapy were identified to construct the model. The C-index of the training group and the validation group was 0.832 and 0.801, respectively, indicating that the model had good prediction ability. The calibration charts of the two groups were drawn respectively, which showed that the calibration line and the standard line had a good consistency, which suggested that the model-predicted risk had a good consistency with the actual risk. Conclusions. Based on the data of our center, a nomogram prediction model with eight variables has been established as an off-the-rack tool and verified its accuracy, which can guide clinical work and provide consultation for patients.

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Section: Discussionmentioning

confidence: 99%

A Model for Predicting Clinical Prognosis in Patients with WHO Grade 2 Glioma

Gao

Zhou

Wang

et al. 2022

Journal of Oncology

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“…Based on molecular findings, new predictions for disease outcome can also be determined. For example, the presence of IDH1 mutations and 1p/19q co-deletions are associated with better survival outcomes for grade II, III, and IV gliomas [7,23,26,27], which may be relevant for determining treatment options for lower grade glioma patients with worse prognoses [7,26].…”

Section: Discussionmentioning

confidence: 99%

“…Treatment of low grade glioma generally consists of debulking surgery, radiation therapy, and sometimes adjuvant chemotherapy [7]. Treatment of grade III and IV gliomas consists of surgical resection followed by radiation and chemotherapy [3], with the extent of surgical resection being a major predictor of disease outcome [8].…”

Section: Introductionmentioning

confidence: 99%

A PTPmu Biomarker is Associated with Increased Survival in Gliomas

Johansen

Vincent

Gittleman

et al. 2019

IJMS

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An integrated approach has been adopted by the World Health Organization (WHO) for diagnosing brain tumors. This approach relies on the molecular characterization of biopsied tissue in conjunction with standard histology. Diffuse gliomas (grade II to grade IV malignant brain tumors) have a wide range in overall survival, from months for the worst cases of glioblastoma (GBM) to years for lower grade astrocytic and oligodendroglial tumors. We previously identified a change in the cell adhesion molecule PTPmu in brain tumors that results in the generation of proteolytic fragments. We developed agents to detect this cell surface-associated biomarker of the tumor microenvironment. In the current study, we evaluated the PTPmu biomarker in tissue microarrays and individual tumor samples of adolescent and young adult (n = 25) and adult (n = 69) glioma populations using a fluorescent histochemical reagent, SBK4-TR, that recognizes the PTPmu biomarker. We correlated staining with clinical data and found that high levels of the PTPmu biomarker correlate with increased survival of glioma patients, including those with GBM. Patients with high PTPmu live for 48 months on average, whereas PTPmu low patients live only 22 months. PTPmu high staining indicates a doubling of patient survival. Use of the agent to detect the PTPmu biomarker would allow differentiation of glioma patients with distinct survival outcomes and would complement current molecular approaches used in glioma prognosis.

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“…LGG is most commonly seen in young adults aged 35–44 years ( Ostrom et al, 2016 ). At present, the standard therapeutic schedules including surgical resection, adjuvant radiotherapy, and chemotherapy are mainly adopted, but the outcomes are always unfavorable ( Semmel et al, 2018 ). Cancers with same origins, pathologic stages, and clinical stages may have different molecular characterizations ( Friedman et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Characterization of the Ferroptosis-Related Genes for Prognosis and Immune Infiltration in Low-Grade Glioma

Yan

Liu

et al. 2022

Front. Genet.

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Background: Although ferroptosis has been validated to play a crucial role in some types of tumors, the influence of ferroptosis-related genes (FRGs) on the immune microenvironment in low-grade glioma (LGG) remains unclear. In this research, we screen the FRGs to assess the prognosis value and immune microenvironment in LGG, to provide reliable diagnosis and treatment evidence for the clinic.Methods: A total of 1,239 patients of LGG samples were selected for subsequent analyses from The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and the Repository of Molecular Brain Neoplasia Data datasets. Univariate Cox regression analysis was used to screen for prognostic FRGs. Consensus clustering was utilized to determine ferroptosis subtypes of LGG patients. Next, the prognostic model was constructed based on differentially expressed FRGs and validation in the validating datasets. The immune microenvironment, biological pathway, and hypoxia score were explored by single-sample gene set enrichment analysis. The potential response of chemotherapy and immune checkpoint blockade therapy was also estimated. In addition, the correlation between the risk score and autophagy-related genes was examined by the Pearson correlation coefficient.Results: A total of three ferroptosis subtypes were identified by consensus clustering for prognostic FRGs which exhibited different outcomes, clinicopathological characteristics, and immune microenvironment. Afterward, a prognostic model that performed great predictive ability based on nine prognostic FRGs has been constructed and validated. Moreover, the prognostic model had the potential to screen the sensitivity to chemotherapy and immunotherapy in LGG patients. Finally, we also found that the prognostic model has a great connection to autophagy and hypoxia.Conclusion: We developed a ferroptosis-related prognostic model which strongly linked to diagnosis, treatment, prognosis, and recurrence of LGG. This study also reveals the connection between ferroptosis and tumor immune microenvironment.

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Evidence-based Treatment for Low-grade Glioma

Cited by 7 publications

References 30 publications

A Model for Predicting Clinical Prognosis in Patients with WHO Grade 2 Glioma

A Model for Predicting Clinical Prognosis in Patients with WHO Grade 2 Glioma

A PTPmu Biomarker is Associated with Increased Survival in Gliomas

Characterization of the Ferroptosis-Related Genes for Prognosis and Immune Infiltration in Low-Grade Glioma

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