 |
 |
GEO help: Mouse over screen elements for information. |
|
| Status |
Public on Aug 14, 2024 |
| Title |
Adipose microenvironment promotes hypersialylation of ovarian cancer cells |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
|
| Summary |
Sialylation, the addition of negatively charged sialic acid sugars to terminal ends of glycans, is upregulated in most cancers. Hypersialylation supports multiple pro-tumor mechanisms such as enhanced migration and invasion, resistance to apoptosis and immune evasion. A current gap in knowledge is the lack of understanding on how the tumor microenvironment regulates cancer cell sialylation. The adipose niche is a main component of most peritoneal cancers’ microenvironment. This includes ovarian cancer (OC), which causes most deaths from all gynecologic cancers. In this report, we demonstrate that the adipose microenvironment is a critical regulator of OC cell sialylation.In vitroadipose conditioning led to an increase in both⍺2,3 and⍺2,6-linked cell surface sialic acids in both human and mouse models of OC.Adipose-induced sialylation reprogramming was also observedin vivofrom intra-peritoneal OC tumors seeded in the adipose-rich omentum. Mechanistically, we observed upregulation of at least three sialylatransferases, St3gal1, St6gal1 and St3galnac3.Hypersialylated OC cells consistently formed intra-peritoneal tumors in both immune-competent mice and immune-compromised athymic nude mice. In contrast, hyposiaylated OC cells persistently formed tumors only in athymic nude mice demonstrating that sialylation impacts OC tumor formation in an immune dependent manner. To our knowledge, this is the first demonstration of the effect of adipose microenvironment on OC tumor sialylation. Our results set the stage for translational applications targeting sialic acid pathways in OC and other peritoneal cancers.
|
| |
|
| Overall design |
mRNA-seq primed from the polyA was used to determine expression profiles. Lexogen’s QuantSeq 3’mRNA-seq Library Prep Kit (FWD for Illumina) was utilized for building RNA-seq librariesfrom 0.1-200ng of total RNA in 5 µl of nuclease-free ultrapure water.Libraries were quantified on the Qubit and Agilent 2200 Tapestation using the DNA High Sensitivity Screen tape. The electrophoretogram, RNA Integrity Number (RIN), and the ratio of the 28S:18S RNA bands are collectively examined to determine overall quality of the RNA. The barcoded libraries were multiplexed at equimolar concentrations and sequenced with 75 bp reads on an Illumina NovaSeq SP flow cell. Data was demultiplexed using Illumina's CASAVA 1.8.2 software. After read quality was assessed[44], reads were aligned to the human genome (Build hg38)[45]and tabulated for each gene region[46]. Differential gene expression analysis was used to compare transcriptome changes between conditions using a paired design[47]. Significantly altered genes (p-value ≤ 0.05) were input in iPathwayGuide (Advaita Bioinformatics, Ann Arbor, MI) to identify differentially regulated Pathways.
|
| |
|
| Contributor(s) |
Fox A, Leonard GD, Adzibolosu N, Wong T, Tedja R, Sharma S, Gogoi R, Morris R, Mor G, Fehl C, Alvero A |
| Citation(s) |
39104719 |
| |
| Submission date |
Jun 13, 2024 |
| Last update date |
Aug 14, 2024 |
| Contact name |
Grace Michelle Swanson |
| E-mail(s) |
[email protected]
|
| Organization name |
Wayne State University
|
| Street address |
275 E. Hancock, C.S. Mott Center room 271
|
| City |
Detroit |
| State/province |
MI |
| ZIP/Postal code |
48201 |
| Country |
USA |
| |
|
| Platforms (1) |
| GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
|
| Samples (8)
|
|
| Relations |
| BioProject |
PRJNA1123758 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE269831_raw_counts.txt.gz |
289.0 Kb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
|
|
|
|
 |
Less...
More...