Severe radiation-induced toxicities limit treatment efficacy and compromise outcomes of lung cancer. We aimed to identify microRNA-related genetic variations as biomarkers for the prediction of radiotherapy-induced acute toxicities. We genotyped 233 SNPs (161 in microRNA binding site and 72 in processing gene) and analyzed their associations with pneumonitis and esophagitis in 167 stage III NSCLC patients received definitive radiation therapy. Sixteen and 11 SNPs were associated with esophagitis and pneumonitis, respectively. After multiple comparison correction, RPS6KB2:rs10274, SMO:rs1061280, SMO:rs1061285 remained significantly associated with esophagitis, while processing gene DGCR8:rs720014, DGCR8:rs3757, DGCR8:rs1633445 remained significantly associated with pneumonitis. Patients with the AA genotype of RPS6KB2:rs10274 had an 81% reduced risk of developing esophagitis (OR: 0.19, 95% CI: 0.07–0.51, p = 0.001, q = 0.06). Patients with the AG+GG genotype of SMO:rs1061280 had an 81% reduced risk of developing esophagitis (OR: 0.19, 95% CI: 0.07–0.53, p = 0.001, q = 0.06). Patients with the GG+GA genotype of DGCR8:rs720014 had a 3.54-fold increased risk of pneumonitis (OR: 3.54, 95% CI: 1.65–7.61, p <0.05, q <0.1). Significantly cumulative effects of the top SNPs were observed for both toxicities (P-trend <0.001). Using bioinformatics tools, we found that the genotype of rs10274 was associated with altered expression of the RPS6KB2 gene. Gene-based analysis showed DGCR8 (p = 0.010) and GEMIN4 (p = 0.039) were the top genes associated with the risk of developing pneumonitis. Our results provide strong evidence that microRNA-related genetic variations contribute to the development of radiotherapy-induced acute esophagitis and pneumonitis and could thus serve as biomarkers to help accurately predict radiotherapy-induced toxicity in NSCLC patients.
Citation: Li R, Pu X, Chang JY, Ye Y, Komaki R, Minna JD, et al. (2016) MiRNA-Related Genetic Variations Associated with Radiotherapy-Induced Toxicities in Patients with Locally Advanced Non–Small Cell Lung Cancer. PLoS ONE 11(3): e0150467. doi:10.1371/journal.pone.0150467
Editor: Alfons Navarro, University of Barcelona, SPAIN
Received: May 26, 2015; Accepted: February 15, 2016; Published: March 18, 2016
Copyright: © 2016 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Research was supported by U.S. NIH grants R01-CA111646 (X. Wu), P50CA070907 (J.D. Minna, J.A. Roth, and X. Wu), R01-CA127615 (X. Wu), and CPRIT RP130502 (X. Wu). Additional support was provided by the Center for Translational and Public Health Genomics of the Duncan Family Institute for Cancer Prevention and Risk Assessment, The University of Texas MD Anderson Cancer Center (X. Wu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancer cases ; approximately one fifth (20%) of NSCLC patients have locally advanced (stage III) disease at the time of diagnosis  and have a poor 5-year survival rate (lower than 14%) . Radiotherapy combined with chemotherapy is the mainstay for locally advanced NSCLC . It can enhance control of local disease and to improve 5 year survival rate by 4.5% [5–6]. However, radiation-induced toxicity to normal tissue often limits the efficacy of definitive radiation therapy. Severe acute esophagitis and symptomatic pneumonitis occur in approximately 15–25% and 5–50% of NSCLC patients, respectively [7–8]. These toxic effects are dose-limiting and can compromise treatment outcomes.
Currently, clinical and dosimetric factors are used to predict the possibility of radiation-induced toxicities and to guide dose design [9–10]. However, these clinical factors lack sufficient accuracy in the prediction of these toxicities, with limited negative predictive values (60% – 80%) and high false-negative rates (25% – 50%) . Therefore, there is a strong need to identify novel biomarkers to assist in the accurate prediction of these toxicities and to guide radiation dose design before treatment. Genetic variations appear to be promising biomarkers, as they have been associated with radiotherapy toxicities in many studies [12–14]; however most of these studies focused on only a limited number of genes.
