Introduction
============

Wilms tumor (nephroblastoma) is the most common pediatric renal malignancy \[[@r1]\].  It is normally derived from embryonal kidney precursor cells in which cell growth and/or differentiation are dysregulated during development \[[@r2],[@r3]\].  The incidence rate of Wilms tumor is about 1 in 10,000 children in Western countries \[[@r4]\].  The overall five-year survival rate exceeds 90% in developed countries \[[@r5]--[@r7]\].  Despite great achievements in the treatment of Wilms tumor, the outcomes for patients with high-risk disease (about 25%) remain disappointing \[[@r8]\].  Apart from this, high treatment costs and severe chronic health conditions that occur in nearly 25% of survivors are also challenging \[[@r9],[@r10]\]. 

There is strong evidence that genetic factors contribute to Wilms tumor risk.  To date, five Wilms tumor susceptibility loci have been well characterized, including Wilms tumor gene 1 (*WT1*), Wilms tumor gene on the X chromosome (*WTX*), catenin beta 1 (*CTNNB1*), tumor protein 53 (*TP53*) and the imprinted 11p15 region \[[@r11]--[@r13]\].  Although additional genetic variants continue to be identified, the carcinogenesis of Wilms tumor remains to be fully explained \[[@r14]--[@r16]\].  Therefore, it is indispensable to identify other genes that increase Wilms tumor susceptibility. 

The *RAS* oncogene family has three members: *KRAS*, *NRAS* and *HRAS*.  These genes encode a family of highly homologous GTPases that are involved in various cellular activities, such as growth, proliferation and differentiation \[[@r17],[@r18]\]. * RAS* mutations have been detected in about 20% of human malignancies \[[@r19]\]. * KRAS* mutations are the most common, accounting for approximately 85% of all *RAS* mutations \[[@r20],[@r21]\], followed by *NRAS* mutations (15%). * HRAS* mutations are very rare, constituting less than 1% of all *RAS* mutations \[[@r22]\]. 

The impact of *RAS* gene variants on the risk of cancer has been widely investigated, including in studies of colorectal cancer \[[@r23]\], lung cancer \[[@r24],[@r25]\], breast cancer \[[@r26]\] and melanoma \[[@r27]\].  Clark et al.  demonstrated that coordinated activation of *RAS* and β-catenin accelerated the growth and metastatic progression of Wilms tumor in a murine model \[[@r28]\].  They later reported that activating *KRAS* mutations were found in human Wilms tumor samples \[[@r29]\].  Recently, another team verified the importance of *RAS* mutations in the development and progression of Wilms tumor \[[@r30]\]. 

Despite these findings, the link between *RAS* gene polymorphisms and Wilms tumor risk remains obscure.  To clarify the association of *RAS* with Wilms tumor risk, we selected single-nucleotide polymorphisms (SNPs) in the two most common diseased-related *RAS* genes, *KRAS* and *NRAS*, for analysis in a four-center hospital-based case-control study. 

RESULTS
=======

Correlation of *RAS* gene polymorphisms with Wilms tumor risk
-------------------------------------------------------------

We successfully genotyped 1070 controls and 351 cases for *KRAS* polymorphisms, along with 1070 controls and 355 cases for *NRAS* polymorphism.  The demographic characteristics of the subjects are presented in [Supplemental Table 1](#SD1){ref-type="supplementary-material"}.  All the SNP genotype frequencies were in Hardy-Weinberg equilibrium in controls (*P*\>0.05).  Our results indicated that the rs12587 GT genotype is a risk variant for Wilms tumor ([Table 1](#t1){ref-type="table"}), as individuals with this genotype had a 1.30-fold greater risk for developing Wilms tumor (95% confidence interval \[CI\]=1.004-1.68, *P*=0.046) than those with the GG genotype.  The individual rs7973450 A\>G, rs7312175 G\>A and rs2273267 A\>T variants did not predispose individuals to Wilms tumor. 

