Back

Probing intratumoral metabolic compartmentalisation in fumarate hydratase-deficient renal cancer using clinical hyperpolarised 13C-MRI and mass spectrometry imaging

Horvat-Menih, I.; Casey, R.; Denholm, J.; Hamm, G.; Hulme, H.; Gallon, J.; Khan, A. S.; Kaggie, J.; Gill, A. B.; Priest, A. N.; Duarte, J. A. G.; Yong, C.; Brodie, C.; Whitworth, J.; Barry, S. T.; Goodwin, R. J. A.; Anand, S.; Dodd, M.; Honan, K.; Welsh, S. J.; Warren, A. Y.; Aho, T.; Stewart, G. D.; Mitchell, T. J.; McLean, M. A.; Gallagher, F. A.

2024-05-08 radiology and imaging
10.1101/2024.05.06.24306817 medRxiv
Show abstract

BackgroundFumarate hydratase-deficient renal cell carcinoma (FHd-RCC) is a rare and aggressive renal cancer subtype characterised by increased fumarate accumulation and upregulated lactate production. Renal tumours demonstrate significant intratumoral metabolic heterogeneity, which may contribute to treatment failure. Emerging non-invasive metabolic imaging techniques have clinical potential to more accurately phenotype tumour metabolism and its heterogeneity. MethodsHere we have used hyperpolarised 13C-pyruvate MRI (HP 13C-MRI) to assess 13C-lactate generation in a patient with an organ-confined FHd-RCC. Post-operative tissue samples were co-registered with imaging and underwent sequencing, IHC staining, and mass spectrometry imaging (MSI). ResultsHP 13C-MRI revealed two metabolically distinct tumour regions. The 13C-lactate-rich region showed a high lactate/pyruvate ratio and slightly lower fumarate on MSI compared to the other tumour region, as well as increased CD8+ T cell infiltration, and genetic dedifferentiation. Compared to the normal kidney, vascularity in tumour was decreased, while immune cell fraction was markedly higher. ConclusionsThis study shows the potential of metabolic HP 13C-MRI to characterise FHd-RCC and how targeting of biopsies to regions of metabolic dysregulation could be used to obtain the tumour samples of greatest clinical significance, which in turn can inform on early and successful response to treatment.

Matching journals

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

1
eBioMedicine
130 papers in training set
Top 0.1%
15.2%
2
Scientific Reports
3102 papers in training set
Top 2%
15.2%
3
Frontiers in Oncology
95 papers in training set
Top 0.5%
6.5%
4
Frontiers in Endocrinology
53 papers in training set
Top 0.5%
3.7%
5
Diagnostics
48 papers in training set
Top 0.5%
3.4%
6
Kidney International
25 papers in training set
Top 0.2%
3.2%
7
Kidney360
22 papers in training set
Top 0.3%
2.8%
8
PLOS ONE
4510 papers in training set
Top 44%
2.7%
50% of probability mass above
9
European Journal of Nuclear Medicine and Molecular Imaging
19 papers in training set
Top 0.1%
2.4%
10
Nature Communications
4913 papers in training set
Top 46%
2.2%
11
Neuro-Oncology Advances
24 papers in training set
Top 0.2%
1.9%
12
Frontiers in Physiology
93 papers in training set
Top 3%
1.7%
13
BMC Medicine
163 papers in training set
Top 3%
1.7%
14
Transplantation
13 papers in training set
Top 0.2%
1.7%
15
Analytical Biochemistry
26 papers in training set
Top 0.1%
1.7%
16
Cancers
200 papers in training set
Top 3%
1.5%
17
Journal of Magnetic Resonance Imaging
14 papers in training set
Top 0.4%
1.5%
18
Kidney International Reports
14 papers in training set
Top 0.2%
1.1%
19
Laboratory Investigation
13 papers in training set
Top 0.1%
1.1%
20
Journal of Medical Imaging
11 papers in training set
Top 0.2%
1.0%
21
JCO Precision Oncology
14 papers in training set
Top 0.3%
0.9%
22
Diabetologia
36 papers in training set
Top 0.8%
0.9%
23
The Lancet Digital Health
25 papers in training set
Top 0.8%
0.9%
24
JAMA Network Open
127 papers in training set
Top 3%
0.9%
25
American Journal of Transplantation
15 papers in training set
Top 0.1%
0.9%
26
Cells
232 papers in training set
Top 5%
0.9%
27
Journal of the American Society of Nephrology
52 papers in training set
Top 0.5%
0.9%
28
Cytometry Part A
30 papers in training set
Top 0.2%
0.9%
29
International Journal of Radiation Oncology*Biology*Physics
21 papers in training set
Top 0.4%
0.8%
30
Photoacoustics
11 papers in training set
Top 0.4%
0.8%