Publications by authors named "Favorov A"

Successful pancreatic ductal adenocarcinoma (PDAC) immunotherapy requires therapeutic combinations that induce quality T cells. Tumor microenvironment (TME) analysis following therapeutic interventions can identify response mechanisms, informing design of effective combinations. We provide a reference single-cell dataset from tumor-infiltrating leukocytes (TILs) from a human neoadjuvant clinical trial comparing the granulocyte-macrophage colony-stimulating factor (GM-CSF)-secreting allogeneic PDAC vaccine GVAX alone, in combination with anti-PD1 or with both anti-PD1 and CD137 agonist.

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Background: Current experimental practices typically produce large multidimensional datasets. Distance matrix calculation between elements (e.g.

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SpliceMutr shows that splicing antigenicity changes in response to ICI therapies and that native modulation of the splicing machinery through mutations increases the contribution of splicing to the neoantigen load of some The Cancer Genome Atlas cancer subtypes. Future studies of the relationship between splicing antigenicity and immune checkpoint inhibitor response pan-cancer are essential to establish the interplay between antigen heterogeneity and immunotherapy regimen on patient response.

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We present a major update of the HOCOMOCO collection that provides DNA binding specificity patterns of 949 human transcription factors and 720 mouse orthologs. To make this release, we performed motif discovery in peak sets that originated from 14 183 ChIP-Seq experiments and reads from 2554 HT-SELEX experiments yielding more than 400 thousand candidate motifs. The candidate motifs were annotated according to their similarity to known motifs and the hierarchy of DNA-binding domains of the respective transcription factors.

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The vasovagal syncope (VVS) is the most common form of syncope. The mechanisms of VVS development are not entirely clear. It is known that there is a genetic predisposition to this disease, but the data on the roles of individual genes are quite contradictory.

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Recent advances in spatial transcriptomics (STs) enable gene expression measurements from a tissue sample while retaining its spatial context. This technology enables unprecedented in situ resolution of the regulatory pathways that underlie the heterogeneity in the tumor as well as the tumor microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as it occurs in tumor-immune interactions.

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The regulatory functions of the B-cell compartment play an important role in the development and suppression of the immune response. Disruption of their anti-inflammatory functions may lead to the acceleration of immunopathological processes, and to autoimmune diseases, in particular. Unfortunately, the exact mechanism underlying the functioning and development of regulatory B cells (Breg) has not yet been fully elucidated.

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Article Synopsis
  • * A study utilized a machine learning approach to identify and classify important PUFA metabolism genes altered in breast cancer tissues compared to normal tissues, achieving high accuracy in predictions.
  • * The research found that PUFA metabolism genes are crucial for breast cancer development, and different molecular subtypes of breast cancer exhibit distinct patterns in the expression of these genes.
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A Molecular Features Set (MFS), is a result of a vast diversity of bioinformatics pipelines. The lack of a "gold standard" for most experimental data modalities makes it difficult to provide valid estimation for a particular MFS's quality. Yet, this goal can partially be achieved by analyzing inner-sample Distance Matrices (DM) and their power to distinguish between phenotypes.

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Background: B lymphocytes play a pivotal regulatory role in the development of the immune response. It was previously shown that deficiency in B regulatory cells (Bregs) or a decrease in their anti-inflammatory activity can lead to immunological dysfunctions. However, the exact mechanisms of Bregs development and functioning are only partially resolved.

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Molecular interactions at identical transcriptomic locations or at proximal but non-overlapping sites can mediate RNA modification and regulation, necessitating tools to uncover these spatial relationships. We present nearBynding, a flexible algorithm and software pipeline that models spatial correlation between transcriptome-wide tracks from diverse data types. nearBynding can process and correlate interval as well as continuous data and incorporate experimentally derived or predicted transcriptomic tracks.

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Sequence variants in gene regulatory regions alter gene expression and contribute to phenotypes of individual cells and the whole organism, including disease susceptibility and progression. Single-nucleotide variants in enhancers or promoters may affect gene transcription by altering transcription factor binding sites. Differential transcription factor binding in heterozygous genomic loci provides a natural source of information on such regulatory variants.

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Determining the etiologic basis of the mutations that are responsible for cancer is one of the fundamental challenges in modern cancer research. Different mutational processes induce different types of DNA mutations, providing 'mutational signatures' that have led to key insights into cancer etiology. The most widely used signatures for assessing genomic data are based on unsupervised patterns that are then retrospectively correlated with certain features of cancer.

