Peer review of: Purine metabolism regulates DNA repair and therapy resistance in glioblastoma (2020)

Reviewer #1 (Remarks to the Author); expert on GBM, mouse models and radioresistance: 

As an approach to overcoming the presumed intra-tumor heterogeneity in radiosensitivity existing 
in GBMs, this manuscript investigates purine synthesis as a determinant of GBM radioresistance. 
Towards this end, a panel of 23 established GBM cell lines are ranked according to their in vitro 
radiosensitivity as determined by clonogenic assay and subjected to metabolic analysis, which 
suggested that purines were related to GBM radioresistance. Inhibition of purine synthesis using 
mycophenolic acid (MPA) was shown to enhance radiosensitivity and replacement with exogenous 
nucleotides was shown to abrogate the radiosensitization. Similar results were obtained using 2 
patient-derived GBM neurosphere cultures. In vivo experiments were then performed using flank 
xenografts grown from a GBM cell line and the neurospheres. Based on the data presented, the 
authors concluded that purine synthesis mediates the radioresistance of GBM and propose a 
clinical trial combining an MPA derivative and radiotherapy. However, there are a number of 
experimental deficiencies in this study (see below). Moreover, the relevance of the established cell 
lines to the biology/radiobiology of GBMs can be questioned. While the in vitro studies are aided by 
the addition of the 2 neurosphere cultures, all in vivo experiments are performed using flank 
xenografts, which do not account for the unique circumstances of brain microenvironment. The 
absence of an orthotopic model system questions the relevance of these results to GBMs and their 
therapy. 
Fig.1. The basis for the ranking of radiosensitivity among the established cell lines (1A) is unclear. 
It appears that for the majority of lines there is no statistically significant difference in Dmid. 
Whereas it seems reasonable to focus subsequent experiments on cell lines on the extremes of the 
measurement, the Dmid ranking does not appear to correspond to the actual survival curves 
shown for “sensitive” lines in figure 5. That is, U118MG, DBTRG-05MG and GB-1 are classified as 
sensitive according to Dmid, yet 6Gy results in a surviving fraction of 0.2 in U118MG (similar to 
U87 and A172, which are classified as resistant – figure 5), and almost 0.01 in the other 2 lines. In 
figure 1D, it is stated that 2 resistant and 2 sensitive lines were subjected to metabolic evaluation 
after irradiation, yet only 2 columns were presented. Were the values averaged? 
Fig.2. The alkaline comet assay is claimed to measure radiation-induced DSBs. This is inaccurate in 
that this assay primarily measures radiation-induced single strand breaks, which are a nonlethal 
event. To measure DSBs, it is necessary to use the neutral comet assay. This is significant in that 
the comet results were used to claim that the nucleosides do not affect the initial level of 
radiation-induced DSBs, but only influenced their repair. The rationale for performing the alkaline 
comet assay was that gammaH2AX analysis cannot distinguish between the induction and repair of 
DSBs, which is also inaccurate. gammaH2AX foci correspond to the initial level of DSBs at 0.5h 
after irradiation; their dispersal correlates with repair. In 2E-G, nucleosides were shown to 
decrease the initial level of gammaH2AX foci detected at 0.5h as well as those detected at times 
out to 24h. Thus, the data presented actually suggest that the nucleoside addition reduces the 
number of radiation-induced DSBs, which is in conflict with the conclusions derived from the comet 
assay. 
Fig.4. Whether the differences between Control and MPA are statistically significant should be 
shown. 
Fig. 7F. For this analysis GBM is combined with low grade gliomas (LGG). To this point the entire 
paper had focused on GBM. The biology as well as the treatment of LGG and GBM are different. 
Moreover, if it was just GBM, the data would have to take into account percent resection, MGMT 
status and patient age, which are not accounted for in LGG analyses. The combination of these 
tumor types certainly complicates data interpretation and should be clearly justified. 

Reviewer #2 (Remarks to the Author); expert on GBM and resistance: 

This is an interesting study, extending the previous work of Jeremy Rich and colleages regarding 

Editorial Note:​ Parts of this Peer Review File have been redacted as indicated to maintain theconfidentiality of unpublished data. Reviewers' comments: the importance of purine metabolism in glioblastoma stem-like cells (Wang Nat Neurosci 2017), 
and targeting of pyrimidine synthesis to overcome resistance to drugs (Wang Sci Trans Med 2019). 

Here, the authors report that inhibition of purine metabolism can lower radioresistance in 
glioblastoma cell lines, spheroids, and subcutaneously growing xenograft models in mice - by 
interfering with DNA repair. This is in principle a valuable extension of the previous work, and of 
high translational significance. The drug they use (MMF) is approved, widely used in the clinic, and 
even capable of passing the blood-brain barrier (a fact the authors should discuss!) - which makes 
it to a very interesting candidate for future combination trials with radiotherapy in the clinic. 

The data appears solid, the manuscript is very well written, the statistics appears adequate and 
sound, and the conclusions well founded. 