MicroRNA (miRNA) is a class of small non-coding RNAs that regulates gene expression by binding to the target mRNA. MiRNAs play an important role in cancer development and therapeutic responses [15–16]. Evidence has linked miRNAs with radiation-induced side effects such as hematopoietic injury . Previous study has also reported that genetic variation within miRNA processing genes or miRNA-mRNA binding sites could influence miRNA maturation or regulation  and were associated with clinical outcomes in NSCLC patients .
In this study, we analyzed 161 SNPs within predicted microRNA binding sites genes in major cancer-related genes and 72 SNPs in microRNA processing genes. We evaluated the relationship between these variants and radiation-induced pneumonitis and esophagitis in patients with locally advanced NSCLC treated with definitive radiation therapy. Using Silicon bioinformation queries (Silicon Genetics), we functionally characterized the potential mechanism of identified loci. To our knowledge, ours is the first effort to comprehensively evaluate the effect of miRNA-related genetic variations on the risk of developing radiation-induced toxicities.
Material and Methods
This study was approved by the institutional review board (IRB) of MD Anderson Cancer Center (Houston, TX), and written informed consent was obtained from all participants according to procedures approved by IRB.
Study population and data collection
All patients had histologically confirmed, newly diagnosed NSCLC and were recruited from MD Anderson Cancer Center between September 1995 and February 2008. Patient eligibility criteria for the study were locally advanced stage III NSCLC, Caucasian race, treated with primary radiation therapy (with or without chemotherapy). In addition, for cases treated with concurrent chemoradiotherapy, all were subjected to platinum-based chemotherapy. Clinical stage was defined according to American Joint Committee on Cancer (AJCC) staging system (version 6).
A questionnaire was used to collect epidemiologic data during an in-person interview. Blood sample of patients were drawn from each patient. Clinical variables and follow-up information were abstracted from medical records. Radiation-induced toxicities were defined following the criteria defined previously (19). Briefly, we used documentation of new-onset pain upon swallowing that occurred during treatment to define esophagitis and we used roentgenographic or CT scan abnormalities that were often associated with nonproductive cough and/or fever to detect pneumonitis. Radiation-induced toxicities graded according to National Cancer Institute Common Terminology Criteria for Adverse Events (version 3.0) guidelines . We defined an event as the occurrence of a severe (grade ≥2) pneumonitis or esophagitis.
SNP selection and genotyping
The details of the SNP selection were described previously [20,21]. Briefly, we previously developed a panel that included major genes in cancer-related pathways , among which there were seven microRNA processing genes. Tagging SNPs (±10 kb flanking each gene) and potential functional SNPs for each gene were included. MiRNA binding site SNPs were identified using the PolymiRTS v3.0  for the genes included on the chip. Genomic DNA was extracted from the study patients’ peripheral blood using the Human Whole Blood Genomic DNA Extraction Kit (Qiagen, Valencia, CA). Genotyping was performed using Custom Illumina iSelect Infinium II Beadchips following the standard protocol (Illumina, San Diego, CA). Only SNPs with a sample call rate greater than 95% and samples with an SNP call rate greater than 95% were included in the final analysis.
Chi-square test, Fisher’s exact test and student’s t-test were used to analyze the distribution of demographic and clinical variables between patients with or without toxic reactions. Multivariate logistic regression was used to assess the main effect of single SNP on the risk of developing pneumonitis or esophagitis, adjusted for patient age, sex, performance status, smoking status, clinical stage of disease, radiation therapy type, chemotherapy, radiation dosimtric variables, and lung function. A complete analysis of the effect of all 233 individual SNPs on risk of esophagitis and pneumonitis are shown in S1 Table and S2 Table, respectively. Multiple hypothesis testing adjustment was performed using the "q-value" package in R software  based on a false discovery rate of 10% that has been used in prior studies of clinical outcomes [24–26]. Cumulative effects were analyzed by calculating unfavorable genotypes (UFGs), which were defined as counting the number genotypes from the identified SNPs (p<0.01) associated with an increased risk of developing radiation-induced toxicity. All the analyses above were performed using STATA software (version 10, STATA Corp., College Station, TX). Gene-based analysis was performed using Versatile Gene-Based Association Study software (VEGAS) . Expression Quantitative Trait Loci (eQTL) analysis was conducted using the Genevar  (GENe Expression VARiation) database(http://www.sanger.ac.uk/resources/software/genevar/). The results were based on data for the Multiple Tissue Human Expression Resource (MuTHER) Study . The potential miRNA binding site SNPs were identified using PolymirTS v1.0 (Table A and Table B in S1 File). Spearman’s correlations were obtained for SNPs and the corresponding mapped genes to perform cis-eQTL. A two-side value of p<0.05 was considered statistically significant.
