Back

Biomimetic 3D mammary duct models of healthy and tumoral tissues engineered by a co-extrusion microfluidic based technology

RICHARD, A.; BERGERON, V.; BOYREAU, A.; DUMOUSSET, D.; Mazari-Arrighi, E.; Recher, G.; ALBIGES-RIZO, C.; NASSOY, P.; Andrique, L.

2026-04-16 bioengineering
10.64898/2026.04.14.718212 bioRxiv
Show abstract

Engineering the human breast in 3D physio-mimetic models is challenging due to its complex multilayered tubular organization, where milk is produced in acini and transported through ductal structures. These functions rely on a highly organized architecture comprising stromal, epithelial, and extracellular matrix compartments. The dysregulation of this architecture perturbs mammary gland homeostasis and promotes the emergence of diverse breast cancer subtypes, from frequent in situ luminal to rarer metastatic basal-like tumors. Despite this knowledge, conventional anti-cancer drug testing still primarily employs high-throughput 3D spheroid models that account for diffusion but lack stromal components, thereby failing to capture stroma-driven treatment resistance. With a unique microfluidic co-extrusion platform, we have developed 3D tubular tissues anchored on a porous and biocompatible alginate shell. Using a one-step protocol, we have bioengineered six relevant ductoid models of healthy and tumoral mammary ducts, most notably a multi-layered model comprising a lumen, mammary epithelium, and stromal compartment made of fibroblasts and matrixes. These new models offer limitless applications in tissue engineering including the characterization of an epithelium and its secretory function, and the identification of the stromal influence on healthy and tumoral mammary gland tissue. Finally, by releasing mechanical constraints, we scale-up the tubular duct model into a mammary assembloid that exhibits branching and budding of acini-like structures from the original duct. We envision that this modular design will broadly impact breast basic and clinical research by opening new experimental avenues toward more physio-mimetic tools through the integration of stromal compartments.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Advanced Science
249 papers in training set
Top 0.5%
14.9%
2
Advanced Healthcare Materials
71 papers in training set
Top 0.1%
12.6%
3
Advanced Materials
53 papers in training set
Top 0.2%
10.6%
4
Lab on a Chip
88 papers in training set
Top 0.2%
8.5%
5
Advanced Functional Materials
41 papers in training set
Top 0.4%
7.3%
50% of probability mass above
6
Biofabrication
32 papers in training set
Top 0.1%
6.9%
7
Nature Communications
4913 papers in training set
Top 33%
4.9%
8
Science Advances
1098 papers in training set
Top 5%
3.6%
9
Biomaterials
78 papers in training set
Top 0.3%
2.8%
10
Advanced Materials Technologies
27 papers in training set
Top 0.2%
2.1%
11
Small
70 papers in training set
Top 0.5%
1.7%
12
Bioengineering & Translational Medicine
21 papers in training set
Top 0.4%
1.7%
13
Cell Systems
167 papers in training set
Top 9%
1.3%
14
APL Bioengineering
18 papers in training set
Top 0.2%
1.3%
15
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 38%
1.2%
16
Small Methods
26 papers in training set
Top 0.7%
1.0%
17
Bioactive Materials
18 papers in training set
Top 0.6%
0.9%
18
Scientific Reports
3102 papers in training set
Top 70%
0.9%
19
Materials Today Bio
18 papers in training set
Top 0.6%
0.7%
20
iScience
1063 papers in training set
Top 34%
0.7%
21
ACS Synthetic Biology
256 papers in training set
Top 3%
0.7%
22
Nature Biomedical Engineering
42 papers in training set
Top 2%
0.7%
23
ACS Nano
99 papers in training set
Top 4%
0.7%
24
ACS Biomaterials Science & Engineering
37 papers in training set
Top 1%
0.7%
25
Nature Materials
21 papers in training set
Top 1%
0.5%
26
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 4%
0.5%
27
Acta Biomaterialia
85 papers in training set
Top 1%
0.5%
28
Disease Models & Mechanisms
119 papers in training set
Top 4%
0.5%