Ion Channels in Glioblastoma

Glioblastoma is the most common primary brain tumor with the most dismal prognosis. It is characterized by extensive invasion, migration, and angiogenesis. Median survival is only 15 months due to this behavior, rendering focal surgical resection ineffective and adequate radiotherapy impossible. At this moment, several ion channels have been implicated in glioblastoma proliferation, migration, and invasion. This paper summarizes studies on potassium, sodium, chloride, and calcium channels of glioblastoma. It provides an up-to-date overview of the literature that could ultimately lead to new therapeutic targets

Recent advances in the molecular understanding of glioblastoma

Glioblastoma is the most common and most aggressive primary brain tumor. Despite maximum treatment, patients only have a median survival time of 15 months, because of the tumor’s resistance to current therapeutic approaches. Thus far, methylation of the O6-methylguanine-DNA methyltransferase (MGMT) promoter has been the only confirmed molecular predictive factor in glioblastoma. Novel “genome-wide” techniques have identified additional important molecular alterations as mutations in isocitrate dehydrogenase 1 (IDH1) and its prognostic importance. This review summarizes findings and techniques of genetic, epigenetic, transcriptional, and proteomic studies of glioblastoma. It provides the clinician with an up-to-date overview of current identified molecular alterations that should ultimately lead to new therapeutic targets and more individualized treatment approaches in glioblastoma

Mutational profiling of kinases in glioblastoma

Background: Glioblastoma is a highly malignant brain tumor for which no cure is available. To identify new therapeutic targets, we performed a mutation analysis of kinase genes in glioblastoma.Methods: Database mining and a literature search identified 76 kinases that have been found to be mutated at least twice in multiple cancer types before. Among those we selected 34 kinase genes for mutation analysis. We also included IDH1, IDH2, PTEN, TP53 and NRAS, genes that are known to be mutated at considerable frequencies in glioblastoma. In total, 174 exons of 39 genes in 113 glioblastoma samples from 109 patients and 16 high-grade glioma (HGG) cell lines were sequenced. Results: Our mutation analysis led to the identification of 148 non-synonymous somatic mutations, of which 25 have not been reported before in glioblastoma. Somatic mutations were found in TP53, PTEN, IDH1, PIK3CA, EGFR, BRAF, EPHA3, NRAS, TGFBR2, FLT3 and RPS6KC1. Mapping the mutated genes into known signaling pathways revealed that the large majority of them plays a central role in the PI3K-AKT pathway. Conclusions: The knowledge that at least 50% of glioblastoma tumors display mutational activation of the PI3K-AKT pathway should offer new opportunities for the rational development of therapeutic approaches for glioblastomas. However, due to the development of resistance mechanisms, kinase inhibition studies targeting the PI3K-AKT pathway for relapsing glioblastoma have mostly failed thus far. Other therapies should be investigated, targeting early events in gliomagenesis that involve both kinases and non-kinases

Molecular Assessment of Bacterial Vaginosis by Lactobacillus Abundance and Species Diversity

Background To date, women are most often diagnosed with bacterial vaginosis (BV) using microscopy based Nugent scoring or Amsel criteria. However, the accuracy is less than optimal. The aim of the present study was to confirm the identity of known BV-associated composition profiles and evaluate indicators for BV using three molecular methods. Methods Evaluation of indicators for BV was carried out by 16S rRNA amplicon sequencing of the V5-V7 region, a tailor-made 16S rRNA oligonucleotide-based microarray, and a PCR-based profiling technique termed IS-profiling, which is based on fragment variability of the 16S-23S rRNA intergenic spacer region. An inventory of vaginal bacterial species was obtained from 40 females attending a Dutch sexually transmitted infection outpatient clinic, of which 20 diagnosed with BV (Nugent score 7–10), and 20 BV negative (Nugent score 0–3). Results Analysis of the bacterial communities by 16S rRNA amplicon sequencing revealed two clusters in the BV negative women, dominated by either Lactobacillus iners or Lactobacillus crispatus and three distinct clusters in the BV positive women. In the former, there was a virtually complete, negative correlation between L. crispatus and L. iners. BV positive subjects showed cluster profiles that were relatively high in bacterial species diversity and dominated by anaerobic species, including Gardnerella vaginalis, and those belonging to the Families of Lachnospiraceae and Leptotrichiaceae. Accordingly, the Gini-Simpson index of species diversity, and the relative abundance Lactobacillus species appeared consistent indicators for BV. Under the conditions used, only the 16S rRNA amplicon sequencing method was suitable to assess species diversity, while all three molecular composition profiling methods were able to indicate Lactobacillus abundance in the vaginal microbiota. Conclusion An affordable and simple molecular test showing a depletion of the genus Lactobacillus in combination with an increased species diversity of vaginal microbiota could serve as an alternative and practical diagnostic method for the assessment of BV

