Diagnostic Accuracy of ß-d-Glucan (Fungitell) Testing Among Patients With Hematologic Malignancies or Solid Organ Tumors: A Systematic Review and Meta-Analysis.

Objectives: To determine the accuracy of Fungitell, a ß-d-glucan (BDG) test, for the diagnosis of invasive fungal infection (IFI) among cancer patients. Methods: For this meta-analysis, MEDLINE and EMBASE were searched for references related to BDG testing. Study quality was evaluated using QUADAS-2. Statistical analysis was performed using Stata 14. Results: We screened 12,426 references and identified 189 studies for full-text review. Nineteen studies were included in the final meta-analysis. There was moderate heterogeneity between studies. Nine studies had a high risk of bias, which significantly elevated the overall specificity estimate. Restricting to only low-bias studies, the sensitivity and specificity were 80% and 63%, respectively. Conclusions: The overall sensitivity and specificity of Fungitell as a diagnostic test for IFI is moderate, and there is substantial heterogeneity between studies. Limiting studies to only low-bias risk reduced heterogeneity but also lowered the overall specificity estimate.

Correction: The anti-rheumatic drug, leflunomide, synergizes with MEK inhibition to suppress melanoma growth.

[This corrects the article DOI: 10.18632/oncotarget.23378.].

The anti-rheumatic drug, leflunomide, synergizes with MEK inhibition to suppress melanoma growth.

Cutaneous melanoma, which develops from the pigment producing cells called melanocytes, is the most deadly form of skin cancer. Unlike the majority of other cancers, the incidence rates of melanoma are still on the rise and the treatment options currently available are being hindered by resistance, limited response rates and adverse toxicity. We have previously shown that an FDA approved drug leflunomide, used for rheumatoid arthritis (RA), also holds potential therapeutic value in treating melanoma especially if used in combination with the mutant BRAF inhibitor, vemurafenib. We have further characterized the function of leflunomide and show that the drug reduces the number of viable cells in both wild-type and BRAFV600E mutant melanoma cell lines. Further experiments have revealed leflunomide reduces cell proliferation and causes cells to arrest in G1 of the cell cycle. Cell death assays show leflunomide causes apoptosis at treatment concentrations of 25 and 50 µM. To determine if leflunomide could be used combinatorialy with other anti-melanoma drugs, it was tested in combination with the MEK inhibitor, selumetinib. This combination showed a synergistic effect in the cell lines tested. This drug combination led to an enhanced decrease in tumor size when tested in vivo compared to either drug alone, demonstrating its potential as a novel combinatorial therapy for melanoma.

Susceptibility profiles of Nocardia isolates based on current taxonomy.

The genus Nocardia has undergone rapid taxonomic expansion in recent years, and an increasing number of species are recognized as human pathogens. Many established species have predictable antimicrobial susceptibility profiles, but sufficient information is often not available for recently described organisms. Additionally, the effectiveness of sulfonamides as first-line drugs for Nocardia has recently been questioned. This led us to review antimicrobial susceptibility patterns for a large number of molecularly identified clinical isolates. Susceptibility results were available for 1,299 isolates representing 39 different species or complexes, including 11 that were newly described, during a 6-year study period. All tested isolates were susceptible to linezolid. Resistance to trimethoprim-sulfamethoxazole (TMP-SMX) was rare (2%) except among Nocardia pseudobrasiliensis (31%) strains and strains of the N. transvalensis complex (19%). Imipenem susceptibility varied for N. cyriacigeorgica and N. farcinica, as did ceftriaxone susceptibility of the N. nova complex. Resistance to more than one of the most commonly used drugs (amikacin, ceftriaxone, TMP-SMX, and imipenem) was highest for N. pseudobrasiliensis (100%), N. transvalensis complex (83%), N. farcinica (68%), N. puris (57%), N. brasiliensis (51%), N. aobensis (50%), and N. amikacinitolerans (43%). Thus, while antimicrobial resistance can often be predicted, susceptibility testing should still be considered when combination therapy is warranted, for less well characterized species or those with variable susceptibility profiles, and for patients with TMP-SMX intolerance.

Extensions to In Silico Bioactivity Predictions Using Pathway Annotations and Differential Pharmacology Analysis: Application to Xenopus laevis Phenotypic Readouts.

The simultaneous increase of computational power and the availability of chemical and biological data have contributed to the recent popularity of in silico bioactivity prediction algorithms. Such methods are commonly used to infer the 'Mechanism of Action' of small molecules and they can also be employed in cases where full bioactivity profiles have not been established experimentally. However, protein target predictions by themselves do not necessarily capture information about the effect of a compound on a biological system, and hence merging their output with a systems biology approach can help to better understand the complex network modulation which leads to a particular phenotype. In this work, we review approaches and applications of target prediction, as well as their shortcomings, and demonstrate two extensions of this concept which are exemplified using phenotypic readouts from a chemical genetic screen in Xenopus laevis. In particular, the experimental observations are linked to their predicted bioactivity profiles. Predicted targets are annotated with pathways, which lead to further biological insight. Moreover, we subject the prediction to further machine learning algorithms, namely decision trees, to capture the differential pharmacology of ligand-target interactions in biological systems. Both methodologies hence provide new insight into understanding the Mechanism of Action of compound activities from phenotypic screens.