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> Disorders > Neoplastic Process > Glioblastoma Multiforme

Glioblastoma Multiforme

Glioblastoma Multiforme: An aggressive and highly malignant form of brain cancer that originates from glial cells.
It is characterized by rapid growth, extensive invasion of surrounding brain tissue, and poor prognosis.
Effective treatment protocols are crucial for improving outcomes in patients with this devastating disease.

Most cited protocols related to «Glioblastoma Multiforme»

1
Pan-Cancer Transcriptomic and Proteomic Analysis
Results are based in part upon data generated by TCGA Research Network (http://cancergenome.nih.gov/). We aggregated TCGA transcriptomic and RPPA data from public repositories, listed in the “Data availability” section. RNA-seq expression data were processed by TCGA at the gene level, rather than at the transcript level. Tumors spanned 32 different TCGA projects, each project representing a specific cancer type, listed as follows: LAML, acute myeloid leukemia; ACC, adrenocortical carcinoma; BLCA, bladder urothelial carcinoma; LGG, lower grade glioma; BRCA, breast invasive carcinoma; CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL, cholangiocarcinoma; CRC, colorectal adenocarcinoma (combining COAD and READ projects); ESCA, esophageal carcinoma; GBM, glioblastoma multiforme; HNSC, head and neck squamous cell carcinoma; KICH, kidney chromophobe; KIRC, kidney renal clear cell carcinoma; KIRP, kidney renal papillary cell carcinoma; LIHC, liver hepatocellular carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; DLBC, lymphoid neoplasm diffuse large B-cell lymphoma; MESO, mesothelioma; OV, ovarian serous cystadenocarcinoma; PAAD, pancreatic adenocarcinoma; PCPG, pheochromocytoma and paraganglioma; PRAD, prostate adenocarcinoma; SARC, sarcoma; SKCM, skin cutaneous melanoma; STAD, stomach adenocarcinoma; TGCT, testicular germ cell tumors; THYM, thymoma; THCA, thyroid carcinoma; UCS, uterine carcinosarcoma; UCEC, uterine corpus endometrial carcinoma; UVM, uveal melanoma. Cancer molecular profiling data were generated through informed consent as part of previously published studies and analyzed per each original study’s data use guidelines and restrictions.
Chen F., Chandrashekar D.S., Varambally S, & Creighton C.J. (2019). Pan-cancer molecular subtypes revealed by mass-spectrometry-based proteomic characterization of more than 500 human cancers. Nature Communications, 10, 5679.
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Publication 2019
4-carboxyphenylglyoxal Adenocarcinoma Adenocarcinoma of Lung Adrenocortical Carcinoma Breast Carcinoma Carcinoma, Thyroid Carcinoma, Transitional Cell Carcinosarcoma Cells Cholangiocarcinoma Chromophobia Chronic Obstructive Airway Disease Diffuse Large B-Cell Lymphoma Endocervix Endometrial Carcinoma Esophageal Cancer Familial Atypical Mole-Malignant Melanoma Syndrome Gene Expression Profiling Genes Glioblastoma Multiforme Glioma Hepatocellular Carcinomas Hypernephroid Carcinomas Kidney Leukemia, Myelocytic, Acute Lung Lymph Malignant Neoplasms Mesothelioma Neck Neoplasms Ovary Pancreas Paraganglioma Pheochromocytoma Prostate Renal Cell Carcinoma RNA-Seq Sarcoma Serous Cystadenocarcinoma Squamous Cell Carcinoma Squamous Cell Carcinoma of the Head and Neck Stomach Testicular Germ Cell Tumor Thymoma Urinary Bladder Uterus Uveal melanoma X-Ray Photoelectron Spectroscopy
2
Comparing Methylation-Based CNS Tumor Classification
To compare our methylation-based classification of CNS tumours with described methylation classes of brain tumours by the Cancer Genome Atlas (TCGA) project, we downloaded the pre-processed methylation dataset described in Ceccarelli et al. 201618 including methylation data of 418 low grade glioma and 377 glioblastoma samples analysed by using the Illumina 450k array or 27k array platforms. To classify our samples according to the TCGA pan-glioma DNA methylation classification, we trained a Random Forest classifier on this dataset using the 1,300 CpG probe signature provided by the authors and using the default settings of the Random Forest algorithms implemented in the R package randomForest. The results of this classification for astrocytomas, oligodendrogliomas and glioblastomas are shown in Extended Data Figure 3d and are given on a case-by-case basis in Supplementary Table 2 and 4.
