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A single-cell and spatial genomics atlas of human skin fibroblasts reveals shared disease-related fibroblast subtypes across tissues
Source paper: PMC12479362
|
[
{
"end": 66,
"label": "CellType",
"start": 50,
"text": "skin fibroblasts"
},
{
"end": 117,
"label": "CellType",
"start": 82,
"text": "disease-related fibroblast subtypes"
},
{
"end": 132,
"label": "Tissue",
"start": 125,
"text": "tissues"
}
] |
Single_Cell
|
Fibroblasts sculpt the architecture and cellular microenvironments of various tissues.
|
[
{
"end": 11,
"label": "CellType",
"start": 0,
"text": "Fibroblasts"
},
{
"end": 85,
"label": "Tissue",
"start": 78,
"text": "tissues"
}
] |
Single_Cell
|
Here we constructed a spatially resolved atlas of human skin fibroblasts from healthy skin and 23 skin diseases, with comparison to 14 cross-tissue diseases.
|
[
{
"end": 90,
"label": "Tissue",
"start": 86,
"text": "skin"
},
{
"end": 72,
"label": "CellType",
"start": 50,
"text": "human skin fibroblasts"
}
] |
Single_Cell
|
We define six major skin fibroblast subtypes in health and three that are disease-specific.
|
[
{
"end": 44,
"label": "CellType",
"start": 20,
"text": "skin fibroblast subtypes"
}
] |
Single_Cell
|
We characterize two fibroblast subtypes further as they are conserved across tissues and are immune-related.
|
[
{
"end": 39,
"label": "CellType",
"start": 20,
"text": "fibroblast subtypes"
},
{
"end": 84,
"label": "Tissue",
"start": 77,
"text": "tissues"
}
] |
Single_Cell
|
The first, F3: fibroblastic reticular cell-like fibroblast ( CCL19 CD74 HLA-DRA ), is a fibroblastic reticular cell-like subtype that is predicted to maintain the superficial perivascular immune niche.
|
[
{
"end": 58,
"label": "CellType",
"start": 15,
"text": "fibroblastic reticular cell-like fibroblast"
},
{
"end": 128,
"label": "CellType",
"start": 88,
"text": "fibroblastic reticular cell-like subtype"
},
{
"end": 200,
"label": "Tissue",
"start": 163,
"text": "superficial perivascular immune niche"
}
] |
Single_Cell
|
The second, F6: inflammatory myofibroblasts ( IL11 MMP1 CXCL8 IL7R ), characterizes early human skin wounds, inflammatory diseases with scarring risk and cancer.
|
[
{
"end": 43,
"label": "CellType",
"start": 16,
"text": "inflammatory myofibroblasts"
}
] |
Single_Cell
|
F6: inflammatory myofibroblasts were predicted to recruit neutrophils, monocytes and B cells across multiple human tissues.
|
[
{
"end": 80,
"label": "CellType",
"start": 71,
"text": "monocytes"
},
{
"end": 69,
"label": "CellType",
"start": 58,
"text": "neutrophils"
},
{
"end": 92,
"label": "CellType",
"start": 85,
"text": "B cells"
},
{
"end": 31,
"label": "CellType",
"start": 4,
"text": "inflammatory myofibroblasts"
},
{
"end": 122,
"label": "Tissue",
"start": 115,
"text": "tissues"
}
] |
Single_Cell
|
Our study provides a harmonized nomenclature for skin fibroblasts in health and disease, contextualized with cross-tissue findings and clinical skin disease profiles.
|
[
{
"end": 65,
"label": "CellType",
"start": 49,
"text": "skin fibroblasts"
}
] |
Single_Cell
|
Fibroblasts are crucial cells for shaping tissue architecture and immune cell niches .
|
[
{
"end": 11,
"label": "CellType",
"start": 0,
"text": "Fibroblasts"
},
{
"end": 29,
"label": "CellType",
"start": 24,
"text": "cells"
},
{
"end": 84,
"label": "Tissue",
"start": 66,
"text": "immune cell niches"
}
] |
Single_Cell
|
Studying the heterogeneity of fibroblast subtypes has been challenging due to the scarcity of unique surface markers and their tendency to adopt activated phenotypes during in vitro culture .
|
[
{
"end": 49,
"label": "CellType",
"start": 30,
"text": "fibroblast subtypes"
}
] |
Single_Cell
|
Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics technologies have overcome these challenges, enabling the dissection of fibroblast heterogeneity in human tissues .
|
[
{
"end": 180,
"label": "Tissue",
"start": 167,
"text": "human tissues"
}
] |
Single_Cell
|
While recent studies have described fibroblast states in human skin, they have not spatially resolved their tissue microanatomical location.
|
[
{
"end": 67,
"label": "Tissue",
"start": 57,
"text": "human skin"
}
] |
Single_Cell
|
Very few, if any, have interrogated fibroblasts in diverse disease conditions in the skin and across human tissues .
|
[
{
"end": 47,
"label": "Tissue",
"start": 36,
"text": "fibroblasts"
},
{
"end": 89,
"label": "Tissue",
"start": 85,
"text": "skin"
},
{
"end": 114,
"label": "Tissue",
"start": 101,
"text": "human tissues"
}
] |
Single_Cell
|
Consequently, the fibroblast composition and function in human skin; how it changes across a range of diseases (inflammatory, cancer and fibrosis/scarring); and how these populations relate to other human tissues is still unclear.
|
[
{
"end": 67,
"label": "Tissue",
"start": 57,
"text": "human skin"
},
{
"end": 212,
"label": "Tissue",
"start": 199,
"text": "human tissues"
}
] |
Single_Cell
|
In this study, we integrated published large-scale scRNA-seq datasets of healthy human skin and 23 skin diseases and generated spatial transcriptomics data from two different modalities to construct a high-resolution spatially resolved atlas of more than 350,000 adult human skin fibroblasts.
|
[
{
"end": 91,
"label": "Tissue",
"start": 73,
"text": "healthy human skin"
},
{
"end": 291,
"label": "CellType",
"start": 263,
"text": "adult human skin fibroblasts"
}
] |
Single_Cell
|
We provide a consensus annotation of skin fibroblasts based on gene expression profiles and spatial locations, and contextualize these findings with fibroblast data from other healthy and diseased human tissues.
|
[
{
"end": 53,
"label": "CellType",
"start": 37,
"text": "skin fibroblasts"
},
{
"end": 210,
"label": "Tissue",
"start": 176,
"text": "healthy and diseased human tissues"
}
] |
Single_Cell
|
Our scRNA-seq and spatial datasets resources are freely available for download and interactive data exploration at https://cellatlas.io/studies/skin-fibroblast .
|
[] |
Single_Cell
|
We re-processed and integrated 2.1 million cells from scRNA-seq data of adult human skin, comprising 32 datasets and 251 donors (Fig. 1a and Supplementary Table 1 ) using single-cell variational inference (scVI) ( Methods ) .
|
[
{
"end": 48,
"label": "CellType",
"start": 43,
"text": "cells"
},
{
"end": 88,
"label": "Tissue",
"start": 72,
"text": "adult human skin"
}
] |
Single_Cell
|
After quality control, 357,276 high-quality fibroblasts were selected based on canonical marker gene expression (Fig. 1a and Extended Data Fig. 1a ).
|
[
{
"end": 55,
"label": "CellType",
"start": 44,
"text": "fibroblasts"
}
] |
Single_Cell
|
In healthy skin, we identified six major fibroblast subtypes based on differential gene expression (Supplementary Data Fig. 1a and Supplementary Table 2 ) and pathway enrichment analysis (Extended Data Fig. 2a and Methods ).
|
[
{
"end": 60,
"label": "CellType",
"start": 41,
"text": "fibroblast subtypes"
},
{
"end": 15,
"label": "Tissue",
"start": 3,
"text": "healthy skin"
}
] |
Single_Cell
|
The six fibroblast subtypes were observed across different covariates (Extended Data Fig. 1b–g and Supplementary Note 1 ).
|
[
{
"end": 27,
"label": "CellType",
"start": 8,
"text": "fibroblast subtypes"
}
] |
Single_Cell
|
Complementary spatial transcriptomic methods validated the presence of each of the six fibroblast subtypes and revealed their distinct microanatomical locations (Fig. 2a–c , Extended Data Figs. 3 and 4 and Supplementary Fig. 2 ).
|
[
{
"end": 106,
"label": "CellType",
"start": 87,
"text": "fibroblast subtypes"
}
] |
Single_Cell
|
Two of the six fibroblast populations (F1: superficial (papillary) and F2: universal (reticular)) were uniformly present throughout skin at different tissue depths.
|
[
{
"end": 136,
"label": "Tissue",
"start": 132,
"text": "skin"
},
{
"end": 37,
"label": "CellType",
"start": 11,
"text": "six fibroblast populations"
},
{
"end": 66,
"label": "CellType",
"start": 43,
"text": "superficial (papillary)"
},
{
"end": 96,
"label": "CellType",
"start": 75,
"text": "universal (reticular)"
}
] |
Single_Cell
|
F1: superficial (papillary) fibroblasts localized adjacent to the skin epithelium in the papillary dermis (Fig. 2b,c ) and expressed genes encoding superficial dermal collagens ( COL13A1 , COL18A1 and COL23A1 ) and Wnt signaling inhibitors ( APCDD1 , WIF1 and NKD2 ) (Fig. 1c ).
|
[
{
"end": 39,
"label": "CellType",
"start": 4,
"text": "superficial (papillary) fibroblasts"
},
{
"end": 81,
"label": "Tissue",
"start": 66,
"text": "skin epithelium"
},
{
"end": 105,
"label": "Tissue",
"start": 89,
"text": "papillary dermis"
}
] |
Single_Cell
|
A Wnt-mediated synergistic interplay between superficial dermal fibroblasts and basal epithelial cells has been reported to reciprocally maintain cellular identity .
|
[
{
"end": 75,
"label": "CellType",
"start": 45,
"text": "superficial dermal fibroblasts"
},
{
"end": 102,
"label": "CellType",
"start": 80,
"text": "basal epithelial cells"
}
] |
Single_Cell
|
F2: universal (reticular) fibroblasts were located deeper in the skin, interspersed between large collagen fibers in the reticular dermis (Fig. 2b,c ).
|
[
{
"end": 69,
"label": "Tissue",
"start": 65,
"text": "skin"
},
{
"end": 37,
"label": "CellType",
"start": 4,
"text": "universal (reticular) fibroblasts"
},
{
"end": 137,
"label": "Tissue",
"start": 121,
"text": "reticular dermis"
}
] |
Single_Cell
|
This population was characterized by high expression of marker genes of universal PI16 fibroblasts ( PI16 , CD34 and MFAP5) , a fibroblast subtype found in many human tissues and postulated to represent a precursor fibroblast cell state .
|
[
{
"end": 98,
"label": "CellType",
"start": 72,
"text": "universal PI16 fibroblasts"
},
{
"end": 146,
"label": "CellType",
"start": 128,
"text": "fibroblast subtype"
},
{
"end": 174,
"label": "Tissue",
"start": 161,
"text": "human tissues"
}
] |
Single_Cell
|
Transcription factor activity inference identified KLF5 in F2: universal fibroblasts (Extended Data Fig. 2b ), which has been reported to drive the universal Pi16 state .
|
[
{
"end": 84,
"label": "CellType",
"start": 63,
"text": "universal fibroblasts"
}
] |
Single_Cell
|
As fascial fibroblasts (F_Fascia) are proposed as a potential progenitor cell in mouse skin , we included these cells in an additional integration, identifying that F_Fascia formed a subset of F2: universal (Extended Data Fig. 1i,j and Supplementary Note 2 ).
|
[
{
"end": 33,
"label": "CellType",
"start": 3,
"text": "fascial fibroblasts (F_Fascia)"
},
{
"end": 91,
"label": "Tissue",
"start": 81,
"text": "mouse skin"
},
{
"end": 173,
"label": "CellType",
"start": 165,
"text": "F_Fascia"
},
{
"end": 77,
"label": "CellType",
"start": 52,
"text": "potential progenitor cell"
}
] |
Single_Cell
|
The remaining fibroblast subsets were more focal in localization, being associated with vascular or adnexal structures.
|
[
{
"end": 32,
"label": "CellType",
"start": 14,
"text": "fibroblast subsets"
},
{
"end": 118,
"label": "Tissue",
"start": 88,
"text": "vascular or adnexal structures"
}
] |
Single_Cell
|
We thus used hematoxylin and eosin (H&E) staining to illustrate these microenvironments.
|
[] |
Single_Cell
|
F3: fibroblastic reticular cell (FRC)-like fibroblasts were located predominantly in the superficial perivascular region in proximity to immune cells (Fig. 2b and Extended Data Figs. 3a,b and 4a,b ).
|
[
{
"end": 54,
"label": "CellType",
"start": 4,
"text": "fibroblastic reticular cell (FRC)-like fibroblasts"
},
{
"end": 120,
"label": "Tissue",
"start": 89,
"text": "superficial perivascular region"
},
{
"end": 149,
"label": "CellType",
"start": 137,
"text": "immune cells"
}
] |
Single_Cell
|
F3: FRC-like fibroblasts transcriptomically resembled FRCs, which are specialized fibroblasts found in lymphoid organs/structures that maintain immune niches (Extended Data Fig. 1h ) , expressing genes that attract and compartmentalize immune cells ( CCL19 , CXCL12 and CH25H ), maintain immune cell survival and function ( IL33 , IL15 , TNFSF13B and VCAM1 ) and enable antigen presentation ( CD74 and major histocompatibility complex (MHC)-II molecules) .
|
[
{
"end": 24,
"label": "CellType",
"start": 4,
"text": "FRC-like fibroblasts"
},
{
"end": 58,
"label": "CellType",
"start": 54,
"text": "FRCs"
},
{
"end": 93,
"label": "CellType",
"start": 70,
"text": "specialized fibroblasts"
},
{
"end": 129,
"label": "Tissue",
"start": 103,
"text": "lymphoid organs/structures"
},
{
"end": 157,
"label": "Tissue",
"start": 144,
"text": "immune niches"
},
{
"end": 248,
"label": "CellType",
"start": 236,
"text": "immune cells"
}
] |
Single_Cell
|
F2/3: perivascular fibroblasts also localized with immune cells but, unlike F3: FRC-like fibroblasts, were additionally enriched in deep perivascular regions and other sites (Fig. 2a–c and Extended Data Fig. 4b,c ).
|
[
{
"end": 63,
"label": "CellType",
"start": 51,
"text": "immune cells"
},
{
"end": 157,
"label": "Tissue",
"start": 132,
"text": "deep perivascular regions"
},
{
"end": 30,
"label": "CellType",
"start": 6,
"text": "perivascular fibroblasts"
},
{
"end": 100,
"label": "CellType",
"start": 80,
"text": "FRC-like fibroblasts"
}
] |
Single_Cell
|
A fraction of F2/3: perivascular fibroblasts showed elevated expression of PPARG (Fig. 1c ) and pathway analysis suggested a role in adipocyte differentiation (Extended Data Fig. 2a ).
|
[
{
"end": 44,
"label": "CellType",
"start": 20,
"text": "perivascular fibroblasts"
}
] |
Single_Cell
|
The capability to differentiate into adipocytes is characteristic of the reticular fibroblast (equivalent to F2: universal) lineage .
|
[
{
"end": 47,
"label": "CellType",
"start": 37,
"text": "adipocytes"
},
{
"end": 93,
"label": "CellType",
"start": 73,
"text": "reticular fibroblast"
},
{
"end": 131,
"label": "CellType",
"start": 113,
"text": "universal) lineage"
}
] |
Single_Cell
|
F2/3: perivascular fibroblasts shared select gene expression with both F2: universal and F3: FRC-like fibroblasts (Fig. 3c ).
|
[
{
"end": 30,
"label": "CellType",
"start": 6,
"text": "perivascular fibroblasts"
},
{
"end": 113,
"label": "CellType",
"start": 93,
"text": "FRC-like fibroblasts"
}
] |
Single_Cell
|
F4: hair follicle-associated fibroblasts ( ASPN COL11A1 ) encompassed three subclusters that were associated with specific regions of the hair follicle (Fig. 2b,c ).
|
[
{
"end": 151,
"label": "Tissue",
"start": 138,
"text": "hair follicle"
},
{
"end": 40,
"label": "CellType",
"start": 4,
"text": "hair follicle-associated fibroblasts"
}
] |
Single_Cell
|
The first is a well-characterized dermal sheath (DS) population (F4: DS_DPEP1 ) that wraps around the lower/mid hair follicle (Fig. 2b ).
|
[
{
"end": 125,
"label": "Tissue",
"start": 112,
"text": "hair follicle"
},
{
"end": 63,
"label": "CellType",
"start": 34,
"text": "dermal sheath (DS) population"
}
] |
Single_Cell
|
The second is a novel F4: TNN COCH subtype, expressing tendon-associated genes ( MKX and TNMD ) and observed at the isthmus (mid-hair shaft) (Fig. 2b and Extended Data Fig. 4d ).