###### Logistic regression analysis of associations between *RAS* polymorphisms and Wilms tumor risk. 

  -------------------------------------------------- ------------- -------------- --------- ----------------------- ----------- ----------------------- -----------
  Genotype                                           Cases\        Controls\      *P* ^a^   Crude OR\               *P*         Adjusted OR\            *P* ^b^
                                                     (N=355)       (N=1070)                 (95% CI)                            (95% CI) ^b^            

  *KRAS* rs12587 G\>T (HWE=0.287)                                                                                                                       

  GG                                                 206 (58.69)   688 (64.30)              1.00                                1.00                    

  GT                                                 129 (36.75)   333 (31.12)              **1.29 (1.002-1.67)**   **0.049**   **1.30 (1.004-1.68)**   **0.046**

  TT                                                 16 (4.56)     49 (4.58)                1.09 (0.61-1.96)        0.772       1.08 (0.60-1.94)        0.806

  Additive                                                                        0.142     1.18 (0.96-1.44)        0.117       1.18 (0.96-1.44)        0.120

  Dominant                                           145 (41.31)   382 (35.70)    0.059     1.27 (0.99-1.62)        0.059       1.27 (0.99-1.63)        0.058

  Recessive                                          335 (95.44)   1021 (95.42)   0.987     1.00 (0.56-1.77)        0.987       0.98 (0.55-1.75)        0.949

  G                                                  541 (77.07)   1709 (79.86)             1.00                                1.00                    

  T                                                  161 (22.93)   431 (20.14)    0.114     1.18 (0.96-1.45)        0.114       1.18 (0.96-1.45)        0.117

  *KRAS* rs7973450 A\>G (HWE=0.080)                                                                                                                     

  AA                                                 282 (80.34)   881 (82.34)              1.00                                1.00                    

  AG                                                 68 (19.37)    185 (17.29)              1.15 (0.84-1.56)        0.380       1.14 (0.84-1.56)        0.402

  GG                                                 1 (0.28)      4 (0.37)                 0.78 (0.09-7.02)        0.825       0.83 (0.09-7.50)        0.870

  Additive                                                                        0.660     1.13 (0.84-1.52)        0.436       1.12 (0.83-1.51)        0.448

  Dominant                                           69 (19.66)    189 (17.66)    0.400     1.14 (0.84-1.55)        0.401       1.14 (0.84-1.54)        0.418

  Recessive                                          350 (99.72)   1066 (99.63)   0.807     0.76 (0.09-6.84)        0.808       0.81 (0.09-7.32)        0.853

  A                                                  632 (90.03)   1947 (90.98)             1.00                                1.00                    

  G                                                  70 (9.97)     193 (9.02)     0.450     1.12 (0.84-1.49)        0.450       1.11 (0.84-1.49)        0.462

  *KRAS* rs7312175 G\>A (HWE=0.130)                                                                                                                     

  GG                                                 270 (76.92)   851 (79.53)              1.00                                1.00                    

  GA                                                 72 (20.51)    201 (18.79)              1.13 (0.84-1.53)        0.431       1.14 (0.84-1.54)        0.404

  AA                                                 9 (2.56)      18 (1.68)                1.58 (0.70-3.55)        0.272       1.54 (0.68-3.48)        0.298

  Additive                                                                        0.423     1.17 (0.91-1.51)        0.222       1.17 (0.91-1.51)        0.218

  Dominant                                           81 (23.08)    219 (20.47)    0.299     1.17 (0.87-1.56)        0.299       1.17 (0.88-1.57)        0.285

  Recessive                                          342 (97.44)   1052 (98.32)   0.294     1.54 (0.69-3.46)        0.297       1.50 (0.67-3.39)        0.326

  G                                                  612 (87.18)   1903 (88.93)             1.00                                1.00                    

  A                                                  90 (12.82)    237 (11.07)    0.208     1.18 (0.91-1.53)        0.209       1.18 (0.91-1.53)        0.205

  *NRAS* rs2273267 A\>T (HWE=0.723)                                                                                                                     

  AA                                                 183 (51.55)   541 (50.56)              1.00                                1.00                    

  AT                                                 142 (40.00)   443 (41.40)              0.95 (0.74-1.22)        0.676       0.95 (0.74-1.23)        0.714

  TT                                                 30 (8.45)     86 (8.04)                1.03 (0.66-1.61)        0.893       1.02 (0.65-1.61)        0.917

  Additive                                                                        0.889     0.99 (0.82-1.19)        0.883       0.99 (0.82-1.19)        0.890

  Dominant                                           172 (48.45)   529 (49.44)    0.747     0.96 (0.76-1.22)        0.747       0.97 (0.76-1.23)        0.774

  Recessive                                          325 (91.55)   984 (91.96)    0.805     1.06 (0.68-1.63)        0.805       1.05 (0.68-1.62)        0.840