Capper D., Jones D.T., Sill M., Hovestadt V., Schrimpf D., Sturm D., Koelsche C., Sahm F., Chavez L., Reuss D.E., Kratz A., Wefers A.K., Huang K., Pajtler K.W., Schweizer L., Stichel D., Olar A., Engel N.W., Lindenberg K., Harter P.N., Braczynski A., Plate K.H., Dohmen H., Garvalov B.K., Coras R., Hölsken A., Hewer E., Bewerunge-Hudler M., Schick M., Fischer R., Beschorner R., Schittenhelm J., Staszewski O., Wani K., Varlet P., Pages M., Temming P., Lohmann D., Selt F., Witt H., Milde T., Witt O., Aronica E., Giangaspero F., Rushing E., Scheurlen W., Geisenberger C., Rodriguez F.J., Becker A., Preusser M., Haberler C., Bjerkvig R., Cryan J., Farrell M., Deckert M., Hench J., Frank S., Serrano J., Kannan K., Tsirigos A., Brück W., Hofer S., Brehmer S., Seiz-Rosenhagen M., Hänggi D., Hans V., Rozsnoki S., Hansford J.R., Kohlhof P., Kristensen B.W., Lechner M., Lopes B., Mawrin C., Ketter R., Kulozik A., Khatib Z., Heppner F., Koch A., Jouvet A., Keohane C., Mühleisen H., Mueller W., Pohl U., Prinz M., Benner A., Zapatka M., Gottardo N.G., Driever P.H., Kramm C.M., Müller H.L., Rutkowski S., von Hoff K., Frühwald M.C., Gnekow A., Fleischhack G., Tippelt S., Calaminus G., Monoranu C.M., Perry A., Jones C., Jacques T.S., Radlwimmer B., Gessi M., Pietsch T., Schramm J., Schackert G., Westphal M., Reifenberger G., Wesseling P., Weller M., Collins V.P., Blümcke I., Bendszus M., Debus J., Huang A., Jabado N., Northcott P.A., Paulus W., Gajjar A., Robinson G., Taylor M.D., Jaunmuktane Z., Ryzhova M., Platten M., Unterberg A., Wick W., Karajannis M.A., Mittelbronn M., Acker T., Hartmann C., Aldape K., Schüller U., Buslei R., Lichter P., Kool M., Herold-Mende C., Ellison D.W., Hasselblatt M., Snuderl M., Brandner S., Korshunov A., von Deimling A, & Pfister S.M. (2018). DNA methylation-based classification of central nervous system tumours. Nature, 555(7697), 469-474.
Publication 2018
Astrocytoma Brain Neoplasm, Malignant Central Nervous System Neoplasms DNA Methylation Genome Glioblastoma Glioblastoma Multiforme Glioma Malignant Neoplasms Methylation Neoplasms Oligodendroglioma
3
Comparing Methylation-Based CNS Tumor Classification
To compare our methylation-based classification of CNS tumours with described methylation classes of brain tumours by the Cancer Genome Atlas (TCGA) project, we downloaded the pre-processed methylation dataset described in Ceccarelli et al. 201618 including methylation data of 418 low grade glioma and 377 glioblastoma samples analysed by using the Illumina 450k array or 27k array platforms. To classify our samples according to the TCGA pan-glioma DNA methylation classification, we trained a Random Forest classifier on this dataset using the 1,300 CpG probe signature provided by the authors and using the default settings of the Random Forest algorithms implemented in the R package randomForest. The results of this classification for astrocytomas, oligodendrogliomas and glioblastomas are shown in Extended Data Figure 3d and are given on a case-by-case basis in Supplementary Table 2 and 4.
Capper D., Jones D.T., Sill M., Hovestadt V., Schrimpf D., Sturm D., Koelsche C., Sahm F., Chavez L., Reuss D.E., Kratz A., Wefers A.K., Huang K., Pajtler K.W., Schweizer L., Stichel D., Olar A., Engel N.W., Lindenberg K., Harter P.N., Braczynski A., Plate K.H., Dohmen H., Garvalov B.K., Coras R., Hölsken A., Hewer E., Bewerunge-Hudler M., Schick M., Fischer R., Beschorner R., Schittenhelm J., Staszewski O., Wani K., Varlet P., Pages M., Temming P., Lohmann D., Selt F., Witt H., Milde T., Witt O., Aronica E., Giangaspero F., Rushing E., Scheurlen W., Geisenberger C., Rodriguez F.J., Becker A., Preusser M., Haberler C., Bjerkvig R., Cryan J., Farrell M., Deckert M., Hench J., Frank S., Serrano J., Kannan K., Tsirigos A., Brück W., Hofer S., Brehmer S., Seiz-Rosenhagen M., Hänggi D., Hans