Back

Predictive targeting of mitochondrial metabolism in Acute Myeloid Leukemia patients with a lipoic acid analog

Reid, M. A.; Bose, S.; Pladna, K. M.; Anderson, R.; Mikhael, P. G.; Xiao, Z.; Dai, Z.; Liu, S.; Liu, J.; Pardee, T.; Locasale, J. W.

2021-06-04 oncology
10.1101/2021.06.03.21257935 medRxiv
Show abstract

Targeting metabolism has long been a theory for cancer therapy, but clinical development has been limited by toxicities, compound availability, overall efficacy, and patient specificity1. CPI-613, a lipoic acid analogue that interferes with enzymes involved in mitochondrial metabolism, has demonstrated clinical activity in lethal malignancies including relapsed or therapy refractory Acute Myeloid Leukemias (AMLs)2,3 and Phase III trials are ongoing1. Using metabolomics, we investigated blood and bone marrow samples from a cohort of 29 relapsed or refractory AML patients involved in Phase I and II studies undergoing CPI-613 treatment (NCT01768897, NCT02484391) including 13 that achieved a complete response. We show that CPI-613 treatment in patients induced defined alterations related to the tricarboxylic acid (TCA) cycle and associated redox, anabolic and catabolic metabolism. These findings are consistent with targeting of several ketoacid dehydrogenase (KADH) enzymes that use lipoic acid as a cofactor and are related to mitochondrial metabolism. The alterations were observed systemically but were more pronounced within the leukemic bone marrow microenvironment consistent with its mechanistic target. Machine learning revealed that metabolic status and changes associated with mitochondrial metabolism were predictive of treatment response, indicating that mechanism-based metabolite biomarkers to a targeted metabolic cancer therapy may be feasible. Finally, we confirm using isotope tracing and flux analysis that these effects are due to disruptions to substrate utilization into the mitochondria. Our findings provide evidence that a tolerated, anti-cancer therapeutic can act by targeting mitochondrial metabolism in humans.

Matching journals

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

1
Leukemia
39 papers in training set
Top 0.1%
18.1%
2
Nature Cancer
35 papers in training set
Top 0.1%
12.0%
3
Nature Communications
4913 papers in training set
Top 23%
8.2%
4
Clinical Cancer Research
58 papers in training set
Top 0.1%
8.0%
5
Blood Advances
54 papers in training set
Top 0.4%
4.2%
50% of probability mass above
6
Cancer Discovery
61 papers in training set
Top 0.4%
4.2%
7
Cancer Cell
38 papers in training set
Top 0.5%
3.5%
8
eLife
5422 papers in training set
Top 30%
3.0%
9
Nature
575 papers in training set
Top 8%
2.8%
10
Journal of Clinical Investigation
164 papers in training set
Top 2%
2.7%
11
Science Advances
1098 papers in training set
Top 11%
2.5%
12
Journal of Hematology & Oncology
10 papers in training set
Top 0.1%
1.8%
13
EMBO Molecular Medicine
85 papers in training set
Top 2%
1.7%
14
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 34%
1.6%
15
Haematologica
24 papers in training set
Top 0.3%
1.6%
16
Cancer Research
116 papers in training set
Top 2%
1.3%
17
Cell Reports
1338 papers in training set
Top 28%
1.2%
18
iScience
1063 papers in training set
Top 24%
1.1%
19
Cell Reports Medicine
140 papers in training set
Top 6%
0.9%
20
Nature Medicine
117 papers in training set
Top 4%
0.9%
21
Cell Chemical Biology
81 papers in training set
Top 3%
0.9%
22
Cancers
200 papers in training set
Top 4%
0.9%
23
npj Precision Oncology
48 papers in training set
Top 1%
0.9%
24
Scientific Reports
3102 papers in training set
Top 74%
0.8%
25
Cancer Letters
32 papers in training set
Top 0.8%
0.7%
26
Metabolites
50 papers in training set
Top 1%
0.7%
27
JCO Precision Oncology
14 papers in training set
Top 0.5%
0.6%
28
Nature Genetics
240 papers in training set
Top 9%
0.6%
29
Med
38 papers in training set
Top 1%
0.6%
30
Oncogene
76 papers in training set
Top 2%
0.6%