A total of 167 patients were included in this study; 71% of patients had grade 2 or higher esophagitis, 38% of patients had grade 2 or higher pneumonitis, and 28% of patients had both esophagitis and pneumonitis (Table 1). There was no significant difference between patients with or without severe toxicities for both esophagitis and pneumonitis in terms of age, sex, smoking pack years, Carbon Monoxide Diffusing Capacity (DLCO), expiratory volume in 1 second (FEV1), planning target volume (PTV), clinical stage of disease, performance status or chemotherapy. The majority of the patients (>95%) were treated with concurrent, platinum-based chemoradiotherapy. Both radiation dosimetrics and radiotherapy type exhibited significant difference between patients with or without esophagitis. Mean esophageal dose was significantly higher for patients with esophagitis (36.79±10.69Gy) than those without esophagitis (30.62±9.32Gy) (p = 0.04). Mean lung radiation dose for patients with pneumonitis was significantly higher (23.03±11.98Gy) than those without pneumonitis (18.86±5.22Gy) (p = 0.01).
Associations between individual SNPs and radiation-induced acute esophagitis
In all, 233 SNPs (161 SNPs from predicted microRNA binding sites and 72 SNPs from microRNA processing sites) were included in the analysis. We found 16 SNPs significantly associated with a risk of developing esophagitis at p<0.05 (Table 2), including 13 SNPs located in microRNA binding sites and 3 SNPs in microRNA processing genes. The predictive miRNAs that may potentially target these binding sites are listed in Table A in S1 file. After multiple comparison corrections, three SNPs (RPS6KB2:rs10274, SMO:rs1061280, SMO:rs1061285) remained significantly associated with esophagitis (q<0.1) (Table 2). Patients with the AA genotype of RPS6KB2:rs10274 has an 81% reduced risk of developing esophagitis (OR: 0.19, 95% CI: 0.07–0.51, p = 0.001, q = 0.06). Patients with AG+GG genotype of SMO:rs1061280 (in high LD with SMO:rs1061285, r2>0.8) had an 81% reduced risk of developing esophagitis (OR: 0.19, 95% CI: 0.07–0.53, p = 0.001, q = 0.06).
To evaluate the potential cumulative effects of these SNPs, we selected top SNPs (p<0.01) and performed unfavorable genotype (UFG) analysis. RPS6KB2:rs10274 (GA+GG), SMO:rs1061280 (AA), NOTCH1:rs3124591 (AG+GG), and GPR30: rs1133043 (CG+GG) were defined as UFGs, and were included in the analysis (Table 3). Significant dose-response effects were identified: with the increase in the number of UFGs, the risk of developing esophagitis (P-trend = p: 1.03×10−6) significantly increased accordingly. Compared with patients with 0–1 UFG, those patients with 2 UFGs had 3.33-fold increased risk of esophagitis (OR: 3.33, 95%CI: 1.19–9.33, p: 0.02). Patients with 3 or 4 UFGs had more than a 13-fold increased risk of developing esophagitis (OR: 13.44, 95% CI: 4.40–41.07, p: 5.11×10−6).
Associations between individual SNPs and radiation-induced acute pneumonitis
In all, 11 SNPs (6 SNPs in microRNA binding sites and 5 SNPs in microRNA processing genes) were significantly associated with pneumonitis (Table 4). The predictive miRNAs that may potentially target the binding site variants are listed in Table B in S1 File. The most significant SNP, rs720014 (in high LD with rs3757 and rs1633445, r2>0.8), was located in 3’ UTR of DGCR8 gene. Patients with GG+GA genotype of DGCR8:rs720014 had 3.54- fold increased risk of pneumonitis (OR: 3.54, 95% CI: 1.65–7.61, p <0.05). This SNP remained significant associated with pneumonitis after multiple comparison corrections (q<0.1).
Using the same approach as in the esophagitis analysis, we also performed UFG analysis for the top SNPs (p<0.01) identified for pneumonitis. DGCR8:rs720014 (GG) and TNFRSF10D:rs7957 (GG) were defined as UFGs and were included in the UFG analysis of pneumonitis (Table 3). A significant dose-response effect was also observed for pneumonitis (P trend = 0.001) with increasing number of UFGs. Compared with patients with no UFG, patients with one UFG had a 1.88-fold increased risk of pneumonitis (OR: 1.88, 95% CI: 1.02–3.64, p: 0.044) and patients with two UFGs had more than a 50-fold increased risk of pneumonitis (OR: 55.89, 95% CI: 3.69–845.54, p = 0.004).
