Back

A metabolic crosstalk between liposarcoma and muscle sustains tumor growth

Manteaux, G.; Prieto Romero, J.; Gayte, L.; Riquier Morcant, B.; Amsel, A.; Jacq, S.; Cisse, M. Y.; Perot, G.; Chibon, F.; Pomies, P.; Firmin, N.; Carrere, S.; Riscal, R.; Linares, L. K.

2023-06-05 cancer biology
10.1101/2023.06.02.543362 bioRxiv
Show abstract

Dedifferentiated (DD-LPS) and Well-differentiated (WD-LPS) liposarcoma are characterized by a systematic amplification of the MDM2 oncogene. We recently demonstrated that p53-independent metabolic functions of chromatin-bound MDM2 (C-MDM2) are exacerbated in LPS and mediate an addiction to serine metabolism in order to sustain tumor growth. Here, we show that metabolic cooperation between LPS and distant muscle, which raise serine and glycine blood levels, is essential for LPS tumor growth. By releasing IL-6, tumor influence distant muscle to upregulate their serine synthesis machinery. Blocking IL-6 secretion or treating LPS cells with FDA approved IL-6 inhibitor, decreased serine production and impaired tumor proliferation. These data reveal IL-6 as a central tumorkine in metabolic crosstalk between tissues and identifies IL-6 as a plausible treatment for LPS patients.

Matching journals

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

1
Nature Communications
○ 5641 papers in training set
Top 6%
22.0%
Similar papers in this journal
2
Nature
○ 645 papers in training set
Top 0.9%
15.1%
Similar papers in this journal
3
Cancer Discovery
● 66 papers in training set
Top 0.4%
5.5%
Similar papers in this journal
4
Cancer Research
● 130 papers in training set
Top 0.8%
4.4%
Similar papers in this journal
5
Science Advances
● 1243 papers in training set
Top 7%
4.3%
Similar papers in this journal
50% of probability mass above
6
Cell Reports
○ 1498 papers in training set
Top 9%
4.3%
7
Cell Stem Cell
○ 62 papers in training set
Top 0.4%
4.1%
8
Nature Cancer
○ 39 papers in training set
Top 0.5%
3.4%
9
eLife
● 5828 papers in training set
Top 35%
3.2%
10
Cell Metabolism
○ 57 papers in training set
Top 0.5%
2.8%
11
Cell
○ 431 papers in training set
Top 4%
2.8%
12
Nature Cell Biology
○ 118 papers in training set
Top 1%
2.1%
13
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 27%
1.7%
14
Journal of Clinical Investigation
● 179 papers in training set
Top 4%
1.5%
15
Communications Biology
○ 993 papers in training set
Top 21%
1.1%
16
Developmental Cell
○ 196 papers in training set
Top 3%
1.1%
17
Science Translational Medicine
● 127 papers in training set
Top 2%
1.1%
18
Cell Research
○ 51 papers in training set
Top 0.8%
1.1%
19
Science
● 477 papers in training set
Top 8%
1.0%
20
Nature Genetics
○ 286 papers in training set
Top 4%
1.0%
21
EMBO Molecular Medicine
○ 95 papers in training set
Top 2%
0.8%
22
Molecular Cell
○ 350 papers in training set
Top 5%
0.8%
23
Nature Materials
○ 28 papers in training set
Top 0.5%
0.8%
24
Journal of Experimental Medicine
● 119 papers in training set
Top 3%
0.6%
25
Nature Metabolism
○ 69 papers in training set
Top 2%
0.6%
26
iScience
○ 1154 papers in training set
Top 40%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.