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Andrew R. Zaretsky

Pirogov Russian National Research Medical University

ORCID: 0000-0002-7778-6617

Publishes on Cancer Immunotherapy and Biomarkers, Bladder and Urothelial Cancer Treatments, Cancer, Hypoxia, and Metabolism. 63 papers and 884 citations.

63Publications
884Total Citations

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Important molecular genetic markers of colorectal cancer
Cited by 112Open Access

// Anna V. Kudryavtseva 1,2,* , Anastasia V. Lipatova 1,* , Andrew R. Zaretsky 3 , Alexey A. Moskalev 1 ,Maria S. Fedorova 1,2 ,Anastasiya S. Rasskazova 1 ,Galina A. Shibukhova 2 ,Anastasiya V. Snezhkina 1 , Andrey D. Kaprin 2 , Boris Y. Alekseev 2 ,Alexey A. Dmitriev 1 and George S. Krasnov 4,1 1 Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia 2 National Medical Research Radiological Centre, Ministry of Healthcare of the Russian Federation, Moscow, Russia 3 Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia 4 Orekhovich Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, Russia * These authors have contributed equally to this work Correspondence to: Anna V. Kudryavtseva, email: // Keywords : colorectal cancer, molecular markers, chromosomal instability, microsatellite instability, CpG island methylator phenotype Received : November 21, 2015 Accepted : May 21, 2016 Published : June 02, 2016 Abstract Colorectal cancer (CRC) ranks third in the incidences of cancer morbidity and mortality worldwide. CRC is rather heterogeneous with regard to molecular genetic characteristics and pathogenic pathways. A wide spectrum of biomarkers is used for molecular subtype determination, prognosis, and estimation of sensitivity to different drugs in practice. These biomarkers can include germline and somatic mutations, chromosomal aberrations, genomic abnormalities, gene expression alterations at mRNA or protein level and changes in DNA methylation status. In the present review we discuss the most important and well-studied CRC biomarkers, and their potential clinical significance and current approaches to molecular classification of colorectal tumors.

Intratumoral immunoglobulin isotypes predict survival in lung adenocarcinoma subtypes
Olga I. Isaeva, Г. В. Шаронов, Ekaterina O. Serebrovskaya et al.|Journal for ImmunoTherapy of Cancer|2019
Cited by 101Open Access

BACKGROUND: The role of tumor-infiltrating B-cells (TIBs) and intratumorally-produced antibodies in cancer-immunity interactions essentially remains terra incognita. In particular, it remains unexplored how driver mutations could be associated with distinct TIBs signatures and their role in tumor microenvironment. METHODS: Here we analyzed associations of immunoglobulin isotypes and clonality with survival in TCGA RNA-Seq data for lung adenocarcinoma (LUAD), stratifying patients into 12 driver mutation and phenotypic tumor subgroups. RESULTS: and proximal proliferative subgroups of LUAD patients. We hypothesize that the positive role of IgG4 antibodies in some of the lung cancer subtypes could be associated with reported inability of IgG4 isotype to form immune complexes, thus preventing immunosuppression via activation of the myeloid-derived suppressor cell (MDSC) phenotype. CONCLUSIONS: We discover prominent and distinct associations between TIBs antibody isotypes and survival in lung adenocarcinoma carrying specific driver mutations. These findings indicate that particular types of tumor-immunity relations could be beneficial in particular driver mutation context, which should be taken into account in developing strategies of cancer immunotherapy and combination therapies. Specificity of protective B cell populations in specific cancer subgroups could become a clue to efficient targeted immunotherapies for appropriate cohorts of patients.

The Dysregulation of Polyamine Metabolism in Colorectal Cancer Is Associated with Overexpression of c‐Myc and C/EBP<i>β</i> rather than Enterotoxigenic <i>Bacteroides fragilis</i> Infection
Anastasiya V. Snezhkina, George S. Krasnov, Anastasiya V. Lipatova et al.|Oxidative Medicine and Cellular Longevity|2016
Cited by 91Open Access

Colorectal cancer is one of the most common cancers in the world. It is well known that the chronic inflammation can promote the progression of colorectal cancer (CRC). Recently, a number of studies revealed a potential association between colorectal inflammation, cancer progression, and infection caused by enterotoxigenic Bacteroides fragilis (ETBF). Bacterial enterotoxin activates spermine oxidase (SMO), which produces spermidine and H2O2 as byproducts of polyamine catabolism, which, in turn, enhances inflammation and tissue injury. Using qPCR analysis, we estimated the expression of SMOX gene and ETBF colonization in CRC patients. We found no statistically significant associations between them. Then we selected genes involved in polyamine metabolism, metabolic reprogramming, and inflammation regulation and estimated their expression in CRC. We observed overexpression of SMOX, ODC1, SRM, SMS, MTAP, c-Myc, C/EBPβ (CREBP), and other genes. We found that two mediators of metabolic reprogramming, inflammation, and cell proliferation c-Myc and C/EBPβ may serve as regulators of polyamine metabolism genes (SMOX, AZIN1, MTAP, SRM, ODC1, AMD1, and AGMAT) as they are overexpressed in tumors, have binding site according to ENCODE ChIP-Seq data, and demonstrate strong coexpression with their targets. Thus, increased polyamine metabolism in CRC could be driven by c-Myc and C/EBPβ rather than ETBF infection.

HK3 overexpression associated with epithelial-mesenchymal transition in colorectal cancer
Cited by 76Open Access

BACKGROUND: Colorectal cancer (CRC) is a common cancer worldwide. The main cause of death in CRC includes tumor progression and metastasis. At molecular level, these processes may be triggered by epithelial-mesenchymal transition (EMT) and necessitates specific alterations in cell metabolism. Although several EMT-related metabolic changes have been described in CRC, the mechanism is still poorly understood. RESULTS: Using CrossHub software, we analyzed RNA-Seq expression profile data of CRC derived from The Cancer Genome Atlas (TCGA) project. Correlation analysis between the change in the expression of genes involved in glycolysis and EMT was performed. We obtained the set of genes with significant correlation coefficients, which included 21 EMT-related genes and a single glycolytic gene, HK3. The mRNA level of these genes was measured in 78 paired colorectal cancer samples by quantitative polymerase chain reaction (qPCR). Upregulation of HK3 and deregulation of 11 genes (COL1A1, TWIST1, NFATC1, GLIPR2, SFPR1, FLNA, GREM1, SFRP2, ZEB2, SPP1, and RARRES1) involved in EMT were found. The results of correlation study showed that the expression of HK3 demonstrated a strong correlation with 7 of the 21 examined genes (ZEB2, GREM1, TGFB3, TGFB1, SNAI2, TWIST1, and COL1A1) in CRC. CONCLUSIONS: Upregulation of HK3 is associated with EMT in CRC and may be a crucial metabolic adaptation for rapid proliferation, survival, and metastases of CRC cells.

MAGERI: Computational pipeline for molecular-barcoded targeted resequencing
Mikhail Shugay, Andrew R. Zaretsky, Dmitry A. Shagin et al.|PLoS Computational Biology|2017
Cited by 72Open Access

Unique molecular identifiers (UMIs) show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline that efficiently handles all caveats of UMI-based analysis to obtain high-fidelity mutation profiles and call ultra-rare variants. Using an extensive set of benchmark datasets including gold-standard biological samples with known variant frequencies, cell-free DNA from tumor patient blood samples and publicly available UMI-encoded datasets we demonstrate that our method is both robust and efficient in calling rare variants. The versatility of our software is supported by accurate results obtained for both tumor DNA and viral RNA samples in datasets prepared using three different UMI-based protocols.