Expression of pluripotency-related genes in human glioblastoma

Background Cancer is a group of heterogeneous diseases characterized by several disruptions of the genetic and epigenetic components of cell biology. Some types of cancer have been shown to be constituted by a mosaic of cells with variable differentiation states, with more aggressive tumors being more undifferentiated. In most cases, undifferentiated tumor cells express associated embryonic markers such as the OCT4, NANOG, SOX2 and CARM1 genes. The ectopic or reminiscent expression of some master regulator genes of pluripotency has been indicated as the cause of the poorly differentiated state of tumors, and based on the evidence of some reports, can be used as a possible therapeutic target. Considering this information, a more detailed investigation of the expression of pluripotency-associated genes is necessary to evaluate the roles of these genes in the etiology of some tumors and their use targets of therapy. Methods The expression of four pluripotency-related genes was investigated (OCT4, NANOG, SOX2 and CARM1) in the most malignant primary human brain tumor, glioblastoma (GBM). Results and Conclusion The results demonstrated a signature of OCT4/SOX2/CARM1 genes and a significant increase of CARM1 expression in GBM cases.

circSMARCA5-SRSF1 interaction is functionally involved in GBM pathogenesis

Glioblastoma multiforme (GBM) is the most aggressive human brain tumor with a median survival of 15 months. The standard treatments of GBM and the total medical resection are unable to contrast this mortal cancer. For these reason new diagnostic approaches and therapies are needed. The identification of molecular features of this cancer may allow to create a personalized therapy. Circular RNAs (circRNAs) are a new class of non-coding RNAs (ncRNAs) highly enriched in brain, stable within the cells, detectable in body fluids and having a potential role and biological importance still object of debate. This thesis investigated the putative involvement of circRNAs in GBM pathogenesis. It has been demonstrated that circSMARCA5 is downregulated in GBM biopsies, its expression is associated to the glioma grade malignancy and it negatively regulates migration of U87MG cells. Moreover, it has been proved the physical interaction between circSMARCA5 and one of its predicted interactor Serine/arginine-rich splicing factor 1 (SRSF1). Interesting splicing targets of SRSF1 are the serine and arginine rich splicing factor 3 (SRSF3) and the vascular endothelial growth factor A (VEGFA). It has been proposed that circSMARCA5 may regulate the alternative splicing of SRSF3 in favor of the formation of a stable oncoprotein in GBM. It also regulates the alternative splicing of VEGFA mRNA through the binding to SRSF1. In addition, blood vascular microvessel density evaluated in GBM negatively correlates with the expression of circSMARCA5, while positively correlates with that of SRSF1 and pro-to-anti-angiogenic VEGFA isoform ratio. GBM patients with low circSMARCA5 expression have lower overall and progression free survival rates. Based on these findings, CircSMARCA5 could be considered a promising druggable tumor suppressor in GBM. Moreover, its interaction with SRSF1 makes circSMARCA5 an upstream regulator of pro- to anti-angiogenic VEGFA isoforms ratio within GBM cells and a highly promising GBM prospective anti-angiogenic molecule.

Automatic cell counting from stimulated Raman imaging using deep learning

In this paper, we propose an automatic cell counting framework for stimulated Raman scattering (SRS) images, which can assist tumor tissue characteristic analysis, cancer diagnosis, and surgery planning processes. SRS microscopy has promoted tumor diagnosis and surgery by mapping lipids and proteins from fresh specimens and conducting a fast disclose of fundamental diagnostic hallmarks of tumors with a high resolution. However, cell counting from label-free SRS images has been challenging due to the limited contrast of cells and tissue, along with the heterogeneity of tissue morphology and biochemical compositions. To this end, a deep learning-based cell counting scheme is proposed by modifying and applying U-Net, an effective medical image semantic segmentation model that uses a small number of training samples. The distance transform and watershed segmentation algorithms are also implemented to yield the cell instance segmentation and cell counting results. By performing cell counting on SRS images of real human brain tumor specimens, promising cell counting results are obtained with > 98% of area under the curve (AUC) and R = 0.97 in terms of cell counting correlation between SRS and histological images with hematoxylin and eosin (H&E) staining. The proposed cell counting scheme illustrates the possibility and potential of performing cell counting automatically in near real time and encourages the study of applying deep learning techniques in biomedical and pathological image analyses.

