Collections / Multi-region spatial transcriptome analysis reveals cellular networks and pathways associated with hepatocellular carcinoma recurrence after surgical resection

Multi-region spatial transcriptome analysis reveals cellular networks and pathways associated with hepatocellular carcinoma recurrence after surgical resection

Hepatocellular carcinoma (HCC) exhibits diverse aetiologies and molecular heterogeneities, with a median 5-year overall survival (OS) of less than 70% due to late diagnosis and high recurrence rates post-curative ablation or surgery. This study investigated the complex tumor microenvironment (TME) in HCC, emphasizing the interactions between various cell types and their role in disease recurrence. Using samples from the PLANet 1.0 cohort (NCT03267641), spatial transcriptomics were performed on 17 tissue samples from 4 patients, and bulk RNA-seq on multi-region tumour sectors from 91 patients. Analysis revealed extensive intra- and inter-tumour gene expression heterogeneity, identifying a specific subset of endothelial cells (ECs), INTS6+ ECs, enriched and spatially co-localized with tumour cells in primary tumours of recurrent cases. A significant ANGPTL4-SDC1 ligand-receptor interaction was found between INTS6+ ECs and tumour cells. Interestingly, INTS6+ ECs were enriched in histologically annotated microvascular invasion (MVI). These findings suggest novel therapeutic targets focusing on endothelial cell interactions within TME.

Datasets17

Size~437 MB

AssayVisium

Samplehuman · liver

KindOther

Flag a data issue

PMID:41950768 ↗

Download the whole collection

Client Lamin CLI

Python · sddb client

from sddb import Catalog

cohort = Catalog().collection("geo-gse281759")
cohort.members        # the 17 datasets as a table

print(cohort.licenses())              # check the terms before you download

sdatas = cohort.to_dict()             # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/")

Install (Python 3.12+) Docs →

Python · lamindb

Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse281759")
coll.ordered_artifacts.to_dataframe()   # the 17 members, ordered

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

Install (Python 3.12+) Docs →

Shell

# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse281759 --dest data/

Install (Python 3.12+) Docs →

Licenses: 17 NCBI GEO policy

Member datasets · 17

Visium

Human liver

GSM8627610

human liver hepatocellular carcinoma 26.5 MB 1,898 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size26.5 MB

Spots1,898

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627616

human liver hepatocellular carcinoma 19.0 MB 1,494 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size19.0 MB

Spots1,494

Magnificationother · 3.363 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627605

human liver hepatocellular carcinoma 48.2 MB 2,356 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size48.2 MB

Spots2,356

Magnificationother · 3.363 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627614

human liver hepatocellular carcinoma 36.4 MB 2,276 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size36.4 MB

Spots2,276

Magnificationother · 3.257 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627613

human liver hepatocellular carcinoma 14.1 MB 937 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size14.1 MB

Spots937

Magnificationother · 3.363 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627615

human liver hepatocellular carcinoma 18.7 MB 1,310 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size18.7 MB

Spots1,310

Magnificationother · 3.258 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627617

human liver hepatocellular carcinoma 26.3 MB 1,731 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size26.3 MB

Spots1,731

Magnificationother · 3.258 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627608

human liver hepatocellular carcinoma 21.6 MB 1,265 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size21.6 MB

Spots1,265

Magnificationother · 3.258 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627609

human liver hepatocellular carcinoma 21.2 MB 1,485 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size21.2 MB

Spots1,485

Magnificationother · 3.364 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627612

human liver hepatocellular carcinoma 19.4 MB 1,489 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size19.4 MB

Spots1,489

Magnificationother · 3.258 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627607

human liver hepatocellular carcinoma 18.5 MB 1,187 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size18.5 MB

Spots1,187

Magnificationother · 3.258 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627611

human liver hepatocellular carcinoma 29.8 MB 1,490 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size29.8 MB

Spots1,490

Magnificationother · 3.261 µm/px

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627606

human liver hepatocellular carcinoma 40.5 MB 1,936 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size40.5 MB

Spots1,936

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627604

human liver hepatocellular carcinoma 23.7 MB 1,329 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size23.7 MB

Spots1,329

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627602

human liver hepatocellular carcinoma 31.6 MB 1,762 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size31.6 MB

Spots1,762

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627601

human liver 14.9 MB 1,714 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Size14.9 MB

Spots1,714

bronze H&E NCBI GEO policy

Visium

Human liver

GSM8627603

human liver hepatocellular carcinoma 26.3 MB 1,565 spots bronze H&E NCBI GEO policy

TechnologyVisium

Organismhuman

Tissueliver

Conditionhepatocellular carcinoma

Size26.3 MB

Spots1,565

bronze H&E NCBI GEO policy

Cite this collection

doi.org/10.1016/j.jhepr.2026.101790 ↗

BibTeX

@article{Seshachalam_2026,
  title = {Multiomics and multi-region spatial transcriptome analysis reveal cellular networks and pathways associated with HCC recurrence},
  volume = {8},
  ISSN = {2589-5559},
  url = {http://dx.doi.org/10.1016/j.jhepr.2026.101790},
  DOI = {10.1016/j.jhepr.2026.101790},
  number = {5},
  journal = {JHEP Reports},
  publisher = {Elsevier BV},
  author = {Seshachalam, Veerabrahma P. and Sari, Ita N. and Toh, Kane and Majee, Prativa and Chong, Shay L. and Sekar, Karthik and Aiderus, Aziz and Idzham, Khaireen and Qi, Ong Y. and Chong, Li Y. and Caldez, Matias and Shanmugam, Raghuvaran and Ying, Dorcas H.H. and Lee, Esmond and Toh, Jiaying and Lele, Wu and Lee, Jia Y.J. and Zhong, Guorui and Chew, Sin C. and Chen, Gao B. and Wu, Lingyan and Chung, Alexander Y.F. and Cheow, Peng C. and Kam, Juinn H. and Kow, Alfred W.C. and Leow, Wei Q. and Jegannathan, Nagalakshmi and Chen, Kaina and Bunchaliew, Chairat and de Villa, Vanessa H. and Koh, Peng S. and Bonney, Glenn and Goh, Brian K.P. and Tam, Wai Leong and Loo, Lit-Hsin and Yeong, Joe and Tergaonkar, Vinay and Chow, Pierce K.H.},
  year = {2026},
  month = May,
  pages = {101790}
}