Prognostic value of Ki-67 index in adult medulloblastoma after accounting for molecular subgroup: a retrospective clinical and molecular analysis

Prognostic value of Ki-67 index in primary intracranial tumors of infants

OBJECTIVE

Primary intracranial tumors are rare tumors in infants. They differ from those found in other pediatric age groups in terms of clinical presentation, histopathological diagnosis, adjuvant therapies, and outcome. Ki-67 index has also shown promising results as a prognostic factor in different types of intracranial tumors in children and adults. However, the importance and the best cutoff point of Ki-67 index in primary intracranial tumors of infants remains unclear. We aimed to analyze prognostic value of Ki-67 index in primary intracranial tumors of infants.

METHODS

This study retrospectively reviewed the records of 28 infants undergoing surgical resection for primary intracranial tumors between April 2016 and March 2021. We analyzed clinical characteristics, tumor location, extent of resection, histopathological diagnosis, Ki-67 index, and overall survival (OS). To define the most relevant cutoff value for Ki-67 index, "Cutoff Finder" was used.

RESULTS

The median age at diagnosis was 188 days for all patients. Fifteen of the patients were boys and 13 were girls. Tumors were located supratentorial in 13 patients and infratentorial in 15 patients. Gross total resection was performed in 7 of 13 supratentorial tumors and 9 of 15 infratentorial tumors. The mean Ki-67 index of the supratentorial tumors was 49.6%, the median was 55%; for infratentorial tumors, the mean was 49.9%, and the median was 70%. Tumor grade (p = 0.019) and Ki-67 index (p = 0.003) were found as significant predictors of OS in log-rank testing for Kaplan-Meier survival analysis. Univariate cox regression analysis identified high Ki-67 index as prognostic factor for worse OS, with hazard ratio of 8.852 (95% CI 1.95-64.80; p = 0.0108). High Ki-67 index was found as independent prognostic factor for worse OS in multivariate cox regression analysis (HR 7.036; 95% CI 1.229-65.82; p = 0.0457).

CONCLUSION

High-grade and high Ki-67 index were associated with worse outcome. Ki-67 index did show a distinct prognostic value for OS within our cohort at a cutoff value of 72.5%.

Exploring the relationship between age and prognosis in glioma: rethinking current age stratification

Background

The age of glioma plays a unique role in prognosis. We hypothesized that age is not positively correlated with survival prognosis and explored its exact relationship.

Methods

Glioma was identified from the SEER database (between 2000 and 2018). A multivariate Cox proportional regression model and restricted cubic spline (RCS) plot were used to assess the relationship between age and prognosis.

Results

A total of 66465 patients with glioma were included. Hazard ratios (HR) for ten-year by age: 0–9 years, HR 1.06 (0.93–1.20); 10–19 years: reference; 20–29 years, HR 0.90 (0.82–1.00); 30–39 years, HR 1.14 (1.04–1.25); 40–49 years, HR 2.09 (1.91–2.28); 50–59 years, HR 3.48 (3.19–3.79); 60–69 years, HR 4.91 (4.51–5.35);70–79 years, HR 7.95 (7.29–8.66); 80–84 years, HR 12.85 (11.74–14.06). After adjusting for covariates, the prognosis was not positively correlated with age. The smooth curve of RCS revealed this non-linear relationship: HR increased to 10 years first, decreased to 23 years, reached its lowest point, and became J-shaped.

Conclusion

The relationship between age and glioma prognosis is non-linear. These results challenge the applicability of current age groupings for gliomas and advocate the consideration of individualized treatment guided by precise age.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-022-02879-9.

Radiomic signatures based on multiparametric MR images for predicting Ki-67 index expression in medulloblastoma

BACKGROUND

Medulloblastoma (MB) is a common central nervous system tumor in children with extensive heterogeneity and different prognoses. This study aimed to classify the Ki-67 index in MB with radiomic characteristics based on multi-parametric magnetic resonance imaging to guide treatment and assess the prognosis of patients.

METHODS

Three sequences of T1W, CE-T1W, and T2W were used as test data. Two experienced radiologists manually segmented the tumors according to T2W images from 90 patients. The patients were divided into training and test sets at a ratio of 7:3, and 833 dimensional image features were extracted for each patient. Five models were trained using the feature set selected in three ways. Finally, the area under the curve (AUC) and accuracy (ACC) were used on the test set to evaluate the performance of the different models.

RESULTS

A random forest (RF) model combining three sequence features achieved the best performance (ACC: 0.771, 95% CI: 0.727 to 0.816; AUC: 0.697, 95% CI: 0.614 to 0.78). The voting model that combined a RF and a support vector machine (SVM) had higher performance than the other models (ACC: 0.796, 95% CI: 0.76 to 0.833; AUC: 0.689, 95% CI: 0.615 to 0.763). The best prediction model that used only one sequence feature was voting in the T2W sequence (ACC: 0.736, 95% CI: 0.705 to 0.766; AUC: 0.636, 95% CI: 0.585 to 0.688). The ensemble model was better than the single training model, and a multi-sequence combination was better than a single sequence prediction. The multiple feature selection methods were better than a combination of the two methods.

