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| Status |
Public on Jul 10, 2024 |
| Title |
The effect of exposure to neighborhood violence on GR signaling in lung tumors [Spatial Transcriptomics] |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
Other
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| Summary |
Despite lower rates and intensity of smoking, Black men experience a higher incidence of lung cancer compared to White men. The racial disparity in lung cancer is particularly pronounced in Chicago, a highly segregated urban city. Neighborhood conditions, particularly social stress, may play a role in lung tumorigenesis. Preliminary studies indicate that Black men residing in neighborhoods with higher rates of violent crime have significantly higher levels of hair cortisol, an indicator of stress response. To examine the relationship between social stress exposure and gene expression in lung tumors, we investigated glucocorticoid receptor (GR) binding in lung tumor samples in relation to GR target gene expression levels and zip code level residential neighborhood violence. Spatial transcriptomics and a version of ChIP-sequencing known as CUT & RUN were used. GR recruitment to chromatin was correlated with neighborhood violent crime rate and overall GR binding increased with increasing neighborhood violent crime rates. Among patients residing in high-violence neighborhoods, tumor samples, compared to normal neighboring lung tissue, had fewer GR binding sites. The opposite was seen in patients residing in low-violence neighborhoods, with tumor samples having more GR binding sites when compared to normal lung tissue. Tumor samples from patients living in high-violence neighborhoods exhibited increased GR recruitment to genes associated with greater tumor aggressiveness. Our findings suggest that exposure to neighborhood violence may influence tumor biology via reprogramming GR recruitment. Prioritizing lung cancer screening in neighborhoods with increased social stress, such as high violence, may reduce racial disparities in lung cancer.
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| Overall design |
Fifteen lung tumor samples from lung adenocarcinoma patient were analyzed using spatial transcriptomics and ChIP-seq (CUT&RUN)
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| Contributor(s) |
Heath H, Yoo J, Akter S, Jain A, Sharma V, McGee H, Soliman A, Mohamed A, Matthews AK, Winn R, Madak-Erdogan Z, Sage KJ |
| Citation(s) |
38912926 |
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| Submission date |
May 21, 2024 |
| Last update date |
Jul 11, 2024 |
| Contact name |
Zeynep Madak Erdogan |
| Organization name |
UIUC
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| Department |
FSHN
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| Lab |
Zeynep Madak Erdogan
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| Street address |
1201 S Goodwin Ave
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| City |
Urbana |
| State/province |
IL |
| ZIP/Postal code |
61801 |
| Country |
USA |
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| Platforms (1) |
| GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
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| Samples (15)
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| Relations |
| BioProject |
PRJNA1114097 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE268049_RAW.tar |
172.1 Mb |
(http)(custom) |
TAR (of CSV, JPG, JSON, MTX, PNG, TSV) |
SRA Run Selector |
| Raw data are available in SRA |
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