To explore the potential function and underlying mechanism for identified loci, we performed expression quantitative trait loci (eQTL) analysis using an online bioinformatics tool. All 27 SNPs significant for esophagitis (16 SNPs) and pneumonitis (11 SNPs) were entered into the analysis. Genevar showed that the genotype of rs10274 was associated with altered expression of the RPS6KB2 gene based on data from the Multiple Tissue Human Expression Resource (MuTHER) Study, which analyzed gene expression in adipose and skin tissues as well as lymphoblastoid cell lines (LCLs) derived from 196 Caucasian female twins split into two groups. Compared with the GG genotype, the AA genotype of rs10274 was associated with lower expression of the RPS6KB2 gene in all tissue types (adipose, skin, and LCLs); the correlation coefficient (rho) ranged from 0.215 to 0.37, and the P value ranged from 0.049 to 8.0×10−4 (Fig 1A–1F).
(A) RPS6KB2 expression in subcutaneous fat in Twin1 group; (B) RPS6KB2 expression in subcutaneous fat in Twin2 group; (C) RPS6KB2 expression in lymphoblastoid cell lines in Twin1 group; (D) RPS6KB2 expression in lymphoblastoid cell lines in Twin2 group; (E) RPS6KB2 expression in skin tissues in Twin1 group; (F) RPS6KB2 expression in skin tissues in Twin2 group.
Because multiple SNPs were analyzed for each gene within the miRNA processing pathway, to summarize the total effects contributed by SNPs within a single gene, we performed a gene-based analysis using VEGAS , which tests the association for multiple SNPs in a pre-defined set and takes into account the linkage disequilibrium structure. This software performed simulations using a less computationally intensive Monte Carlo approach. We observed that DGCR8 (p value: 0.010) and GEMIN4 (p value: 0.039) were significantly associated with pneumonitis, while XPO5 reached borderline significance (P = 0.087). However, only DGCR8 remained significant after adjustment for multiple testing at false discovery rate (FDR) of 10%). GEMIN4 was the only gene that reached borderline significance for esophagitis (P = 0.065) (Table 5).
We identified genetic variations in miRNA-related genes that were significantly associated with the risk of developing radiation-induced pneumonitis and esophagitis. After multiple comparisons, RPS6KB2 and SMO binding site SNPs remained significantly associated with radiotherapy-induced acute esophagitis, while TNFRSF10D:rs7957 was significantly associated with radiotherapy-induced acute pneumonitis. Gene based analysis supported a significant role of DGCR8 and GEMIN4 in the risk of pneumonitis. eQTL analysis showed that the top SNP (RPS6KB2:rs10274) for esophagitis analysis could potentially affect RPS6KB2 expression. These results suggest that genetic variants in miRNA-related genes may serve as potential predictive markers of the risk of developing radiation-induced acute toxicities.
In our analysis, we found that RPS6KB2:rs10274 was the most significant SNP associated with the risk of esophagitis. The RPS6KB2 gene encodes for protein S6 kinase 2 (S6K2), which affects many cellular processes such as cell proliferation, survival, and metastasis. RPS6KB2 was also reported to have a role in acute radiation effects via the AKT/mTOR pathway [30–32]. RPS6KB2 was found to be the direct target of mir-193a-3p . We found that the AA genotype of RPS6KB2:rs10274 had a protective effect against the risk of esophagitis, and cis-eQTL analysis further supported that the AA genotype of rs10274 is associated with lower expression of the RPS6KB2 gene, while the GG genotype of rs10274 was associated with higher expression of RPS6KB2. Although not yet reported in the literature, it is likely that the A genotype of RPS6KB2:rs10274 itself or SNP tagged by it could create a new miRNA binding site for miR-193a regulation, which would enable the down regulation of miR-193a-3p on the host gene. The decreased level of RPS6KB2 expression in turn would protect the cell from radiation-induced toxicity through the AKT/mTOR pathway. Two SNPs (rs1061280 and rs1061285) in the SMO gene were also identified as significantly associated with the risk of esophagitis after multiple comparison corrections. Smoothened (SMO) encoded a protein that belongs to the G-protein–coupled receptor superfamily. As an important member of the hedgehog (Hh) pathway, this protein SMO was reported to have a driver role in the carcinogenesis of esophagus . It is likely that the binding site SNPs (SMO: rs1061280, SMO: rs1061285) could affect SMO gene transcription or functions that contribute to the etiology of esophagitis after radiotherapy.
