Human gliomatosis cerebri vs. non-neoplastic adult brain tissue
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE19870 | GEO | 2011/01/07
SECONDARY ACCESSION(S): PRJNA121961
REPOSITORIES: GEO
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Project description:We report the results of a molecular study in thirty-seven cases of gliomatosis cerebri, correlating these results with prognosis. The well-known prognostic factors of gliomas, i.e., age, KPS, histology (Grade 2 vs. 3), or contrast enhancement, was predictive of response or outcome only in a percentage of patients but not in all patients. We identified an 8 miRNA signature able to predict patient prognosis with microarray gene expression profiling. The 8 gene features were used to built a prediction method able to distinguish patients with good prognosis (more likely to be responsive to therapy) from patients with a poor prognosis (less likely to be responsive to therapy). Keywords: miRNA expression profile Fifty-nine patients, between 12- and 73-years-old, with clinical signs of increased intracranial pressure were admitted to our institutions between January 2000 to September 2005. Pre-operative neuroradiological studies (CT scan and MRI) showed diffuse infiltrative processes involving more than two different lobes, no identifiable focal mass, and contrast enhancement absent or less than 1 cm in diameter. Written informed consent and tumour DNA were obtained for molecular analysis. Other eligibility criteria included a Karnofsky Performance Scale index (KPS) >50, normal bone marrow function (white blood cell count >3.0X109/l, neutrophil count >1.5X109/l, platelet count >100X109/l, and haemoglobin >10g/dL), normal liver function (aspartate aminotransferase or alanine aminotransferase <2 times the upper limit of laboratory normal, normal bilirubin, and alkaline phosphatase < 2 times the upper limit of normal), and normal renal function (serum creatinine <1.5 mg/dL). The patients received chemotherapy with temozolamide and radiotherapy. The TMZ schedule consisted of 150 to 200 mg/m2 was orally administered once daily on days 1 to 5. Treatment cycles were repeated every 28 days, with a maximum of 24 months. All patients had a monthly neurological and performance status evaluation and a radiological (MRI) evaluation every 2 to 3 months. Responses were evaluated according to previously described criteria (8): a clinical response was defined as an improvement of a neurological deficit or cognitive function evaluated by Mini-Mental Status Examination, an improvement of at least 75% in seizure frequency, or the disappearance of intracranial hypertension. When radiological MRI scans showed a reduction of more than 50% in the hyper intense area it was considered a partial response (PR), and a <50% regression or an objective regression of mass effect, was considered a minor response (MR). Disease was considered as stable when no clinical or radiological changes were seen for at least 6 months, whereas neurological deterioration, a need to increase corticosteroids, or evidence of tumour progression on MRI (an increase in the T2 or the appearance of contrast enhancement) indicated tumour progression.
2011-01-07 | E-GEOD-19870 | biostudies-arrayexpress
Project description:In modern clinical neuro-oncology the pathological diagnoses are very challenging creating significant clinical confusion and affecting therapeutic decisions and prognostic estimation. We investigated whether gene expression profiling, coupled with class prediction methodology, could be used to predict prognosis of gliomatosis cerebri in a more consistent manner then standard pathology. We report the results of a molecular study in fifty-nine cases of gliomatosis cerebri, correlating these results with prognosis. TP53 and PTEN gene sequences were analyzed and microarray expression profiling were also performed. At the 24 month follow-up, 17 patients were alive, while 42 patients were died. We identified a 23 gene signature able to predict patient prognosis with microarray gene expression profiling. With the aim to produce a prognostication tool useful in clinical investigation we studied the expression of this 23 gene signature by RT-qPCR. Real time expression values relative to these 23 gene features were used to built a prediction method able to distinguish patients with good prognosis (more likely responsive to therapy) from patients with a bad prognosis (more likely irresponsive to therapy). These results demonstrated not only strong association of gene expression patterns with the survival of the patients but also a robust reproducibility of these gene expression– based predictors.
2009-06-17 | GSE11822 | GEO
Project description:Meningiomas are common brain tumors that are classified into three World Health Organization grades (Grade I: benign, Grade II: atypical and Grade III: malignant) and are molecularly ill-defined tumors. The purpose of this study was identify microRNA (miRNA) molecular signatures unique to the different grades of meningiomas correlating them to prognosis. We have used a miRNA expression microarray to show that meningiomas of all three grades fall into two main molecular groups designated “benign” and “malignant” meningiomas. While all typical meningiomas fall into the benign group and all anaplastic meningiomas fall into the malignant group, atypical meningiomas distribute into either one of these groups. We have identified a miRNA signature that distinguishes benign meningiomas from malignant meningiomas. We studied the gene expression profiles of 340 mammalian miRNAs in 37 primary meningioma tumors by means of DNA microarrays.
