Organoid Culture of Human Cancer Stem Cells.
Methods in molecular biology (Clifton, N.J.)
Organoid culture is a three-dimensional culture method that enables ex vivo analysis of stem cell behavior and differentiation. This method is also applicable to the studies on stem cell characters of human cancer stem cells. The components of organoid culture include Matrigel® and a culture medium containing growth factor cocktails that mimic the microenvironments of organ stem cell niches. Here, we describe the basic methods for the organoid culture of dissociated or FACS-sorted human cancer stem cells. Then, we introduce a method to dissociate the organoids for serial passage and propagation.
View details for PubMedID 27654995
A cell-intrinsic role for TLR2-MYD88 in intestinal and breast epithelia and oncogenesis.
Nature cell biology
2014; 16 (12): 1238-1248
It has been postulated that there is a link between inflammation and cancer. Here we describe a role for cell-intrinsic toll-like receptor-2 (TLR2; which is involved in inflammatory response) signalling in normal intestinal and mammary epithelial cells and oncogenesis. The downstream effectors of TLR2 are expressed by normal intestinal and mammary epithelia, including the stem/progenitor cells. Deletion of MYD88 or TLR2 in the intestinal epithelium markedly reduces DSS-induced colitis regeneration and spontaneous tumour development in mice. Limiting dilution transplantations of breast epithelial cells devoid of TLR2 or MYD88 revealed a significant decrease in mammary repopulating unit frequency compared with the control. Inhibition of TLR2, its co-receptor CD14, or its downstream targets MYD88 and IRAK1 inhibits growth of human breast cancers in vitro and in vivo. These results suggest that inhibitors of the TLR2 pathway merit investigation as possible therapeutic and chemoprevention agents.
View details for DOI 10.1038/ncb3058
View details for PubMedID 25362351
Migration of cells in a social context
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2013; 110 (1): 129-134
In multicellular organisms and complex ecosystems, cells migrate in a social context. Whereas this is essential for the basic processes of life, the influence of neighboring cells on the individual remains poorly understood. Previous work on isolated cells has observed a stereotypical migratory behavior characterized by short-time directional persistence with long-time random movement. We discovered a much richer dynamic in the social context, with significant variations in directionality, displacement, and speed, which are all modulated by local cell density. We developed a mathematical model based on the experimentally identified "cellular traffic rules" and basic physics that revealed that these emergent behaviors are caused by the interplay of single-cell properties and intercellular interactions, the latter being dominated by a pseudopod formation bias mediated by secreted chemicals and pseudopod collapse following collisions. The model demonstrates how aspects of complex biology can be explained by simple rules of physics and constitutes a rapid test bed for future studies of collective migration of individual cells.
View details for DOI 10.1073/pnas.1204291110
View details for Web of Science ID 000313630300038
View details for PubMedID 23251032
View details for PubMedCentralID PMC3538227
Single-cell dissection of transcriptional heterogeneity in human colon tumors
2011; 29 (12): 1120-U11
Cancer is often viewed as a caricature of normal developmental processes, but the extent to which its cellular heterogeneity truly recapitulates multilineage differentiation processes of normal tissues remains unknown. Here we implement single-cell PCR gene-expression analysis to dissect the cellular composition of primary human normal colon and colon cancer epithelia. We show that human colon cancer tissues contain distinct cell populations whose transcriptional identities mirror those of the different cellular lineages of normal colon. By creating monoclonal tumor xenografts from injection of a single (n = 1) cell, we demonstrate that the transcriptional diversity of cancer tissues is largely explained by in vivo multilineage differentiation and not only by clonal genetic heterogeneity. Finally, we show that the different gene-expression programs linked to multilineage differentiation are strongly associated with patient survival. We develop two-gene classifier systems (KRT20 versus CA1, MS4A12, CD177, SLC26A3) that predict clinical outcomes with hazard ratios superior to those of pathological grade and comparable to those of microarray-derived multigene expression signatures.
View details for DOI 10.1038/nbt.2038
View details for PubMedID 22081019