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Proliferation and aneusomy predict survival of young patients with astrocytoma grade II.

ABSTRACT: The clinical course of astrocytoma grade II (AII) is highly variable and not reflected by histological characteristics. As one of the best prognostic factors, higher age identifies rapid progressive A II. For patients over 35 years of age, an aggressive treatment is normally propagated. For patients under 35 years, there is no clear guidance for treatment choices, and therefore also the necessity of histopathological diagnosis is often questioned. We studied the additional prognostic value of the proliferation index and the detection of genetic aberrations for patients with A II. The tumour samples were obtained by stereotactic biopsy or tumour resection and divided into two age groups, that is 18-34 years (n=19) and > or =35 years (n=28). Factors tested included the proliferation (Ki-67) index, and numerical aberrations for chromosomes 1, 7, and 10, as detected by in situ hybridisation (ISH). The results show that age is a prognostic indicator when studied in the total patient group, with patients above 35 years showing a relatively poor prognosis. Increased proliferation index in the presence of aneusomy appears to identify a subgroup of patients with poor prognosis more accurately than predicted by proliferation index alone. We conclude that histologically classified cases of A II comprise a heterogeneous group of tumours with different biological and genetic constitution, which exhibit a highly variable clinical course. Immunostaining for Ki-67 in combination with the detection of aneusomy by ISH allows the identification of a subgroup of patients with rapidly progressive A II. This is an extra argument not to defer stereotactic biopsy in young patients with radiological suspicion of A II.

SUBMITTER: Wessels PH

PROVIDER: S-EPMC2394227 | biostudies-other | 2003 Jul

REPOSITORIES: biostudies-other

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Project description:BackgroundDiffuse gliomas, grades II and III, hereafter called lower-grade gliomas (LGG), have variable, difficult to predict clinical courses, resulting in multiple studies to identify prognostic biomarkers. The purpose of this study was to assess expression or methylation of the homeobox family gene SHOX2 as independent markers for LGG survival.MethodsWe downloaded publically available glioma datasets for gene expression and methylation. The Cancer Genome Atlas (TCGA) (LGG, n=516) was used as a training set, and three other expression datasets (n=308) and three other methylation datasets (n=320), were used for validation. We performed Kaplan-Meier survival curves and univariate and multivariate Cox regression model analyses.FindingsSHOX2 expression and gene body methylation varied among LGG patients and highly significantly predicted poor overall survival. While they were tightly correlated, SHOX2 expression appeared more potent as a prognostic marker and was used for most further studies. The SHOX2 prognostic roles were maintained after analyses by histology subtypes or tumor grade. We found that the combination of SHOX2 expression and IDH genotype status identified a subset of LGG patients with IDH wild-type (IDHwt) and low SHOX2 expression with considerably favorable survival. We further investigated the combination of SHOX2 with other known clinically relevant markers of LGG (TERT expression, 1p/19q chromosome co-deletion, MGMT methylation, ATRX mutation and NES expression). When combined with SHOX2 expression, we identified subsets of LGG patients with significantly favorable survival outcomes, especially in the subgroup with worse prognosis for each individual marker. Finally, multivariate analysis demonstrated that SHOX2 was a potent independent survival marker.InterpretationWe have identified that SHOX2 expression or methylation are potent independent prognostic indicators for predicting LGG patient survival, and have potential to identify an important subset of LGG patients with IDHwt status with significantly better overall survival. The combination of IDH or other relevant markers with SHOX2 identified LGG subsets with significantly different survival outcomes, and further understanding of these subsets may benefit therapeutic target identification and therapy selections for glioma patients.

Project description:BackgroundSince autophagy remains an important topic of investigation, the RNA-sequence profiles of autophagy-related genes (ARGs) can provide insights into predicting low-grade gliomas (LGG) prognosis.MethodsThe RNA-seq profiles of autophagic genes and prognosis data of LGG were integrated from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). Univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) regression model were carried out to identify the differentially expressed prognostic autophagy-related genes. Then, the autophagic-gene signature was formed and verified in TCGA test set and external CGGA cohorts. Time-dependent receiver operating characteristic (ROC) was examined to test the accuracy of this signature feature. A nomogram was conducted to meet the needs of clinicians. Sankey diagrams were performed to visualize the relationship between the multigene signatures and clinic-pathological features.ResultsTwenty-four ARGs were finally identified most relevant to LGG prognosis. According to the specific prediction index formula, the patients were classified into low-risk or high-risk groups. Prognostic accuracy was proved by time-dependent ROC analysis, with AUC 0.9, 0.93, and 0.876 at the survival time of 2-, 3-, and 5-year, respectively, which was superior to the AUC of the isocitrate dehydrogenase (IDH) mutation. The result was confirmed while validated in the TCGA test set and external validation CGGA cohort. A nomogram was constructed to meet individual needs. With a visualization approach, Sankey diagrams show the relationship of the histological type, IDH status, and predict index. In TCGA and CGGA cohorts, both low-risk groups displayed better survival rate in LGG while histological type and IDH status did not show consistency results.Conclusions24-ARGs may play crucial roles in the progression of LGG, and LGG patients were effectively divided into low-risk and high-risk groups according to prognostic prediction. Overall, our study will provide novel strategies for clinical applications.

Project description:Astrocytomas are the most common and aggressive type of primary brain tumors in adults. The World Health Organization (WHO) assorts them into grades, from I to IV, based on histopathological features that reflect their malignancy [1]. Alongside with tumor progression, comes an increased proliferation, genomic instability, infiltration in normal brain tissue and resistance to treatments. The high genomic instability forges tumor cells enhancing key proteins that avoid cells from collapsing and favor therapy resistance [2]. To explore genes and pathways associated with tumor progression phenotypes we analyzed gene expression in a panel of non-tumor and glioma cell lines, namely: ACBRI371, non-tumor human astrocytes; HDPC, fibroblasts derived from dental pulp; Res186, Res259, Res286 and UW467 that include grade I, II and III astrocytoma cell lines derived from pediatric tumors; and T98G, U343MG, U87MG, U138MG and U251MG, all derived from GBM (grade IV). We also profiled gene expression changes caused by exogenously induced replicative stress, performing RNA sequencing with camptothecin (CPT)-treated cells. Here we describe the RNA-sequencing data set acquired, including quality of reads and sequencing consistency, as well as the bioinformatics strategy used to analyze it. We also compared gene expression patterns and pathway enrichment between non-tumor versus lower-grade (LGG), non-tumor versus GBM, LGG versus GBM, and CPT-treated versus non-treated cells. In brief, a total of 6467 genes showed differential expression and 5 pathways were enriched in tumor progression, while 2279 genes and 7 pathways were altered under the replication stress condition. The raw data was deposited in the NCBI BioProject database under the accession number PRJNA631805. Our dataset is valuable for researchers interested in differential gene expression among different astrocytoma grades and in expression changes caused by replicative stress, facilitating studies that seek novel biomarkers of glioma progression and treatment resistance.

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Proliferation and aneusomy predict survival of young patients with astrocytoma grade II.

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