Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas: next-generation sequencing and machine learning for full tumor exome analysis.

About 7% of all cancer deaths are caused by pancreatic cancer (PCa). PCa is known for its lowest survival rates among all oncological diseases and heterogenic molecular profile. Enormous amount of genetic changes, including somatic mutations, exceeds the limits of routine clinical genetic laboratory tests and further stagnates the development of personalized treatments. We aimed to build a mutational landscape of PCa in the Russian population based on full exome next-generation sequencing (NGS) of the limited group of patients. Applying a machine learning model on full exome individual data we received personalized recommendations for targeted treatment options for each clinical case and summarized them in the unique therapeutic landscape.

Characteristics of Stenotrophomonas maltophilia isolates from cystic fibrosis patients in Russia.

Stenotrophomonas maltophilia is a common opportunistic microorganism and an important respiratory pathogen in cystic fibrosis (CF). The aim of this study was to determine antimicrobial resistance phenotypes, sequence-types (ST) and genetic determinants of antibiotic resistance in S. maltophilia strains recovered from CF patients in Russia. S. maltophilia isolates recovered from 170 CF patients were analyzed. Minimum inhibitory concentrations of antibacterial agents were determined using Sensititre Gram Negative GNX2F plates and the results were interpreted according to Clinical and Laboratory Standards Institute (CLSI) criteria. Whole-genome sequencing (WGS) was performed on MGISEQ-2000 platform. SPAdes software, Galaxy, ResFinder, Integrall and PubMLST were used for analysis of WGS data. S. maltophilia strains were identified from 24/170 (14%) CF patients. In total, 25 isolates were detected, two strains were isolated from the same patient. The isolates belonged to 17 different STs, including 5 new STs; ST4 was the most prevalent ST. Resistance to ceftazidime was observed in 60% of strains, to ticarcillin-clavulanate - in 32%, to levofloxacin - in 24%, to trimethoprim/sulfamethoxazole - in 12% of strains. All isolates were susceptible to minocycline. All ST4 isolates were resistant or intermediate to ceftazidime and ticarcillin-clavulanate. In two isolates, the sul1 gene was detected. In one isolate, sul1 was part of a class 1 integron. The detected integron also contained the blaGES-7 and aac(6')-Ib-cr genes. The ST4 sequence-type was the most prevalent ST among S. maltophilia strains recovered from CF patients in Russia. Antibiotic resistance genes, including sul1, blaGES-7, aac(6')-Ib-cr, were detected in single strains.

Identification of bacterial antibiotic resistance genes in next-generation sequencing data (review of literature).

The spread of antibiotic-resistant human bacterial pathogens is a serious threat to modern medicine. Antibiotic susceptibility testing is essential for treatment regimens optimization and preventing dissemination of antibiotic resistance. Therefore, development of antibiotic susceptibility testing methods is a priority challenge of laboratory medicine. The aim of this review is to analyze the capabilities of the bioinformatics tools for bacterial whole genome sequence data processing. The PubMed database, Russian scientific electronic library eLIBRARY, information networks of World health organization and European Society of Clinical Microbiology and Infectious Diseases (ESCMID) were used during the analysis. In this review, the platforms for whole genome sequencing, which are suitable for detection of bacterial genetic resistance determinants, are described. The classic step of genetic resistance determinants searching is an alignment between the query nucleotide/protein sequence and the subject (database) nucleotide/protein sequence, which is performed using the nucleotide and protein sequence databases. The most commonly used databases are Resfinder, CARD, Bacterial Antimicrobial Resistance Reference Gene Database. The results of the resistance determinants searching in genome assemblies is more correct in comparison to results of the searching in contigs. The new resistance genes searching bioinformatics tools, such as neural networks and machine learning, are discussed in the review. After critical appraisal of the current antibiotic resistance databases we designed a protocol for predicting antibiotic resistance using whole genome sequence data. The designed protocol can be used as a basis of the algorithm for qualitative and quantitative antimicrobial susceptibility testing based on whole genome sequence data.

Genome features and antibiotic resistance of Pseudomonas aeruginosa strains isolated in patients with cystic fibrosis in the Russian Federation.

