To our knowledge, we present the first NSCLC prognostic gene expression signature generated from microarray studies using samples collected prospectively in a randomized phase III ACT trial. The samples from the untreated control group led to the identification of a stage independent 15-gene signature that separated the cohort into good and poor prognosis patients (adjusted HR, 18.00; P
< .001). Our signature was validated for its prognostic significance in independent microarray data sets of 96 patients with stage IB to II adenocarcinoma15
and 79 patients with squamous cancer.9
Further, cross-platform validation of the signature was demonstrated in 133 NLCI patients profiled by the Agilent array,20
and showed a trend of similar magnitude in a smaller Duke data set (n = 48).8
Importantly, the 15-gene signature and its prognostic value also were verified by RT-qPCR both in the original 133 samples profiled by microarray and in 30 additional JBR.10 samples not profiled by microarray.
ACT for resected NSCLC was not considered standard until recently, when the results of several trials, including JBR.10 became available.1,2
To date, there is no laboratory or clinical marker other than stage that can identify patients who are likely to benefit from ACT. Therefore, this is the first study, to our knowledge, that has shown that a prognostic microarray signature can also be predictive of benefit from ACT. Patients identified as high-risk benefited significantly (HR, 0.33; P
= .0008). In contrast, low-risk patients did not benefit from ACT (HR, 3.67; P
= .021), and the interaction P
value was highly significant (P
< .001). As no other microarray studies performed using tumor samples from randomized trials with treated and untreated patients are available we could not validate the predictive value of our signature, either in the data sets used to validate its prognostic strength or in other data sets. We realize, therefore, that while promising, these results cannot be considered conclusive, and that they must be validated prospectively in future trials.
The benefit of ACT in stage IB remains controversial.1,3
We showed that stage IB patients also could be separated into low-risk and high-risk groups using our signature (HR, 13.22; 95% CI, 2.86 to 62.11; P
< .001). Furthermore, the survival of high-risk IB patients was greatly improved with ACT (HR, 0.44; 95% CI, 0.18 to 1.09; P
= .07), whereas low-risk patients had no survival benefit when treated with chemotherapy. Although JBR.10 did not demonstrate benefit from ACT in stage IB overall,1
this study suggests that a subset of patients within stage IB may have the potential to benefit from adjuvant therapy. The Lung Adjuvant Cisplatin Evaluation meta-analysis3
reported a small but clinically and statistically nonsignificant benefit from chemotherapy in stage IB (HR, 0.93; 95% CI, 0.78 to 1.10). It is possible that this modest benefit arose almost entirely from a small subset of patients with a poorer prognosis, who potentially could have been identified by our gene signature.
The current practice is to treat all stage II patients with ACT. Our signature identified stage II patients who had a good prognosis and who did not appear to benefit from chemotherapy or potentially could be affected adversely by ACT (HR, 2.93; 95% CI, 0.63 to 13.57; P = .15).
As there are no other frozen tumor banks associated with a clinical trial containing patients randomly assigned to treatment and no treatment, we attempted to evaluate the predictive value of previously published prognostic signatures when applied to treated and untreated patients in the JBR.10 data set. We were able to replicate eight of these signatures (reviewed in Zhu21
) in JBR.10 cases.6,12,13,15,22–25
Only the six-gene signature identified by Boutros22
was significant in JBR.10 OBS patients. This signature also showed that only high-risk patients benefited from chemotherapy in JBR.10 (HR, 0.21; 95% CI, 0.05 to 0.84; P
= .027; interaction P
= .0323; Data Supplement). A significant beneficial effect of ACT in the high-risk group was also achieved by the three-gene signature of Lau13
(HR, 0.48; 95% CI, 0.23 to 1.00; P
= .05; Data Supplement), but the interaction with low-risk group did not reach significance. However, the signatures reported by Chen,6
Shedden (method E in DCC),15
were neither significantly prognostic when applied to the observation arm of JBR.10, nor predictive of benefit from adjuvant chemotherapy. The results demonstrate the significant challenges faced in validating prognostic gene expression signatures. More importantly, the JBR.10 microarray data set now available with this report may be used for testing future predictive markers.
Functional annotation for the 15 genes reveals properties that may elucidate their role in lung cancer biology. Using annotation from Gene Ontology26
and KEGG pathways,27
cellular localization and functions that predominate among these genes (six of 15) are nuclear proteins or transcription regulators MDM2, ZNF236, FOSL2, HEXIM1, MYT1L and IKBKAP. MDM2 is an E3 ubiquitin ligase that targets p53 for proteasomal degradation,28,29
and may represses transcriptional activity of p53.30–32 MDM2
is amplified in 6.2% of lung adenocarcinoma33,34
and overexpression was associated with poor prognosis in NSCLC.35
MDM2 amplification also appears mutually exclusive with p53 mutation33,34
further demonstrating the importance of MDM2
in the p53 pathway. This supports the notion that a minimal signature would include genes that regulate additional key genes and pathways, rather than belonging to a single dominant process or pathway. The second subset of genes includes MLANA
, which encode for transmembrane- or membrane-associated proteins, potentially involved in signaling pathways.36
and UMPS are involved in purine and pyramidine metabolism, respectively, suggesting dependency of NSCLC on these pathways.
Direct comparison of the 15 genes in our signature with those in the published signatures we evaluated (Data Supplement) shows no overlap but they are connected at the protein level (Data Supplement; eg, ATP1B1
with epidermal growth factor receptor25
with hypoxia-inducible factor 1α),13
suggesting they may share common signaling networks.
To our knowledge, this is the first report of a gene signature that is both independently prognostic in patients with untreated NSCLC, and predictive of survival benefit from ACT. With this signature, we have provided the algorithm to classify individual patients. The predictive role of our signature should be tested in prospectively planned adjuvant chemotherapy trials.