Molecular assessment of bacterial vaginosis by Lactobacillus abundance and species diversity

__Background:__ To date, women are most often diagnosed with bacterial vaginosis (BV) using microscopy based Nugent scoring or Amsel criteria. However, the accuracy is less than optimal. The aim of the present study was to confirm the identity of known BV-associated composition profiles and evaluate indicators for BV using three molecular methods. __Methods:__ Evaluation of indicators for BV was carried out by 16S rRNA amplicon sequencing of the V5-V7 region, a tailor-made 16S rRNA oligonucleotide-based microarray, and a PCR-based profiling technique termed IS-profiling, which is based on fragment variability of the 16S-23S rRNA intergenic spacer region. An inventory of vaginal bacterial species was obtained from 40 females attending a Dutch sexually transmitted infection outpatient clinic, of which 20 diagnosed with BV (Nugent score 7-10), and 20 BV negative (Nugent score 0-3). __Results:__ Analysis of the bacterial communities by 16S rRNA amplicon sequencing revealed two clusters in the BV negative women, dominated by either Lactobacillus iners or Lactobacillus crispatus and three distinct clusters in the BV positive women. In the former, there was a virtually complete, negative correlation between L. crispatus and L. iners. BV positive subjects showed cluster profiles that were relatively high in bacterial species diversity and dominated by anaerobic species, including Gardnerella vaginalis, an

IDH1/2 Mutations in Cancer Stem Cells and Their Implications for Differentiation Therapy

Isocitrate dehydrogenase 1 and 2 (IDH1/2) are enzymes recurrently mutated in various types of cancer, including glioma, cholangiocarcinoma, chondrosarcoma, and acute myeloid leukemia. Mutant IDH1/2 induce a block in differentiation and thereby contribute to the stemness and oncogenesis of their cells of origin. Recently, small-molecule inhibitors of mutant IDH1/2 have been Food and Drug Administration–approved for the treatment of IDH1/2-mutated acute myeloid leukemia. These inhibitors decrease the stemness of the targeted IDH1/2-mutated cancer cells and induce their differentiation to more mature cells. In this review, we elucidate the mechanisms by which mutant IDH1/2 induce a block in differentiation and the biological and clinical effects of the release into differentiation by mutant-IDH1/2 inhibitors. (J Histochem Cytochem 70:83–97, 2022

A simple in silico approach to generate gene-expression profiles from subsets of cancer genomics data

In biomedical research, large-scale profiling of gene expression has become routine and offers a valuable means to evaluate changes in onset and progression of diseases, in particular cancer. An overwhelming amount of cancer genomics data has become publicly available, and the complexity of these data makes it a challenge to perform in silico data exploration, integration and analysis, in particular for scientists lacking a background in computational programming or informatics. Many web interface tools make these large datasets accessible but are limited to process large datasets. To accelerate the translation of genomic data into new insights, we provide a simple method to explore and select data from cancer genomic datasets to generate gene-expression profiles of subsets that are of specific genetic, biological or clinical interest