|
[
{
"end": 140,
"label": "Tissue",
"start": 116,
"text": "isthmus (mid-hair shaft)"
},
{
"end": 42,
"label": "CellType",
"start": 26,
"text": "TNN COCH subtype"
}
] |
Single_Cell
|
The third F4: DP_HHIP subtype uniquely expressed dermal papilla marker genes ( CORIN , HHIP , RSPO3 and LEF1 ) .
|
[
{
"end": 29,
"label": "CellType",
"start": 14,
"text": "DP_HHIP subtype"
}
] |
Single_Cell
|
F5: Schwann-like fibroblasts (SCN7A, FMO2 , FGFBP2 and OLFML2A ) contained two subclusters (F5: NGFR and F5: RAMP1 ) (Extended Data Fig. 1k ) .
|
[
{
"end": 28,
"label": "CellType",
"start": 4,
"text": "Schwann-like fibroblasts"
},
{
"end": 100,
"label": "CellType",
"start": 92,
"text": "F5: NGFR"
},
{
"end": 114,
"label": "CellType",
"start": 105,
"text": "F5: RAMP1"
}
] |
Single_Cell
|
F5: RAMP1 fibroblasts were enriched near innervated eccrine glands and expressed genes encoding the receptor complex for the neuropeptide CGRP (Fig. 2b,c and Extended Data Figs. 1l , 3c,d and 4c ), suggesting a possible interface with the nervous system.
|
[
{
"end": 253,
"label": "Tissue",
"start": 239,
"text": "nervous system"
},
{
"end": 21,
"label": "CellType",
"start": 4,
"text": "RAMP1 fibroblasts"
},
{
"end": 66,
"label": "Tissue",
"start": 41,
"text": "innervated eccrine glands"
}
] |
Single_Cell
|
F5: NGFR colocalized with Schwann cells, suggesting that they are a nerve-associated population.
|
[
{
"end": 8,
"label": "CellType",
"start": 0,
"text": "F5: NGFR"
},
{
"end": 39,
"label": "CellType",
"start": 26,
"text": "Schwann cells"
},
{
"end": 95,
"label": "CellType",
"start": 68,
"text": "nerve-associated population"
}
] |
Single_Cell
|
Fibroblasts have been described in the endoneurium and perineurium of nerve fibers from imaging studies , and ‘Schwann-like fibroblasts’ have recently been reported in human skin scRNA-seq data .
|
[
{
"end": 11,
"label": "Tissue",
"start": 0,
"text": "Fibroblasts"
},
{
"end": 50,
"label": "Tissue",
"start": 39,
"text": "endoneurium"
},
{
"end": 82,
"label": "Tissue",
"start": 55,
"text": "perineurium of nerve fibers"
},
{
"end": 135,
"label": "CellType",
"start": 111,
"text": "Schwann-like fibroblasts"
}
] |
Single_Cell
|
We confirmed that our six fibroblast subtypes were distinct from Schwann cells and pericytes (Extended Data Fig. 1j,k and Supplementary Note 2 ).
|
[
{
"end": 92,
"label": "CellType",
"start": 83,
"text": "pericytes"
},
{
"end": 45,
"label": "CellType",
"start": 26,
"text": "fibroblast subtypes"
},
{
"end": 78,
"label": "CellType",
"start": 65,
"text": "Schwann cells"
}
] |
Single_Cell
|
In addition, we harmonized our skin fibroblast annotation with a previous classification (Supplementary Data Fig. 1b ).
|
[] |
Single_Cell
|
Overall, we provide a new framework for healthy human skin fibroblast annotation based on gene expression profiles (Fig. 1 ) and spatial location (Fig. 2 ) that integrates previous fibroblast descriptions in skin and across tissues.
|
[
{
"end": 212,
"label": "Tissue",
"start": 208,
"text": "skin"
},
{
"end": 231,
"label": "Tissue",
"start": 224,
"text": "tissues"
}
] |
Single_Cell
|
Our findings of transcriptionally defined fibroblast subtypes in distinct microanatomical locations suggest a role for regional fibroblasts in supporting distinct niche functions.
|
[
{
"end": 61,
"label": "CellType",
"start": 16,
"text": "transcriptionally defined fibroblast subtypes"
},
{
"end": 99,
"label": "Tissue",
"start": 74,
"text": "microanatomical locations"
},
{
"end": 139,
"label": "CellType",
"start": 119,
"text": "regional fibroblasts"
}
] |
Single_Cell
|
We next sought to identify how fibroblast states change in diseased skin.
|
[
{
"end": 72,
"label": "Tissue",
"start": 59,
"text": "diseased skin"
}
] |
Single_Cell
|
We used scPoli , a deep-learning model for integration and identification of novel cell states in single-cell transcriptome data ( Methods ) (Fig. 3a ).
|
[] |
Single_Cell
|
We mapped fibroblasts from skin diseases to our healthy/nonlesional F1–F5 fibroblast reference.
|
[
{
"end": 21,
"label": "CellType",
"start": 10,
"text": "fibroblasts"
}
] |
Single_Cell
|
Out of 190,756 fibroblasts from diseased states, 121,167 diseased cells were confidently assigned existing F1–F5 cell labels (Extended Data Fig. 5a,b ).
|
[
{
"end": 26,
"label": "CellType",
"start": 15,
"text": "fibroblasts"
}
] |
Single_Cell
|
The remaining 69,589 fibroblasts from the disease data were classified as uncertain (unlabeled) by scPoli (Fig. 3b ).
