Evaluation of antifungal combination against Cryptococcus spp

The second cause of death among systemic mycoses, cryptococcosis treatment represents a challenge since that 5-flucytosine is not currently available in Brazil. Looking for alternatives, this study evaluated antifungal agents, alone and combined, correlating susceptibility to genotypes. Eighty Cryptococcus clinical isolates were genotyped by URA5 gene restriction fragment length polymorphism. Antifungal susceptibility was assessed following CLSI-M27A3 for amphotericin (AMB), 5-flucytosine (5FC), fluconazole (FCZ), voriconazole (VRZ), itraconazole (ITZ) and terbinafine (TRB). Drug interaction chequerboard assay evaluated: AMB + 5FC, AMB + FCZ, AMB + TRB and FCZ + TRB. Molecular typing divided isolates into 14 C. deuterogattii (VGII) and C. neoformans isolates were found to belong to genotype VNI (n = 62) and VNII (n = 4). C. neoformans VNII was significantly less susceptible than VNI (P = 0.0407) to AMB; C. deuterogattii was significantly less susceptible than VNI and VNII to VRZ (P < 0.0001). C. deuterogattii was less susceptible than C. neoformans VNI for FCZ (P = 0.0170), ITZ (P < 0.0001) and TRB (P = 0.0090). The combination FCZ + TRB showed 95.16% of synergistic effect against C. neoformans genotype VNI isolates and all combinations showed 100% of synergism against genotype VNII isolates, suggesting the relevance of cryptococcal genotyping as it is widely known that the various genotypes (now species) have significant impact in antifungal susceptibilities and clinical outcome. In difficult-to-treat cryptococcosis, terbinafine and different antifungal combinations might be alternatives to 5FC599585593JICA (Japan International Cooperation Agency); SATREPS (Science and Technology Research Partnership for Sustainable Development

Comprehensive genome methylation and whole genome expression analysis in penile carcinoma: Uncovering new molecular markers

Background: Penile carcinoma (PeCa) is frequently associated with high morbidity rates. Unlikely of the vast majority of tumors, there is no molecular markers described that are able to assist in diagnosis and prognosis or with potential to be therapeutic targets in PeCa. Patients and methods: DNA methylation status (244K Human DNA Methylation Microarray platform, Agilent Technologies) and large-scale expression analysis (4x44K Whole Human Genome Microarray, Agilent Technologies) were performed in 35 and 37 PeCa, respectively. Quantitative bisulfite pyrosequencing (qBP) and RT-qPCR were used to validate the findings in 93 samples. HPV status was assessed using the Linear Array HPV Genotyping kit (Roche Molecular Diagnostics, CA, USA). Results: Methylome analysis revealed 171 hypermethylated and 449 hypomethylated CpGs sites and the transcriptome profiling showed 2986 down- and 2817 over-expressed genes. HPV positivity was found in 32.7% of the cases, mainly the HPV16. The integrative analysis in 32 PeCa revealed a panel of 96 genes with inverse correlation between methylation and gene expression levels. The CpG hypermetlylation and gene downexpression, was confirmed for TWIST1, RSOP2, SOX3, SOX17, CD133, OTX2, HOXA3 and MEIS. In addition, BIRC5, DNMT1 and DNMT3B presented low levels of methylation and overexpression. The comparison of the results with clinical findings revealed that LIN28A, NKX2.2, NKX2.3, LHX5, BDNF, FOXA1 and CDX2 were associated with poor prognosis features. Conclusion: Putative prognostic markers were detected revealing that DNA methylation modulates the expression of several genes in PeCa. These data may prove instrumental for biomarker discovery in clinics and molecular epidemiology of PeCa

Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

Abstract Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics limiting the standard tumor−node−metastasis prognosis classification. Therefore, defining biological signatures that allow assessing the prognostic outcomes for OSCC patients would be of great clinical significance. Using histopathology-guided discovery proteomics, we analyze neoplastic islands and stroma from the invasive tumor front (ITF) and inner tumor to identify differentially expressed proteins. Potential signature proteins are prioritized and further investigated by immunohistochemistry (IHC) and targeted proteomics. IHC indicates low expression of cystatin-B in neoplastic islands from the ITF as an independent marker for local recurrence. Targeted proteomics analysis of the prioritized proteins in saliva, combined with machine-learning methods, highlights a peptide-based signature as the most powerful predictor to distinguish patients with and without lymph node metastasis. In summary, we identify a robust signature, which may enhance prognostic decisions in OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis