Back

Extracellular matrix guidance determines proteolytic and non-proteolytic cancer cell patterning

Beunk, L.; van Helvert, S.; Bekker, B.; Ran, L.; Kang, R.; Paulat, T.; Syga, S.; Deutsch, A.; Friedl, P.; Wolf, K.

2022-03-18 cancer biology
10.1101/2022.03.16.484647 bioRxiv
Show abstract

Metastatic tumor cell invasion into interstitial tissue is a mechanochemical process that responds to tissue cues and further involves proteolytic remodeling of the tumor stroma. How matrix density, tissue guidance and the ability of proteolytic tissue remodeling cooperate and determine decision-making of invading tumor cells in complex-structured three-dimensional (3D) tissue remains unclear. We here developed a collagen-based invasion assay containing a guiding interface of low collagen density adjacent to randomly organized 3D fibrillar lattice and examined the invasion of melanoma cells from multicellular spheroids in response to matrix density, guidance cues and collagenolysis. After 48 hours of culture, two invasion niches developed, (i) sheet-like collective migration along the interface and (ii) single cell- and strand-like invasion into randomly organized 3D matrix. High collagen density impeded migration into the random matrix, whereas migration along a high-density collagen interface was increased compared to the low-density matrix assay. In silico analysis predicted that facilitated interface migration in high-density matrix depended on physical guidance without collagen degradation, whereas migration into randomly organized matrix was strongly dependent on collagenolysis. When tested in 3D culture, inhibition of matrix metalloprotease (MMP)-mediated collagen degradation compromised migration into random matrix in dependence of density, whereas interface-guided migration remained effective. In conclusion, with increasing tissue density, matrix cues bordered by dense matrix, but not randomly organized matrix, support effective MMP-independent migration. This identifies the topology of interstitial tissue a primary determinant of switch behaviors between MMP-dependent and MMP-independent cancer cell invasion.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

1
Scientific Reports
3102 papers in training set
Top 7%
10.0%
2
PLOS Computational Biology
1633 papers in training set
Top 4%
8.4%
3
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 0.7%
6.3%
4
Experimental Cell Research
24 papers in training set
Top 0.1%
4.1%
5
eLife
5422 papers in training set
Top 26%
3.6%
6
Advanced Science
249 papers in training set
Top 6%
3.6%
7
PLOS ONE
4510 papers in training set
Top 40%
3.6%
8
Cancers
200 papers in training set
Top 2%
3.1%
9
iScience
1063 papers in training set
Top 10%
2.1%
10
Computational and Structural Biotechnology Journal
216 papers in training set
Top 3%
2.1%
11
Communications Biology
886 papers in training set
Top 6%
1.9%
12
Cells
232 papers in training set
Top 2%
1.9%
50% of probability mass above
13
Evolutionary Applications
91 papers in training set
Top 0.6%
1.7%
14
Cell Communication and Signaling
35 papers in training set
Top 0.4%
1.7%
15
The FASEB Journal
175 papers in training set
Top 1%
1.7%
16
PeerJ
261 papers in training set
Top 7%
1.7%
17
npj Biofilms and Microbiomes
56 papers in training set
Top 1%
1.7%
18
Cell Death & Disease
126 papers in training set
Top 1%
1.7%
19
Integrative Biology
13 papers in training set
Top 0.1%
1.7%
20
International Journal of Cancer
42 papers in training set
Top 0.7%
1.5%
21
Cancer Research
116 papers in training set
Top 2%
1.5%
22
Cellular and Molecular Bioengineering
21 papers in training set
Top 0.1%
1.5%
23
Journal of Biological Chemistry
641 papers in training set
Top 2%
1.3%
24
APL Bioengineering
18 papers in training set
Top 0.2%
1.3%
25
Cell Death Discovery
51 papers in training set
Top 0.9%
1.2%
26
International Journal of Biological Macromolecules
65 papers in training set
Top 2%
1.2%
27
Nature Communications
4913 papers in training set
Top 56%
1.2%
28
Physical Biology
43 papers in training set
Top 2%
1.1%
29
European Journal of Cell Biology
14 papers in training set
Top 0.1%
0.9%
30
Biomaterials
78 papers in training set
Top 0.9%
0.9%