Back

Endothelial Cell Autophagy Suppresses Metastasis In Mouse Mammary and Pancreatic Neuroendocrine Tumor Models

Leon-Rivera, N.; Chin, B.; Quintana, A.; Eguiguren, S. B.; Gacasan, A. C.; Nanni, M.; Debnath, J.; Monkkonen, T.

2026-01-29 cancer biology
10.64898/2026.01.28.702341 bioRxiv
Show abstract

Autophagy, a key lysosomal degradation pathway regulating metabolic adaptation in cancer, plays fundamental roles in both the tumor and host stromal compartments during cancer progression. An important unanswered question is whether and how autophagy in specific host stromal elements, such as endothelial cells, influences metastasis. Here, we scrutinize how the genetic loss of autophagy in endothelial cells impacts primary tumor progression and metastasis in the Polyoma Middle T (PyMT) model of luminal B breast cancer. In both autochthonous and orthotopic mammary transplant models, PyMT primary tumor growth is significantly delayed upon endothelial cell Atg12 or Atg5 genetic deletion (Atg12 or 5 ECKO), which correlates with increased tumor cell apoptosis and HIF1 activation. In contrast, PyMT-bearing Atg12 ECKO mice exhibit increased metastasis, as well as higher rates of primary tumor and lung metastatic recurrence following surgical resection of PyMT primary tumors. Experimental metastasis assays further corroborate that loss of endothelial cell autophagy in Atg12 ECKO host animals promotes PyMT metastatic colonization and outgrowth, resulting in increased lung metastases compared to controls. Similarly, in the Rat Insulin Promoter T antigen pancreatic neuroendocrine tumor (RT2-PNET) model, endothelial cell deletion of Atg12 promotes liver micro-metastases. Taken together, these results from distinct preclinical cancer models reveal that endothelial cell autophagy suppresses metastatic seeding and progression and broach that autophagy inhibition in host endothelial cells may adversely influence the efficacy of systemic autophagy-lysosomal pathway inhibition in the clinical oncology setting.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Oncogene
76 papers in training set
Top 0.1%
18.3%
2
Cancer Research
116 papers in training set
Top 0.2%
7.0%
3
Cancers
200 papers in training set
Top 0.9%
6.2%
4
Journal for ImmunoTherapy of Cancer
64 papers in training set
Top 0.3%
4.8%
5
Molecular Cancer Therapeutics
33 papers in training set
Top 0.1%
4.2%
6
Clinical Cancer Research
58 papers in training set
Top 0.4%
3.9%
7
Cancer Letters
32 papers in training set
Top 0.1%
3.9%
8
Cell Reports
1338 papers in training set
Top 15%
3.6%
50% of probability mass above
9
Cancer Research Communications
46 papers in training set
Top 0.1%
3.5%
10
eLife
5422 papers in training set
Top 30%
3.0%
11
Journal of Clinical Investigation
164 papers in training set
Top 1%
2.8%
12
Nature Communications
4913 papers in training set
Top 44%
2.7%
13
Molecular Oncology
50 papers in training set
Top 0.3%
1.9%
14
BMC Cancer
52 papers in training set
Top 1%
1.7%
15
JCI Insight
241 papers in training set
Top 4%
1.6%
16
Molecular Cancer Research
42 papers in training set
Top 0.3%
1.6%
17
Journal of Experimental & Clinical Cancer Research
25 papers in training set
Top 0.1%
1.6%
18
Frontiers in Oncology
95 papers in training set
Top 2%
1.5%
19
British Journal of Cancer
42 papers in training set
Top 1.0%
1.5%
20
Cancer Immunology, Immunotherapy
11 papers in training set
Top 0.2%
1.3%
21
Cancer Discovery
61 papers in training set
Top 2%
0.9%
22
Journal of Experimental Medicine
106 papers in training set
Top 3%
0.9%
23
Nature Cancer
35 papers in training set
Top 1%
0.9%
24
International Journal of Cancer
42 papers in training set
Top 1%
0.9%
25
Neoplasia
22 papers in training set
Top 0.5%
0.9%
26
Cell Death & Disease
126 papers in training set
Top 2%
0.8%
27
Translational Oncology
18 papers in training set
Top 0.4%
0.8%
28
Gastroenterology
40 papers in training set
Top 2%
0.8%
29
Cancer Immunology Research
34 papers in training set
Top 0.5%
0.7%
30
Neuro-Oncology
30 papers in training set
Top 0.8%
0.7%