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Adenoid cystic carcinoma (ACC) is the second most common malignancy of the salivary gland. Although characterized as an indolent tumor, ACC often leads to incurable metastatic disease. Patients with ACC respond poorly to currently available therapeutic drugs and factors contributing to the limited response remain unknown.

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Head and neck squamous cell carcinoma (HNSCC) has a high recurrence and metastatic rate with an unknown mechanism of cancer spread. Tumor inflammation is the most critical processes of cancer onset, growth, and metastasis. We hypothesize that the release of extracellular vesicles (EVs) by tumor endothelial cells (TECs) induce reprogramming of immune cells as well as stromal cells to create an immunosuppressive microenvironment that favor tumor spread.

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Amino acid propensities at a site change in the course of protein evolution. This may happen for two reasons. Changes may be triggered by substitutions at epistatically interacting sites elsewhere in the genome.

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The dominant paradigm for HPV carcinogenesis includes integration into the host genome followed by expression of E6 and E7 (E6/E7). We explored an alternative carcinogenic pathway characterized by episomal E2, E4, and E5 (E2/E4/E5) expression. Half of HPV positive cervical and pharyngeal cancers comprised a subtype with increase in expression of E2/E4/E5, as well as association with lack of integration into the host genome.

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Article Synopsis
  • Long noncoding RNAs (lncRNAs) make up most of transcripts in mammalian genomes, but their functions are still not well understood.
  • The FANTOM6 project systematically knocked down 285 lncRNAs in human dermal fibroblasts and analyzed changes in cell growth, shape, and gene expression using CAGE techniques.
  • This study provides a comprehensive lncRNA knockdown data set (over 1000 CAGE sequencing libraries) and reveals important findings about their roles and impact on various cellular pathways.
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While the methods available for single-cell ATAC-seq analysis are well optimized for clustering cell types, the question of how to integrate multiple scATAC-seq data sets and/or sequencing modalities is still open. We present an analysis framework that enables such integration across scATAC-seq data sets by applying the CoGAPS Matrix Factorization algorithm and the projectR transfer learning program to identify common regulatory patterns across scATAC-seq data sets. We additionally integrate our analysis with scRNA-seq data to identify orthogonal evidence for transcriptional regulators predicted by scATAC-seq analysis.

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Human papillomavirus-related oropharyngeal squamous cell carcinoma (HPV+ OPSCC) represents a unique disease entity within head and neck cancer with rising incidence. Previous work has shown that alternative splicing events (ASEs) are prevalent in HPV+ OPSCC, but further validation is needed to understand the regulation of this process and its role in these tumours. In this study, eleven ASEs (, and were selected for validation from 109 previously published candidate ASEs to elucidate the post-transcriptional mechanisms of oncogenesis in HPV+ disease.

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Long noncoding RNAs (lncRNAs) have emerged as key coordinators of biological and cellular processes. Characterizing lncRNA expression across cells and tissues is key to understanding their role in determining phenotypes, including human diseases. We present here FC-R2, a comprehensive expression atlas across a broadly defined human transcriptome, inclusive of over 109,000 coding and noncoding genes, as described in the FANTOM CAGE-Associated Transcriptome (FANTOM-CAT) study.

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Risk of the development of multiple sclerosis (MS) is known to be increased in individuals bearing distinct class II human leukocyte antigen (HLA) variants, whereas some of them may have a protective effect. Here we analyzed distribution of a highly polymorphous HLA- locus in more than one thousand relapsing-remitting MS patients and healthy individuals of Russian ethnicity. Carriage of HLA*15 and HLA*03 alleles was associated with MS risk, whereas carriage of HLA*01 and HLA*11 was found to be protective.

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Background: We aimed to use genomic data for optimizing polymerase chain reaction (PCR) primer/probe sets for detection of human papillomavirus (HPV)-16 in body fluids of patients with HPV-related head and neck squamous cell carcinoma (HPV-HNSCC).

Methods: We used genomic HPV-HNSCC sequencing data from a single institutional and a TCGA cohort. Optimized primer/probe sets were designed and tested for analytical performance in CaSki HPV-16 genome and confirmed in salivary rinse samples from patients with HPV-HNSCC.

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Many problems of modern genetics and functional genomics require the assessment of functional effects of sequence variants, including gene expression changes. Machine learning is considered to be a promising approach for solving this task, but its practical applications remain a challenge due to the insufficient volume and diversity of training data. A promising source of valuable data is a saturation mutagenesis massively parallel reporter assay, which quantitatively measures changes in transcription activity caused by sequence variants.

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