Evaluation of anti-tumorigenic effects of anti-Lipocalin2 (anti-LCN2) monoclonal antibody against human cervical cancer xenografts in athymic nude mice
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE242667
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This study investigated the impact of an anti-LCN2 monoclonal antibody on STR-authenticated HeLa cells using a xenograft model in athymic nude mice. Treatment of tumors with anti-LCN2 antibody resulted in 39 – 60% reduction in tumor volume. RNA extracted from the tumors post-treatment was sequenced and aligned to human and mouse genome separately. Differential expression analysis of human mapped overexpressed genes in treated tumor revealed suppression of pro-tumorigenic TNF- and IL17 signalling pathways, whereas the corresponding mouse-mapped genes indicated pathways including activation of T-cells and T-cell mediated killing in treated tumors. M2 mouse macrophage markers showed a decline under treatment signifying tumor regression. This observed T-cell activation and debilitation of M2 mouse macrophages by anti-LCN2 underlies its potential as an immune sensitizer that can potentially devour tumor cells through T-cell mediated cytotoxicity. Cultured HeLa cells (5 X 106) were injected subcutaneously into the dorsal flanks of NCr transgenic male nude mice. Mice were maintained under sterile and controlled conditions. Once tumors grew to about 100 mm3 in volume, they were injected with 100 µg anti-LCN2 antibody every alternate day directly into the tumor with PBS as the vehicle control in no treatment group. Animals were sacrificed when the tumor grew ~ 2000 mm3, after 2 weeks of treatment. RNA was isolated from the tumors (with and without treatment) and was subjected to sequencing on a NovaSeq 6000 (illumina) platform using 2 x 150 bp chemistry. Sequence reads were filtered for quality using Trimmomatic and filtered reads were separated based on mapping to human (GRCh38) and mouse (GRCm39) reference assembly using FastQ Screen. Separated reads were aligned to respective genome using STAR pipeline and differentially expressed genes were determined using edgeR.
创建时间:
2023-12-31