TNFRSF10D: rs7957 is the most significant binding site SNP identified for pneumonitis. TNFRSF10D belongs to the tumor necrosis factor receptor superfamily. TNFRSF10D can trigger activation of the AKT pathway , which contributes to acute radiation response and acute radiation toxicity . We found that the GG genotype of rs7957 is associated with a higher risk of radiotherapy-induced pneumonitis and at the same time it confers a longer survival time (data not shown). This result may suggest that patients with a high risk of radiation toxicity are those who respond well to radiation. Biologically, the association between TNFRSF10D and radiation outcomes may be attributed to the activation of stem cell signaling via TNFRSF10D-activated AKT pathway. Activating stem cell signal pathways will start the repair of radiotherapy-induced cell necrosis or apoptosis [35,36]; at the same time this activation will also promote the proliferation of cancer stem cells, which is the cause of cell resistance to therapy and of metastasis . Consistent with this theory, the GG genotype of TNFRSF10D: rs7957 indicates higher risk of pneumonitis and longer survival duration, probably due to the activation of the stem cell pathway- AKT pathway. The role of stem cell signaling pathways in radiotherapy-induced side effects have not been reported. Our data suggest that the AKT/mTOR and SMO-Hh pathway probably contribute to radiotherapy-induced esophagitis, while the AKT pathway probably contributes to the pneumonitis.
By summarizing the effects from multiple SNPs in the same gene, the DGCR8 and GEMIN4 are the top genes identified for pneumonitis at the single gene level. DGCR8 is an important gene that participates in microRNA processing  and helps in generating RNA hairpins known as pre-microRNA. Daniel Gomez-Cabello  found that DGCR8 may participate in pneumonitis through affecting fibroblasts ‘cell proliferation. Our results show that three SNPs in the DGCR8 gene are among the top SNPs identified in pneumonitis, and gene-based analysis showed that the DGCR8 gene is the most significant gene in the analysis of pneumonitis (P = 0.010). GEMIN4 is another important microRNA processing gene that interacts with microRNA and forms a ribonucleoprotein to form the RNA-induced silencing complex . GEMIN4 contributes to carcinogenesis in many cancers, such as kidney  and ovarian cancer . Here, we report that the AA genotype of GEMIN4: rs3087833 would confer a higher risk of radiation-induced pneumonitis.
This study is the first to comprehensively evaluate the effect of miRNA-related genetic variants on the risk of developing radiation-induced toxicities. However, our study also had a few limitations. First, because of the limited sample size and the paucity of comparable studies available, we did not include a validation step; instead, we performed multiple comparison corrections, which reduced the likelihood of false discovery. Nerveless, independent studies will be warranted to confirm our findings. Second, although eQTL analysis suggests that one of the SNPs may affect gene expression, the biological mechanisms underlying the association of these SNPs with radiation outcome are unclear. Mechanistic studies are needed to clarify the functional impact of the SNPs.
In conclusion, we have provided strong evidence that microRNA-related SNPs can contribute to the prediction of radiation-induced esophagitis and pneumonitis. eQTL analysis further suggests that microRNA binding site SNPs could affect miRNA regulation of host gene expression and thus influence the risk of developing radiotherapy-induced toxicities. Since radiotherapy is important for lung cancer patients, especially those with locally advanced NSCLC, our findings may assist in the customized planning of radiation dose based on the patients’ risk of developing toxicities prior to treatment, thus maximizing treatment effects while minimizing toxicities that are sometimes life threatening.
S1 File. Potential targeting miRNAs for the significant miRNA binding site SNPs associated with esophagitis (Table 2) (Table A).
Potential targeting miRNAs for the significant miRNA binding site SNPs associated with pneumonitis (Table 4) (Table B).
S1 Table. Logistic regression analysis of 233 miRNA-related SNPs and risk of esophagitis in locally-advanced lung cancer patients.
S2 Table. Logistic regression analysis of 233 miRNA-related SNPs and risk of pneumonitis in locally-advanced lung cancer patients.