I have two major issues: 

1.) It is well known today that radioresistance in vitro, and very likely also in non-orthotopic tumor 
models in vivo is a very poor readout for the "real" radioresistance seen in glioblastoma growing 
where it belongs (brain). There are several important cellular mechanisms of radioresistance that 
appear to be brain-specific (e.g., see Osswald et al., Nature 2015). Therefore, the authors MUST 
add data of patient-derived glioma stem-like cell lines (NOT U87, which is a very, very bad cell line 
for glioma research today), growing in the mouse brain - and confirm their radiosensitization 
findings with MMF. As discussed above, they are in a very good position: MMF is brain-penetrant, 
which is a rare feature for oncological drugs, so these are highly meaningful experiments that, if 
positive, would dramatically increase the value of this manuscript. 

2.) The supportive patient data (Fig. 7F) is interesting. I would like to see the same data for IDH-
mutant gliomas. Is this mechanism of (potential) relevance here, too? - I am aware that IDHmut 
glioma models in vitro and in vivo are tricky, so I am not asking to provide experimental data - but 
in silico analyses from the TCGA and other databases are straightforward, and would also benefit 
this manuscript. 

Reviewer #3 (Remarks to the Author); expert on organic medicinal chemistry and drug design: 

This manuscript systematically demonstrates that radiation (RT) resistance in GBM cells results 
from an increased ability to repair RT-induced DSBs. Further, increased expression of IDH1 is 
associated with RT-resistance. The study also demonstrates that GBMs with depleted purines 
resulted in RT-sensitivity and that protection with added nucleotides in RT-sensitive GBMs 
facilitates repair of DSB and manifests resistance. In contrast, inhibition of de novo purine 
synthesis, particularly GTP synthesis via MMF, results in RT-sensitization of GBMs in cells as well as 
in patient-derived GBN neurospheres. 

These results are further extended to show that a combination of purine synthesis inhibition (MMF) 
along with RT is synergistic and significantly better than either treatment alone, in vivo. This 
establishes the clinical treatment potential of this combination and is further suggested by the 
reported high expression of TMPDH1 in aggressive brain tumor patients with lower survival. The 
experimental methodology is sound and the results most exciting and appropriate. 

In the discussion section, the mechanism(s) by which GTP regulates RT-resistance is provocatively 
and perhaps correctly suggested to be a signaling process rather than simple nucleotide 
availability for DSD-repair. With regard to this suggestion, it would be most appropriate to look at 
the metabolism and the levels of AICA (ZMP), AMPK and effects with metformin in the presence of 
radiation, as well as MMF to determine if GTP signaling and feedback modulates these levels. With 
these minor studies in hand, the manuscript should be acceptable for publication, with significant 
contribution to the GBM literature and potential treatment modalities. 

Reviewer #4 (Remarks to the Author); expert on one-carbon metabolism: 

Attached

Comments on Zhou, W. et al. “Purine metabolism regulates DNA repair and therapy resistance in 
glioblastoma” 
 
The paper describes a correlation of purine metabolites with radiation resistance in glioblastoma cells. The 
effect is demonstrated both in cell lines and xenograft models. The authors also show that the protection arises 
from a purine fueled increase in DNA repair. When de novo purine synthesis was inhibited, radiation sensitivity 
was restored. Overall, the findings are significant in understanding the differences in cellular response to 
radiation. The experiments are comprehensive and well executed; although possibly compromised by the 
possible loss of amplicons from these types of cells. However, there is one major oversight in the interpretation 
of the results. The authors cannot conclude the effect is due to de novo purine biosynthesis because their 
particular inhibitor affects both de novo as well as salvage synthesis. The paper should include a knockdown or 
pharmalogical inhibition of a key enzyme necessary only for de novo biosynthesis. All they can claim is that the 
level of cellular purines affects radiation sensitivity. Likewise, the effect of radiation may compromise other 
cellular functions dependent on purines  
Notably, Wang X., et. al. Nature Neuroscience (2017) 20(5) 661-673 have reported a similar phenomenon with 
the brain tumor inducing cells (BTICs), where a clear effect on the de novo purine biosynthesis has been 
demonstrated. In my opinion the manuscript requires considerable revision before it would be considered 
suitable for publication in the Journal. 
Specific comments. 
 
1.  (Results: Nucleotide metabolites correlate…) Can the authors please expand upon why no IDH1 mutations 

are good models of GBM? How might this impact the results? 

2.  (Results: Nucleotide metabolites correlate…) At the end of the third paragraph, the authors state that 

“Downregulation of the cytidine pathway was the third most-correlated metabolic pathway with RT-
sensitivity...”; however, I do not see this represented in Figure 1C. Are the authors only showing those that 
are significant? Could p-values be added to Fig 1 C to demonstrate this? 

3.  (Fig. 1D.) It is somewhat perplexing that the total amount of AMP and GMP is constant between the 
radiation resistant and sensitive lines, while several other purine metabolites are different. Is there a 
metabolic or genetic reason for this observation? 

4.  (Results: Figure 2E) There seems to be a discrepancy between the 24 h time point result in Figure 2E 

(~70%) when compared to Figure 1B (~45%). 