  A                                                  508 (71.55)   1525 (71.26)             1.00                                1.00                    

  T                                                  202 (28.45)   615 (28.74)    0.883     0.99 (0.82-1.19)        0.883       0.99 (0.82-1.19)        0.891

  Combined effect of risk genotypes for *KRAS* ^c^                                                                                                      

  0                                                  200 (56.98)   673 (62.90)              1.00                                1.00                    

  1                                                  13 (3.70)     28 (2.62)                1.56 (0.80-3.07)        0.196       1.57 (0.80-3.10)        0.192

  2                                                  132 (37.61)   345 (32.24)              1.29 (1.00-1.66)        0.052       1.29 (1.00-1.66)        0.052

  3                                                  6 (1.71)      24 (2.24)                0.84 (0.34-2.09)        0.709       0.84 (0.34-2.09)        0.709

  Trend                                                                           0.157     1.11 (0.98-1.25)        0.094       1.11 (0.98-1.25)        0.093

  0                                                  200 (56.98)   673 (62.90)              1.00                                1.00                    

  1-3                                                151 (43.02)   397 (37.10)    0.048     **1.28 (1.002-1.64)**   **0.048**   **1.28 (1.002-1.64)**   **0.048**
  -------------------------------------------------- ------------- -------------- --------- ----------------------- ----------- ----------------------- -----------

OR, odds ratio; CI, confidence interval; HWE, Hardy-Weinberg equilibrium.  ^a^ *χ^2^* test for genotype distributions between Wilms tumor patients and cancer-free controls.  ^b^ Adjusted for age and gender.  ^c^ Risk genotypes were carriers with rs12587 GT/TT, rs7973450 AG/GG and rs7312175 GA/AA genotypes. 

We further examined the combined effects of the risk genotypes for *KRAS* on Wilms tumor risk.  Compared to individuals without a risk genotype, those harboring one to three of these genotypes were at 1.28-fold greater risk for Wilms tumor (95% CI=1.002-1.64, *P*=0.048). 

Stratification analysis
-----------------------

[Tables 2 and 3](#t2){ref-type="table"}[](#t3){ref-type="table"} summarize the analysis of *KRAS* and *NRAS* polymorphisms and Wilms tumor risk after stratification by age, gender and clinical stage.  A significant association between rs12587 GT/TT and Wilms tumor risk was only found in children \>18 months old among the analyzed strata (adjusted odds ratio \[OR\]=1.39, 95% CI=1.02-1.89, *P*=0.037). 

###### Stratification analysis for association between *KRAS* genotypes and Wilms tumor susceptibility. 

  ----------------- ---------------- ----------------- ---------------------- ---------------- ----------------- -------- ------------------ ----------------- --------- -------------------- ------------------ -------- --------- --------- ------------------ -------
  Variables         rs12587\         AOR (95% CI)^a^   *P*^a^                 rs7973450\       AOR (95% CI)^a^   *P*^a^   rs7312175\         AOR (95% CI)^a^   *P*^a^    Combine genotypes\   AOR (95% CI)^a^    *P*^a^                                          
                    (case/control)                                            (case/control)                              (case/control)                                 (case/control)                                                                          

                    GG               GT/TT                                                     AA                AG/GG                                         GG        GA/AA                                            0         1-3                          

  Age, month                                                                                                                                                                                                                                                     

  ≤18               77/272           46/153            1.06 (0.70-1.61)       0.771            97/341            26/84    1.09 (0.67-1.79)   0.726             99/345    24/80                1.04 (0.63-1.74)   0.870    74/269    49/156    1.14 (0.76-1.73)   0.522

  \>18              129/416          99/229            **1.39 (1.02-1.89)**   **0.037**        185/540           43/105   1.20 (0.81-1.77)   0.373             171/506   57/139               1.21 (0.85-1.73)   0.286    126/404   102/241   1.35 (0.99-1.83)   0.056

  Gender                                                                                                                                                                                                                                                         

  Female            97/283           66/165            1.17 (0.81-1.68)       0.412            128/369           35/79    1.28 (0.82-1.99)   0.285             129/354   34/94                0.99 (0.64-1.54)   0.973    93/277    70/171    1.22 (0.85-1.75)   0.287