CONCLUSIONS

A model obtained by machine learning could help doctors predict the Ki-67 values of patients more efficiently to make targeted judgments for subsequent treatments.

Novel Molecular Hallmarks of Group 3 Medulloblastoma by Single-Cell Transcriptomics

Medulloblastoma (MB) is a highly heterogeneous and one of the most malignant pediatric brain tumors, comprising four subgroups: Sonic Hedgehog, Wingless, Group 3, and Group 4. Group 3 MB has the worst prognosis of all MBs. However, the molecular and cellular mechanisms driving the maintenance of malignancy are poorly understood. Here, we employed high-throughput single-cell and bulk RNA sequencing to identify novel molecular features of Group 3 MB, and found that a specific cell cluster displayed a highly malignant phenotype. Then, we identified the glutamate receptor metabotropic 8 (GRM8), and AP-1 complex subunit sigma-2 (AP1S2) genes as two critical markers of Group 3 MB, corresponding to its poor prognosis. Information on 33 clinical cases was further utilized for validation. Meanwhile, a global map of the molecular cascade downstream of the MYC oncogene in Group 3 MB was also delineated using single-cell RNA sequencing. Our data yields new insights into Group 3 MB molecular characteristics and provides novel therapeutic targets for this relentless disease.

Loss of 5-Hydroxymethylcytosine as an Epigenetic Signature That Correlates With Poor Outcomes in Patients With Medulloblastoma

Medulloblastoma, as the most common malignant brain tumor in children, exhibits highly dysregulated DNA methylation. The novel epigenetic marker—5-hydroxymethylcytosine (5hmC) plays essential role in gene regulation during brain development and in brain tumors. However, the biological and clinical implications of 5hmC in medulloblastoma are still unclear. Here, we detected global 5hmC levels in two independent medulloblastoma patient cohorts (discovery cohort: n = 81; validation cohort: n = 171) using ultra-high performance liquid chromatography-tandem mass spectrometry analysis. Immunohistochemistry was used to identify the cell proliferation and expression of Ten-eleven translocation 1 and 2 (TET1/2). The prognostic impacts of covariates on progression-free survival (PFS) and overall survival (OS) were evaluated using multivariate Cox hazards regression models. We observed that global 5hmC levels were decreased in medulloblastomas compared to normal cerebellums (P < 0.001). Multivariate analysis showed that low global 5hmC levels correlated with poor PFS and OS rates (discovery cohort: PFS: P = 0.003, OS: P = 0.002; validation cohort: PFS: P = 0.0002, OS: P = 0.001). Immunohistochemistry showed an inverse correlation between 5hmC score and Ki-67 index (r = -0.747, P < 0.0001). Moreover, 5hmC score in MB samples was associated with nuclear expression of TET1 (r = -0.419, P = 0.003) and TET2 (r = -0.399, P = 0.005) proteins. Our study demonstrates that loss of 5hmC is an epigenetic biomarker in medulloblastomas. Our results indicate that 5hmC could be a candidate prognostic indicator for improving survival prediction of risk stratification in patients with medulloblastoma.

Survival and Prognostic Factors of Adult Intracranial Ependymoma: A Single-institutional Analysis of 236 Patients

Adult intracranial ependymomas (EPNs) are extremely rare brain tumors. Currently, clinical and molecular factors that could inform individualized treatment strategies are still lacking for EPNs in this age group. The aim of this study was to investigate potential prognostic indicators and rational therapeutic management in a large cohort of adult intracranial EPNs. Adult patients who underwent resection of World Health Organization (WHO) grade II or III intracranial EPNs were included. The demographic features, clinicopathologic manifestations, molecular subgroups, and outcomes were retrospectively analyzed. Overall survival and progression-free survival were calculated using the Kaplan-Meier analysis. Potential prognostic indicators were identified using multivariable Cox proportional hazards model. This cohort included 236 adult patients with a mean age of 36.2 years (range: 18 to 72 y) at diagnosis. The tumor location was supratentorial (ST) in 102 (43.2%) and infratentorial in 134 (56.8%). Pathologic analysis revealed 43.1% of ST-EPNs with RELA fusion and 88.1% of posterior fossa ependymomas (PF-EPNs) with positive H3K27me3 staining. Gross total removal was achieved in 169 cases (71.6%). During follow-up, 97 (41.1%) patients had disease progression and 39 (16.5%) died. Kaplan-Meier analysis showed that patients with H3K27me3-positive PF-EPN had excellent survival, whereas patients with RELA fusion-positive ST-EPN or H3K27me3-negative PF-EPN had poor prognosis (progression-free survival: P=1.3E-16, overall survival: P=2.5E-12). Multivariate analysis showed that molecular subgroup, extent of resection, and Ki-67 index were strong independent prognostic indicators. In conclusion, our study provides essential information on the prognostic prediction of adult intracranial EPNs that will assist in establishing appropriate risk stratification and individualized treatment strategies in future clinical trials.