5.  (Results: Supplementing nucleotide pools protects…) The last sentence in the first paragraph states “… 
reduced the DSBs presented 24 h after RT to near baseline levels”. It appears that 20% of cells still were 
scored as having positive γ-H2AX signal. This seems like a considerable amount of cells given that without 
RT, there were no (or minimal cells) having γ-H2AX signal. Please revise. 

6.  (Results: Inhibition…slows DSB repair…) The last sentence on page 9 states “…increased IMP levels by 
more than 10 fold and slightly increased ATP levels…” In the associated figure (Fig 3D), the increase in 
ATP abundance seems to be statistically significant (p-value associated with that read-out). I would 
suggest that a fold change value be included given the significance that has been assigned to the 
metabolite level (+MPA) relative to the control. 

7.  (Results: Figure 3D) Please extend the abundance axis marks, so we have a more clear idea of the ATP 

level in the MPA treated cells. 

8.  (Results: Inhibition…slows DSB repair…) Please define ER in the main text. 
9.  (Results: Inhibition…slows DSB repair…) Add errors to the ER values in the text since error was 

determined and presented in the associated figures. Also, the ratios used to compute ER seems to have 
been reversed between the Fig. 1B, C and D versus Fig. 2E and F. In Fig. 1B, C and D, was there a reason 
for following the survival of U118 for 6 hours but on DBTRG-05MG and GB1 for 8 hrs. The survival fraction 
curve for the control cells of U118 (Fig. 1B) has been fitted to a straight-line, has an exponential decay 
reaching a constant value been considered? 

10. (Results: Figure 3F) Can the authors please state why there appears to be a substantial decrease in A172 

resistance cells treated with nucleosides (lane 4)? 

11. (Results: Inhibition…slows DSB repair…) What is the formulation of the +Nuc treatment exactly? Please 
provide details as to the composition in the main text and the formulation in the methods section. How do 
those levels compare to those in serum? Also, can you contribute the effect to decreased GMP/GTP when 
you supplement with guanosine? It might be converted to GMP directly. What would happen to the percent 
of positive γ-H2AX cells if you to remove guanosine from the nucleoside pool? Are you still able to rescue 
the cells from damage? 

12. (Results: Figure 4A,B) In the test, the cells were allowed to “grow for 7-10 days before viability assessed”; 

however, the legend does not correctly state this. It states “…for Cell-Titer Glo assay 24 h post-RT 
(A&B)…”. Additionally, “MSP12 and HF2303 neurospheres were treated as discussed above..” There is no 
discussion above. Please revise to be consistent with the text. 

13. (Results: Inhibition…radiosensitizes…) The way the data are presented in the middle of the second 

paragraph, HF2303 data is presented first then MSP12. However, the figures are the other way around 
(MSP12 is Figs 4A and C; HF2303 is Figs 4B and D). Please switch around values for consistency in the 
presentation of data. 

14. (Results: Inhibition…radiosensitizes…) The authors confused me on how they were able to go from cell 
growth to enrichment ratio. Please explain or convert numbers to be consistent with the way the data is 
presented in Figs 4A and 4B. 

15. (Results: Purines, not…) In this section, a new cell line, GB-1, was introduced. Please explain why the cell 

line changed from MSP12 in the previous studies to GB-1. 

16. (Results: Purines, not…) In the second sentence of the second paragraph it states “In the RT-sensitive GB-

1 cell line, purines alone (adenosine and guanosine) promoted the repair of RT-induced DSBs nearly as 
much as pooled nucleosides.” From my interpretation of Fig 5E, I see that only 60% rescue was obtained 
compared to 95-100% in the nucleotide pool. Even with error, this does seem to be more than “nearly as 
much”. Please be more quantitative with the result and give a reason for why there appears to be a 
decrease in GB-1 cells. 

17. (Results, Fig 7C) Please explain the discrepancy with tumor #3. This appears to be an outlier. 
18. (Discussion/General Comment) In the second paragraph and mentioned throughout the text, the authors 

state that their data suggests “high rates of de novo purine synthesis”. I can see where this could be 
misinterpreted. The de novo pathway (as illustrated in Fig 3A) starts with PRPP to make IMP; however, in 
your metabolomics studies, you cannot verify that this the case. It is possible that the salvage process is 
taking the free base and making the mono-phosphate form of the purine and from there, generating the 
triphosphate. I would highly recommend that the authors use a stable isotope label for glutamine and show 
how it is being incorporated into GMP/GTP and AMP/ATP. By doing this experiment, we are able to 
understand the original substrate for the purines and the process that RT-resistant or -sensitive GBM cells 
use to make purines. 

19. The authors show the metabolic effect of MPA on GTP accumulation after 24 hours post treatment. Was 
the overall NADPH/NADP+ ratio and NADH/NAD+ assessed? Have the authors considered the effect on 
mitochondrial DNA replication and maintenance of the function owing to the requirement of GTP by the 
mitochondrial DNA polymerase. 

20. For consistency, only one of the three phases should be used- intratumorally, Intra-tumoral, or intra-

tumoral. 

21. Fig. 3 B and D- data can be plotted to show y-axis end points.