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Establishment of age group classification for risk stratification in glioma patients.

ABSTRACT: 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.

SUBMITTER: Lin Z

PROVIDER: S-EPMC7439690 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Establishment of age group classification for risk stratification in glioma patients.

Lin Zhiying Z Yang Runwei R Li Kaishu K Yi Guozhong G Li Zhiyong Z Guo Jinglin J Zhang Zhou Z Junxiang Peng P Liu Yawei Y Qi Songtao S Huang Guanglong G

BMC neurology 20200820 1

<h4>Background</h4>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.<h4>Methods</h4>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 stra ...[more]

PMID: 32819307

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Project description:Sclerosing and spindle cell rhabdomyosarcoma is a rare histologic subtype, designated in the latest WHO classification as a stand-alone pathologic entity. Three genomic groups have been defined: an infantile subset of spindle cell rhabdomyosarcoma harboring VGLL2-related gene fusions, a MYOD1-mutant subset commonly associated with sclerosing morphology, and a subset lacking recurrent genetic abnormalities. In this study, we focus on MYOD1-mutant rhabdomyosarcoma to further define their clinicopathologic characteristics and behavior in a larger patient cohort. We investigated 30 cases of MYOD1-mutant rhabdomyosarcoma (12 previously reported and 18 newly diagnosed) with an age range of 2-94 years, including 15 children. All cases showed morphology within the spectrum of spindle cell/sclerosing rhabdomyosarcoma (8 cases showing pure sclerosing morphology, 8 cases showing pure spindle cell morphology and 14 cases showing a hybrid phenotype of spindle, sclerosing and primitive undifferentiated areas). All tumors harbored either homozygous or heterozygous MYOD1 (p.L122R) exon 1 mutations. In 10 (33%) cases, a co-existent PIK3CA mutation was identified. Hot-spot mutations in NRAS and HRAS were each identified in a single case, respectively. Follow-up was available on 22 (73%) patients with a median duration of 28 months. Local recurrence was seen in 12 (55%) and distant recurrence in 12 (55%) cases, despite multimodality chemoradiation therapy. At last follow-up, 15 (68%) patients died of the disease, one patient was alive with disease and five had no evidence of disease. The prognosis was equally poor in pediatric and adult patients. In conclusion, MYOD1 mutation defines an aggressive rhabdomyosarcoma subset, with poor outcome and response to therapy, irrespective of age. Given that this distinct molecular subtype is characterized by an aggressive biologic behavior compared to other genetic subtypes of spindle and sclerosing rhabdomyosarcoma, the MYOD1 genotype should be used as a molecular marker in both subclassification and prognostication of rhabdomyosarcoma.

Project description:ObjectiveThe aim of the study was to perform mRNA-miRNA regulatory network analyses to identify a miRNA panel for molecular subtype identification and stratification of high-risk patients with pancreatic ductal adenocarcinoma (PDAC).BackgroundRecent transcriptional profiling effort in PDAC has led to the identification of molecular subtypes that associate with poor survival; however, their clinical significance for risk stratification in patients with PDAC has been challenging.MethodsBy performing a systematic analysis in The Cancer Genome Atlas and International Cancer Genome Consortium cohorts, we discovered a panel of miRNAs that associated with squamous and other poor molecular subtypes in PDAC. Subsequently, we used logistic regression analysis to develop models for risk stratification and Cox proportional hazard analysis to determine survival prediction probability of this signature in multiple cohorts of 433 patients with PDAC, including a tissue cohort (n = 199) and a preoperative serum cohort (n = 51).ResultsWe identified a panel of 9 miRNAs that were significantly upregulated (miR-205-5p and -934) or downregulated (miR-192-5p, 194-5p, 194-3p, 215-5p, 375-3p, 552-3p, and 1251-5p) in PDAC molecular subtypes with poor survival [squamous, area under the receiver operating characteristic curve (AUC) = 0.90; basal, AUC = 0.89; and quasimesenchymal, AUC = 0.83]. The validation of this miRNA panel in a tissue clinical cohort was a significant predictor of overall survival (hazard ratio = 2.48, P < 0.0001), and this predictive accuracy improved further in a risk nomogram which included key clinicopathological factors. Finally, we were able to successfully translate this miRNA predictive signature into a liquid biopsy-based assay in preoperative serum specimens from PDAC patients (hazard ratio: 2.85, P = 0.02).ConclusionWe report a novel miRNA risk-stratification signature that can be used as a noninvasive assay for the identification of high-risk patients and potential disease monitoring in patients with PDAC.

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Establishment of age group classification for risk stratification in glioma patients.

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Establishment of age group classification for risk stratification in glioma patients.

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