V., Rozsnoki S., Hansford J.R., Kohlhof P., Kristensen B.W., Lechner M., Lopes B., Mawrin C., Ketter R., Kulozik A., Khatib Z., Heppner F., Koch A., Jouvet A., Keohane C., Mühleisen H., Mueller W., Pohl U., Prinz M., Benner A., Zapatka M., Gottardo N.G., Driever P.H., Kramm C.M., Müller H.L., Rutkowski S., von Hoff K., Frühwald M.C., Gnekow A., Fleischhack G., Tippelt S., Calaminus G., Monoranu C.M., Perry A., Jones C., Jacques T.S., Radlwimmer B., Gessi M., Pietsch T., Schramm J., Schackert G., Westphal M., Reifenberger G., Wesseling P., Weller M., Collins V.P., Blümcke I., Bendszus M., Debus J., Huang A., Jabado N., Northcott P.A., Paulus W., Gajjar A., Robinson G., Taylor M.D., Jaunmuktane Z., Ryzhova M., Platten M., Unterberg A., Wick W., Karajannis M.A., Mittelbronn M., Acker T., Hartmann C., Aldape K., Schüller U., Buslei R., Lichter P., Kool M., Herold-Mende C., Ellison D.W., Hasselblatt M., Snuderl M., Brandner S., Korshunov A., von Deimling A, & Pfister S.M. (2018). DNA methylation-based classification of central nervous system tumours. Nature, 555(7697), 469-474.
Publication 2018
Astrocytoma Brain Neoplasm, Malignant Central Nervous System Neoplasms DNA Methylation Genome Glioblastoma Glioblastoma Multiforme Glioma Malignant Neoplasms Methylation Neoplasms Oligodendroglioma
4
Molecular Characterization of Glioma Tumors
To better understand the genetic pathogenesis of gliomas and begin to identify potential glioma-specific molecular therapeutic targets, consistent molecular characterization of a large number of tumors is required.
This process was undertaken under a national prospective clinical trial that would eventually be IRB-approved both within the NCI intramural program as well as through both CTEP-sponsored adult brain tumor consortia (NABTT and NABTC protocol # 01-07). With the activation of this study, we collected matched tumor, blood and plasma from the 14 contributing institutions (National Institutes of Health, Henry Ford Hospital, Thomas Jefferson University, University of California San Francisco, H. Lee Moffitt Hospital, University of Wisconsin, University of Pittsburgh Medical Center, University of California Los Angeles, M.D. Anderson Cancer Center, Dana Farber Cancer Center, Duke University, Johns Hopkins University, Massachusetts General Hospital and Memorial Sloan Kettering Cancer Center). All tissue collected is sent to the Neuro-Oncology Branch laboratory for processing. The samples were provided as snap frozen sections of areas immediately adjacent to the region used for the histopathological diagnosis. Initial histopathological diagnosis is performed at the tissue collecting institution following the World Health Organization (WHO) standards(6 (link)). The initial diagnosis is reviewed by in-house neuropathologists to assure a measure of consistency across samples. To date, 874 complete frozen sample sets have been accrued, of those 389 are Glioblastoma Multiforme, 122 are Astrocytomas, 113 are Oligodendrogliomas, 33 are Mixed with the reminder still unclassified.
Clinical data on the patients is collected prospectively until the patient’s death through the NABTC Operations Office at M.D. Anderson Cancer Center, Houston, Texas and the NABTT Operations office at the Johns Hopkins University, Baltimore, MD. The clinical data collected is updated into the Rembrandt database on a quarterly basis.
In order to assure consistency in the collection, shipment, processing, assaying, storage, data retrieval and dissemination, we have put together a series of standard operating procedures (SOPs) that have resulted in a streamlined, high-throughput operation capable of handling large numbers of samples in a consistent, operator-independent fashion. Consistency of data over time is continuously monitored by looking for any signs of batch effect in the analyses.
Madhavan S., Zenklusen J.C., Kotliarov Y., Sahni H., Fine H.A, & Buetow K. (2009). Rembrandt: Helping Personalized Medicine Become a Reality Through Integrative Translational Research. Molecular cancer research : MCR, 7(2), 157-167.
Publication 2009