Conceived and designed the experiments: BH XW. Performed the experiments: RL XP. Analyzed the data: RL XP YY XW. Contributed reagents/materials/analysis tools: JC RK JM JR XW. Wrote the paper: RL XP BH XW.
- 1. NSCLC Meta-analysis Collaborative Group. Preoperative chemotherapy for non-small-cell lung cancer: a systematic review and meta-analysis of individual participant data. Lancet. 2014, 3:1561–1571. doi: 10.1016/s0140-6736(13)62159-5
- 2. Yazbeck VY, Villaruz L, Haley M, Socinski MA. Management of normal tissue toxicity associated with chemoradiation (primary skin, esophagus, and lung). CANCER J.2013, 19: 231–237. doi: 10.1097/PPO.0b013e31829453fb. pmid:23708070
- 3. Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA-CANCER J CLIN. 2014, 64: 9–29. doi: 10.3322/caac.21208. pmid:24399786
- 4. Price A. Emerging developments of chemoradiotherapy in stage III NSCLC. NAT REV CLIN ONCOL. 2012, 9: 591–598. doi: 10.1038/nrclinonc.2012.135. pmid:22926022
- 5. Ramnath N, Dilling TJ, Harris LJ, Kim AW, Michaud GC, Balekian AA, et al.Treatment of stage III non-small cell lung cancer: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. CHEST. 2013, 143(5 Suppl): e314S–340S. doi: 10.1378/chest.12-2360. pmid:23649445
- 6. Masson-Côté L1, Couture C, Fortin A, Dagnault A. Postoperative radiotherapy for lung cancer: improvement in locoregional control using three-dimensional compared with two-dimensional technique. INT J RADIAT ONCOL. 2011, 80: 686–691. doi: 10.1016/j.ijrobp.2010.02.010
- 7. Werner-Wasik M1, Yorke E, Deasy J, Nam J, Marks LB. Radiation dose-volume effects in the esophagus. INT J RADIAT ONCOL J RADIAT ONCOL, 2010,76(3 Suppl): S86–93. doi: 10.1016/j.ijrobp.2009.05.070
- 8. Marks LB, Bentzen SM, Deasy JO, Kong FM, Bradley JD, Vogelius IS, et al. Radiation dose-volume effects in the lung. INT J RADIAT ONCOL. 2010, 76(3 Suppl): S70–76. doi: 10.1016/j.ijrobp.2009.06.091
- 9. Topkan E1, Yavuz MN, Onal C, Yavuz AA. Prevention of acute radiation-induced esophagitis with glutamine in non-small cell lung cancer patients treated with radiotherapy: evaluation of clinical and dosimetric parameters. LUNG CANCER-J IASLC, 2009, 63: 393–399. doi: 10.1016/j.lungcan.2008.06.015
- 10. Uyterlinde W, Belderbos J, Baas C, van Werkhoven E, Knegjens J, Baas P,et al. Prediction of acute toxicity grade ≥ 3 in patients with locally advanced non-small-cell lung cancer receiving intensity modulated radiotherapy and concurrent low-dose Cisplatin. CLIN LUNG CANCER, 2013, 14: 541–548. doi: 10.1016/j.cllc.2013.04.001. pmid:23835165
- 11. Madani I, De Ruyck K, Goeminne H, De Neve W, Thierens H, Van Meerbeeck J. Predicting risk of radiation-induced lung injury. J THORAC ONCOL. 2007, 2: 864–874. pmid:17805067 doi: 10.1097/jto.0b013e318145b2c6
- 12. Chen Y, Zhu M, Zhang Z, Jiang G, Fu X, Fan M, et al. A NEIL1 single nucleotide polymorphism (rs4462560) predicts the risk of radiation-induced toxicities in esophageal cancer patients treated with definitive radiotherapy. CANCER, 2013, 119: 4205–4211. doi: 10.1002/cncr.28338. pmid:24022861
- 13. Fachal L, Gómez-Caamaño A, Peleteiro P, Carballo A, Calvo-Crespo P, Sánchez-García M, et al. Association of a XRCC3 polymorphism and rectum mean dose with the risk of acute radio-induced gastrointestinal toxicity in prostate cancer patients. RADIOTHER ONCOL. 2012, 105: 321–328. doi: 10.1016/j.radonc.2012.09.013. pmid:23075580
