In this study, we systematically evaluated genetic variations in TGF-β pathway as predictors of survival in advanced NSCLC. Previous studies have suggested that candidate SNPs and haplotypes in selected genes of TGF-β pathway were associated with the risk of developing lung cancer (26
) and acute lung injury in mice (28
). This is the first study to link TGF-β pathway SNPs with lung cancer survival.
In the main effect analysis, BMP2:rs235756 and SMAD3:rs4776342 showed strong association with NSCLC outcomes. The oncogenic activities of BMP signaling have been shown to be involved in the development of several cancers and associated with poor prognosis (29
). The mature active form of BMP2 was overexpressed in 98% of NSCLC samples and may be involved in promoting tumor growth, progression and angiogenesis (31
). BMP2:rs235756 is located in the flanking region of the BMP2 gene and has already been shown to alter normal BMP function. One study suggests that this variant can alter serum ferritin levels in hemochromatosis (32
). Other SNPs in BMP genes have also been shown to result in higher production of the gene product. One example is the non-synonymous BMP4
SNP rs17563, which was also associated with NSCLC survival in our results. This SNP has been related to higher plasma concentrations of BMP4 and increased transcriptional activity, which were shown to predispose individuals to the development malignant melanoma (33
). Thus, it is plausible that BMP2:rs235756 and BMP4:rs17563 may increase the production of BMP protein and favor a tumor promotion role of BMP signaling in cancer progression. Our study also suggests that SMAD3:rs4776342, or a functional SNP tagged by this locus, may inactivate SMAD3 resulting in restrained TGF-β signals, which is consistent with the finding that ~85% of lung cancer cell lines become resistant to the growth inhibitory effect of TGF-β (34
A single SNP often provides a modest or undetectable effect, whereas the amplified effects of combined SNPs in the same pathway may enhance predictive power. Because multiple deleterious variants with the TGF-β pathway may have a similar effect on overall survival, we analyzed the association with clinical outcomes in patients with increasing number of adverse genotypes. A clear and significant trend was evident for worsening outcomes with increasing number of unfavorable genotypes. These results suggest a cumulative influence by multiple genetic variants within the TGF-β-signaling pathway were able to further enhance the separation of patients based on clinical outcome.
In this study, multiple SMAD3 genotypes were associated with overall survival, including in treatment-specific analyses. Therefore, to understand the combinatory effect of multiple SMAD3 alleles functioning within a haplotype, we determined the LD structure of SMAD3. Haplotype 3 (H3) of SMAD3 in block 5 had consistent effect on variation in two clinical outcomes and also showed an adverse prognosis. These results suggest that haplotype-based analysis may be more informative in prediction of prognosis for NSCLC patients compared with single SNP analysis. Resequencing of DNA samples from individuals carrying the high-risk and low-risk survival haplotypes may be able to discriminate various prognostic subpopulations.
Epistasis is a ubiquitous component of the genetic architecture of common diseases. Complex interactions could determine the functional outcome over the independent main effects of any one susceptibility gene (35
). In order to evaluate the effects of TGF-β signaling variation on overall survival for patients receiving chemotherapy or chemoradiotherapy more clearly, we explored higher order gene–gene interactions using survival tree analysis. The discriminative ability of the analysis identified subgroups of patients with different risk levels based on combinations of genotypes. BMP2:rs235753 had the strongest influence on clinical outcome for the chemoradiation groups in this population as this locus was the primary split in survival tree structure. This observation seems to be consistent with our findings in stratified analysis (). SMAD3:rs11632964 was the initial split on the survival tree for the chemotherapy group. It is known that TGF-β signals are transduced through SMAD3 and in vivo
studies have shown that blocking TGF-β signaling can result in resistance to DNA-damaging agents including cisplatin (36
). Therefore, the effect of SMAD3:rs11632964 in our study is in agreement with SMAD3–SMAD4 controlled upregulation of Bim playing an important role in TGF-β -induced apoptosis (38
). It is important to point out that the statistical modeling of an interaction does not amount to a true biological interaction and caution should be paid when interpreting these results. It has been generally accepted that activated SMAD3 forms heterogenic complexes with SMAD4 through complementary MH2 domains (39
) and a recent study has already demonstrated that BMP2 activates SMAD6 gene transcription through the bone-specific transcription factor Runx2 (40
). The biological plausibility of these results is intriguing, especially considering that the terminal nodes with different survival times, if further validated by the analysis for untreated control group, will assist in the identification of subgroups who will receive benefit from specific treatment modalities.
To gain better power and greater insight, we took a comprehensive approach to assess individual and collective effects of genetic variants in the TGF-β pathway on NSCLC clinical outcomes. The major strength of our study is the large population size from a single institution to minimize treatment heterogeneity. Furthermore, we have available to us comprehensive epidemiologic and clinical data for each of these patients. Although function is not known for all genotyped loci, our results have biological plausibility and warrant further study. Further research, including validation and functional studies, is needed to move this information into the clinic.
In conclusion, these results suggest that genetic variations in the TGF-β pathway modulate clinical outcomes in advanced NSCLC patients. We were able to identify subgroups of patients with differences in predicted survival when treated with chemotherapy with or without radiation.