Cystic fibrosis (CF) is a common genetic disease, manifested by airway obstruction and chronic respiratory infection. The most prevalent infectious agent in airways of CF patients is Pseudomonas aeruginosa. This study aimed to determine sequence-types, antimicrobial resistance phenotypes and genes defining adaptive antibiotic resistance in P. aeruginosa isolates recovered from CF patients in Russia. In total, 84 P. aeruginosa strains from 64 CF patients were analyzed. Susceptibility to antibiotics was determined by disk diffusion test. Whole-genome sequencing (WGS) was performed on MGISEQ-2000 platform. SPAdes software, Galaxy, ResFinder, PubMLST were used for analysis of WGS data. Examined P. aeruginosa isolates belonged to 53 different sequence-types (STs), including 6 new STs. High-risk epidemic clone ST235 (10%) and clonal CF P. aeruginosa strains ST17, ST242, ST274 (7%) were detected. Non-susceptibility to ticarcillin-clavulanate, cefepime, imipenem was observed in 63%, 12% and 25% of isolates, respectively; to tobramycin - in 24%, to amikacin - in 35%; to ciprofloxacin, levofloxacin - in 35% and 57% of strains, respectively. Multidrug-resistant phenotype was detected in 18% of isolates. In examined strains, genes of beta-lactamases VIM-2 (5 ST235 strains), VEB-1 (two ST2592 strains), GES-1 (1 ST235 strain), PER-1 (1 ST235 strain) were found. Ciprofloxacin-modifying enzyme CrpP gene was detected in 67% of isolates, aminoglycoside-modifying enzymes AAD, ANT, AAC genes - in 7%, 4%, 12% of strains, respectively. P. aeruginosa isolates from CF patients in Russia demonstrate a high clonal diversity, which is similar to other P. aeruginosa infections. The isolates of high-risk clone and clonal CF P. aeruginosa strains are detected.

[A bioinformatic pipeline for NGS data analysis and mutation calling in human solid tumors]. / Bioinformaticheskii protokol dlia obrabotki NGS-dannykh i identifikatsii mutatsii v solidnykh opukholiakh cheloveka.

We aimed to develop a pipeline for the bioinformatic analysis and interpretation of NGS data and detection of a wide range of single-nucleotide somatic mutations within tumor DNA. Initially, the NGS reads were submitted to a quality control check by the Cutadapt program. Low-quality 3¢-nucleotides were removed. After that the reads were mapped to the reference genome hg19 (GRCh37.p13) by BWA. The SAMtools program was used for exclusion of duplicates. MuTect was used for SNV calling. The functional effect of SNVs was evaluated using the algorithm, including annotation and evaluation of SNV pathogenicity by SnpEff and analysis of such databases as COSMIC, dbNSFP, Clinvar, and OMIM. The effect of SNV on the protein function was estimated by SIFT and PolyPhen2. Mutation frequencies were obtained from 1000 Genomes and ExAC projects, as well as from our own databases with frequency data. In order to evaluate the pipeline we used 18 breast cancer tumor biopsies. The MYbaits Onconome KL v1.5 Panel ("MYcroarray") was used for targeted enrichment. NGS was performed on the Illumina HiSeq 2500 platform. As a result, we identified alterations in BRCA1, BRCA2, ATM, CDH1, CHEK2, TP53 genes that affected the sequence of encoded proteins. Our pipeline can be used for effective search and annotation of tumor SNVs. In this study, for the first time, we have tested this pipeline for NGS data analysis of samples from patients of the Russian population. However, further confirmation of efficiency and accuracy of the pipeline is required on NGS data from larger datasets as well as data from several types of solid tumors.

[Genetic determinants of resistance of hospital-associated strains of Klebsiella pneumoniae to ß-lactam antibiotics isolated in neonates].

According to the results of analysis of whole genome sequencing, the presence of genes having resistance to ß-lactam antibiotics in hospital-associated strains of Klebsiella pneumoniae was studied. The strains were isolated from neonatal intensive care units. The data obtained were compared with the results of antimicrobial susceptibility testing of isolated microorganisms. Among other strains resistant to cephalosporins, the dominance of genes of CTX-M-type extended-spectrum ß-lactamases was shown. It was revealed that one of eight strains phenotypically resistant and moderately resistant to carbapenems have the blaOXA-48 carbapenemase gene.