Prognostic Impact of the Combination of MGMT Methylation and TERT Promoter Mutation in Glioblastoma

Background The concept of combinational analysis between the methylation of O6-methylguanine-DNA methyltransferase (MGMT) and telomerase reverse transcriptase promoter (pTERT) mutation in glioblastoma (GBM) has been reported. The main study objective was to determine the prognosis of patients with GBM based on MGMT/pTERT classification, while the secondary objective was to estimate the temozolomide effect on the survival time of GBM with MGMT/pTERT classification. Methods A total of 50 GBM specimens were collected after tumor resection and were selected for investigating MGMT methylation and pTERT mutation. Clinical imaging and pathological characteristics were retrospectively analyzed. Patients with MGMT/pTERT classification were analyzed using survival analysis to develop the nomogram for forecasting and individual prognosis. Results All patients underwent resection (total resection: 28%, partial resection: 64%, biopsy: 8%). Thirty-two percent of all cases received adjuvant temozolomide with radiotherapy. Sixty-four percent of the case was found methylated MGMT, and 56% of the present cohort found pTERT mutation. Following combinational analysis of biomarkers, results showed that the GBMs with methylated MGMT and wild-type pTERT had a superior prognosis compared with other subtypes. Using Cox regression analysis with multivariable analysis, the extent of resection, postoperative chemoradiotherapy, MGMT/pTERT classification were associated with a favorable prognosis. Hence, a web-based nomogram was developed for deploying individual prognostication. Conclusions The interaction of MGMT methylation and pTERT mutation was confirmed for predicting prognosis. The results from the present study could help physicians create treatment strategies for GBM patients in real-world situations.

Prognostic Values of B7-H3, B7-H4, and HHLA2 Expression in Human Pancreatic Cancer Tissues Based on mIHC and Spatial Distribution Analysis

Background: Pancreatic cancer (PC) is one of the most malignant cancers and its 5-year survival rate remains poor. Although immunotherapy has achieved certain therapeutic efficacy in some clinical trials, such treatment still shows low responsiveness and overall remission rate. Therefore, it is urgently necessary to dissect the tumor microenvironment and optimize the immunotherapeutic strategies against this malignancy.Methods: Using the multi-color immunohistochemistry, we investigated the expressions of B7-H3, B7-H4, HHLA2, CD8, and CD68 in 63 cases of PC tissues with the tissue microarray. Moreover, we analyzed immunolocalization features, prognostic values of this immune contexture, and clinical associations.Results: The expressions of B7-H3, B7-H4, and HHLA2 could be detected in cytokeratin (CK)+ tumor cells, CD68+macrophages, and even stromal cells. Higher expression of B7-H3 in tumor cells could predict a better survival of the PC patients. A positive correlation was found between the expressions of B7-H3 and HHLA2 in tumor cells, while there was a negative correlation between the expressions of B7-H4 and HHLA2 in tumor cells. A positive correlation was found between the expressions of B7-H3 and B7-H4 or HHLA2 in tumor-associated macrophages (TAMs), but not B7-H4 and HHLA2. Tumor-infiltrating CD8+T cells in combination with CD68+TAMs could serve as an important predictor for the postoperative prognosis of PC patients. Higher expression of B7-H3, or HHLA2 in CD68+TAMs could serve as an important predictor for poorer prognosis of PC patients. Patients with B7-H3lowB7-H4low, B7-H3lowHHLA2low, or B7-H4lowHHLA2low on CD68+TAMs could have a better postoperative prognosis compared with the other sub-populations in the combinational analysis.Conclusions: Taken together, our study indicated variable expressions and prognostic values of B7-H3, B7-H4, and HHLA2, in human PC tissues, and distinctively demonstrated that these immunosuppressive co-stimulators expressed by CD68+TAMs could be used as important bio-markers for the prognostic prediction of PC patients. Moreover, these results supported that the evaluation of these markers could be used as essential candidate targets for immunotherapy against PC.

Svalbamides A and B, Pyrrolidinone-Bearing Lipodipeptides from Arctic Paenibacillus sp.

Two new secondary metabolites, svalbamides A (1) and B (2), were isolated from a culture extract of Paenibacillus sp. SVB7 that was isolated from surface sediment from a core (HH17-1085) taken in the Svalbard archipelago in the Arctic Ocean. The combinational analysis of HR-MS and NMR spectroscopic data revealed the structures of 1 and 2 as being lipopeptides bearing 3-amino-2-pyrrolidinone, d-valine, and 3-hydroxy-8-methyldecanoic acid. The absolute configurations of the amino acid residues in svalbamides A and B were determined using the advanced Marfey’s method, in which the hydrolysates of 1 and 2 were derivatized with l- and d- forms of 1-fluoro-2,4-dinitrophenyl-5-alanine amide (FDAA). The absolute configurations of 1 and 2 were completely assigned by deducing the stereochemistry of 3-hydroxy-8-methyldecanoic acid based on DP4 calculations. Svalbamides A and B induced quinone reductase activity in Hepa1c1c7 murine hepatoma cells, indicating that they represent chemotypes with a potential for functioning as chemopreventive agents.

