Literature DB >> 28881622

Is FTO gene variant related to cancer risk independently of adiposity? An updated meta-analysis of 129,467 cases and 290,633 controls.

Yu Kang1, Fang Liu2, Yao Liu2.   

Abstract

Previous studies have examined the association between the fat mass and obesity-associated (FTO) gene variant and risk of cancer in diverse populations. However, the results have been inconsistent. PubMed and Embase databases were searched for the eligible publications in English language by July, 2016. The associations of FTO variants with cancer risk were estimated by calculating the pooled odds ratios and 95% confidence intervals by meta-analyses. A total of 27 publications (129,467 cancer cases and 290,633 normal controls) were included in our meta-analysis. Overall, FTO rs9939609 variant (or its proxy) was not associated with cancer risk without adjustment for body mass index, as well as additional adjustment for body mss index. However, FTO rs9939609 variant was associated with some types of cancer in the subgroup analysis. In addition, overall, there was no significant association between FTO rs1477196 variant and cancer risk regardless of adjustment for body mass index. However, FTO rs11075995 variant risk allele was associated with breast cancer risk without adjustment for body mass index, but the association disappeared with further adjustment for body mass index. This study overall does not support that the FTO variant is associated with cancer risk independently of the adiposity.

Entities:  

Keywords:  FTO; cancer; meta-analysis; obesity

Year:  2017        PMID: 28881622      PMCID: PMC5584223          DOI: 10.18632/oncotarget.16446

Source DB:  PubMed          Journal:  Oncotarget        ISSN: 1949-2553


INTRODUCTION

In 2007, the fat mass and obesity associated (FTO) gene was reported as the first obesity related gene by the genome-wide association studies (GWAS) in Caucasian population [1, 2]. Subsequently, the following studies confirmed the positive associations between single nucleotide polymorphisms (SNPs) in/near FTO gene and obesity risk in diverse populations [3-5]. FTO gene was found to affect the function of the central nervous system, as well as adipose tissue at a peripheral level. As obesity is a well established risk factor for most types of cancer, it is interesting and important to investigate whether FTO SNPs are associated with risk of cancer. Up to now, a total of 27 publications have examined the associations between FTO SNPs and risk of cancer [6-32]. However, the results have been inconsistent. Three meta-analyses have summarized the associations between FTO SNPs and risk of cancer [33-35]; however, there are several limitations for them. First, they did not address whether the associations were mediated through body mass index (BMI)/obesity. Second, many eligible studies were omitted. Third, two of three from the same study team examined the association between each of two SNPs (rs8050136[34] and rs9939609[35]) in/near FTO gene and cancer risk. It is illogical to do the separate analyses for these two SNPs as they are in strong linkage disequilibrium (LD, r2>0.90) in both European and Asian populations. Therefore, we aimed to perform an updated meta-analysis to investigate the associations between FTO rs9939609 SNP (or any proxy SNP, r2>0.90) and other SNPs which are not in tight LD with rs9939609 SNP (such as rs1477196 and rs11075995) and cancer risk. In addition, we also aimed to examine whether the associations are independent of adiposity.

RESULTS

Characteristics of the studies

A flow chart describing the process of inclusion/exclusion of studies is presented in Figure 1. The literature search identified a total of 238 potentially relevant articles. At last, a total of 27 publications (129,467 cancer cases and 290,633 normal controls) were included in our meta-analysis. There were 24 publications (113780 cases and 210593 controls) for FTO rs9939609 SNP, 5 publications (1594 cases and 2034 controls) for FTO rs1477196 SNP, and 3 publications (14144 cases and 79973 controls) for rs11075995 variant. All three SNPs in the each of included studies were in Hardy-Weinberg Equivalent. The characteristics of the included studies are listed in Table 1.
Figure 1

Flowchart for inclusion/exclusion of studies

Table 1

The detailed characteristics of the included studies in the meta-analysis

Study *CountryEthnicityType ofcancerNo. of casesNo. of controlsOR95% CISNPAdjustmentfor BMI
Brennan, 2009 [6]Czech Republic, Hungary, Poland, Romania, Russia, and SlovakiaEuropeanLung cancer225030520.920.841.00rs9939609No
Brennan, 2009 [6]Czech Republic, Hungary, Poland, Romania, Russia, and SlovakiaEuropeanKidney cancer95430521.060.951.19rs9939609No
Brennan, 2009 [6]Czech Republic, Hungary, Poland, Romania, Russia, and SlovakiaEuropeanUpper aerodigestive cancer81130520.980.871.12rs9939609No
Gaudet, 2010 [7]USA and AustraliaMixedEndometrial cancer4174061.050.861.28rs8050136No
Lewis, 2010 [8]UKEuropeanProstate cancer155018150.940.851.03rs9939609Yes
Meyer, 2010 [9]USAMixedProstate cancer37958741.040.911.20rs8050136No
Delahanty, 2011 [10]ChinaEast AsianEndometrial cancer83220491.070.891.29rs9939609No
Kaklamani, 2011 [11]USAMixedBreast cancer3023490.9920.781.26rs9939609No
0.9750.771.23Yes
1.4081.111.79rs1477196No
1.4471.131.85Yes
Lurie, 2011 [12]Australia, USA, Poland, and CanadaEuropeanEndometrial cancer356151671.070.991.14rs9939609No
1.010.941.08Yes
Pierce, 2011 [13]Finland, USA, China, France, Germany, Greece, Italy, The Netherlands, Spain, and the UKEuropeanPancreatic cancer176318021.121.021.23rs8050136No
Tang, 2011 [14]USAMixedPancreatic cancer105311301.080.961.22rs9939609No
1.030.801.30Yes
Brooks, 2012 [15]USA and DenmarkEuropeanBreast cancer64312711.10.91.3rs9939609No
Hubacek, 2012 [16]Czech Republic, Hungary, Poland, Romania, Russia, and SlovakiaEuropeanColorectal cancer100568271.020.931.13rs17817449No
Kitahara, 2012 [17]USAEuropeanThyroid cancer3414440.770.620.94rs9939609No
0.760.610.93Yes
1.311.071.61s1477196No
1.321.071.61Yes
Kusinska, 2012 [18]PolandEuropeanBreast cancer1343571.050.681.61rs9939609No
Lim, 2012 [19]USAMixedColorectal cancer203396401.020.931.11rs9939609No
Machiela, 2012 [20]USA and several European countriesEuropeanProstate cancer278244580.930.861.00rs9939609Yes
Tarabra, 2012 [21]ItalyEuropeanColorectal cancer3413111.010.811.25rs9939609No
Akilzhanova, 2013 [22]KazakhstanEuropeanBreast cancer3156040.960.781.17rs1477196No
0.960.781.17Yes
da Cunha, 2013 [23]BrazilEuropeanBreast cancer1001480.860.601.25rs9939609No
0.870.611.26Yes
Garcia-Closas, 2013 [24]USA and many European countriesEuropeanBreast cancer10706766471.111.071.15rs11075995No
3071201301.161.091.24Yes
Iles, 2013 [25]European countriesEuropeanMelanoma13060607261.030.971.10rs8050136No
Lin, 2013 [26]JapanEast AsianPancreatic cancer3604001.331.041.72rs9939609No
1.411.071.85Yes
Long, 2013 [27]USAAfricanBreast cancer11139301.211.061.37rs17817449Yes
Zheng, 2013 [28]China, Korea, Japan and ThailandEast AsianBreast cancer16797189830.920.880.97rs17817449No
Zhang, 2014 [29]ChinaEast AsianBreast cancer290127891.060.981.14rs11075995No
Mojaver, 2015 [30]IranMiddle EastBreast cancer991000.850.511.41rs9939609No
1.2150.6832.161Yes
1.140.642.01rs1477196No
0.8900.4641.707Yes
Zeng,2015 [31]ChinaEast AsianBreast cancer5375371.190.901.57rs9939609No
1.180.891.56Yes
0.730.580.93rs1477196No
0.750.590.96Yes
0.900.711.15rs11075995No
0.940.731.20Yes
Zhao, 2016[32]Several European countriesEuropeanBreast cancer62328838170.940.920.95rs9939609No

* All included studies were case-control designed.

* All included studies were case-control designed.

Meta-analysis results

Overall, FTO rs9939609 SNP was not associated with cancer risk without adjustment for BMI (OR=1.01, 95%CI=0.97-1.05). In the subgroup analysis by race/ethnicity, before adjustment for BMI, there was no any significant associations in European population, East Asian population, Middle East population and mixed population (all P>0.05) (Figure 2). After adjustment for BMI, FTO rs9939609 SNP risk allele was associated with cancer risk in East Asian population (OR=1.29, 95%CI=1.06-1.57) and African population (OR=1.21, 95%CI=1.06-1.38), but not in European population, Middle East population and Mixed population (all P>0.05) (Figure 3). In the subgroup analysis by cancer type, FTO rs9939609 SNP risk allele marginally increased risk of endometrial cancer (OR=1.07, 95%CI=1.00-1.14) and pancreatic cancer (OR=1.12, 95%CI=1.04-1.21), while it marginally decreased risk of breast cancer (OR=0.94, 95%CI=0.92-0.96) (Table 2 and Supplementary Figure 1). Overall, there was also no significant association between FTO rs9939609 SNP and cancer risk with adjustment for BMI (OR=1.01, 95%CI=0.93-1.10). FTO rs9939609 SNP risk allele marginally decreased risk of prostate cancer (OR=0.93, 95%CI=0.88-0.99), while it marginally increased risk of breast cancer (OR=1.12, 95%CI=0.99-1.26) (Table 2 and Supplementary Figure 2).
Figure 2

Forest plot of the effect of FTO rs9939609 on risk of cancer by race/ethnicity without adjustment for body mass index

Figure 3

Forest plot of the effect of FTO rs9939609 on risk of cancer by race/ethnicity with adjustment for body mass index

Table 2

Associations between FTO variants and cancer risk by cancer type

OR95% CII2 (%)P for heterogeneity
rs9939609
 Before BMI adjustment
  All1.010.97-1.0565.8<0.001
  Endometrial cancer1.071.00-1.1400.985
  Breast cancer0.940.92-0.961.80.416
  Pancreatic cancer1.121.04-1.216.80.342
  Colorectal cancer1.020.96-1.0900.996
  Others0.980.92-1.0557.40.038
 After BMI adjustment
  All1.010.93-1.1064.90.001
  Breast cancer1.120.99-1.2614.20.324
  Pancreatic cancer1.200.88-1.6364.70.093
  Prostate cancer0.930.88-0.9900.864
  Others0.890.68-1.1884.10.012
rs1477196
 Before BMI adjustment
  All1.070.97-1.2080.1<0.001
  Breast cancer1.000.88-1.1380.20.002
  Thyroid cancer1.311.07-1.61--
 After BMI adjustment
  All1.080.97-1.2179.40.001
  Breast cancer1.000.88-1.1479.10.002
  Thyroid cancer1.321.08-1.62--
rs11075995
 Before BMI adjustment
  Breast cancer1.081.01-1.1547.20.150
  After BMI adjustment
  Breast cancer1.080.89-1.3161.20.108
There was no significant association between FTO rs1477196 SNP and cancer risk without (OR=1.07, 95%CI= 0.97-1.20) or with (OR=1.08, 95%CI=0.97-1.21) adjustment for BMI. However, we found a significant association between FTO rs1477196 SNP and risk of thyroid cancer without (OR=1.31, 95%CI=1.07-1.61) or with (OR=1.32, 95%CI=1.08-1.62) adjustment for BMI (Table 2 and Supplementary Figures 3-4). FTO rs11075995 SNP risk allele was associated with breast cancer risk without adjustment for BMI (OR=1.08, 95%CI=1.01-1.15) (Table 2 and Supplementary Figure 5). However, the significant association disappeared after adjustment for BMI (OR=1.08, 95%CI=0.89-1.31) (Table 2 and Supplementary Figure 6).

Publication bias

There was no publication bias for FTO rs9939609, rs1477196 or rs11075995 SNP using Begg's test or Egger's test (all P>0.05).