  Male              109/405          79/217            1.37 (0.98-1.92)       0.064            154/512           34/110   1.03 (0.67-1.57)   0.897             141/497   47/125               1.34 (0.91-1.97)   0.135    107/396   81/226    1.35 (0.96-1.88)   0.081

  Clinical stages                                                                                                                                                                                                                                                

  I                 71/688           48/382            1.23 (0.84-1.82)       0.293            101/881           18/189   0.82 (0.48-1.38)   0.446             90/851    29/219               1.28 (0.82-2.00)   0.276    69/673    50/397    1.25 (0.85-1.84)   0.261

  II                51/688           39/382            1.37 (0.89-2.13)       0.154            68/881            22/189   1.48 (0.89-2.45)   0.134             71/851    19/219               1.06 (0.62-1.80)   0.836    50/673    40/397    1.36 (0.88-2.09)   0.172

  III               47/688           32/382            1.21 (0.76-1.93)       0.425            67/881            12/189   0.84 (0.44-1.58)   0.587             57/851    22/219               1.48 (0.88-2.47)   0.138    46/673    33/397    1.20 (0.75-1.91)   0.443

  IV                28/688           17/382            1.08 (0.59-2.01)       0.797            34/881            11/189   1.51 (0.75-3.04)   0.246             39/851    6/219                0.59 (0.25-1.42)   0.241    27/673    18/397    1.12 (0.61-2.06)   0.714

  I+II              122/688          87/382            1.29 (0.96-1.75)       0.096            169/881           40/189   1.08 (0.74-1.58)   0.698             161/851   48/219               1.19 (0.83-1.69)   0.350    119/673   90/397    1.30 (0.96-1.75)   0.093

  III+IV            75/688           49/382            1.16 (0.79-1.71)       0.439            101/881           23/189   1.06 (0.66-1.72)   0.800             96/851    28/219               1.12 (0.72-1.75)   0.617    73/673    51/397    1.17 (0.80-1.71)   0.413
  ----------------- ---------------- ----------------- ---------------------- ---------------- ----------------- -------- ------------------ ----------------- --------- -------------------- ------------------ -------- --------- --------- ------------------ -------

AOR, adjusted odds ratio; CI, confidence interval.  ^a^ Adjusted for age and gender, omitting the corresponding stratify factor. 

###### Stratification analysis for the association between *NRAS* rs2273267 A\>T polymorphism and Wilms tumor risk. 

  ----------------- ------------------ ---------- ------------------ ----------------- ------------------ -------
  Variables         rs2273267\         Crude OR   *P*                Adjusted OR ^a^   *P* ^a^            
                    (cases/controls)                                                                      

                    AA                 AT/TT      (95% CI)                             (95% CI)           

  Age, month                                                                                              

  ≤18               58/199             67/226     1.02 (0.68-1.52)   0.934             1.01 (0.67-1.50)   0.975

  \>18              125/342            105/303    0.95 (0.70-1.28)   0.730             0.96 (0.71-1.30)   0.799

  Gender                                                                                                  

  Females           91/234             72/214     0.87 (0.60-1.24)   0.431             0.87 (0.60-1.24)   0.432

  Males             92/307             100/315    1.06 (0.77-1.46)   0.727             1.05 (0.76-1.45)   0.764

  Clinical stages                                                                                         

  I                 67/541             52/529     0.79 (0.54-1.16)   0.235             0.80 (0.55-1.17)   0.252

  II                41/541             51/529     1.27 (0.83-1.95)   0.271             1.27 (0.83-1.96)   0.269

  III               41/541             38/529     0.95 (0.60-1.50)   0.819             0.95 (0.60-1.51)   0.832

  IV                28/541             19/529     0.69 (0.38-1.26)   0.229             0.70 (0.38-1.26)   0.233

  I+II              108/541            103/529    0.98 (0.73-1.31)   0.868             0.98 (0.73-1.32)   0.888

  III+IV            69/541             57/529     0.85 (0.58-1.22)   0.373             0.85 (0.59-1.23)   0.392
  ----------------- ------------------ ---------- ------------------ ----------------- ------------------ -------

OR, odds ratio; CI, confidence interval.  ^a^ Adjusted for age and gender, omitting the corresponding stratify factor. 

False-positive report probability (FPRP) analysis
-------------------------------------------------

In FPRP analysis ([Table 4](#t4){ref-type="table"}), only at a prior probability level of 0.25 and an FPRP threshold of 0.2 did the increased Wilms tumor risk remain noteworthy in carriers of rs12587 GT (FPRP=0.141), children \>18 months old with rs12587 GT/TT (FPRP=0.131) and those with one to three risk genotypes (FPRP=0.139). 