Adult Astrocytoma BLOOD Brain Neoplasms Diagnosis Freezing Frozen Sections Glioblastoma Multiforme Glioma Malignant Neoplasms Neoplasms Neuropathologist Oligodendroglioma pathogenesis Patients Plasma Surgery, Office Therapeutics Tissues
5
Comprehensive Pan-cancer RNA-Seq and Protein Expression Analysis
The pancan normalized gene-level RNA-Seq data for the TCGA cohorts were downloaded from the UC Santa Cruz Cancer Genomics Browser [67 (link)] (https://genome-cancer.ucsc.edu/). These cohorts consisted of adrenocortical cancer (ACC, Ntumor = 79, Nnormal 
= 0), bladder urothelial carcinoma (BLCA, Ntumor = 407, Nnormal 
= 19), lower grade glioma (LGG, Ntumor = 530, Nnormal 
= 0), breast invasive carcinoma (BRCA, Ntumor = 1097, Nnormal 
= 113), cervical and endocervical cancer (CESC, Ntumor = 305, Nnormal 
= 3), colon and rectum adenocarcinoma (COADREAD, Ntumor = 383, Nnormal 
= 50), glioblastoma multiforme (GBM, Ntumor = 167, Nnormal 
= 5), head and neck squamous cell carcinoma (HNSC Ntumor = 521, Nnormal 
= 43), kidney chromophobe (KICH, Ntumor = 66, Nnormal 
= 25), kidney clear cell carcinoma (KIRC, Ntumor = 530, Nnormal 
= 72), kidney papillary cell carcinoma (KIRP, Ntumor = 291, Nnormal 
= 32), liver hepatocellular carcinoma (LIHC, Ntumor = 373, Nnormal 
= 50), lung adenocarcinoma (LUAD, Ntumor = 510, Nnormal 
= 58), lung squamous cell carcinoma (LUSC, Ntumor = 502, Nnormal 
= 51), ovarian serous cystadenocarcinoma (OVCA, Ntumor = 266, Nnormal 
= 0), prostate adenocarcinoma (PRAD, Ntumor = 498, Nnormal 
= 52), skin cutaneous melanoma (SKCM, Ntumor = 472, Nnormal 
= 1), thyroid carcinoma (THCA, Ntumor = 513, Nnormal 
= 59), and uterine carcinosarcoma (UCS, Ntumor = 57, Nnormal 
= 0).
TCGA ccRCC-specific analyses were performed with the KIRC datasets downloaded from Firebrowse (http://firebrowse.org). RSEM-normalized gene level data and reverse phase protein array (RPPA) data were used for gene and protein expression analyses, respectively. Samples that had RNA-Seq, mutation and clinical data (n = 415) were included in the discovery phase of the immune infiltration clusters.
The Sato et al. [29 (link)] Agilent microarray gene expression dataset was downloaded from ArrayExpress (http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1980/) and all samples (n = 101) were included in the analysis. The probe identifiers in the Agilent platform were mapped to HGNC gene symbols and the arithmetic mean across identifiers was used for cases where multiple Agilent identifiers mapped to a single HGNC symbol.
The Gerlinger et al. [57 (link)] Affymetrix Human Gene 1.0 ST microarray gene expression dataset was obtained via personal communication with the authors on 10 November 2014. This dataset includes 56 tumor and six normal samples from nine ccRCC patients. All samples were included in our analysis. The probe sets in this Affymetrix platform were mapped to HGNC gene symbols and the geometric mean across probe sets was used for cases where multiple probe sets mapped to a single HGNC symbol.
Şenbabaoğlu Y., Gejman R.S., Winer A.G., Liu M., Van Allen E.M., de Velasco G., Miao D., Ostrovnaya I., Drill E., Luna A., Weinhold N., Lee W., Manley B.J., Khalil D.N., Kaffenberger S.D., Chen Y., Danilova L., Voss M.H., Coleman J.A., Russo P., Reuter V.E., Chan T.A., Cheng E.H., Scheinberg D.A., Li M.O., Choueiri T.K., Hsieh J.J., Sander C, & Hakimi A.A. (2016). Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures. Genome Biology, 17, 231.
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Publication 2016
Adenocarcinoma Adenocarcinoma of Lung Breast Carcinoma Cancer of Adrenal Cortex Carcinoma, Thyroid Carcinoma, Transitional Cell Carcinosarcoma Chromophobia Colon Endocervix Familial Atypical Mole-Malignant Melanoma Syndrome Gene Expression Genes Genome Glioblastoma Multiforme Glioma Hepatocellular Carcinomas Homo sapiens Hypernephroid Carcinomas Kidney Lung Malignant Neoplasms Microarray Analysis Mutation Neck Neoplasms Ovary Patients Prostate Protein Arrays Proteins Rectum RNA-Seq Serous Cystadenocarcinoma Squamous Cell Carcinoma Squamous Cell Carcinoma of the Head and Neck Urinary Bladder Uterus