|
[
{
"end": 32,
"label": "CellType",
"start": 21,
"text": "fibroblasts"
}
] |
Single_Cell
|
Manual annotation based on differential gene expression (Supplementary Data Fig. 1c and Supplementary Table 3 ) and pathway analysis (Extended Data Fig. 5c ) revealed two ‘disease-adapted’ and three ‘disease-specific’ fibroblast subtypes (Fig. 3b–f ).
|
[
{
"end": 237,
"label": "CellType",
"start": 171,
"text": "‘disease-adapted’ and three ‘disease-specific’ fibroblast subtypes"
}
] |
Single_Cell
|
‘Disease-adapted’ fibroblasts resembled a healthy fibroblast subtype counterpart (Fig. 3e ) and were expanded in disease settings (Fig. 3d ).
|
[
{
"end": 29,
"label": "CellType",
"start": 0,
"text": "‘Disease-adapted’ fibroblasts"
},
{
"end": 68,
"label": "CellType",
"start": 42,
"text": "healthy fibroblast subtype"
}
] |
Single_Cell
|
The first disease-adapted fibroblast subtype resembled F1: superficial fibroblasts in healthy skin (Fig. 3e ).
|
[
{
"end": 44,
"label": "CellType",
"start": 10,
"text": "disease-adapted fibroblast subtype"
},
{
"end": 82,
"label": "CellType",
"start": 55,
"text": "F1: superficial fibroblasts"
},
{
"end": 98,
"label": "Tissue",
"start": 86,
"text": "healthy skin"
}
] |
Single_Cell
|
The F1-like disease population upregulated genes suggestive of regenerative function ( CRABP1 , CYP26B1 and WNT5A ) .
|
[
{
"end": 30,
"label": "CellType",
"start": 4,
"text": "F1-like disease population"
}
] |
Single_Cell
|
CRABP1 and CYP26B1 are markers of superficial/upper wound fibroblasts in mice , which are thought to be the source of wound-induced hair follicle neogenesis , and involved in retinoic acid degradation.
|
[
{
"end": 69,
"label": "CellType",
"start": 34,
"text": "superficial/upper wound fibroblasts"
}
] |
Single_Cell
|
CRABP1 fibroblasts are also associated with regeneration in reindeer skin and early-gestational human skin .
|
[
{
"end": 18,
"label": "CellType",
"start": 0,
"text": "CRABP1 fibroblasts"
},
{
"end": 73,
"label": "Tissue",
"start": 60,
"text": "reindeer skin"
},
{
"end": 106,
"label": "Tissue",
"start": 78,
"text": "early-gestational human skin"
}
] |
Single_Cell
|
The second disease-adapted fibroblast subtype resembled F3: FRC-like fibroblasts and upregulated CXCL9 and/or ADAMDEC1 (Fig. 3e ).
|
[
{
"end": 45,
"label": "CellType",
"start": 11,
"text": "disease-adapted fibroblast subtype"
},
{
"end": 80,
"label": "CellType",
"start": 60,
"text": "FRC-like fibroblasts"
}
] |
Single_Cell
|
CXCL9 is a chemoattractant for CXCR3 cells and has been reported as an activation marker for FRCs in lymphoid tissues .
|
[
{
"end": 117,
"label": "Tissue",
"start": 101,
"text": "lymphoid tissues"
},
{
"end": 42,
"label": "CellType",
"start": 31,
"text": "CXCR3 cells"
},
{
"end": 97,
"label": "CellType",
"start": 93,
"text": "FRCs"
}
] |
Single_Cell
|
‘Disease-specific’ fibroblasts (F6: inflammatory myofibroblasts, F7: myofibroblasts and F8: fascia-like myofibroblasts) did not have a healthy skin fibroblast counterpart and highly expressed a myofibroblast gene signature.
|
[
{
"end": 30,
"label": "CellType",
"start": 0,
"text": "‘Disease-specific’ fibroblasts"
},
{
"end": 158,
"label": "CellType",
"start": 135,
"text": "healthy skin fibroblast"
},
{
"end": 63,
"label": "CellType",
"start": 36,
"text": "inflammatory myofibroblasts"
},
{
"end": 83,
"label": "CellType",
"start": 69,
"text": "myofibroblasts"
},
{
"end": 118,
"label": "CellType",
"start": 92,
"text": "fascia-like myofibroblasts"
}
] |
Single_Cell
|
This myofibroblast signature included contractility ( ACTA2 ), extracellular matrix (ECM) ( COL3A1 , COL5A1 , COL8A1 , POSTN and CTHRC1 ) and other myofibroblast-associated genes ( LRRC15 , SFRP4 , ASPN , RUNX2 and SCX ) (Fig. 3c,g and Extended Data Fig. 5d,e ) .
|
[] |
Single_Cell
|
F6: inflammatory myofibroblasts additionally expressed immune-related genes such as interleukins ( IL11 and IL24 ), chemokines ( CXCL5 , CXCL8 , CXCL13 and CCL11 ) and matrix metalloproteinases that can remodel tissue to facilitate immune cell infiltration ( MMP1 ) (Fig. 3c ).
|
[
{
"end": 217,
"label": "Tissue",
"start": 211,
"text": "tissue"
},
{
"end": 31,
"label": "CellType",
"start": 4,
"text": "inflammatory myofibroblasts"
}
] |
Single_Cell
|
JAK–STAT and hypoxic signaling genes were also elevated (Fig. 3h ).
|
[] |
Single_Cell
|
F7: myofibroblasts and F8: fascia-like myofibroblasts were distinguished by a higher expression of ECM and TGFβ signaling genes, as well as the mechanotransducer PIEZO2 (Fig. 3c,h ).
|
[
{
"end": 18,
"label": "CellType",
"start": 4,
"text": "myofibroblasts"
},
{
"end": 53,
"label": "CellType",
"start": 27,
"text": "fascia-like myofibroblasts"
}
] |
Single_Cell
|
F8: fascia-like myofibroblasts were distinguished by expression of F_Fascia-associated genes (Fig. 3c ).