- 14. Andreassen CN, Alsner J. Genetic variants and normal tissue toxicity after radiotherapy: a systematic review. RADIOTHER ONCOL. 2009,92: 299–309. doi: 10.1016/j.radonc.2009.06.015. pmid:19683821
- 15. Yanaihara N, Harris CC. MicroRNA Involvement in Human Cancers. CLIN CHEM, 2013, 59: 1811–1812. doi: 10.1373/clinchem.2012.198176. pmid:23462030
- 16. Cellini F, Morganti AG, Genovesi D, Silvestris N, Valentini V. Role of microRNA in response to ionizing radiations: evidences and potential impact on clinical practice for radiotherapy. MOLECULES. 2014, 19: 5379–5401. doi: 10.3390/molecules19045379. pmid:24879584
- 17. Jacob NK, Cooley JV, Yee TN, Jacob J, Alder H, Wickramasinghe P, et al. Identification of sensitive serum microRNA biomarkers for radiation biodosimetry. PLoS One. 2013, 8: e57603. doi: 10.1371/journal.pone.0057603. pmid:23451251
- 18. Ryan BM, Robles AI, Harris CC. Genetic variation in microRNA networks: the implications for cancer research. NAT REV CANCER. 2010, 10: 389–402. doi: 10.1038/nrc2867. pmid:20495573
- 19. Hildebrandt MA, Komaki R, Liao Z, Gu J, Chang JY, Ye Y, et al. Genetic variants in inflammation-related genes are associated with radiation-induced toxicity following treatment for non-small cell lung cancer. PLoS One. 2010, 5: e12402. doi: 10.1371/journal.pone.0012402. pmid:20811626
- 20. Pu X, Roth JA, Hildebrandt MA, Ye Y, Wei H, Minna JD, et al. MicroRNA-related genetic variants associated with clinical outcomes in early-stage non-small cell lung cancer patients. CANCER RES. 2013, 15: 1867–1875. doi: 10.1158/0008-5472.can-12-0873
- 21. Wu X, Spitz MR, Lee JJ, Lippman SM, Ye Y, Yang H, et al. Novel susceptibility loci for second primary tumors/recurrence in head and neck cancer patients: large-scale evaluation of genetic variants. CANCER PREV RES. 2009, 2: 617–624. doi: 10.1158/1940-6207.capr-09-0025
- 22. Bao L, Zhou M, Wu L, Lu L, Goldowitz D, Williams RW, et al. PolymiRTS Database: linking polymorphisms in microRNA target sites with complex traits. NUCLEIC ACIDS RES. 2007, 35: D51–54. pmid:17099235 doi: 10.1093/nar/gkl797
- 23. Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci USA. 2003,100:9440–5. pmid:12883005 doi: 10.1073/pnas.1530509100
- 24. Li J, Lindström LS, Foo JN, Rafiq S, Schmidt MK, Pharoah PD, Michailidou K, Dennis J, et al. K.2q36.3 is associated with prognosis for oestrogen receptor-negative breast cancer patients treated with chemotherapy. Nat Commun. 2014,5:4051. doi: 10.1038/ncomms5051. pmid:24937182
- 25. Pu X, Ye Y, Spitz MR, Wang L, Gu J, Lippman SM, et al. Predictors of Survivor in never-smokers with non-small cell lung cancer: A large-scale two-phase genetic study. Clin Cancer Res. 2012,18:5983–5991. doi: 10.1158/1078-0432.CCR-12-0774. pmid:22977190
- 26. Ke H, Chen M, Ye Y, Hildebrandt MAT, Wu W, Wei H, et al. Genetic variations in micro-RNA biogenesis genes and clinical outcomes in noninvasive bladder cancer. Carcinogenesis. 2013, 34:1006–1011. doi: 10.1093/carcin/bgt006. pmid:23322153
- 27. Liu JZ, McRae AF, Nyholt DR, Medland SE, Wray NR, Brown KM, et al. A versatile gene-based test for genome-wide association studies. AM J HUM GENET. 2010, 87: 139–145. doi: 10.1016/j.ajhg.2010.06.009. pmid:20598278
- 28. Yang TP, Beazley C, Montgomery SB, Dimas AS, Gutierrez-Arcelus M, Stranger BE, et al. Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies. Bioinformatics. 2010, 26: 2474–2476. doi: 10.1093/bioinformatics/btq452. pmid:20702402