###### False-positive report probability analysis for the association between *KRAS* genotypes and Wilms tumor susceptibility. 

  ---------------- ------------------- --------- ----------------------- ------------------- ------- ------- ------- -------
  Genotype         Crude OR\           *P* ^a^   Statistical power ^b^   Prior probability                           
                   (95% CI)                                                                                          

  0.25             0.1                 0.01      0.001                   0.0001                                      

  rs12587 G\>T                                                                                                       

  GT vs. GG        1.29 (1.002-1.67)   0.049     0.886                   **0.141**           0.330   0.844   0.982   0.998

  GT/TT vs. GG                                                                                                       

  \>18 months      1.39 (1.02-1.89)    0.037     0.682                   **0.131**           0.311   0.832   0.980   0.998

  Risk genotypes                                                                                                     

  1-3 vs. 0        1.28 (1.002-1.64)   0.048     0.903                   **0.139**           0.326   0.841   0.982   0.998
  ---------------- ------------------- --------- ----------------------- ------------------- ------- ------- ------- -------

OR, odds ratio; CI, confidence interval.  ^a^ χ^2^ test was used to calculate the genotype frequency distributions.  ^b^ Statistical power was calculated using the number of observations in the subgroup and the OR and *P* values in this table. 

DISCUSSION
==========

Thus far, only a small portion of genetic loci have been found to increase the risk of Wilms tumor.  This underscores the need to reveal more genetic loci that could predispose individuals to this disease.  Herein, we evaluated the impact of *KRAS* and *NRAS* gene SNPs on the risk of Wilms tumor in 355 Wilms tumor patients and 1070 healthy control subjects.  To the best of our knowledge, we are the first to report the association of *RAS* gene polymorphisms with Wilms tumor risk in Chinese children. 

*KRAS* and *NRAS* have been mapped to chromosomes 12p12.1 and 1p13.2, respectively.  Many studies have investigated the mechanisms by which *RAS* gene polymorphisms impact cancer risk.  In particular, rs61764370 and rs712, two *KRAS* polymorphisms in miRNA-binding sites, have been intensively studied.  These two SNPs are located in the 3' untranslated region (UTR) of *KRAS*, where they disrupt a let-7 miRNA binding site, thus increasing *KRAS* expression and enhancing tumor growth \[[@r31]\].  Chin et al.  studied 46 populations worldwide, and identified the rs61764370 SNP in the 3' UTR of the *KRAS* gene (*KRAS*-LCS6).  This SNP was associated with increased expression of *KRAS,* reduced expression of let-7 and increased risk of lung cancer \[[@r31]\].  Furthermore, this allele was demonstrated to elevate the risk of epithelial ovarian cancer \[[@r32]\] and triple-negative breast cancer \[[@r33]\].  In a population-based case-control study conducted in the US by Christensen et al.,  the *KRAS*-LCS6 variant genotype (rs61764370) was not associated with the overall risk of head and neck squamous cell carcinoma, but was associated with a significantly reduced survival time \[[@r34]\]. 

Wang et al.  \[[@r7]\] reported that the rs712 polymorphism in the *KRAS* 3' UTR was associated with a reduced risk for oral squamous cell carcinoma, while rs1137282 in *KRAS* exon 6 was not \[[@r35]\].  In contrast, in a study of 181 gastric cancer patients and 674 cancer-free controls, Li et al.  found that the T allele of rs712 significantly enhanced the susceptibility to gastric cancer \[[@r36]\].  As different types of tissues and cells have different miRNA profiles, the effects of SNPs in specific 3' UTRs may vary accordingly.  Moreover, differences in the population sources, environmental exposures, sample sizes and selection criteria of subjects may also have influenced the contribution of *RAS* SNPs to cancer susceptibility of different types.  Therefore, it is necessary to define the impact of *RAS* polymorphisms on the risk of a certain cancer type in a certain population. 

Our findings indicated that carriers of the *KRAS* rs12587 GT genotype had a genetic predisposition to Wilms tumor risk.  Unexpectedly, rs7973450 A\>G, rs7312175 G\>A and rs2273267 A\>T were not significantly associated with Wilms tumor risk.  The rs12587 G\>T, rs7973450 A\>G and rs2273267 A\>T polymorphisms reside in different complementary miRNA sites.  The different locations of these SNPs may be one reason for their different effects on cancer risk.  Other plausible interpretations of the null association include the relatively small sample size and the low-penetrance susceptibility of single polymorphisms. 