|
[
{
"end": 30,
"label": "CellType",
"start": 4,
"text": "fascia-like myofibroblasts"
}
] |
Single_Cell
|
Overall, our results indicate that healthy fibroblasts can acquire a regenerative phenotype in F1: superficial fibroblasts ( CRABP1 CYP27B1 ), a distinct polarization in F3: FRC-like fibroblasts ( CXCL9 / ADAMDEC1 ) and potentially give rise to myofibroblast states ( ACTA2 COL8A1 SFRP4 ) in diseased skin.
|
[
{
"end": 54,
"label": "CellType",
"start": 35,
"text": "healthy fibroblasts"
},
{
"end": 265,
"label": "CellType",
"start": 245,
"text": "myofibroblast states"
},
{
"end": 305,
"label": "Tissue",
"start": 292,
"text": "diseased skin"
},
{
"end": 122,
"label": "CellType",
"start": 99,
"text": "superficial fibroblasts"
},
{
"end": 194,
"label": "CellType",
"start": 174,
"text": "FRC-like fibroblasts"
}
] |
Single_Cell
|
We next leveraged the diverse clinical profiles of skin diseases to assess whether fibroblast subtypes provide molecular insights into disease endotypes with respect to scarring.
|
[
{
"end": 102,
"label": "CellType",
"start": 83,
"text": "fibroblast subtypes"
}
] |
Single_Cell
|
We assigned the 23 skin diseases into three clinically determined risk of scarring groups: low scarring risk, moderate scarring risk, and established scarring/fibrosis (see Methods ) (Fig. 4a ).
|
[] |
Single_Cell
|
We excluded neurofibroma from this analysis as it was the only case of benign neoplasia, consisting primarily of F5: Schwann-like and F2/3: perivascular fibroblasts (Extended Data Fig. 6a ).
|
[
{
"end": 129,
"label": "CellType",
"start": 117,
"text": "Schwann-like"
},
{
"end": 164,
"label": "CellType",
"start": 140,
"text": "perivascular fibroblasts"
}
] |
Single_Cell
|
We identified distinct fibroblast compositions for each scarring risk category (Fig. 4b ).
|
[] |
Single_Cell
|
Low scarring risk diseases were characterized by a high prevalence of F1: superficial ( CRABP CYP27B1 ) and F3: FRC-like fibroblasts ( CXCL9 / ADAMDEC1 ) (Fig. 4b ), without notable F6–F8 myofibroblast populations.
|
[
{
"end": 132,
"label": "CellType",
"start": 112,
"text": "FRC-like fibroblasts"
},
{
"end": 213,
"label": "CellType",
"start": 188,
"text": "myofibroblast populations"
}
] |
Single_Cell
|
This finding agrees with the regenerative-associated gene profile of disease-associated F1: superficial fibroblasts and a role for F3: FRC-like fibroblasts in maintaining immune niches.
|
[
{
"end": 115,
"label": "CellType",
"start": 92,
"text": "superficial fibroblasts"
},
{
"end": 155,
"label": "CellType",
"start": 135,
"text": "FRC-like fibroblasts"
}
] |
Single_Cell
|
Diseases with scarring risk were characterized by a uniquely high prevalence of F6: inflammatory myofibroblasts, which was not observed in low scarring risk or established fibrosis (Fig. 4b ).
|
[
{
"end": 111,
"label": "CellType",
"start": 84,
"text": "inflammatory myofibroblasts"
}
] |
Single_Cell
|
F7: myofibroblasts were observed at a similar prevalence in diseases with scarring risk and established fibrosis.
|
[
{
"end": 18,
"label": "CellType",
"start": 4,
"text": "myofibroblasts"
}
] |
Single_Cell
|
These data point toward F6: inflammatory myofibroblast as a population influencing scarring risk, but which are largely absent in established fibrosis.
|
[
{
"end": 54,
"label": "CellType",
"start": 28,
"text": "inflammatory myofibroblast"
}
] |
Single_Cell
|
F8: fascia-like myofibroblasts were also elevated in established fibrosis but were predominantly observed in Dupuytren contracture, a fibroproliferative disease of the palmar fascia (Fig. 4a ).
|
[
{
"end": 181,
"label": "Tissue",
"start": 168,
"text": "palmar fascia"
},
{
"end": 30,
"label": "CellType",
"start": 4,
"text": "fascia-like myofibroblasts"
}
] |
Single_Cell
|
We used two further approaches to demonstrate the role for distinct fibroblast subtypes predicting scarring risk.
|
[
{
"end": 87,
"label": "CellType",
"start": 68,
"text": "fibroblast subtypes"
}
] |
Single_Cell
|
First, we trained a random forest classifier and identified that F6: inflammatory myofibroblasts and F7: myofibroblasts were the most important fibroblast subtypes for predicting scarring risk category (Extended Data Fig. 6b ).
|
[
{
"end": 119,
"label": "CellType",
"start": 105,
"text": "myofibroblasts"
},
{
"end": 96,
"label": "CellType",
"start": 69,
"text": "inflammatory myofibroblasts"
},
{
"end": 163,
"label": "CellType",
"start": 144,
"text": "fibroblast subtypes"
}
] |
Single_Cell
|
Second, we profiled a well-recognized myofibroblast marker (LRRC15) at the protein level.
|
[] |
Single_Cell
|
LRRC15 was evident in inflammation with scarring risk (inflamed hidradenitis suppurativa skin) but not in noninflamed skin or inflamed skin without scarring risk (atopic dermatitis skin) (Fig. 4c ).
