Peer review of: Using arterial–venous analysis to characterize cancer metabolic consumption in patients (2020)

Reviewers' comments: 

Reviewer #1 (Remarks to the Author): Expert in metabolomics 

In this manuscript entitled "Using arterial-venous analysis to characterize cancer metabolic 
consumption in patients", Xiong and colleagues performed metabolomics analyses of the blood 
from arteries and veins surrounding brain tumours in humans. They compare these analyses to 
peripheral blood in the foot. 

This report is to my knowledge the first to present arterial-venous metabolomics analyses in 
human patients. However, apart from this aspect, the paper falls short in providing any biological 
or clinical relevance, critically reducing the impact of the work. Also, several of the metabolites 
presented in the heatmaps and VIP score graph do not have established biological functions, 
further limiting the relevance of the findings. In its current form, this work appears more 
appropriate for a more specialised journal. 

Reviewer #2 (Remarks to the Author): Expert in metabolomics 

The manuscript “Using arterial-venous analysis to characterize cancer metabolic consumption in 
patients” provides blood metabolome data of artery and vein around human glioma, which is rare 
and highly valuable for cancer metabolism. Some quantitative methods like principle components 
analysis (PCA) are utilized to cluster the data. This study shows those metabolites uniquely 
produced and consumed by gliomas. Generally this manuscript provides some informative results 
and will be valuable to the cancer metabolism community. Nevertheless, some questions in data 
processing and interpretation need to be addressed. Most importantly more mathematical rigor is 
needed especially regarding the definition of the VIP scores. 

(0) The abstract needs much more detail. 
(1) The variation of metabolites are reflected by VIP score. However, there is no rigorous definition 
nor clear explanation of VIP score. In Methods part, only “VIP scores > 1 between groups were 
considered as significantly discriminating” is mentioned. However, what does VIP scores reflect? Is 
it non-negative? Is it dimensionless? Will it bias some high-concentration metabolite (such as 
glucose)? As a metric of variation, those properties may largely affect its reliability and 
applicability, and therefore should be explained in detail to readers. 

(2) One of the main conclusions is unique metabolites produced or consumed by glioma compared 
to pedal tissue. Therefore, a rigorous definition of “unique” should be introduced. For instance, 
supplement figure 2 displays VIP scores between glioma vein and pedal vein, but requires a 
intuitive explanation for those statistics. Readers need to know what’s the clear criteria of “unique 
metabolites”. 

(3) Some confusing points are in figure 2: figure 2C shows each metabolite has one VIP score, and 
they are all positive, but figure 2D shows each metabolite has two VIP scores for artery and vein, 
and some of them are negative. Their scales are also different. I guess it is because PCA is 
executed on different data set. In 2C PCA is done in total data set and in 2D PCA is down 
separately in artery and vein for each metabolite. These different protocols on data processing 
should be clearly explained to readers. Furthermore, two columns in heatmap in figure 2D seems 
to be exactly opposite. The meaning of this subfigure requires more explanation. 

(4) Some confusing points are in supplement figure 1 and 2: similar with comment #(3), they 
have different VIP scores in different subplots. Furthermore, heatmaps in supplement figure 1D 
and 2D look very strange. Those heatmaps seem to be binary. What information do they express? 

Reviewer #3 (Remarks to the Author): Expert in glioma surgery 

In their manuscript entitled “Using arterial-venous analysis to characterize cancer metabolic 
consumption in patients” Xiong and colleagues provide insight into the metabolic properties of 
gliomas through a comparison of metabolites within arterial and venous blood associated with 
human gliomas. I have been a reviewer for over one hundred manuscripts in my career. This is 
easily one of the most interesting and bold experimental designs I have encountered. I have a 
strong bias towards the publication of this paper for this reason alone. I think the data are 
extraordinarily valuable because of the rigor of the experimental design and they are hard to argue 
with. I can think of no better way to study the key elements of human glioma metabolism. 
Therefore, I think the results will be of high value to the field. 

In glioma biology and in the care of glioma patients the IDH mutation is central. I was surprised in 
reading this manuscript- which certainly contains IDH mutant and wild-type tumors that the 
authors did not evaluate the upstream and downstream concentrations of 2HG. I view this as an 
essential internal control for their methodology. As there is no physiologic source of 2HG in the 
body, 2HG should be low in arterial blood and high in venous blood in an IDH mutant tumor. In 
IDH wild-type tumors the concentration of 2HG should not vary between arterial and venous 
blood- and may not be detectable. To me, including a detailed analysis of 2HG in the collected 
samples is essential. Without this, I think the authors are missing a key control. With 2HG 
measurements that make sense, I think the authors will greatly improve the acceptance of the 
other metabolic results they provide.