TY - JOUR
T1 - Multiplex immunofluorescence and histopathology dataset of cell‐cycle related proteins in renal cell carcinoma
AU - Abdullah, Hazem
AU - Um, In
AU - Stewart, Grant D.
AU - Laird, Alexander
AU - Kirkwood, Kathryn
AU - Jeong, Chang Wook
AU - Kwak, Cheol
AU - Moon, Kyung Chul
AU - TranSORCE Team
AU - Eisen, Tim
AU - Frangou, Elena
AU - Warren, Anne
AU - Meade, Angela
AU - Harrison, David J.
N1 - Funding: This work was supported by the Industrial Centre for AI Research in Digital Diagnostics 306 (iCAIRD), funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [Project No. 307 104690]. Additional support was provided by the KATY project, which received funding from the 308 European Union’s Horizon 2020 research and innovation programme under grant agreement No. 309 101017453. H.A. acknowledges support from the University of St Andrews Sanctuary Scholarship.
PY - 2026/2/1
Y1 - 2026/2/1
N2 - Clear-cell renal cell carcinoma (ccRCC) accounts for the majority of
kidney cancer diagnoses and exhibits widely variable clinical behaviour.
The dataset described here was generated to support the discovery of
robust biomarkers of tumour cell-cycle arrest and to inform the
risk-stratified management of ccRCC. We assembled four independent
cohorts including 480 patients from the UK arm of the SORCE adjuvant
trial, 300 patients from a surgically treated series in Korea, 120
patients from a retrospective Scottish cohort, and a paired
primary–metastatic cohort comprising 62 patients. Formalin-fixed
paraffin-embedded nephrectomy specimens were processed for routine
hematoxylin and eosin (H&E) histology, and for multiplex
immunofluorescence (mIF). The mIF panels detect the cyclin-dependent
kinase inhibitor p21CDKN1a, the DNA replication licencing
factor MCM2, endoglin/CD105, Lamin B1 and nuclear DNA (Hoechst).
Whole-slide images (WSIs) were acquired at high resolution, and
artificial-intelligence pipelines were used to segment nuclei, classify
individual cells into arrested phenotypes, and calculate the fraction of
cells. Accompanying metadata include demographics, tumour stage, grade,
Leibovich score, treatment arm (sorafenib/placebo), relapse events, and
disease-free survival. All images and derived tables are released under
a CC0 licence via the BioImage Archive, ensuring unrestricted reuse.
This multi-cohort dataset provides a rich resource for studying
cell-cycle arrest and proliferation markers, training image-analysis
algorithms, and developing prognostic signatures in RCC.
AB - Clear-cell renal cell carcinoma (ccRCC) accounts for the majority of
kidney cancer diagnoses and exhibits widely variable clinical behaviour.
The dataset described here was generated to support the discovery of
robust biomarkers of tumour cell-cycle arrest and to inform the
risk-stratified management of ccRCC. We assembled four independent
cohorts including 480 patients from the UK arm of the SORCE adjuvant
trial, 300 patients from a surgically treated series in Korea, 120
patients from a retrospective Scottish cohort, and a paired
primary–metastatic cohort comprising 62 patients. Formalin-fixed
paraffin-embedded nephrectomy specimens were processed for routine
hematoxylin and eosin (H&E) histology, and for multiplex
immunofluorescence (mIF). The mIF panels detect the cyclin-dependent
kinase inhibitor p21CDKN1a, the DNA replication licencing
factor MCM2, endoglin/CD105, Lamin B1 and nuclear DNA (Hoechst).
Whole-slide images (WSIs) were acquired at high resolution, and
artificial-intelligence pipelines were used to segment nuclei, classify
individual cells into arrested phenotypes, and calculate the fraction of
cells. Accompanying metadata include demographics, tumour stage, grade,
Leibovich score, treatment arm (sorafenib/placebo), relapse events, and
disease-free survival. All images and derived tables are released under
a CC0 licence via the BioImage Archive, ensuring unrestricted reuse.
This multi-cohort dataset provides a rich resource for studying
cell-cycle arrest and proliferation markers, training image-analysis
algorithms, and developing prognostic signatures in RCC.
KW - Renal cell carcinoma
KW - p21 (CDKN1A)
KW - MCM2
KW - Cell-cycle arrest
KW - Multiplex immunofluoresence
KW - H&E
KW - Histopathology
KW - Dataset
U2 - 10.3390/data11020027
DO - 10.3390/data11020027
M3 - Article
SN - 2306-5729
VL - 11
SP - 1
EP - 10
JO - Data
JF - Data
IS - 2
M1 - 27
ER -