Inducing expression of ICOS-L by oncolytic adenovirus to enhance tumor-specific bi-specific antibody efficacy.

BACKGROUND: Intratumoral injection of oncolytic viruses (OVs) shows promise in immunotherapy: ONCOS-102, a genetically engineered OV that encodes Granulocyte-Macrophage Colony-Stimulating Factor (GM-CSF) demonstrated efficacy in early clinical trials, enhancing T cell infiltration in tumors. This suggests OVs may boost various forms of immunotherapy, including tumor-specific bi-specific antibodies (BsAbs). METHODS: Our study investigated in vitro, how ONCOS-204, a variant of ONCOS-virus expressing the ligand of inducible T-cell co-stimulator (ICOSL), modulates the process of T cell activation induced by a BsAb. ONCOS-102 was used for comparison. Phenotypic and functional changes induced by combination of different OVs, and BsAb in T cell subsets were assessed by flow cytometry, viability, and proliferation assays. RESULTS: Degranulation and IFNγ and TNF production of T cells, especially CD4 + T cells was the most increased upon target cell exposure to ONCOS-204. Unexpectedly, ONCOS-204 profoundly affected CD8 + T cell proliferation and function through ICOS-L/ICOS interaction. The effect solely depended on cell surface expression of ICOS-L as soluble ICOSL did not induce notable T cell activity. CONCLUSIONS: Together, our data suggests that oncolytic adenoviruses encoding ICOSL may enhance functional activity of tumor-specific BsAbs thereby opening a novel avenue for clinical development in immunotherapeutics.

Developmental and Housekeeping Genes: Two Types of Genetic Organization in the Drosophila Genome.

We developed a procedure for locating genes on Drosophila melanogaster polytene chromosomes and described three types of chromosome structures (gray bands, black bands, and interbands), which differed markedly in morphological and genetic properties. This was reached through the use of our original methods of molecular and genetic analysis, electron microscopy, and bioinformatics data processing. Analysis of the genome-wide distribution of these properties led us to a bioinformatics model of the Drosophila genome organization, in which the genome was divided into two groups of genes. One was constituted by 65, in which the genome was divided into two groups, 62 genes that are expressed in most cell types during life cycle and perform basic cellular functions (the so-called "housekeeping genes"). The other one was made up of 3162 genes that are expressed only at particular stages of development ("developmental genes"). These two groups of genes are so different that we may state that the genome has two types of genetic organization. Different are the timings of their expression, chromatin packaging levels, the composition of activating and deactivating proteins, the sizes of these genes, the lengths of their introns, the organization of the promoter regions of the genes, the locations of origin recognition complexes (ORCs), and DNA replication timings.

Genomic background sequences systematically outperform synthetic ones in de novo motif discovery for ChIP-seq data.

Efficient de novo motif discovery from the results of wide-genome mapping of transcription factor binding sites (ChIP-seq) is dependent on the choice of background nucleotide sequences. The foreground sequences (ChIP-seq peaks) represent not only specific motifs of target transcription factors, but also the motifs overrepresented throughout the genome, such as simple sequence repeats. We performed a massive comparison of the 'synthetic' and 'genomic' approaches to generate background sequences for de novo motif discovery. The 'synthetic' approach shuffled nucleotides in peaks, while in the 'genomic' approach selected sequences from the reference genome randomly or only from gene promoters according to the fraction of A/T nucleotides in each sequence. We compiled the benchmark collections of ChIP-seq datasets for mouse, human and Arabidopsis, and performed de novo motif discovery. We showed that the genomic approach has both more robust detection of the known motifs of target transcription factors and more stringent exclusion of the simple sequence repeats as possible non-specific motifs. The advantage of the genomic approach over the synthetic approach was greater in plants compared to mammals. We developed the AntiNoise web service (https://denovosea.icgbio.ru/antinoise/) that implements a genomic approach to extract genomic background sequences for twelve eukaryotic genomes.