Most recents protocols related to «Glioblastoma Multiforme»

1
Enhancing Anti-Cancer Activity in Brain Cancers
Not available on PMC !

Example 7

An amount of any one of the compounds of the present invention in combination with an anti-cancer agent is administered to a subject afflicted with brain cancer. The amount of the compound is effective to enhance the anti-cancer activity of the anti-cancer agent.

An amount of any one of the compounds of the present invention in combination with ionizing radiation, x-radiation, docetaxel or temozolomide is administered to a subject afflicted with brain cancer. The amount of the compound is effective to enhance the anti-cancer activity of the ionizing radiation, x-radiation, docetaxel or temozolomide.

An amount of any one of the compounds of the present invention in combination with an anti-cancer agent is administered to a subject afflicted with diffuse intrinsic pontine glioma or glioblastoma multiforme. The amount of the compound is effective to enhance the anti-cancer activity of the anti-cancer agent.

An amount of any one of the compounds of the present invention in combination with ionizing radiation, x-radiation, docetaxel or temozolomide is administered to a subject afflicted with diffuse intrinsic pontine glioma or glioblastoma multiforme. The amount of the compound is effective to enhance the anti-cancer activity of the ionizing radiation, x-radiation, docetaxel or temozolomide.

US11866444B2. Oxabicycloheptane prodrugs (2024-01-09). Lixte Biotechnology, Inc. [US]. Inventors: John S. Kovach [US], Robert A. Volkmann [US], Anthony Marfat [US].
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Patent 2024
Brain Neoplasm, Malignant Diffuse Intrinsic Pontine Glioma Docetaxel Glioblastoma Multiforme Malignant Neoplasms Radiation, Ionizing Roentgen Rays Temozolomide
2
GWAS of Malignant Brain Tumors
We used summary data from a GWAS that was made public by the FinnGen consortium (Release 5, https://www.finngen.fi/en), including 464 cases and 174,006 controls for malignant brain tumors (all cancers excluded), 91 cases and 174,006 controls for brain glioblastoma (all cancers excluded) and 640 cases and 174,006 controls for malignant neoplasm of meninges (all cancers excluded).
All GWAS summary data on exposure and outcomes were based on the European population.
Zhang Q., Wu G., Zhang X., Zhang J., Jiang M., Zhang Y., Ding L, & Wang Y. (2023). Vascular endothelial growth factor and risk of malignant brain tumor: A genetic correlation and two-sample Mendelian randomization study. Frontiers in Oncology, 13, 991825.
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Publication 2023
Brain Europeans Genome-Wide Association Study Glioblastoma Multiforme Malignant Neoplasms Malignant Primary Brain Neoplasms Meningeal Cancer
3
Awake Surgery for Dominant and Non-Dominant Glioma
As an observational retrospective study, we reviewed a cohort of 80 patients who underwent awake surgery with intraoperative direct electrical mapping for dominant and nondominant hemispheres. All patients were treated at Department of Neurosurgery, Tangdu Hospital, Airforce Medical University, from January 2013 to December 2021. The inclusion criteria were (1) age ≥ 18 years, (2) newly diagnosed glioma, including astrocytoma, oligodendroglioma, anaplastic oligodendroglioma, anaplastic astrocytoma, anaplastic oligoastrocytoma, and glioblastoma, based on the WHO 2007 classification. The WHO 2016 classification was applied in 2017-2019 (31 cases), and the WHO 2021 classification of glioma was applied in 2021 (18 cases). The exclusion criteria included biopsy and incomplete MRI data calculating the tumor volume.
Demographic, clinical, and histological data were collected and analyzed from patients and neurocognitive and functional outcomes. The Institutional Review Board at Tangdu Hospital approved the study (TDLL-202210-18).
Wang Y., Guo S., Wang N., Liu J., Chen F., Zhai Y., Wang Y., Jiao Y., Zhao W., Fan C., Xue Y., Gao G., Ji P, & Wang L. (2023). The clinical and neurocognitive functional changes with awake brain mapping for gliomas invading eloquent areas: Institutional experience and the utility of The Montreal Cognitive Assessment. Frontiers in Oncology, 13, 1086118.
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Publication 2023
Anaplasia Anaplastic Oligodendroglioma Astrocytoma Astrocytoma, Anaplastic Biopsy Electricity Ethics Committees, Research Glioblastoma Multiforme Glioma Mixed Oligodendroglioma-Astrocytoma Neurosurgical Procedures Oligodendroglioma Operative Surgical Procedures Patients
4
Prognostic Analysis of Glioma Subtypes
To determine the correlation between single gene expression and clinical characteristics and prognosis of glioma patients, we conducted univariate and multivariate independent prognostic analysis on gene expression profile, clinical profile, and survival profile in CGGA and GSE43378 by Cox regression method using survival R package. The clinical profile of glioma patients in CGGA and GSE43378 are shown in Table 1. We further screened out clinical characteristics relating to glioma prognosis and determined the prognostic value of the single gene, p<0.05 was considered statistically significant.