2011-01-02 | E-GEOD-19720 | biostudies-arrayexpress
Project description:Meningiomas are common brain tumors that are classified into three World Health Organization grades (Grade I: benign, Grade II: atypical and Grade III: malignant) and are molecularly ill-defined tumors. The purpose of this study was identify microRNA (miRNA) molecular signatures unique to the different grades of meningiomas correlating them to prognosis. We have used a miRNA expression microarray to show that meningiomas of all three grades fall into two main molecular groups designated “benign” and “malignant” meningiomas. While all typical meningiomas fall into the benign group and all anaplastic meningiomas fall into the malignant group, atypical meningiomas distribute into either one of these groups. We have identified a miRNA signature that distinguishes benign meningiomas from malignant meningiomas.
2011-01-02 | GSE19720 | GEO
Project description:In modern clinical neuro-oncology the pathological diagnoses are very challenging creating significant clinical confusion and affecting therapeutic decisions and prognostic estimation. We investigated whether gene expression profiling, coupled with class prediction methodology, could be used to predict prognosis of gliomatosis cerebri in a more consistent manner then standard pathology. We report the results of a molecular study in fifty-nine cases of gliomatosis cerebri, correlating these results with prognosis. TP53 and PTEN gene sequences were analyzed and microarray expression profiling were also performed. At the 24 month follow-up, 17 patients were alive, while 42 patients were died. We identified a 23 gene signature able to predict patient prognosis with microarray gene expression profiling. With the aim to produce a prognostication tool useful in clinical investigation we studied the expression of this 23 gene signature by RT-qPCR. Real time expression values relative to these 23 gene features were used to built a prediction method able to distinguish patients with good prognosis (more likely responsive to therapy) from patients with a bad prognosis (more likely irresponsive to therapy). These results demonstrated not only strong association of gene expression patterns with the survival of the patients but also a robust reproducibility of these gene expressionâ?? based predictors. We have analyzed 59 gliomatosis cerebri bioptic tissue comparing them with normal brain tissue derived by non-tumor surrounding tissue or commercial brain tissue. We alternatively labeled test sample and reference with Cy3 and Cy5 so to avoid a systematic bias due to label efficiency. Since the aim of the work was to find a correlation between prognosis and expression profile we considered each sample of a one prognosis group like a replicate of that group. Median survival data allowed us to distinguish 59 gliomatosis cerebri patients in two group: bad prognosis group, counting 42 patients, with a median survival of 14.58 months and good prognosis group with a median survival of 41.20 months. Moreover TP53 and PTEN mutation analysis was performed on this patients. Kaplan-Meier survival curve with log-rank test showed like each prognosis group can be furthermore divided in 2 groups where bad prognosis group patients bringing a mutation in one of the two gene analized or both genes showed the wrong survival. Microarray expression profile follwed by average linkage clustering analysis based on Pearson correlation coefficients was applied to all tissues on the basis of similarity in the expression pattern over all genes. As expected, it yielded two major clusters, one representing the good prognosis group and the other the bad prognosis one. Interesting these cluster are identical to cluster based on survival. Tumour classification based upon WHO 2007.
2010-05-18 | E-GEOD-11822 | biostudies-arrayexpress
Project description:The outcome of patients with anaplastic gliomas varies considerably depending on histology and single molecular markers such as codeletion of 1p/19q and mutations of the isocitrate dehydrogenase (IDH) gene. Whether a molecularly-based classification of anaplastic gliomas based on large scale genomic or epigenomic analyses is superior to histopathology, may reflect distinct biological subtypes, predict outcome and guide therapy decisions had yet to be determined. Epigenome-wide DNA methylation analysis, which also allows for the detection of copy-number aberrations, was performed in a cohort of 228 patients with anaplastic gliomas (astrocytomas, oligoastrocytomas and oligodendrogliomas), including 115 patients of the NOA-04 trial. We further compared these tumors with a group of 55 glioblastomas. Unsupervised clustering demonstrated two main groups based on IDH mutation status: CpG island methylator phenotype (CIMP) positive (77.5%) or negative (22.5%). CIMP+ (IDH mutant) tumors showed a further separation based on copy-number status of chromosome arms 1p and 19q, but not based on histopathology. CIMP- (IDH wild type) tumors on the other hand showed hallmark copy-number alterations of glioblastomas. These tumors clustered together with CIMP- glioblastomas without forming separate groups based on WHO grade. There was no Tumor classification based on CIMP and 1p/19q status was significantly associated with survival allowing a better prediction of outcome than the current histopathological classification alone: Patients with CIMP+ tumors with 1p/19q codeletion had the best prognosis, followed by patients with CIMP+ but intact 1p/19q status. Patients with CIMP- anaplastic gliomas had the worst prognosis. Collectively, our data suggest that anaplastic gliomas can be grouped into three molecular subtypes with clear association to underlying biology and clinical outcome based on IDH and 1p/19q status. The data do not provide a molecular basis for the diagnosis of anaplastic oligoastrocytoma. We investigated a subset of 228 anaplastic gliomas using the Illumina 450k methylation array.
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