Association between single nucleotide polymorphisms of the transforming growth factor-beta1 gene and overall survival in unresectable locally advanced non-small-cell lung cancer patients treated with radio(chemo)therapy in a Chinese population

Genetic Variations in the Transforming Growth Factor-β1 Pathway May Improve Predictive Power for Overall Survival in Non-small Cell Lung Cancer

Purpose: Transforming growth factor-β1 (TGF-β1), a known immune suppressor, plays an important role in tumor progression and overall survival (OS) in many types of cancers. We hypothesized that genetic variations of single nucleotide polymorphisms (SNPs) in the TGF-β1 pathway can predict survival in patients with non-small cell lung cancer (NSCLC) after radiation therapy. Materials and Methods: Fourteen functional SNPs in the TGF-β1 pathway were measured in 166 patients with NSCLC enrolled in a multi-center clinical trial. Clinical factors, including age, gender, ethnicity, smoking status, stage group, histology, Karnofsky Performance Status, equivalent dose at 2 Gy fractions (EQD2), and the use of chemotherapy, were first tested under the univariate Cox's proportional hazards model. All significant clinical predictors were combined as a group of predictors named "Clinical." The significant SNPs under the Cox proportional hazards model were combined as a group of predictors named "SNP." The predictive powers of models using Clinical and Clinical + SNP were compared with the cross-validation concordance index (C-index) of random forest models. Results: Age, gender, stage group, smoking, histology, and EQD2 were identified as significant clinical predictors: Clinical. Among 14 SNPs, BMP2:rs235756 (HR = 0.63; 95% CI:0.42-0.93; p = 0.022), SMAD9:rs7333607 (HR = 2.79; 95% CI 1.22-6.41; p = 0.015), SMAD3:rs12102171 (HR = 0.68; 95% CI: 0.46-1.00; p = 0.050), and SMAD4: rs12456284 (HR = 0.63; 95% CI: 0.43-0.92; p = 0.016) were identified as powerful predictors of SNP. After adding SNP, the C-index of the model increased from 84.1 to 87.6% at 24 months and from 79.4 to 84.4% at 36 months. Conclusion: Genetic variations in the TGF-β1 pathway have the potential to improve the prediction accuracy for OS in patients with NSCLC.

Prognostic significance of genetic variants in GLUT1 in stage III non-small cell lung cancer treated with radiotherapy

BACKGROUND

To examine the impact of polymorphisms of glucose transporter 1 (GLUT1) gene on the prognosis of patients with stage III non-small cell lung cancer (NSCLC) who received radiotherapy.

METHODS

Five single nucleotide polymorphisms (SNPs) (rs4658C>G, rs1385129G>A, rs3820589A>T, rs3806401A>C and rs3806400C>T) in GLUT1 gene were evaluated in 90 patients with pathologically confirmed stage III NSCLC. A total of 21 patients were treated with radiotherapy alone, 25 with sequential chemoradiotherapy, and 44 with concurrent chemoradiotherapy. The association of the genetic variations of five SNPs with overall survival (OS) and progression-free survival (PFS) was analyzed.

RESULTS

Two SNPs (rs1385129 and rs3806401) were significant risk factors for OS. Three SNPs (rs1385129, rs3820589 and rs3806401) were in linkage disequilibrium. In Cox proportional hazard models, GAA haplotype was a good prognostic factor for OS (hazard ratio [HR] = 0.57, 95% confidence interval [CI]: 0.39-0.81, p = 0.002) and PFS (HR = 0.68, 95% CI: 0.47-0.99, p = 0.043), compared to variant haplotypes. The GAA/GAA diplotype was observed in 46.7% of patients; these patients showed significantly better OS (HR = 0.38, 95% CI: 0.22-0.65, p < 0.001) and PFS (HR = 0.51, 95% CI: 0.31-0.85, p = 0.009) compared to those with other diplotypes.

CONCLUSIONS

These results suggest that polymorphisms of GLUT1 gene could be used as a prognostic marker for patients with stage III NSCLC treated with radiotherapy.

Radiogenomics helps to achieve personalized therapy by evaluating patient responses to radiation treatment

Radiogenomics is the whole genome application of radiogenetics, which focuses on uncovering the underlying genetic causes of individual variation in sensitivity to radiation. There is a growing consensus that radiosensitivity is a complex, inherited polygenic trait, dependent on the interaction of many genes involved in multiple cell processes. An understanding of the genes involved in processes such as DNA damage response and oxidative stress response, has evolved toward examination of how genetic variants, most often, single nucleotide polymorphisms (SNPs), may influence interindividual radioresponse. Many experimental approaches, such as candidate SNP association studies, genome-wide association studies and massively parallel sequencing are being proposed to address these questions. We present a review focusing on recent advances in association studies of SNPs to radiotherapy response and discuss challenges and opportunities for further studies. We also highlight the clinical perspective of radiogenomics in the future of personalized treatment in radiation oncology.

The associations between immunity-related genes and breast cancer prognosis in Korean women

We investigated the role of common genetic variation in immune-related genes on breast cancer disease-free survival (DFS) in Korean women. 107 breast cancer patients of the Seoul Breast Cancer Study (SEBCS) were selected for this study. A total of 2,432 tag single nucleotide polymorphisms (SNPs) in 283 immune-related genes were genotyped with the GoldenGate Oligonucleotide pool assay (OPA). A multivariate Cox-proportional hazard model and polygenic risk score model were used to estimate the effects of SNPs on breast cancer prognosis. Harrell’s C index was calculated to estimate the predictive accuracy of polygenic risk score model. Subsequently, an extended gene set enrichment analysis (GSEA-SNP) was conducted to approximate the biological pathway. In addition, to confirm our results with current evidence, previous studies were systematically reviewed. Sixty-two SNPs were statistically significant at p-value less than 0.05. The most significant SNPs were rs1952438 in SOCS4 gene (hazard ratio (HR) = 11.99, 95% CI = 3.62–39.72, P = 4.84E-05), rs2289278 in TSLP gene (HR = 4.25, 95% CI = 2.10–8.62, P = 5.99E-05) and rs2074724 in HGF gene (HR = 4.63, 95% CI = 2.18–9.87, P = 7.04E-05). In the polygenic risk score model, the HR of women in the 3^rd tertile was 6.78 (95% CI = 1.48–31.06) compared to patients in the 1^st tertile of polygenic risk score. Harrell’s C index was 0.813 with total patients and 0.924 in 4-fold cross validation. In the pathway analysis, 18 pathways were significantly associated with breast cancer prognosis (P<0.1). The IL-6R, IL-8, IL-10RB, IL-12A, and IL-12B was associated with the prognosis of cancer in data of both our study and a previous study. Therefore, our results suggest that genetic polymorphisms in immune-related genes have relevance to breast cancer prognosis among Korean women.