Biology subjects

Kiemen, A.

Publications and source records attributed to Kiemen, A..

4 recordsLinked to original sources

bioRxiv2023

Mechano-induced homotypic patterned domain formation by monocytes

Matrix stiffness and corresponding mechano-signaling play indispensable roles in cellular phenotypes and functions. How tissue stiffness influences the behavior of monocytes, a major circulating leukocyte of the innate system, and how it may promote the emergence of collective cell behavior is less understood. Here, using tunable collagen-coated hydrogels of physiological stiffness, we show that human primary monocytes undergo a dynamic local phase separation to form highly patterned multicellular multi-layered domains on soft matrix. Local activation of the {beta}2 integrin initiates inter-cellular adhesion, while global soluble inhibitory factors maintain the steady-state domain pattern over days. Patterned domain formation generated by monocytes is unique among other key immune cells, including macrophages, B cells, T cells, and NK cells. While inhibiting their phagocytic capability, domain formation promotes monocytes survival. We develop a computational model based on the Cahn-Hilliard equation, which includes combined local activation and global inhibition mechanisms of intercellular adhesion suggested by our experiments, and provides experimentally validated predictions of the role of seeding density and both chemotactic and random cell migration on pattern formation.

biophysics↗

bioRxiv2023

Precision-engineered biomimetics: the human fallopian tube

The fallopian tube has an essential role in several physiological and pathological processes from pregnancy to ovarian cancer. However, there are no biologically relevant models to study its pathophysiology. The state-of-the-art organoid model has been compared to two-dimensional tissue sections and molecularly assessed providing only cursory analyses of the models accuracy. We developed a novel multi-compartment organoid model of the human fallopian tube that was meticulously tuned to reflect the compartmentalization and heterogeneity of the tissues composition. We validated this organoids molecular expression patterns, cilia-driven transport function, and structural accuracy through a highly iterative platform wherein organoids are compared to a three-dimensional, single-cell resolution reference map of a healthy, transplantation-quality human fallopian tube. This organoid model was precision-engineered to match the human microanatomy. One sentence summaryTunable organoid modeling and CODA architectural quantification in tandem help design a tissue-validated organoid model.

bioengineering↗

bioRxiv2020

Deep Learning Identification of Stiffness Markers in Breast Cancer

While essential to our understanding of solid tumor progression, the study of cell and tissue mechanics has yet to find traction in the clinic. Determining tissue stiffness, a mechanical property known to promote a malignant phenotype in vitro and in vivo, is not part of the standard algorithm for the diagnosis and treatment of breast cancer. Instead, clinicians routinely use mammograms to identify malignant lesions and radiographically dense breast tissue is associated with an increased risk of developing cancer. Whether breast density is related to tumor tissue stiffness, and what cellular and non-cellular components of the tumor contribute the most to its stiffness are not well understood. Through training of a deep learning network and mechanical measurements of fresh patient tissue, we create a bridge in understanding between clinical and mechanical markers. The automatic identification of cellular and extracellular features from hematoxylin and eosin (H&E)-stained slides reveals that global and local breast tissue stiffness best correlate with the percentage of straight collagen. Global breast tissue mechanics correlate weakly with the percentage of blood vessels and fibrotic tissue, and non-significantly with the percentage of fat, ducts, tumor cells, and wavy collagen in tissue. Importantly, the percentage of dense breast tissue does not directly correlate with tissue stiffness or straight collagen content.

cancer biology↗

bioRxiv2020

Multi-compartment tumor organoids

Organoid cultures are widely used because they preserve many features of cancer cells in vivo. Here, we developed high-throughput oil-in-water droplet microtechnology to generate highly uniform, small-volume, multi-compartment organoids. Each organoid culture features a microenvironmental architecture that mimics both the basement membrane and stromal barriers. This matrix architecture, which allows accessing both proliferative and invasive features of cancer cells in a single platform, has profound effect on observed drug responsiveness and tumor progression that correlate well with in vivo and clinical outcomes. The method was tested on multiple types of cancer cells including primary cells and immortalized cell lines, and we determined our platform is suitable even for cells of poor organoid-forming ability. These new organoids also allow for direct orthotopic mouse implantation of cancer cells with unprecedented success.

cancer biology↗