HCA Data Explorer

A multi-omic single-cell landscape of human gynecologic malignancies

Access Granted
Updated August 4, 2023

Deconvolution of regulatory mechanisms that drive transcriptional programs in cancer cells is key to understanding tumor biology. Herein, we present matched transcriptome (scRNA-seq) and chromatin accessibility (scATAC-seq) profiles at single-cell resolution from human ovarian and endometrial tumors processed immediately following surgical resection. This dataset reveals the complex cellular heterogeneity of these tumors and enabled us to quantitatively link variation in chromatin accessibility to gene expression. We show that malignant cells acquire previously unannotated regulatory elements to drive hallmark cancer pathways. Moreover, malignant cells from within the same patients show substantial variation in chromatin accessibility linked to transcriptional output, highlighting the importance of intratumoral heterogeneity. Finally, we infer the malignant cell type-specific activity of transcription factors. By defining the regulatory logic of cancer cells, this work reveals an important reliance on oncogenic regulatory elements and highlights the ability of matched scRNA-seq/scATAC-seq to uncover clinically relevant mechanisms of tumorigenesis in gynecologic cancers.

Hector L FrancoLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Bioinformatics and Computational Biology Graduate Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Electronic address: hfranco@med.unc.edu.hfranco@med.unc.edu
Matthew J Regner1
Kamila Wisniewska2
Susana Garcia-Recio2
Aatish Thennavan3
Raul Mendez-Giraldez2
Venkat S Malladi4
Gabrielle Hawkins5
Joel S Parker6
Charles M Perou7
Victoria L Bae-Jump8
Hector L Franco9
1Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Bioinformatics and Computational Biology Graduate Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
3Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Oral and Craniofacial Biomedicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
4Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
5Division of Gynecologic Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
6Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
7Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
8Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Division of Gynecologic Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
9Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Bioinformatics and Computational Biology Graduate Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Electronic address: hfranco@med.unc.edu.
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To reference this project, please use the following link:

https://explore.data.humancellatlas.org/projects/9746f4e0-d3b2-4543-89b3-10288162851b
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INSDC Project Accessions:GEO Series Accessions:INSDC Study Accessions:

Atlas

None

Analysis Portals

None

Project Label

regnerGynecologicMalignancies

Species

Homo sapiens

Sample Type

specimens

Anatomical Entity

2 anatomical entities

Organ Part

endometrium

Selected Cell Types

Unspecified

Disease Status (Specimen)

3 disease statuses

Disease Status (Donor)

4 disease statuses

Development Stage

human adult stage

Library Construction Method

2 library construction methods

Nucleic Acid Source

2 nucleic acid sources

Paired End

false

Analysis Protocol

analysis_protocol_1, analysis_protocol_2

File Format

2 file formats

Cell Count Estimate

150.0k

Donor Count

11
tar1 file(s)xlsx1 file(s)