Clinical Characteristics of Patients with Glioma in CGGA and GSE43378

ParametersCGGA (N=749)GSE43378 (N=50)
Age
<=41, n (%)342(45.7)12(24.0)
>41, n (%)407(54.3)38(76.0)
Gender
Female, n (%)307(41.0)16(32.0)
Male, n (%)442(59.0)34(68.0)
Radio
No, n (%)124(16.6)–
Yes, n (%)625(83.4)–
Chemo
No, n (%)229(30.6)–
Yes, n (%)520(69.4)–
Histology
Astrocytoma (A), n (%)75(10.0)5(10.0)
Anaplastic astrocytoma (AA), n (%)75(10.0)7(14.0)
Anaplastic oligodendroglioma (AO), n (%)37(04.9)4(08.0)
Anaplastic oligoastrocytoma (AOA), n (%)128(17.1)2(04.0)
Oligodendroglioma (O), n (%)39(05.2)–
Oligoastrocytoma (OA), n (%)104(13.9)–
Glioblastoma (GBM), n (%)291(38.9)32(64.0)
PRS_type
Primary, n (%)502(67.0)–
Recurrent, n (%)222(29.7)–
Secondary, n (%)25(03.3)–
Grade
WHO II, n (%)218(29.1)5(10.0)
WHO III, n (%)240(32.0)13(26.0)
WHO IV, n (%)291(38.9)32(64.0)
IDH_mutation
Wildtype, n (%)339(45.3)–
Mutant, n (%)410(54.7)–
1p19q_codeletion
Non-codel, n (%)594(79.3)–
Codel, n (%)155(20.7)–
Survival state
Live, n (%)293(39.1)8(16.0)
Dead, n (%)456(60.9)42(84.0)
Zhang J.J., Zhang Y., Chen Q., Chen Q.N., Yang X., Zhu X.L., Hao C.Y, & Duan H.B. (2023). A Novel Prognostic Marker and Therapeutic Target Associated with Glioma Progression in a Tumor Immune Microenvironment. Journal of Inflammation Research, 16, 895-916.
Publication 2023
Anaplasia Anaplastic Oligodendroglioma Astrocytoma, Anaplastic Gene Expression Gene Expression Profiling Genes Glioblastoma Multiforme Glioma Males Mixed Oligodendroglioma-Astrocytoma Oligodendroglioma Patients Prognosis
5
TCGA pan-cancer gene expression profiling
Manifests containing fragments per kilobase per million (FPKM) normalized RNA-seq data from 34 TCGA cohorts – Acute Myeloid Leukemia - (TCGA-LAML), Adrenocortical carcinoma (TCGA-ACC), Bladder Urothelial Carcinoma (TCGA-BLCA), Glioblastoma multiforme and Brain Lower Grade Glioma and (TCGA-GBMLGG), Breast Invasive Carcinomas (TCGA-BRCA), Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (TCGA-CESC), Cholangiocarcinoma (TCGA-CHOL), Chronic Myelogenous Leukemia (TCGA-LCML), Colon Adenocarcinoma (TCGA-COAD), Esophageal