DISCUSSION

Our updated meta-analysis shows that FTO rs9939609 SNP was associated with some types of cancer, such as endometrial cancer, pancreatic cancer and breast cancer without adjustment for BMI, while it was still associated with breast cancer and prostate cancer with adjustment for BMI. In addition, FTO rs1477196 SNP was associated with thyroid cancer independently of BMI and FTO rs11075995 SNP was associated with breast cancer dependently on BMI. Several meta-analyses have addressed the association between FTO SNP and risk of diabetes, [36] hypertension, [37] cardiovascular disease, [38] polycystic ovary syndrome [39] and mortality [40]. Most of these meta-analyses supported FTO SNP was associated with health outcomes independently of adiposity. A meta-analysis of data from 169,551 Caucasian adults showed that the hazards ratio (HR) for the A minor allele of the FTO rs9939609 SNP was 1.02 (1.00–1.04, P=0.097), but the association disappeared after adjustment for BMI (HR=1.00; 0.98–1.03, P=0.662) [40]. These results suggested that FTO SNP risk allele increases risk of mortality directly through adiposity pathway. It seemed that FTO rs9939609 SNP played different roles in the development of different cancer, as well as in different populations. Previous studies demonstrated that BMI was associated with risk of common cancer, but its association with some cancer types differed between sexes and different ethnic populations [41]. As FTO SNP rs9939609 was strongly associated with BMI, it is not surprising that this variant was associated with some types of cancer but not with other types of cancer. The FTO protein is highly expressed in hypothalamus, as well as in many other tissues: mesenteric fat, adipose, pancreatic, and liver. It regulates the global metabolic rate, energy expenditure, energy homeostasis, body size and body fat accumulation [42]. FTO rs8050136 was reported to preferentially bind to cut-like homeobox (CUTL1) in human fibroblast DNA and silencing this transcriptional factor CUTL1 could lead to decreased FTO expression in fibroblasts [43]. In addition, FTO SNP was strongly associated with expression of a tumor suppressor/cell cycle-repressing gene, namely retinoblastoma-like 2 [44]. Further studies are necessary to clarify the underlying mechanism between FTO SNP and cancer risk. Our study has several strengths. First, our study included 27 publications consisting of ~130, 000 cases and ~300,000 controls, which had the larger statistical power than three previous meta-analyses [33-35]. Second, we presented results without and with adjustment for BMI, but the previous three meta-analyses didn’t. Third, besides rs9939609 and its proxy SNP (rs8050136 and rs17817449), we also investigated two other SNPs (rs1477196 or rs11075995), which are not in high LD with rs9939609. However, several limitations should be noted. First, the effects of gene-gene/gene-environment interactions were not addressed in this meta-analysis as the included individual studies did not provided us with these data. Second, although the total sample size was large enough, it was still limited for some types of cancer. Thus, the subgroup results with limited statistical power should be interpreted with caution. Third, there was significant heterogeneity between studies for three SNPs and the results should be interpreted cautiously. In conclusion, our updated meta-analysis supported that FTO SNP was associated with some types of cancer, which was mediated by BMI or independent of BMI. Further studies should focus on gene-gene/gene-environment interaction in the development of cancer. Epigenetics and metabonomics should be paid more attention in order to solve how BMI modify the association between FTO SNP and cancer risk.

MATERIALS AND METHODS

Literature and search strategy

We searched PubMed and Embase databases for the potentially eligible studies. The following key words were used to search the eligible publications: (fat-mass and obesity-associated gene OR FTO) and (polymorphism OR variant OR variation OR genotype) and (cancer OR tumor OR carcinoma). We restricted publication language to English. The reference lists of retrieved articles were also hand-searched. The literature search was updated by July 14, 2016.

