Circadian Regulation Patterns With Distinct Immune Landscapes in Gliomas Aid in the Development of a Risk Model to Predict Prognosis and Therapeutic Response

Circadian disruption in tumorigenesis has been extensively studied, but how circadian rhythm (CR) affects the formation of tumor microenvironment (TME) and the crosstalk between TME and cancer cells is largely unknown, especially in gliomas. Herein, we retrospectively analyzed transcriptome data and clinical parameters of glioma patients from public databases to explore circadian rhythm-controlled tumor heterogeneity and characteristics of TME in gliomas. Firstly, we pioneered the construction of a CR gene set collated from five datasets and review literatures. Unsupervised clustering was used to identify two CR clusters with different CR patterns on the basis of the expression of CR genes. Remarkably, the CR cluster-B was characterized by enriched myeloid cells and activated immune-related pathways. Next, we applied principal component analysis to construct a CRscore to quantify CR patterns of individual tumors, and the function of the CRscore in prognostic prediction was further verified by univariate and multivariate regression analyses in combination with a nomogram. The CRscore could not only be an independent factor to predict prognosis of glioma patients but also guide patients to choose suitable treatment strategies: immunotherapy or chemotherapy. A glioma patient with a high CRscore might respond to immune checkpoint blockade, whereas one with a low CRscore could benefit from chemotherapy. In this study, we revealed that circadian rhythms modulated tumor heterogeneity, TME diversity, and complexity in gliomas. Evaluating the CRscore of an individual tumor would contribute to gaining a greater understanding of the tumor immune status of each patient, enhancing the accuracy of prognostic prediction, and suggesting more effective treatment options.

Spontaneous Regression of Tumor in an Optic Pathway Glioma Patient With Diencephalic Syndrome: Case Report and Literature Review

Background: Diencephalic syndrome (DS) can cause failure to thrive in pediatrics, which is mostly found in optic pathway gliomas (OPGs) patients. OPGs patients with DS always show a poor outcome. Case presentation: We present the case of an OPG patient with DS who got a spontaneous regression without any treatment. A 6-month-old girl presented with failure to thrive for two months and visual dysfunction with bilateral horizontal nystagmus. MRI demonstrated a 42mm*37mm*36mm enhanced and lobulated lesion located in the sellar region with a clear boundary with surrounding tissues. OPG and DS was diagnosed according to her radiological examination and manifestation. Conservative follow-up was given. There was a spontaneous decrease in tumor size during follow-up. Symptom improves and the patient continues to have a good quality of life despite a moderate dysfunction of her left eye.Conclusions: Conservative observation can be used as a treatment for some OPG patients, body weight may be a marker of the growth of tumor in OPG patients with DS.

NQPC-2 Cognitive function of a low-grade glioma patient treated with radiation therapy 28 years ago

While there are many reports that long-term survivors of low-grade glioma patients treated with radiation therapy cannot lead a healthy social life due to cognitive dysfunction, we report a low-grade glioma patient with almost normal cognitive function even after radiation therapy 28 years ago. CASE REPORT. A 64-year-old woman developed with sudden left hemiparesis and was diagnosed as a small infarction in the left corona radiata. After treated by anticoagulant therapy, she was admitted to our hospital for rehabilitation. Twenty-eight years ago, she underwent surgical resection and radiation therapy with 60 Gy for astrocytoma (WHO grade 2) in the right insular cortex. At the time of this admission, she presented with a good MMSE score of 30 points, but she couldn’t walk and her left hand was less maneuverable. After 109 days of intensive rehabilitation in our hospital, she was discharged on a cane walk, and returned to work as a gas station clerk. COGNITIVE FUNCION. We evaluated her cognitive function on TMT-A/B test, CAT (Clinical Assessment for Attention)and WAIS-4. The TMT test was normal with age adjustments. In CAT, the percentage of correct answers for the 7 constituent items was within the standard range, but in the task of evaluating the required time, a slight delay in processing speed was observed. In WAIS-4, the Full scale IQ was 98 points (normal range) including normal 3 of 4 constituent items. But, only the PSI (processing speed) of 75 point was below the standard range. CONCLUSION: We observed a slight delay in processing speed on her high-level cognitive function tests, but determined that she would be well-adapted to a familiar job in a small community. In fact, she was doing well on the job 10 months after her discharge.