Multiple Screening of Pesticides Toxicity in Zebrafish and Daphnia Based on Locomotor Activity Alterations

Pesticides are widely used to eradicate insects, weed species, and fungi in agriculture. The half-lives of some pesticides are relatively long and may have the dire potential to induce adverse effects when released into the soil, terrestrial and aquatic systems. To assess the potential adverse effects of pesticide pollution in the aquatic environment, zebrafish (Danio rerio) and Daphnia magna are two excellent animal models because of their transparent bodies, relatively short development processes, and well-established genetic information. Moreover, they are also suitable for performing high-throughput toxicity assays. In this study, we used both zebrafish larvae and water flea daphnia neonates as a model system to explore and compare the potential toxicity by monitoring locomotor activity. Tested animals were exposed to 12 various types of pesticides (three fungicides and 9 insecticides) for 24 h and their corresponding locomotor activities, in terms of distance traveled, burst movement, and rotation were quantified. By adapting principal component analysis (PCA) and hierarchical clustering analysis, we were able to minimize data complexity and compare pesticide toxicity based on locomotor activity for zebrafish and daphnia. Results showed distinct locomotor activity alteration patterns between zebrafish and daphnia towards pesticide exposure. The majority of pesticides tested in this study induced locomotor hypo-activity in daphnia neonates but triggered locomotor hyper-activity in zebrafish larvae. According to our PCA and clustering results, the toxicity for 12 pesticides was grouped into two major groups based on all locomotor activity endpoints collected from both zebrafish and daphnia. In conclusion, all pesticides resulted in swimming alterations in both animal models by either producing hypo-activity, hyperactivity, or other changes in swimming patterns. In addition, zebrafish and daphnia displayed distinct sensitivity and response against different pesticides, and the combinational analysis approach by using a phenomic approach to combine data collected from zebrafish and daphnia provided better resolution for toxicological assessment.

Clinical exome sequencing as the first-tier test for diagnosing developmental disorders covering both CNV and SNV: a Chinese cohort

BackgroundDevelopmental disorders (DDs) are early onset disorders affecting 5%–10% of children worldwide. Chromosomal microarray analysis detecting CNVs is currently recommended as the first-tier test for DD diagnosis. However, this analysis omits a high percentage of disease-causing single nucleotide variations (SNVs) that warrant further sequencing. Currently, next-generation sequencing can be used in clinical scenarios detecting CNVs, and the use of exome sequencing in the DD cohort ahead of the microarray test has not been evaluated.MethodsClinical exome sequencing (CES) was performed on 1090 unrelated Chinese DD patients who were classified into five phenotype subgroups. CNVs and SNVs were both detected and analysed based on sequencing data.ResultsAn overall diagnostic rate of 41.38% was achieved with the combinational analysis of CNV and SNV. Over 12.02% of patients were diagnosed based on CNV, which was comparable with the published CMA diagnostic rate, while 0.74% were traditionally elusive cases who had dual diagnosis or apparently homozygous mutations that were clarified. The diagnostic rates among subgroups ranged from 21.82% to 50.32%. The top three recurrent cytobands with diagnostic CNVs were 15q11.2-q13.1, 22q11.21 and 7q11.23. The top three genes with diagnostic SNVs were: MECP2, SCN1A and SCN2A. Both the diagnostic rate and spectrums of CNVs and SNVs showed differences among the phenotype subgroups.ConclusionWith a higher diagnostic rate, more comprehensive observation of variations and lower cost compared with conventional strategies, simultaneous analysis of CNVs and SNVs based on CES showed potential as a new first-tier choice to diagnose DD.

Combinational analysis of IDH1/IDH2 mutations, 1p/19q deletions and MGMT promoter methylation for molecular testing of glioma.

e13152 Background: Mutations in IDH1 and IDH2, co-deletion of 1p and 19q, and the hyper methylation of the MGMT promoter are the most reported genetic alterations in glioma tumors. Therefore, we designed a study to analyze the prevalence of these biomarkers in glioma, and the correlation of these biomarkers with diagnosis and prognosis. Methods: From September 2018 to January 2019, eighteen patients with primary glioma were prospectively enrolled. For each patient, freshly frozen tissue or FFPE samples were collected. DNA was extracted from these samples and sequenced to at least 5,000× coverage. IDH1/IDH2 mutations and 1p/19q deletions were detected from the sequencing data, whereas MGMT promoter methylation was evaluated by real-time fluorescence qPCR. Results: Of the eighteen patients, 44.4%(8/18) and 33.3%(6/18) harbored IDH1 /IDH2 mutations and 1p/19q deletions, respectively, and 72.2%(13/18) contained MGMT promoter hyper methylation. Within these patients, we found a correlation between IDH1/IDH2 mutation and 1p/19q deletion. Namely, among the 8 patients with a IDH1/IDH2 mutation, 75%(6/8) also contained a 1p/19q deletion, whereas none of the 10 patients with wide-type IDH1/IDH2 displayed the 1p/19q deletion. There was also a correlation between mutations at the loci and MGMT promoter hyper-methylation, specifically, 87.5%(7/8) of the patients with IDH1/IDH2 mutations also exhibited hyper-methylation in MGMT, whereas only hyper-methylation was observed in only 40% (4/10) of IDH1/IDH2 negative patients. Conclusions: From our preliminary result, IDH1/IDH2 mutations may be associated with 1p/19q deletion. To further verify this result, a larger, longitudinal study is ongoing at our institution.

Objective and Combinational Analysis of Multiple Kinds of Data Obtained from Severe-Mild Wear Transition

The authors have been developing objective and combinational analysis method for multiple kinds of data obtained by a repeated sliding test performed with a pin-on-disk apparatus to clarify the wear mechanisms. The developed analysis method successfully showed the growth rate and the size of adhered substances on the sliding surface for adhesive wear mechanism. In this paper, the developed method was applied for analyzing chronological changes in severe-mild wear forms transition to understand the phenomena more quantitatively. Friction force, pin specimen displacement perpendicular to the slid surface and electrical contact resistance between pin and disk specimens were employed as the multiple kinds of data. The devised analysis showed that the formation of a plateau with around 25 μm height on the slid surface is a key factor for the transition.