Carcinoma (TCGA-ESCA), Head and Neck Squamous Cell Carcinoma (TCGA-HNSC), pan-Kidney Cancer (TCGA-KIPAN), Liver Hepatocellular Carcinoma (TCGA-LIHC), Lung Adenocarcinoma (TCGA-LUAD), Lung Squamous Cell Carcinoma (TCGA-LUSC), Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (TCGA-DLBC), Mesothelioma (TCGA-MESO), Ovarian Serous Cystadenocarcinoma (TCGA-OV), Pancreatic Adenocarcinoma (TCGA-PAAD), Pheochromocytoma and Paraganglioma (TCGA-PCPG), Prostate Adenocarcinoma (TCGA-PRAD), Rectum Adenocarcinoma (TCGA-READ), Sarcoma (TCGA-SARC), Skin Cutaneous Melanoma (TCGA-SKCM), Stomach Adenocarcinoma (TCGA-STAD), Testicular Germ Cell Tumors (TCGA-TGCT), Thymoma (TCGA-TGCT), Thyroid Carcinoma (TCGA-THCA), Uterine Carcinosarcoma (TCGA-USC), Uterine Corpus Endometrial Carcinoma (TCGA-UCES), Uveal Melanoma (TCGA-UVM) were downloaded from the Broad Institute GDAC (TCGA data version 20150601). Patients were then sorted by increasing B7-H3 expression in each cohort.
Liu H.J., Du H., Khabibullin D., Zarei M., Wei K., Freeman G.J., Kwiatkowski D.J, & Henske E.P. (2023). mTORC1 upregulates B7-H3/CD276 to inhibit antitumor T cells and drive tumor immune evasion. Nature Communications, 14, 1214.
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Publication 2023
4-carboxyphenylglyoxal Adenocarcinoma Adenocarcinoma of Lung Adrenocortical Carcinoma Brain Breast Carcinoma Cancer of Kidney Carcinoma, Thyroid Carcinoma, Transitional Cell Carcinosarcoma Cholangiocarcinoma Chronic Obstructive Airway Disease Colon Adenocarcinomas Diffuse Large B-Cell Lymphoma Endocervix Endometrial Carcinoma Esophageal Cancer Familial Atypical Mole-Malignant Melanoma Syndrome Glioblastoma Multiforme Glioma Hepatocellular Carcinomas Leukemia, Myelocytic, Acute Leukemias, Chronic Granulocytic Lung Lymph Mesothelioma Neck Neoplasms Ovary Pancreas Paraganglioma Patients Pheochromocytoma Prostate Rectum RNA-Seq Sarcoma Serous Cystadenocarcinoma Squamous Cell Carcinoma Squamous Cell Carcinoma of the Head and Neck Stomach Testicular Germ Cell Tumor Thymoma Urinary Bladder Uterus Uveal melanoma X-Ray Photoelectron Spectroscopy