Establishment of age group classification for risk stratification in glioma patients

Background

Age is associated with the prognosis of glioma patients, but there is no uniform standard of age-group classification to evaluate the prognosis of glioma patients. In this study, we aimed to establish an age group classification for risk stratification in glioma patients.

Methods

1502 patients diagnosed with gliomas at Nanfang Hospital between 2000 and 2018 were enrolled. The WHO grade of glioma was used as a dependent variable to evaluate the effect of age on risk stratification. The evaluation model was established by logistic regression, and the Akaike information criterion (AIC) value of the model was used to determine the optimal cutoff points for age-classification. The differences in gender, WHO grade, pathological subtype, tumor cell differentiation, tumor size, tumor location, and molecular markers between different age groups were analyzed. The molecular markers included GFAP, EMA, MGMT, P53, NeuN, Oligo2, EGFR, VEGF, IDH1, Ki-67, PR, CD3, H3K27M, TS, and 1p/19q status.

Results

The proportion of men with glioma was higher than that of women with glioma (58.3% vs 41.7%). Analysis of age showed that appropriate classifications of age group were 0–14 years old (pediatric group), 15–47 years old (youth group), 48–63 years old (middle-aged group), and ≥ 64 years old (elderly group).The proportions of glioblastoma and large tumor size (4–6 cm) increased with age (p = 0.000, p = 0.018, respectively). Analysis of the pathological molecular markers across the four age groups showed that the proportion of patients with larger than 10% area of Ki-67 expression or positive PR expression increased with age (p = 0.000, p = 0.017, respectively).

Conclusions

Appropriate classifications of the age group for risk stratification are 0–14 years old (pediatric group), 15–47 years old (young group), 48–63 years old (middle age group) and ≥ 64 years old (elderly group). This age group classification is effective in evaluating the risk of glioblastoma in glioma patients.

Characterization of global 5-hydroxymethylcytosine in pediatric posterior fossa ependymoma

Background

5-Hydroxymethylcytosine (5hmC) is a novel epigenetic mark and may be involved in the mechanisms of tumorigenesis and malignant transformation. However, the role of 5hmC in ependymoma, the third most common brain tumor in children, remains unclear. The aim of this study sought to identify the characterization of 5hmC levels in pediatric posterior fossa ependymoma and to evaluate whether 5hmC levels could be a potential factor to predict clinical outcomes.

Results

Our results showed that 5hmC levels were globally decreased in posterior fossa ependymoma compared with normal cerebellum tissues (P < 0.001). Group A posterior fossa ependymomas had higher 5hmC levels than group B tumors (P = 0.007). Moreover, 5hmC levels positively correlated with Ki-67 index in posterior fossa ependymoma (r = 0.428, P = 0.003). Multivariate Cox hazards model revealed that patients with high 5hmC levels (> 0.102%) had worse PFS and OS than patients with lower 5hmC levels (< 0.102%) (PFS: HR = 3.014; 95% CI, 1.040–8.738; P = 0.042; OS: HR = 2.788; 95% CI, 0.974–7.982; P = 0.047).

Conclusions

Our findings suggest that loss of 5hmC is an epigenetic hallmark for pediatric posterior fossa ependymoma. 5hmC levels may represent a potential biomarker to predict prognosis in children with posterior fossa ependymoma.

Human Medulloblastoma Cell Lines: Investigating on Cancer Stem Cell-Like Phenotype

Medulloblastoma (MB) is the most common malignant pediatric brain tumor. Despite the progress of new treatments, the risk of recurrence, morbidity, and death remains significant and the long-term adverse effects in survivors are substantial. The fraction of cancer stem-like cells (CSCs) because of their self-renewal ability and multi-lineage differentiation potential is critical for tumor initiation, growth, and resistance to therapies. For the development of new CSC-targeted therapies, further in-depth studies are needed using enriched and stable MB-CSCs populations. This work, aimed at identifying the amount of CSCs in three available human cell lines (DAOY, D341, and D283), describes different approaches based on the expression of stemness markers. First, we explored potential differences in gene and protein expression patterns of specific stem cell markers. Then, in order to identify and discriminate undifferentiated from differentiated cells, MB cells were characterized using a physical characterization method based on a high-frequency dielectrophoresis approach. Finally, we compared their tumorigenic potential in vivo, through engrafting in nude mice. Concordantly, our findings identified the D283 human cell line as an ideal model of CSCs, providing important evidence on the use of a commercial human MB cell line for the development of new strategic CSC-targeting therapies.