Convection-enhanced delivery for high-grade glioma

Glioblastoma (GBM) is the most common adult primary malignant brain tumor and is associated with a dire prognosis. Despite multi-modality therapies of surgery, radiation, and chemotherapy, its 5-year survival rate is 6.8%. The presence of the blood-brain barrier (BBB) is one factor that has made GBM difficult to treat. Convection-enhanced delivery (CED) is a modality that bypasses the BBB, which allows the intracranial delivery of therapies that would not otherwise cross the BBB and avoids systemic toxicities. This review will summarize prior and ongoing studies and highlights practical considerations related to clinical care to aid providers caring for a high-grade glioma patient being treated with CED. Although not the main scope of this paper, this review also touches upon relevant technical considerations of using CED, an area still under much development.

TMOD-05. GENETIC AND MOLECULAR PROPERTIES OF LONG-TERM PROLIFERATING TUMORSPHERE -FORMING GLIOMA DERIVED CELLS

Long-term proliferating tumorsphere (LTP-TS)-forming glioma derived cells (GDCs) and patient derived xenografts (PDXs) are essential tools for translational research for glioma. However, only small subsets of glioma samples are established as LTP-TS and/or PDXs and little is known about the genetics and molecular properties of LTP-TS -forming GDCs and PDX. In this study, we aim to analyze the characteristics of LTP-TS -forming GDCs and PDXs. We tried primary sphere cultures from 56 glioma patient-derived samples and established 14 LTP-TS -forming GDCs out of 48 glioblastoma samples and no long-term sphere culture was isolated from grade3 and grade 2 gliomas. LTP-TS -forming GDCs had self-renewal ability and possessed certain multipotency. However, they significantly less expressed SOX1 FOXG1 and TUBB3, whereas they expressed LGALS1 significantly higher than normal neural stem/progenitor cells. In addition, we found that LTP-TS -forming GDCs shared the same genetic profiles with original patients’ tumors. Furthermore, we investigated the genetic differences between the glioma tissues which were successfully established as LTP-TS -forming GDCs and those which were not. We found that glioma tissues with TERT promotor mutations and triple CNA (EGFR, CDKN2A, and PTEN loci) are significantly established as LTP-TS -forming GDCs. Lastly, we next investigated in vivo characteristics of glioma PDXs. We have injected glioma PDXs lines into immunodeficient mice and histopathologically analyzed the characteristics of xenografts. Each xenograft well recapitulated histological features of original patients’ tumors and tumor cells remarkably invade through subventricular zone. In conclusion, each LTP-TS -forming GDCs and PDXs had various gene expression profiles, reflecting intratumoral and interpatient heterogeneities of glioma. In addition, TERT promotor mutations and triple CNA significantly correlated with success rate of LTP-TS -forming GDCs. These findings will be of use and advance the preclinical and translational researches of glioma.

Prognostic Biomarker SYK and its Correlation with Immune Infiltrates in Glioma

Background: Tumor microenvironment (TME) has great effects on the development process of glioma, and we sought to identify effective prognostic factors by analyzing data from patients with glioma. In this paper, CIBERSORT and ESTIMATE calculations were employed to figure up the ratio of tumor-infiltrating immune cells (TICs) and the quantity of immune and stromal components in 698 glioma dates from The Cancer Genome Atlas (TCGA) database. In addition, differentially expressed genes (DEGs) were studied by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and single genes associated with prognosis were identified by PPI network and COX combined analysis. Results: Immune and stromal scores of TME were significantly correlated with glioma patient survival. Through protein–protein interaction (PPI) network and regression analysis of COX, we finally determined that SYK was the best prognostic factor for patients with glioma. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis were also employed, with the former showed that high-expression SYK group’s genes are principally enriched immune-related activities and the latter revealed that SYK expression was positively associated with T cells CD4 memory resting and Monocytes. All the above experimental analyses provided the theoretical basis for the biological prediction of SYK.Conclusions: SYK contributes to immune predictors in glioma patients by facilitating the shift of TME from immune dominance to metabolic activity, which provides promising insights into the treatment of glioma.

Promoting Prognostic Model Application: A Review Based on Gliomas

Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.

Nanoribbon-Based Electronic Detection of a Glioma-Associated Circular miRNA

Nanoribbon chips, based on “silicon-on-insulator” structures (SOI-NR chips), have been fabricated. These SOI-NR chips, whose surface was sensitized with covalently immobilized oligonucleotide molecular probes (oDNA probes), have been employed for the nanoribbon biosensor-based detection of a circular ribonucleic acid (circRNA) molecular marker of glioma in humans. The nucleotide sequence of the oDNA probes was complimentary to the sequence of the target oDNA. The latter represents a synthetic analogue of a glioma marker—NFIX circular RNA. In this way, the detection of target oDNA molecules in a pure buffer has been performed. The lowest concentration of the target biomolecules, detectable in our experiments, was of the order of ~10−17 M. The SOI-NR sensor chips proposed herein have allowed us to reveal an elevated level of the NFIX circular RNA in the blood of a glioma patient.