Collections / Spatial transcriptomics unveils estrogen-modulated immune responses and structural alterations in the ectocervical mucosa of depot medroxyprogesterone acetate users

Spatial transcriptomics unveils estrogen-modulated immune responses and structural alterations in the ectocervical mucosa of depot medroxyprogesterone acetate users

The injectable contraceptive, depot medroxyprogesterone acetate (DMPA), is associated with compromised cervical mucosal barriers. High-resolution spatial transcriptomics is applied here to reveal the spatial localization of these altered molecular markers. Ectocervical tissue samples from Kenyan sex workers using DMPA, or non-hormonal contraceptives, underwent spatial transcriptomics and gene set enrichment analyses. Integrated systemic estradiol levels and bulk tissue gene expression data from a larger cohort enhanced the study’s scope. Unsupervised clustering unveiled four epithelial and seven submucosal layers, showcasing spatially restricted and diverse functional epithelial responses, and a less structured submucosal spatial ordering. DMPA associated with mucosal-wide immunoglobulin gene upregulation, verified by CD20+ B-cell immunostaining, and upregulated immune markers adjacent to the basal membrane. Downregulated genes represented spatially restricted disrupted epithelial barrier integrity and submucosal extracellular matrix dysfunction. The transcriptional profile was associated with markers of estrogen regulation. Collectively, our findings reveal estrogen-modulated distinct ectocervical transcriptional profiles associated with DMPA usage. While upregulation of immunoglobulin genes occurs throughout the mucosa, activation of innate immune responses and dysregulation of barrier integrity markers are spatially restricted. These results extend previous analyses using bulk transcriptomics and provide insights into the molecular landscape influenced by DMPA, shedding light on contraceptive effects and health implications.

Datasets8
Size~63 MB
AssayVisium
Samplehuman · ectocervix
KindOther
PMID:39762272 ↗
Python · lamindb
import lamindb as ln
import spatialdata as sd

coll = ln.Collection.get(key="geo-gse299708")
coll.ordered_artifacts.df()                 # the 8 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]

# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()}
Open in Vitessce
Visium
Human ectocervix
GSM9044528
human ectocervix 7.9 MB 760 obs silver H&E
TechnologyVisium
Organismhuman
Tissueectocervix
Size7.9 MB
Obs760
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human ectocervix
GSM9044530
human ectocervix 10 MB 1,280 obs silver H&E
TechnologyVisium
Organismhuman
Tissueectocervix
Size10 MB
Obs1,280
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human ectocervix
GSM9044529
human ectocervix 9.3 MB 1,124 obs silver H&E
TechnologyVisium
Organismhuman
Tissueectocervix
Size9.3 MB
Obs1,124
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human ectocervix
GSM9044534
human ectocervix 8.6 MB 969 obs silver H&E
TechnologyVisium
Organismhuman
Tissueectocervix
Size8.6 MB
Obs969
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human ectocervix
GSM9044535
human ectocervix 13 MB 1,130 obs silver H&E
TechnologyVisium
Organismhuman
Tissueectocervix
Size13 MB
Obs1,130
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human ectocervix
GSM9044532
human ectocervix 4.3 MB 418 obs silver H&E
TechnologyVisium
Organismhuman
Tissueectocervix
Size4.3 MB
Obs418
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human ectocervix
GSM9044533
human ectocervix 4.1 MB 307 obs silver H&E
TechnologyVisium
Organismhuman
Tissueectocervix
Size4.1 MB
Obs307
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human ectocervix
GSM9044531
human ectocervix 6.0 MB 712 obs silver H&E
TechnologyVisium
Organismhuman
Tissueectocervix
Size6.0 MB
Obs712
silver H&E Open in Vitessce

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