Introduction
Cancer cell metabolism characterized by high glycolysis rate in presence of oxygen has been confirmed in many tumors [
1]. This phenomenon, discovered by O. Warburg in 1924 [
2] and once considered as the result of a “damaged” metabolism [
3], has presently been found also in many rapidly multiplying non-cancerous cells, leading to an increased focus of cancer research on the specific characteristics of tumor metabolism [
4].
This field of cancer research is promising. In fact the high glycolysis rate in tumors, as assessed by diagnostic positron emission tomography (PET) imaging of fluorodeoxyglucose (FDG) uptake, is also exploited in clinical practice, in the differential diagnosis of nodules of unknown origin, and, more recently, also in prognostic studies [
5‐
7]. However, specific investigations must be performed because we can expect that tumors with different characteristics-origin, grow dynamics, etc.-have different metabolic requirements.
Diagnostic PET imaging is routinely performed in NSCLC, the most frequent histological type of lung cancer (still the leading cause of cancer death in the world [
8]). There is evidence that high glucose metabolism is present in NSCLC, so a role of metabolism as prognostic factor can be hypothesized; in fact this role is actually investigated in lung cancer by the assessment of FDG uptake level [
6,
9,
10].
New effective prognostic factors could be very useful for NSCLC patients. Presently, pathological stage of the resected tumor is the main prognostic factor used in clinical practice to select NSCLC patients to be referred for additional therapies after surgery [
11], but many early staged patients actually relapse [
12]. In fact, many proteins or genes, differently expressed in tumor samples from patients with different survivals, are investigated as possible prognostic biomarkers; but NSCLC is probably a very heterogeneous disease [
13] and this could justify the high number of mostly non-overlapping gene lists proposed as prognostic signatures [
14]. However, PET effectiveness in distinguishing NSCLC from non-tumor lung tissue suggests that genes related to glucose metabolism bear an important role in all NSCLC, regardless of tumor heterogeneity.
Among these genes,
GAPDH has an essential role in glucose metabolism, where the corresponding enzyme converts glyceraldehydes-3-phosphate to 1,3-diphosphoglycerate with reduction of nicotinamide adenine dinucleotide (NAD+) to NADH. In fact
GAPDH gene is expressed in all tissue, so to be classically used as housekeeping gene, but it is known to be over expressed in many tumors as compared to normal tissues, and also to be correlated with poor prognosis or tumor aggressiveness in ovarian, breast, renal, colorectal, melanoma cancer [
15]. Furthermore, GAPDH protein is able to bind to RNA and DNA, supporting glycolytic and extra-glycolytic regulatory roles in cell stress, apoptosis, and metabolism [
16‐
18]. In lung cancer, GAPDH protein is well known to be over expressed as compared to normal lung tissue [
19], and
GAPDH gene is known to be expressed at high levels as compared to the surrounding non cancerous lung biopsies [
20]. However, while evidences accumulate that preoperative FDG uptake level is a prognostic factor in NSCLC, the prognostic value of
GAPDH expression level in resected NSCLC samples is still to be assessed. In this retrospective study, we measured
GAPDH gene expression, by RQ-PCR, on tumor samples from a group 82 resected NSCLC patients. After detecting a significant correlation of
GAPDH with survival from our patient follow-up data, we decided to further investigate the expression of
GAPDH gene in six large publicly available NSCLC microarray datasets, collecting data from over 1250 total NSCLC patients.
Discussion
It is well known that lung tumors present with high glycolysis level, but it is yet to demonstrate that glycolysis level, as assessed in resected NSCLC patient tumor sample, can be a prognostic factor; we think that our results gave some evidence suggesting its prognostic capabilities. In the present study we assessed the gene expression level of GAPDH, that has a key role in glucose breakdown; with our surprise, we found no studies specifically addressing the prognostic capabilities of GAPDH gene expression in resected NSCLC samples.
GAPDH protein is known to have also extra-glycolytic capabilities, being able to move to the nucleus, to support cell response to stress, and to initiate apoptosis [
18]. However
GAPDH gene is always expressed at high levels, with high glycolysis levels, in NSCLC compared to normal lung cells; so we think that our
GAPDH prognostic results reflect an increased catalytic activity of GAPDH protein in glucose metabolism. In this sense our results are in agreement with the studies that are correlating glucose metabolism to NSCLC prognosis by using different approaches, among which FDG uptake level assessment by PET imaging of the tumor before resection. Furthermore, on the same reasoning, many studies in NSCLC are recently addressing the prognostic value of other key proteins or gene involved in glucose metabolism, e.g. GLUT1, HK2 [
10]. In fact, it is still unknown which aspects of glycolysis have strong prognostic value in NSCLC, but many available evidences, including our present study results, support that the level of glycolysis has indeed prognostic value.