One limitation of this study was the relatively small sample size, which may have impaired the statistical power, especially for the stratification analysis.  Another limitation was the restriction of the included population to a single ethnicity (Chinese Han), which may render the findings inapplicable to other populations.  Further, though we analyzed four SNPs in the current study, additional SNPs should be considered in future studies.  Lastly, the current study only focused on genetic factors, and gene-environment interaction analysis was not performed due to the lack of relevant information.  Wilms tumor is a heterogeneous disease, and both genetic and environmental factors contribute to its tumorigenesis.  Thus, more comprehensive studies are warranted. 

In conclusion, this was the first multi-center evaluation of the association of *KRAS* and *NRAS* gene SNPs with Wilms tumor susceptibility.  Our study has provided the first evidence that *KRAS* gene SNPs may increase Wilms tumor susceptibility.  Ongoing epidemiological studies in other independent populations are warranted prior to extrapolation of the current conclusions. 

MATERIALS AND METHODS
=====================

Study subjects
--------------

In total, 355 cases and 1070 healthy controls were included in this study ([Supplemental Table 1](#SD1){ref-type="supplementary-material"}).  The subject selection criteria were described in detail in our previous study \[[@r37]--[@r43]\].  In brief, cases with newly diagnosed and histologically confirmed Wilms tumor were recruited from four centers in China (Guangzhou Women and Children's Medical Center \[[@r37]--[@r43]\], The First Affiliated Hospital of Zhengzhou University, The Second Affiliated Hospital and Yuying Children\'s Hospital of Wenzhou Medical University, and The Second Affiliated Hospital of Xi\'an Jiao Tong University).  All the included cases were sporadic cases.  The controls were healthy volunteers without a history of Wilms tumor, matched to the cases by age, gender and city of residency.  All the subjects or their guardians provided written informed consent before participating.  Approval of the study protocol was obtained from the Institutional Review Board of each center prior to the study. 

Polymorphism selection and genotyping
-------------------------------------

We analyzed three potential functional SNPs in the *KRAS* gene and one potential functional SNP in the *NRAS* gene.  SNPs were selected from the NCBI dbSNP database (<http://www.ncbi.nlm.nih.gov/projects/SNP>) and SNPinfo (<http://snpinfo.niehs.nih.gov/snpfunc.htm>).  These four SNPs could capture an additional 89 SNPs with R^2^ ≥ 0.8 ([Supplemental Table 2](#SD1){ref-type="supplementary-material"}).  The selection criteria were set as previously described \[[@r42],[@r44]\].  Genomic DNA was extracted from venous blood with a TIANamp Blood DNA Kit (TianGen Biotech Co. Ltd., Beijing, China).  SNP genotyping was performed with a TaqMan SNP Genotyping Assay (Applied Biosystems, Foster City, CA, USA).  Negative controls with water and 10% replicates were also genotyped to ensure genotyping accuracy.  No discordant genotypes were found in the replicates. 

Statistical analysis
--------------------

Statistical analysis was performed in SAS release 9.1 (SAS Institute, Cary, NC, USA).  The genotype frequency distributions of the polymorphisms were first evaluated among the controls, and Hardy-Weinberg equilibrium was assessed with the χ^2^ test.  The distribution of subject characteristics between cases and controls was examined with a two-sided χ^2^ test.  Unadjusted and adjusted (for age and gender) ORs and 95% CIs were generated for both single and combined SNPs.  We then determined the association of the SNPs with Wilms tumor risk using the OR and 95% CI calculated from multivariable logistic regression analysis.  FPRP analysis was performed as described previously \[[@r45]\].  All results were considered statistically significant if *P*\<0.05. 

SUPPLEMENTARY MATERIAL
======================

**CONFLICTS OF INTEREST:** There are no competing interests to declare. 

**FUNDING:** This study was funded by grants from the National Natural Science Foundation of China (No: 81803320), the Pearl River S&T Nova Program of Guangzhou (No: 201710010086), the Science and Technology Project of Guangzhou (No: 201804010037) and the Science and Technology Planning Project of Guangdong Province (No: 2016A020215009).