Our data provide evidence that the cerebral metabolic status of lung cancer patients is altered prior to treatment when compared to an age-matched control group. Specifically we showed that [Glu] in the occipital cortex of the lung cancer patients was approximately 10% lower than controls; even in patients without evidence of brain metastases. The lung cancer patients were also characterized by more fatigue and higher levels of IL-6 when compared to controls.
To our knowledge, the finding of cerebral metabolic status changes in lung cancer patients prior to treatment is novel and not previously documented. However, several prospective studies have documented the effects of chemotherapy or hormone treatment on cognition and revealed significant deterioration in neuropsychological test scores when compared to baseline performance in women with breast cancer [18
] and in men with prostate cancer [19
]. Functional MRI studies have also supported evidence of cognitive dysfunction by demonstrating that treatment results in differences of task-related neural activation patterns in patients with prostate cancer in comparison to controls [20
]. Further, women treated with tamoxifen to reduce the risk of breast cancer display changes in brain metabolites including choline containing compounds [21
]. Measurements of the cerebral metabolic rate of glucose using 18
FDG PET have also shown that patients with breast cancer (but no metastases) can display abnormalities following treatment [22
]. Another recent study demonstrated that 23% of patients with breast cancer exhibit cognitive impairment prior to treatment [23
] suggesting that having a diagnosis of cancer affects brain function. In our patients the documented changes in occipital [Glu] were not associated with changes in cognitive performance in comparison to controls as evaluated by the brief battery of neurocognitive testing, possibly due to the fact that our groups were well matched at baseline in terms of estimated premorbid IQ (Wechsler Test of Adult Reading test done at screening). However, the lung cancer patients were characterized by higher fatigue scores which have also previously been demonstrated in cancer patients including lung cancer [24
Spectroscopy studies using combined proton and 13
C-labeled precursors have shown that [Glu] is directly related to neuronal mitochondrial metabolism [neuronal tricarboxylic acid cycle (TCA) cycle rate (VTCAn
)] in normal brain [28
]. Further, a decrease in VTCAn
in the elderly has been shown to correlate with decreases in [Glu] and [NAA], suggesting that mitochondria lose oxidative capacity with normal aging [10
]. If one accepts, that [Glu] represents brain 'energy metabolism' and thereby indirectly brain function, the decrease in [Glu] observed in the lung cancer patients suggests that the presence of lung cancer itself reduces brain function prior to treatment. However, it is important to point out that the patients included in this study were heterogeneous with respect to their final lung mass diagnosis and included early as well as more advanced stages of lung cancer. Due to the small sample size it was not possible to correlate the cerebral metabolomic status specifically with tumor staging; and since our sample was dominated by early stage lung cancer patients it is likely that the overall impact of ‘lung cancer’ on [Glu] and potentially other brain metabolites may have been underestimated and might prove more significant in patients with more advanced disease. In support of this statement, shows that the highest levels of [Glu] of the patient group belonged to two of the subjects with non-cancer. Future studies focused on characterizing a larger group of patients with lung cancer at various stages of progression will help address this issue.
It is important to also consider how the patient’s other comorbidities might have interacted with metabolism and influenced [Glu]. For example, in contrast to controls a larger proportion of the lung cancer patients were diagnosed with COPD and it is possible therefore that this chronic condition is responsible for the change in [Glu] at baseline. However, none of the COPD patients were oxygen dependent and all had normal hematocrit and oxygen saturation at baseline. Further, a recent 1
HMRS study on oxygen-dependent and oxygen-independent COPD patients did not reveal metabolic differences in the brain when compared to controls [32
], supporting our main hypothesis that the metabolic changes we observed in the cancer patients are caused by the cancer and not by COPD. Nonetheless, to further evaluate our preliminary findings and ascertain their independence of comorbidities such as COPD, it will be essential to enlarge our sample size and also include other cancer types.
Previous quantitative 1
HMRS studies of the normal human brain have documented a heterogeneous distribution of [NAA] and [GPC+PCh] in the brain with higher [NAA] in the occipital cortex when compared to the parietal and frontal cortices; and higher [GPC+PCh] in the parietal compared to occipital cortex [33
]. In contrast, [Glu] in grey matter is not region-dependent at least in normal, young human brain [33
]. In our study, the quantitative profile of metabolites of control subjects also revealed higher concentrations of choline-containing compounds in the parietal compared to the occipital cortex (); but we did not observe higher [NAA] in the occipital compared to the parietal cortex as previously reported, which might be related to age-differences of the two control populations [33
]. We also did not observe a [Glu] decrease in the parietal cortex of the patient group in comparison to controls, however, [NAA] trended to be lower in the patients (p=0.09). The relatively small sample size prohibits further interpretation and conclusions as to whether the effect of ‘lung mass’ or lung cancer exert a region-specific or global effect on cerebral metabolic status.
The measurements of proinflammatory cytokines revealed higher [IL-6] in the patients with a malignant lung mass compared to controls which is in agreement with previous reports [17
]. The normal range of [IL-6] in human serum is reported in the literature to be <15-20pg/ml [34
]; and has been shown to increase in patients with lung cancer, although the increase varies greatly and is also dependent on tumor type and stage [17
]. In our study the patient’s average [IL-6] was still within the reported normal range probably because the majority of the patients were sampled at an early diagnostic stage (i.e. stage I-II). In the patient group, [TNF-α] was also within normal range and no different from controls; which also indicates the early stage of the cancer. When exploring the potential relation between the metabolic activity of the lung mass as evaluated by the SUVmax
and inflammation, we found a positive association (p=0.066) between [TNF-α] and SUVmax
. This finding indirectly supports previous data reporting that 1) TNF-α and other proinflammatory cytokines are produced locally in lung cancers [35
] and 2) the metabolic activity of the lung cancer is related to proliferative tumor activity [37
] and increased tumor cell glycolysis secondary to local hypoxia [38
It was intriguing that [TNF-α] was found to be negatively associated with [NAA] in the occipital cortex suggesting that ‘inflammation’(regardless of cancer state) influences cerebral metabolic status, in agreement with previous reports. Thus, proinflammatory cytokines can cause cognitive dysfunction [39
]; and elevations of cytokines have been found to co-occur with a reduction of the metabolic rate of glucose utilization in the brain [42
Limitations of the study
The major limitation of the current study is the small sample size and as such the data presented are preliminary. The enrollment of patients for the study was difficult due to the often urgent need for extensive clinical work-up and the patient’s emotional stress associated with the diagnosis and imminent need for surgery. The ability to perform 1HMRS in conjunction with 18FDG-PET would be ideal for this patient population since the study protocols could be carried out with less of a time-burden for the patient. This approach may be possible in the future with implementation of a combined MRI-PET imaging modality the clinical arena. It would also be important to compare 1HMRS results with corresponding regional cerebral metabolic rate of glucose data in order to obtain more accurate spatial information. The latter will enable a better understanding of the neuronal networks involved in cerebral effects associated with cancer.