In their recent article, Weller et al1 delineate the minor improvement in survival rates among patients with glioblastoma treated with various chemotherapeutic strategies. Malignant gliomas resort in the group of highly glycolytic cancers and metastases (HGCM) responsible for 90% of cancer-associated deaths.2 Is it possible to improve the outcome in these patients by considering the brain's strong metabolic regulation?
The brain is the healthy body's most glycolytic organ, with a typical 18fluorodeoxyglucose (FDG) PET-derived standard uptake value of 8.22.3 Of interest, this is close to the mean standard uptake value of 9.25 (variance, 5–22) for the HGCM that we investigated previously.3 This means that the level of cerebral blood glucose (BG) metabolism is similar to that of the mean HGCM.
Therefore, the brain with its strong energy regulation should provide the ideal microenvironment for highly glycolytic metastasis. This is indeed what is found in practice (US data), with 40% of all metastases also occupying the brain.4 With the high BG microenvironment, brain metastases are also lethal within months.1,4
Because brain BG needs are similar to those of HGCM, any aggressive antiglycolytic treatment must account for the brain's BG needs. This is indeed what is starting to emerge in practice. Before entering phase II clinical trials, the glycolytic inhibitor 2DG showed brain toxicity.5
Should we not devise methods to harm HGCM in a controlled manner while still satisfying the brain's minimum metabolic needs?3 In vivo data 6,7 suggest that such an approach (via extracorporeal glucose deprivation)3 could potentially work. Furthermore, the latest BG control technology may make such an approach practical.8
When devising clinical trials for antiglycolytic treatments, it should be borne in mind that rodent models will not manifest the key invasive properties of malignant gliomas.9 This is attributable to the vastly different regulation strengths that the rodent and the human brains have on their respective BG environments.10
There is an urgent need to more fully explore antiglycolytic treatments for patients with glioblastoma. We hypothesize that the human brain metabolism may be the limiting factor for any aggressive antiglycolytic HGCM treatment. Exploiting such a fact could result in more successful therapies targeting this tumor-protective niche. We believe that this merits further investigation.
Funding
None declared.
Conflict of interest statement. None declared.
References
- 1.Weller M, Cloughesy T, Perry JR, Wick W. Standards of care for treatment of recurrent glioblastoma—are we there yet? Neuro Oncol. 2013;15(1):4–27. doi: 10.1093/neuonc/nos273. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Chaffer CI, Weinberg RA. A perspective on cancer cell metastasis. Science. 2011;331:435–9. doi: 10.1126/science.1203543. [DOI] [PubMed] [Google Scholar]
- 3.Mathews EH, Liebenberg L, Pelzer R. High-glycolytic cancers and their interplay with the body's glucose demand and supply cycle. Med Hypoth. 2011;76:157–165. doi: 10.1016/j.mehy.2010.09.006. [DOI] [PubMed] [Google Scholar]
- 4.Fidler IJ. The role of the organ microenvironment on brain metastasis. Sem Cancer Biol. 2011;21:107–112. doi: 10.1016/j.semcancer.2010.12.009. [DOI] [PubMed] [Google Scholar]
- 5.Porpanto PE, Dhup S, Dadhich RK, Copetti T, Sonveaux P. Anticancer targets in the glycolytic metabolism of tumors: a comprehensive review. Front Pharmacol. 2011;2(49):1–18. doi: 10.3389/fphar.2011.00049. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Mathews EH, Liebenberg L. Can successful cancer therapies build on what we learn from complex disorders? Med Hypoth. 2012;78:687–689. doi: 10.1016/j.mehy.2012.02.005. [DOI] [PubMed] [Google Scholar]
- 7.Fine EJ, Segal-Isaacson CJ, Feinman RD, et al. Targeting insulin inhibition as a metabolic therapy in advanced cancer: a pilot safety and feasibility dietary trial in 10 patients. Nutrition. 2012;28:1028–1035. doi: 10.1016/j.nut.2012.05.001. [DOI] [PubMed] [Google Scholar]
- 8.Nguyen LB, Ling SSH, Jones TW, et al. Identification of hypoglycaemic states using various parameters derived from EEG signals. Proc. 33rd Annual International Conference of the IEEE EMBS; Boston, Massachusetts: 2011. Aug 30 – Sept 3. [DOI] [PubMed] [Google Scholar]
- 9.Seyfried TN, Shelton LM, Huysentruyt LC. The VM mouse model of glioblastoma multiforme. Neurometh. 2013;77:39–55. [Google Scholar]
- 10.Mathews EH, Liebenberg L. Revival of “unsuccessful” chemotherapeutics for highly glycolytic cancers? Med Hypoth. 2011;77:1150. doi: 10.1016/j.mehy.2011.09.020. [DOI] [PubMed] [Google Scholar]