|
[
{
"end": 93,
"label": "Tissue",
"start": 55,
"text": "inflamed hidradenitis suppurativa skin"
},
{
"end": 122,
"label": "Tissue",
"start": 106,
"text": "noninflamed skin"
},
{
"end": 139,
"label": "Tissue",
"start": 126,
"text": "inflamed skin"
},
{
"end": 185,
"label": "Tissue",
"start": 163,
"text": "atopic dermatitis skin"
}
] |
Single_Cell
|
Having established that disease-associated fibroblasts are enriched in distinct scarring categories, we next used spatial transcriptomics to validate these fibroblast populations in distinct scarring risk stroma (Fig. 4d–f and Supplementary Fig. 3 ) .
|
[
{
"end": 54,
"label": "CellType",
"start": 24,
"text": "disease-associated fibroblasts"
},
{
"end": 178,
"label": "CellType",
"start": 156,
"text": "fibroblast populations"
},
{
"end": 211,
"label": "Tissue",
"start": 191,
"text": "scarring risk stroma"
}
] |
Single_Cell
|
In keeping with scRNA-seq data (Fig. 4a ), F3: FRC-like fibroblasts were expanded in inflamed atopic dermatitis skin (low risk), without major myofibroblasts (Fig. 4d,f and Extended Data Fig. 6c ).
|
[
{
"end": 67,
"label": "CellType",
"start": 47,
"text": "FRC-like fibroblasts"
},
{
"end": 116,
"label": "Tissue",
"start": 85,
"text": "inflamed atopic dermatitis skin"
},
{
"end": 157,
"label": "CellType",
"start": 143,
"text": "myofibroblasts"
}
] |
Single_Cell
|
We localized the F3: FRC-like population to the superficial perivascular immune niche (Fig. 4d ), which we further validated using 10x Visium data (Extended Data Fig. 6d–f ).
|
[
{
"end": 40,
"label": "CellType",
"start": 21,
"text": "FRC-like population"
},
{
"end": 85,
"label": "Tissue",
"start": 48,
"text": "superficial perivascular immune niche"
}
] |
Single_Cell
|
In melanoma (scarring risk), aside from F1, the entire stroma comprised F6: inflammatory myofibroblasts and F7: myofibroblasts (Fig. 4e,f and Extended Data Fig. 6g ).
|
[
{
"end": 61,
"label": "Tissue",
"start": 55,
"text": "stroma"
},
{
"end": 126,
"label": "CellType",
"start": 112,
"text": "myofibroblasts"
},
{
"end": 103,
"label": "CellType",
"start": 76,
"text": "inflammatory myofibroblasts"
}
] |
Single_Cell
|
F7: myofibroblasts showed a matrix-producing phenotype ( COL1A1 , COL3A1 and POSTN ) that characterizes myofibroblastic cancer-associated fibroblasts (CAFs) (myoCAFs) .
|
[
{
"end": 18,
"label": "CellType",
"start": 4,
"text": "myofibroblasts"
},
{
"end": 149,
"label": "CellType",
"start": 104,
"text": "myofibroblastic cancer-associated fibroblasts"
},
{
"end": 155,
"label": "CellType",
"start": 151,
"text": "CAFs"
},
{
"end": 165,
"label": "CellType",
"start": 158,
"text": "myoCAFs"
}
] |
Single_Cell
|
F6: inflammatory myofibroblasts demonstrated high expression of inflammatory CAF (iCAF) marker genes ( MMP1 , MMP3 , CXCL8 and IL24 ), which was observed in both cancer and inflammatory diseases with scarring risk (Extended Data Fig. 6h,i ).
|
[
{
"end": 31,
"label": "CellType",
"start": 4,
"text": "inflammatory myofibroblasts"
}
] |
Single_Cell
|
Finally, to complement our analysis of fibroblast proportions by disease, we assessed transcriptomic variability of disease-associated fibroblast subtypes by calculating gene module scores for each disease using defined marker genes to define transcriptomic variability across different disease conditions (Fig. 4g and Methods ).
|
[
{
"end": 154,
"label": "CellType",
"start": 116,
"text": "disease-associated fibroblast subtypes"
}
] |
Single_Cell
|
The F6: inflammatory myofibroblast signature score was highest in hidradenitis suppurativa, acne and keratinocytic skin cancers.
|
[] |
Single_Cell
|
Overall, our findings support distinct stromal composition in skin diseases associated with differential scarring risk.
|
[] |
Single_Cell
|
F6: inflammatory myofibroblasts were observed in diseases with scarring risk but relatively infrequently observed in established fibrosis, raising the possibility that they may be an intermediate differentiation state toward F7: myofibroblasts.
|
[
{
"end": 243,
"label": "CellType",
"start": 229,
"text": "myofibroblasts"
},
{
"end": 31,
"label": "CellType",
"start": 4,
"text": "inflammatory myofibroblasts"
}
] |
Single_Cell
|
The differentiation process of healthy fibroblasts into myofibroblasts remains poorly understood in human tissues despite its clinical relevance.
|
[
{
"end": 70,
"label": "CellType",
"start": 56,
"text": "myofibroblasts"
},
{
"end": 50,
"label": "CellType",
"start": 31,
"text": "healthy fibroblasts"
},
{
"end": 113,
"label": "Tissue",
"start": 100,
"text": "human tissues"
}
] |
Single_Cell
|
Fibroblasts are tissue resident, and thus intermediate states of myofibroblast differentiation are likely to be captured in the molecular snapshots of skin diseases analyzed.
|
[
{
"end": 11,
"label": "CellType",
"start": 0,
"text": "Fibroblasts"
}
] |
Single_Cell
|
We therefore performed trajectory analysis of fibroblasts in diseased skin to gain further insights into myofibroblast differentiation, before utilizing time-resolved human wound data as a validation of dynamic changes in stromal composition.