Effects of Electroporation on Anticancer Activity of 5-FU and Newly Synthesized zinc(II) Complex in Chemotherapy-resistance Human Brain Tumor Cells

Zn(II) complex of Schiff base derived from the condensation of 4-aminopyrimidine-2(1H)-one with salicylaldehyde was prepared and characterized by various physico‐chemical and spectral methods for structure determination. The cytotoxic activity of the Zn(II) complex was investigated in comparison with 5-fluorouracil (5-FU) against two different human brain tumor cell lines (T98G and U118), while primer human dermal fibroblast cells (HDF) was used as control for biocompatibility. Then, the effectiveness of electroporation (EP) on cytotoxic activities of these compounds has been examined. The cytotoxicities of the 5-FU and new Zn(II) complex, alone or in combination with electroporation, were determined by MTT assay. The Zn(II) complex showed good cytotoxicity against T98G and U118 brain tumor cell lines with IC50 = 282.47 and 297.91 μM respectively, while it was safe on HDF healthy cells with IC50 = 826.72 μM. The 5-FU exhibited less cytotoxicity compared to the Zn(II) complex against T98G (IC50 = 382.35 μM) and U118 (IC50 = 396.56 μM) tumor cell lines. The combined application of Zn (II) + EP decreased the IC50 value by 5.96-fold in T98G cells and 4.76-fold in U118 cells. EP showed a similar effect in its combined application with 5-FU, resulting in a decrease of the IC50 value of 4.22-fold in the T98G cells and 3.84-fold in the U118 cells. In a conclusion, the Zn(II) complex exhibited an anticancer potential against both brain tumor cell lines (T98G and U118) and EP greatly increased the cytotoxicity of Zn(II) complex and 5-FU on these chemotherapy-resistant cells.

Extracellular Sphingosine-1-Phosphate Downstream of EGFR Increases Human Glioblastoma Cell Survival

Sphingosine-1-phosphate (S1P) is a crucial mediator involved in the progression of different cancers, including glioblastoma multiforme (GBM), the most frequent and deadly human brain tumor, characterized by extensive invasiveness and rapid cell growth. Most of GBMs overexpress the epidermal growth factor receptor (EGFR), and we investigated the possible link between S1P and EGFR signaling pathways, focusing on its role in GBM survival, using the U87MG human cell line overexpressing EGFR (EGFR+). We previously demonstrated that EGFR+ cells have higher levels of extracellular S1P and increased sphingosine kinase-1 (SK1) activity than empty vector expressing cells. Notably, we demonstrated that EGFR+ cells are resistant to temozolomide (TMZ), the standard chemotherapeutic drug in GBM treatment, and the inhibition of SK1 or S1P receptors made EGFR+ cells sensitive to TMZ; moreover, exogenous S1P reverted this effect, thus involving extracellular S1P as a survival signal in TMZ resistance in GBM cells. In addition, both PI3K/AKT and MAPK inhibitors markedly reduced cell survival, suggesting that the enhanced resistance to TMZ of EGFR+ cells is dependent on the increased S1P secretion, downstream of the EGFR-ERK-SK1-S1P pathway. Altogether, our study provides evidence of a functional link between S1P and EGFR signaling pathways enhancing the survival properties of GBM cells.

Raman imaging and statistical methods for analysis various type of human brain tumor

Spectroscopic methods provide information on the spatial localization of biochemical components based on the analysis of vibrational spectra. Raman spectroscopy and Raman imaging can be used to analyze various types of human brain tissue. The objective of this study is employment of Raman spectroscopy and Raman imaging to evaluate the Raman biomarkers to distinguish tumor types. We have demonstrated that bands characteristic for carotenoids (1156 cm-1, 1520 cm-1), proteins (1004 cm-1), fatty acids (1444 cm-1, 1655 cm-1) and cytochrome (1585 cm-1) can be used as universal biomarkers to distinguish aggressiveness in human brain tumor. The sensitivity and specificity obtained from PLS-DA have been over 85%. Only for pituitary adenoma the specificity is lower and takes equal 46%. The presented results confirm the potential applications of vibrational spectroscopy methods in oncological diagnostics.