In our study we measured RQ-PCR GAPDH gene expression levels in the resected tumors from 82 patients of our hospital and found a significant correlation with their prognosis. Then we decided to verify this correlation in the largest NSCLC public microarray datasets, and we found a confirmation of our result. We showed all results in forest plot style, for an individual comparison. In fact, not all the available public data feature the same accuracy; especially some datasets, e.g. Sh2008, are better annotated so to be used as a reference in many studies. Among the confirmations coming from the microarray datasets, we think that the Sh2008 data gave a strong support to our results.
Our results for
GAPDH also agree with the findings of a very recent paper from Wang et al. [
34] in which the authors show the prognostic value of some genes correlated with
GAPDH (GACC genes) together with
GAPDH itself; Sh2008 was used as verification dataset. Authors don't show the prognostic performance of
GAPDH alone; however, our results, confirmed on a large number of public datasets including Sh2008, suggest that large part of the prognostic performances shown in Sh2008 have to be attributed to
GAPDH alone.
In the forest plots we showed the Ro2009 dataset results too, by plotting its
TPI1 gene levels instead of the unavailable
GAPDH ones. Actually this substitution was based on the strict metabolic relation between the two catalytic proteins – however the high correlation of the two genes was verified in the other datasets, and is confirmed by other authors too [
34]. So, Ro2009 results for
TPI1, very similar to
GAPDH results in the other datasets, can further support that the prognostic capabilities of
GAPDH in NSCLC reflect the role of the corresponding enzyme in glucose metabolism.
However one dataset (Bo2013) had a null result for GAPDH correlation with prognosis (HR = 1.0); this dataset was also featuring some characteristics different from all the other ones: i) a low cumulative survival, also at low tumor stages, and ii) a low tumor stage HR and significance, despite the high patient and event numbers. We have no data supporting a correlation of these characteristics with a strong decrease of HR values for GAPDH, so we can only conclude that the Bo2013 dataset is different from the other datasets from more than a single point of view.
GAPDH HR was not affected when selecting only patients that had not received any adjuvant therapy; we performed this comparison in the Sh2008 dataset. This result was helpful for our data analysis; in fact our patients had not received radiotherapy or chemotherapy, but in most microarray datasets the information, whether adjuvant treatments had been performed or not, was not available at patient level. Actually, adjuvant treatment presence could confound a survival analysis because there is-finally- evidence that it can increase survival also in lower stages patient [
12]. Furthermore, clinicians select patients with presumed poor prognosis to be referred for adjuvant therapies-in fact patient selection is one of the main reasons why retrospective studies cannot address adjuvant treatment effectiveness; this selection was resulting in the low cumulative survival found in Sh2008 adjuvant treated patient only subset. However, we observed that this selection probably did not much influence
GAPDH HR value (Additional file
2). So,
GAPDH HR insensitivity to the presence of adjuvant treatments suggests that
GAPDH is still a prognostic factor in adjuvant treated patients, but is not promising as predictive factor of adjuvant effectiveness, as performed in Sh2008 patients.
However, in more recent years, some anti-tumor drugs under investigation are involving tumor metabolism, e.g. by reducing glucose availability as metformin [
35], or by directly targeting glycolysis proteins [
36]; our results suggest that in clinical investigations on these drugs,
GAPDH levels in resected NSCLC samples should be investigated as possible predictor of treatment effectiveness.
From the clinical point of view the GAPDH HR value found in our patients is interesting; however after tumor stage adjusting, significance was lost, pointing out that GAPDH gene expression had some correlation with tumor stage. Indeed, adjusting for tumor stage in the regression model had small effect on HR calculation in microarray datasets, suggesting that our patient number was simply critically too low to overpass the significance level for HR after adjusting for stage, but that GAPDH HR is for large part independent from stage. It will be therefore interesting to investigate how GAPDH could contribute with FDG uptake level and tumor stage in building a composite prognostic marker, possibly also correlating it with the status of known NSCLC oncogenic genes (PI3K, EGFR, KRAS, ALK, etc.).
Finally, not only our results warn researchers from using GAPDH as housekeeper gene in NSCLC prognostic studies involving RQ-PCR measurements; we also suggest that any past NSCLC prognostic study using GAPDH as housekeeper gene should be considered potentially biased.
In conclusion, GAPDH gene expression level in resected tumor, as assessed by RQ-PCR or microarray, is an important prognostic factor in NSCLC, that confirms the importance of investigating metabolism in lung cancer.
Competing interest
The authors declare that they have no competing interests.
Authors’ contributions
RP, GS conceived the study, contributed to the interpretation of the data and wrote the manuscript. GS and AE performed RQ-PCR analysis and interpretation. RP performed all statistical analyses and public microarray dataset selection, collection and handling. SS and MT performed tumor sample handling, staging, storage and selection. MGDB, GB, ER, CG, CS fulfilled ethical authorizations, collected and stored patient data, clinical data and follow-up. UP, FG contributed to the interpretation of the data and revised manuscript. All authors reviewed and approved the manuscript.