Meningiomas are the most common primary brain tumors bearing in a minority of cases an aggressive phenotype. Although meningiomas are stratified according to their histology and clinical behavior, the underlying molecular genetics predicting aggressiveness are not thoroughly understood. We performed whole transcript expression profiling in 10 grade I and four grade II meningiomas, three of which invaded the brain. Microarray expression analysis identified deleted in colorectal cancer (DCC) as a differentially expressed gene (DEG) enabling us to cluster meningiomas into DCC low expression (3 grade I and 3 grade II tumors), DCC medium expression (2 grade I and 1 grade II tumors), and DCC high expression (5 grade I tumors) groups. Comparison between the DCC low expression and DCC high expression groups resulted in 416 DEGs (p-value < 0.05; fold change > 2). The most significantly downregulated genes in the DCC low expression group comprised DCC, phosphodiesterase 1C (PDE1C), calmodulin-dependent 70kDa olfactomedin 2 (OLFM2), glutathione S-transferase mu 5 (GSTM5), phosphotyrosine interaction domain containing 1 (PID1), sema domain, transmembrane domain (TM) and cytoplasmic domain, (semaphorin) 6D (SEMA6D), and indolethylamine N-methyltransferase (INMT). The most significantly upregulated genes comprised chromosome 5 open reading frame 63 (C5orf63), homeodomain interacting protein kinase 2 (HIPK2), and basic helix-loop-helix family, member e40 (BHLHE40). Biofunctional analysis identified as predicted top upstream regulators beta-estradiol, TGFB1, Tgf beta complex, LY294002, and dexamethasone and as predicted top regulator effectors NFkB, PIK3R1, and CREBBP. The microarray expression data served also for a comparison between meningiomas from female and male patients and for a comparison between brain invasive and non-invasive meningiomas resulting in a number of significant DEGs and related biofunctions. In conclusion, based on its expression levels, DCC may constitute a valid biomarker to identify those benign meningiomas at risk for progression.

Table of contents O1 Regulation of genes by telomere length over long distances Jerry W. Shay O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa O3 Integration of metagenomics and metabolomics in gut microbiome research Maryam Goudarzi, Albert J. Fornace Jr. O4 A unique integrated system to discern pathogenesis of central nervous system tumors Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis Heba Alkhatabi O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp O7 Targeted sequencing panels and their utilization in personalized medicine Adel M. Abuzenadah O8 International biobanking in the era of precision medicine Jim Vaught O9 Biobank and biodata for clinical and forensic applications Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors Jaudah Al-Maghrabi O11 The CEGMR biobanking unit: achievements, challenges and future plans Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad O12 Phylomedicine of tumors Sudhir Kumar, Sayaka Miura, Karen Gomez O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment Angel Carracedo, Mahmood Rasool O14 From association to causality: translation of GWAS findings for genomic medicine Ahmed Rebai O15 E-GRASP: an interactive database and web application for efficient analysis of disease-associated genetic information Sajjad Karim, Hend F Nour Eldin, Heba Abusamra, Elham M Alhathli, Nada Salem, Mohammed H Al-Qahtani, Sudhir Kumar O16 The supercomputer facility “AZIZ” at KAU: utility and future prospects Hossam Faheem O17 New research into the causes of male infertility Ashok Agarwa O18 The Klinefelter syndrome: recent progress in pathophysiology and management Eberhard Nieschlag, Joachim Wistuba, Oliver S. Damm, Mohd A. Beg, Taha A. Abdel-Meguid, Hisham A. Mosli, Osama S. Bajouh, Adel M. Abuzenadah, Mohammed H. Al-Q...

Mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 are oncogenic drivers to a variable extent in several tumors, including gliomas, acute myeloid leukemia (AML), cholangiocarcinoma, melanoma, and thyroid carcinoma. The pathobiological effects of these mutations vary considerably, impeding the identification of common expression profiles. We performed an expression meta-analysis between IDH-mutant (IDHmut) and IDH-wild-type (IDHwt) conditions in six human and mouse isogenic disease models. The datasets included colon cancer cells, glioma cells, heart tissue, hepatoblasts, and neural stem cells. Among differentially expressed genes (DEGs), serine protease 23 (PRSS23) was upregulated in four datasets, i.e., in human colon carcinoma cells, mouse heart tissue, mouse neural stem cells, and human glioma cells. Carbonic anhydrase 2 (CA2) and prolyl 3-hydroxylase 2 (P3H2) were upregulated in three datasets, and SOX2 overlapping transcript (SOX2-OT) was downregulated in three datasets. The most significantly overrepresented protein class was termed intercellular signal molecules. An additional DEG set contained genes that were both up- and downregulated in different datasets and included oxidases and extracellular matrix structural proteins as the most significantly overrepresented protein classes. In conclusion, this meta-analysis provides a comprehensive overview of the expression effects of IDH mutations shared between different isogenic disease models. The generated dataset includes biomarkers, e.g., PRSS23 that may gain relevance for further research or clinical applications in IDHmut tumors.