- 29. Grundberg E, Small KS, Hedman ÅK, Nica AC, Buil A, Keildson S, et al. Mapping cis- and trans-regulatory effects across multiple tissues in twins. Nat Genet. 2012,44:1084–1089. doi: 10.1038/ng.2394. pmid:22941192
- 30. Sridharan S1, Basu A. S6 kinase 2 promotes breast cancer cell survival via Akt. CANCER RES. 2011, 71: 2590–2599. doi: 10.1158/0008-5472.CAN-10-3253. pmid:21427355
- 31. Yu T, Li J, Yan M, Liu L, Lin H, Zhao F, Sun L, et al. MicroRNA-193a-3p and -5p suppress the metastasis of human non-small-cell lung cancer by downregulating the ERBB4/PIK3R3/mTOR/S6K2 signaling pathway. Oncogene. 2015, 34: 413–423. doi: 10.1038/onc.2013.574. pmid:24469061
- 32. Osuka S, Sampetrean O, Shimizu T, Saga I, Onishi N, Sugihara E, et al. IGF1 receptor signaling regulates adaptive radioprotection in glioma stem cells. STEM CELLS. 2013, 31: 627–640. doi: 10.1002/stem.1328. pmid:23335250
- 33. Pelczar P, Zibat A, van Dop WA, Heijmans J, Bleckmann A, Gruber W, et al. Inactivation of Patched1 in mice leads to development of gastrointestinal stromal-like tumors that express Pdgfralpha but not kit. GASTROENTEROLOGY. 2013,144: 134–144. doi: 10.1053/j.gastro.2012.09.061. pmid:23041331
- 34. Lalaoui N, Morlé A, Mérino D, Jacquemin G, Iessi E, Morizot A, et al. TRAIL-R4 promotes tumor growth and resistance to apoptosis in cervical carcinoma HeLa cells through AKT. PLoS One. 2011, 6: e19679. doi: 10.1371/journal.pone.0019679. pmid:21625476
- 35. Tanaka T, Komai Y, Tokuyama Y, Yanai H, Ohe S, Okazaki K, et al. Identification of stem cells that maintain and regenerate lingual keratinized epithelial cells. NAT CELL BIOL. 2013,15: 511–518. doi: 10.1038/ncb2719. pmid:23563490
- 36. Xue J, Li X, Lu Y, Gan L, Zhou L, Wang Y, et al. Gene-modified mesenchymal stem cells protect against radiation-induced lung injury. Mol Ther. 2013, 21: 456–465. doi: 10.1038/mt.2012.183. pmid:23299797
- 37. Eramo A, Haas TL, De Maria R. Lung cancer stem cells: tools and targets to fight lung cancer. Oncogene. 2010, 29: 4625–4635. doi: 10.1038/onc.2010.207. pmid:20531299
- 38. Gong M, Chen Y, Senturia R, Ulgherait M, Faller M, Guo F. () Caspases cleave and inhibit the microRNA processing protein DiGeorge Critical Region 8. PROTEIN SCI. 2012, 21: 797–808. doi: 10.1002/pro.2062. pmid:22434730
- 39. Gómez-Cabello D, Adrados I, Gamarra D, Kobayashi H, Takatsu Y, Takatsu K, et al. DGCR8-mediated disruption of miRNA biogenesis induces cellular senescence in primary fibroblasts. Aging cell. 2013, 12: 923–931. doi: 10.1111/acel.12117. pmid:23773483
- 40. Wilker EH, Baccarelli A, Suh H, Vokonas P, Wright RO, Schwartz J. Black carbon exposures, blood pressure, and interactions with single nucleotide polymorphisms in MicroRNA processing genes. ENVIRON HEALTH PERSP. 2010, 118: 943–948. doi: 10.1289/ehp.0901440
- 41. Horikawa Y, Wood CG, Yang H, Zhao H, Ye Y, Gu J, et al. Single nucleotide polymorphisms of microRNA machinery genes modify the risk of renal cell carcinoma. Clin Cancer Res. 2008,14: 7956–7962. doi: 10.1158/1078-0432.CCR-08-1199. pmid:19047128
- 42. Liang D, Meyer L, Chang DW, Lin J, Pu X, Ye Y, et al. Genetic variants in MicroRNA biosynthesis pathways and binding sites modify ovarian cancer risk, survival, and treatment response. Cancer Res. 2010, 70: 9765–9776. doi: 10.1158/0008-5472.CAN-10-0130. pmid:21118967