|
[
{
"end": 57,
"label": "CellType",
"start": 46,
"text": "fibroblasts"
},
{
"end": 74,
"label": "Tissue",
"start": 61,
"text": "diseased skin"
}
] |
Single_Cell
|
We first included all fibroblast subtypes in a partition-based graph abstraction (PAGA) analysis (Extended Data Fig. 7a ), and then focused further analyses on fibroblast populations found across diseases on hair-bearing and hairless skin ( Methods ).
|
[
{
"end": 41,
"label": "CellType",
"start": 22,
"text": "fibroblast subtypes"
},
{
"end": 182,
"label": "CellType",
"start": 160,
"text": "fibroblast populations"
},
{
"end": 220,
"label": "Tissue",
"start": 208,
"text": "hair-bearing"
},
{
"end": 238,
"label": "Tissue",
"start": 225,
"text": "hairless skin"
}
] |
Single_Cell
|
F7: myofibroblasts were a terminally differentiated myofibroblast state (Fig. 5a–c ), consistent with their presence in established fibrosis.
|
[
{
"end": 18,
"label": "CellType",
"start": 4,
"text": "myofibroblasts"
},
{
"end": 71,
"label": "CellType",
"start": 26,
"text": "terminally differentiated myofibroblast state"
}
] |
Single_Cell
|
We observed two potential sources for F7: myofibroblasts in skin across analyses (Fig. 5b,c and Extended Data Fig. 7b ).
|
[
{
"end": 56,
"label": "CellType",
"start": 42,
"text": "myofibroblasts"
},
{
"end": 64,
"label": "Tissue",
"start": 60,
"text": "skin"
}
] |
Single_Cell
|
End of preview. Expand
in Data Studio
Proposed Active Learning Data split- V1
Overview
This dataset release represents a proposed and experimental data split designed specifically to support and validate planned active learning (AL) cycles for biomedical Named Entity Recognition (NER).
The current version is not a final benchmark split. Instead, it serves as an initial, controlled setup for testing active learning strategies, model uncertainty sampling, and iterative annotation workflows prior to large-scale development.
All splits (train,validation,test) have been carefully curated to ensure coverage of all three target entity types:
CellLine
CellType
Tissue
This balanced representation is critical for meaningful evaluation of active learning behavior across heterogeneous biomedical entities.
Dataset Structure
Each split contains the following fields:
- sentence: a single sentence extracted from a biomedical article
- entities: a list of entity annotations associated with the sentence
- data_source: the originating corpus or article collection from which the sentence was derived
Annotations are provided at the sentence level to facilitate downstream NER training, evaluation, and AL-driven re-annotation workflows
Data Sources and Composition
The dataset has been curated from three complementary biomedical domains, each contributing distinct entity distributions:
- Single-Cell transciptomics literature: High prevalence of CellType and Tissue entities
- ChembL assay desriptions: Enriched for CellLine mentions
- Stem-Cell research: Contains a mix of CellLine, CellType, and Tissue entities, significantly richer in CellType
ChEMBL Data Source: V1 vs V2
- ChEMBL-V1 (Silver Standard)
The ChEMBL-V1 dataset represents a silver-standard corpus generated during the early stages of the project using the following process:
- A curated dictionary was constructed by combining:
internal ChEMBL assay descriptions, and
IntAct curated CellLine terminology
Articles were retrieved from Europe PMC (EPMC) based on dictionary term mentions.
Retrieved texts were automatically annotated using a machine learning model trained specifically for CellLine recognition.
- ChEMBL-V2 (Gold Standard)
The ChEMBL-V2 dataset is a gold-standard corpus comprising 12 full-text biomedical articles that have been manually curated and annotated by domain experts.
Article selection was guided by two primary criteria:
High-frequency CellLine coverage — articles were chosen to maximise representation of the most commonly occurring CellLine entities observed in the broader corpus.
Journal diversity — articles were sampled across a diverse set of biomedical journals to reduce source-specific bias and improve generalisability.
Further details on the article selection and curation strategy can be found here
Stem Cell Article Source
The stem cell–related articles were collected from the CellFinder data repository. The creation and annotation methodology of the original CellFinder dataset are described in the following reference:
Mariana Neves, Alexander Damaschun, Andreas Kurtz, Ulf Leser (2012) Annotating and evaluating text for stem cell research. In Proceedings Third Workshop on Building and Evaluation Resources for Biomedical Text Mining (BioTxtM 2012), Language Resources and Evaluation (LREC) 2012.
Article PMCIDs and source
Train Set
| PMCID | In-Split | Source |
|---|---|---|
| PMC12479362 | train | Single-Cell |
| PMC12435838 | train | Single-Cell |
| PMC12081310 | train | Single-Cell |
| PMC11116453 | train | Single-Cell |
| PMC12408821 | train | Single-Cell |
| PMC12116388 | train | Single-Cell |
| PMC10968586 | train | CheMBL-V1 |
| PMC12819543 | train | CheMBL-V1 |
| PMC7642379 | train | CheMBL-V1 |
| PMC6889484 | train | CheMBL-V1 |
| PMC12101583 | train | CheMBL-V2 |
| PMC12072392 | train | CheMBL-V2 |
| PMC12115102 | train | CheMBL-V2 |
| PMC11641291 | train | CheMBL-V2 |
| PMC1315352 | train | CellFinder |
| PMC2041973 | train | CellFinder |
| PMC2238795 | train | CellFinder |
Validation Set
| PMCID | In-Split | Source |
|---|
Intended Use
Primary Use
- Supervised NER training for biomedical NLP tasks
Not Intended For
- Clinical or patient-level decision making
Notes and Limitations
This is an experimental split, subject to change.
Entity distributions may not reflect real-world prevalence.
Annotation density varies across domains by design
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