ECM Signatures Reveal Quiescent Stem Cell Diversity in the Colonic Niche
Hickey, S. E.; Andreatta, M.; Enright, C.; Boucrot, E.; Kiely, P.; Cashman, S.; Carmona, S. J.; McGourty, K.
Show abstract
Colonic stem cells have a key role in the continuous regeneration of a healthy intestinal epithelium. Despite considerable advances in single-cell omics technologies, the transcriptional heterogeneity of rare cell types such as colonic stem cells, as well as their functional states and niche-specific behaviors, remain poorly characterised. In this study, we leverage a meta-analysis of scRNA-seq and spatial transcriptomic datasets to comprehensively map the heterogeneity of colonic stem cells. We identify multiple, previously underappreciated stem cell states, including distinct quiescent subtypes marked by CDKN1A (P21), CDKN1B (P27), and CDKN1C (P57), proliferative populations defined by MKI67 (Ki67) and LRIG1, and a lineage-committed intermediate subpopulation expressing MUC2. Strikingly, we find that these states can be robustly identified solely by their extracellular matrix (ECM) gene expression signatures, revealing ECM composition as a critical determinant of stem cell identity. Notably, LAMA1 expression is highly specific to the P57+ quiescent population, linking laminin-mediated microenvironments to the active maintenance of deep quiescence, consistent with our recent findings associating LAMA1 with quiescent cell survival. By applying these ECM gene signatures, we delineate discrete "micro-niches" of quiescent stem cells in healthy tissue and provide evidence that analogous states persist in the colorectal cancer (CRC) environment. Extending our approach to an unrelated tissue, the pancreas, we detect parallel quiescent cell subtypes, illustrating the broader applicability of ECM-based signatures. Taken together, our findings redefine the concept of stem cell heterogeneity in the colon, establish ECM-driven gene signatures as a powerful tool for characterizing stem cell states, and offer new perspectives on the niche-dependent regulation of both healthy and cancerous stem cell populations.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Mapping and modeling human colorectal carcinoma interactions with the tumor microenvironment 96%
- Multiomic analysis reveals cellular and epigenetic plasticity in intestinal pouches of ulcerative colitis patients 96%
- Single-Cell RNA Sequencing Reveals the Effects of Chemotherapy on Human Pancreatic Adenocarcinoma and its Tumor Microenvironment 96%
Similar papers in this journal
- An iPSC-derived small intestine-on-chip with self-organizing epithelial, mesenchymal and neural cells 96%
- MAPK14/p38α Shapes the Molecular Landscape of Endometrial Cancer and promotes Tumorigenic Characteristics 95%
- A single cell framework identifies functionally and molecularly distinct multipotent progenitors in adult human hematopoiesis 94%
Similar papers in this journal
- JAK/STAT signaling promotes the emergence of unique cell states in ulcerative colitis 95%
- High resolution multi-scale profiling of embryonic germ cell-like cells derivation reveals pluripotent state transitions in humans 95%
- Developmental regulation of endothelial-to-hematopoietic transition from induced pluripotent stem cells 94%
Similar papers in this journal
- Detailed Survey of an in-vitro Intestinal Epithelium Model by Single-Cell Transcriptomics 95%
- Proximity and metabolic activity of the Tumour Microenvironment as predictors of survival in High Grade Serous Ovarian Cancer (HGSOC) 94%
- The transcriptional landscape of glycosylation-related genes in cancer 94%
Similar papers in this journal
- Molecular phenotyping of colorectal neoplasia shows dynamic and adaptive cancer stem cell population admixture 95%
- A stem cell zoo uncovers intracellular scaling of developmental tempo across mammals 93%
- Space-Time Mapping Identifies Concerted Multicellular Patterns and Gene Programs in Healing Wounds and their Conservation in Cancers 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.