Back

Elevated arginine levels in liver tumors promote metabolic reprogramming and tumor growth

Mossmann, D.; Park, S.; Ryback, B.; Weissenberger, D.; Colombi, M.; Hindupur, S. K.; Dazert, E.; Coto-Llerena, M.; Caner, E.; Cenzano, V. J.; Piscuoglio, S.; Bosch, F.; Terracciano, L. M.; Sauer, U.; Hall, M. N.

2022-04-27 cancer biology
10.1101/2022.04.26.489545 bioRxiv
Show abstract

Arginine auxotropy, due to reduced expression of urea cycle genes, is common in cancer. However, little is known about the levels of arginine in these cancers. Here, we report that arginine levels are elevated in hepatocellular carcinoma (HCC) despite reduced expression of urea cycle enzymes. Liver tumors accumulate high levels specifically of arginine via increased uptake and, more importantly, via suppression of arginine-to-polyamine conversion due to reduced arginase 1 (ARG1) and agmatinase (AGMAT) expression. Furthermore, the high levels of arginine are required for tumor growth. Mechanistically, high levels of arginine promote tumorigenesis via transcriptional regulation of metabolic genes, including upregulation of asparagine synthetase (ASNS). ASNS-derived asparagine further enhances arginine uptake, creating a positive feedback loop to sustain high arginine levels and oncogenic metabolism. Thus, arginine is a novel second messenger-like molecule that reprograms metabolism to promote tumor growth.

Matching journals

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

1
eLife
● 5828 papers in training set
Top 8%
11.6%
Similar papers in this journal
2
Nature Communications
○ 5641 papers in training set
Top 22%
7.7%
Similar papers in this journal
3
Cancer Research
● 130 papers in training set
Top 0.4%
6.5%
Similar papers in this journal
4
Hepatology
○ 22 papers in training set
Top 0.1%
6.5%
Similar papers in this journal
5
Cancer Discovery
● 66 papers in training set
Top 0.4%
6.1%
Similar papers in this journal
6
Cell Reports
○ 1498 papers in training set
Top 7%
5.4%
7
Science Advances
● 1243 papers in training set
Top 5%
5.3%
8
Cellular and Molecular Gastroenterology and Hepatology
○ 46 papers in training set
Top 0.3%
4.2%
50% of probability mass above
9
Gastroenterology
○ 42 papers in training set
Top 0.2%
4.2%
10
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 17%
3.2%
11
Science
● 477 papers in training set
Top 3%
2.7%
12
Gut
● 40 papers in training set
Top 0.3%
2.7%
13
Nature
○ 645 papers in training set
Top 6%
2.3%
14
Journal of Clinical Investigation
● 179 papers in training set
Top 3%
2.1%
15
Journal of Hepatology
○ 21 papers in training set
Top 0.2%
1.9%
16
Cell
○ 431 papers in training set
Top 6%
1.7%
17
JCI Insight
● 277 papers in training set
Top 5%
1.5%
18
iScience
○ 1154 papers in training set
Top 22%
1.5%
19
Hepatology Communications
○ 22 papers in training set
Top 0.3%
1.3%
20
Cell Stem Cell
○ 62 papers in training set
Top 1%
1.1%
21
Genome Medicine
○ 183 papers in training set
Top 4%
1.1%
22
JHEP Reports
○ 11 papers in training set
Top 0.2%
1.1%
23
Journal of Experimental Medicine
● 119 papers in training set
Top 3%
0.9%
24
Cell Genomics
○ 172 papers in training set
Top 5%
0.8%
25
Molecular Cell
○ 350 papers in training set
Top 5%
0.8%
26
Developmental Cell
○ 196 papers in training set
Top 4%
0.8%
27
Cell Reports Medicine
○ 153 papers in training set
Top 6%
0.6%
28
Nature Cell Biology
○ 118 papers in training set
Top 4%
0.6%
29
Cell Metabolism
○ 57 papers in training set
Top 2%
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.