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Penicillin streptomycin by Thermo Fisher Scientific
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Penicillin/streptomycin is a commonly used antibiotic solution for cell culture applications. It contains a combination of penicillin and streptomycin, which are broad-spectrum antibiotics that inhibit the growth of both Gram-positive and Gram-negative bacteria.
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Ln229 by American Type Culture Collection
Sourced in United States, China, United Kingdom, Switzerland, Japan, Germany
The LN229 is a cell line derived from human glioblastoma. It is a commonly used in vitro model for the study of glioblastoma, a type of brain cancer. The LN229 cell line is available for purchase from the American Type Culture Collection (ATCC) for research purposes.
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Penicillin by Thermo Fisher Scientific
Sourced in United States, United Kingdom, Germany, China, France, Canada, Japan, Australia, Switzerland, Italy, Israel, Belgium, Austria, Spain, Brazil, Netherlands, Gabon, Denmark, Poland, Ireland, New Zealand, Sweden, Argentina, India, Macao, Uruguay, Portugal, Holy See (Vatican City State), Czechia, Singapore, Panama, Thailand, Moldova, Republic of, Finland, Morocco
Penicillin is a type of antibiotic used in laboratory settings. It is a broad-spectrum antimicrobial agent effective against a variety of bacteria. Penicillin functions by disrupting the bacterial cell wall, leading to cell death.
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U87mg by American Type Culture Collection
Sourced in United States, China, Italy, Germany, Japan, United Kingdom
U87MG is a human glioblastoma cell line derived from a malignant brain tumor. It is a well-established model system used in cancer research and drug discovery studies.
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Streptomycin by Thermo Fisher Scientific
Sourced in United States, United Kingdom, Germany, China, France, Canada, Australia, Japan, Switzerland, Italy, Belgium, Israel, Austria, Spain, Netherlands, Poland, Brazil, Denmark, Argentina, Sweden, New Zealand, Ireland, India, Gabon, Macao, Portugal, Czechia, Singapore, Norway, Thailand, Uruguay, Moldova, Republic of, Finland, Panama
Streptomycin is a broad-spectrum antibiotic used in laboratory settings. It functions as a protein synthesis inhibitor, targeting the 30S subunit of bacterial ribosomes, which plays a crucial role in the translation of genetic information into proteins. Streptomycin is commonly used in microbiological research and applications that require selective inhibition of bacterial growth.
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Fetal bovine serum (fbs) by Merck Group
Sourced in United States, Germany, United Kingdom, Japan, Italy, China, Macao, Switzerland, France, Canada, Sao Tome and Principe, Spain, Australia, Ireland, Poland, Belgium, Denmark, India, Sweden, Israel, Austria, Brazil, Czechia, Netherlands, Portugal, Norway, Holy See (Vatican City State), New Zealand, Hungary, Senegal, Argentina, Thailand, Singapore, Ukraine, Mexico
FBS, or Fetal Bovine Serum, is a commonly used cell culture supplement. It is derived from the blood of bovine fetuses and provides essential growth factors, hormones, and other nutrients to support the growth and proliferation of a wide range of cell types in vitro.

More about "Glioblastoma Multiforme"

Glioblastoma Multiforme (GBM) is an aggressive and highly malignant form of brain cancer that originates from glial cells.
It is characterized by rapid growth, extensive invasion of surrounding brain tissue, and poor prognosis.
GBM is the most common and deadly primary brain tumor, accounting for over 50% of all brain cancer cases.
Effective treatment protocols are crucial for improving outcomes in patients with this devastating disease.
Researchers often use cell lines like LN229 and U87MG to study GBM in the lab.
These cell lines are commonly cultured in Dulbecco's Modified Eagle Medium (DMEM) supplemented with Fetal Bovine Serum (FBS) and antibiotics like Penicillin and Streptomycin to prevent bacterial contamination.
Understanding the molecular mechanisms driving GBM, as well as developing novel therapies, is an active area of research.
Synonyms for GBM include glioblastoma, GBM, grade IV astrocytoma, and malignant glioma.
Related terms include astrocytes, glial cells, brain cancer, and neuro-oncology.
Abbreviations used in the field include GBM, WHO (World Health Organization), and CNS (Central Nervous System).
Key subtopics in GBM research include tumor heterogeneity, angiogenesis, invasion, tumor microenvironment, cancer stem cells, and resistance to treatment.
Leveraging the power of AI, platforms like PubCompare.ai can help researchers optimize their GBM research protocols by identifying the most effective methods and products from the literature, pre-prints, and patents.
This can enhance reproducibility and accuracy in GBM studies, ultimately leading to better outcomes for patients.