Inclusion criteria and data extraction

The included studies met all the following inclusion criteria: (1) investigation of the association of FTO rs9939609 SNP (or any proxy SNP (rs8050136, rs17817449), r2>0.90) or other SNPs which are not in tight LD with rs9939609 (such as rs1477196 and rs11075995) with cancer risk; (2) use of a case–control or cohort design; and (3) provision of an odds ratio (OR) with 95% confidence interval (CI) with or without adjustment for body mass index (BMI). The following information was extracted from each study: (1) name of the first author; (2) year of publication; (3) country of origin; (4) race/ethnicity of the study population; (5) number of cases and controls; (6) type of cancer; (7) studied SNP; and (8) whether adjusted for BMI in the logistical regression model. Two authors independently reviewed the articles for compliance with the inclusion/exclusion criteria, resolved disagreements and reached a consistent decision after discussion with the third author.

Statistical analysis

The associations of FTO SNPs with cancer risk were estimated by calculating the pooled ORs and 95% CIs under an additive genetic model. The significance of the OR was determined by the Z test (p<0.05 was considered statistically significant). Cochrane's Q test was performed to test the between-study heterogeneity [45, 46]. I2 represents the range for degree of heterogeneity. A random-effects (DerSimonian–Laird [45]) or fixed-effects (Mantel–Haenszel [46]) model was used to calculate the pooled OR in the presence (p≤0.10 or I2≥50%) or absence (p>0.10 and I2<50%) of heterogeneity, respectively. Publication bias was assessed by Begg's test and Egger's test [47] (p<0.05 was considered statistically significant). Data were analyzed using STATA version 11.0 (StataCorp LP, College Station, TX, USA).
  47 in total

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Authors:  Zhiguo Zhao; Wanqing Wen; Kyriaki Michailidou; Manjeet K Bolla; Qin Wang; Ben Zhang; Jirong Long; Xiao-Ou Shu; Marjanka K Schmidt; Roger L Milne; Montserrat García-Closas; Jenny Chang-Claude; Sara Lindstrom; Stig E Bojesen; Habibul Ahsan; Kristiina Aittomäki; Irene L Andrulis; Hoda Anton-Culver; Volker Arndt; Matthias W Beckmann; Alicia Beeghly-Fadiel; Javier Benitez; Carl Blomqvist; Natalia V Bogdanova; Anne-Lise Børresen-Dale; Judith Brand; Hiltrud Brauch; Hermann Brenner; Barbara Burwinkel; Qiuyin Cai; Graham Casey; Georgia Chenevix-Trench; Fergus J Couch; Angela Cox; Simon S Cross; Kamila Czene; Thilo Dörk; Martine Dumont; Peter A Fasching; Jonine Figueroa; Dieter Flesch-Janys; Olivia Fletcher; Henrik Flyger; Florentia Fostira; Marilie Gammon; Graham G Giles; Pascal Guénel; Christopher A Haiman; Ute Hamann; Patricia Harrington; Mikael Hartman; Maartje J Hooning; John L Hopper; Anna Jakubowska; Farzana Jasmine; Esther M John; Nichola Johnson; Maria Kabisch; Sofia Khan; Muhammad Kibriya; Julia A Knight; Veli-Matti Kosma; Mieke Kriege; Vessela Kristensen; Loic Le Marchand; Eunjung Lee; Jingmei Li; Annika Lindblom; Artitaya Lophatananon; Robert Luben; Jan Lubinski; Kathleen E Malone; Arto Mannermaa; Siranoush Manoukian; Sara Margolin; Frederik Marme; Catriona McLean; Hanne Meijers-Heijboer; Alfons Meindl; Hui Miao; Kenneth Muir; Susan L Neuhausen; Heli Nevanlinna; Patrick Neven; Janet E Olson; Barbara Perkins; Paolo Peterlongo; Kelly-Anne Phillips; Katri Pylkäs; Anja Rudolph; Regina Santella; Elinor J Sawyer; Rita K Schmutzler; Minouk Schoemaker; Mitul Shah; Martha Shrubsole; Melissa C Southey; Anthony J Swerdlow; Amanda E Toland; Ian Tomlinson; Diana Torres; Thérèse Truong; Giske Ursin; Rob B Van Der Luijt; Senno Verhoef; Shan Wang-Gohrke; Alice S Whittemore; Robert Winqvist; M Pilar Zamora; Hui Zhao; Alison M Dunning; Jacques Simard; Per Hall; Peter Kraft; Paul Pharoah; David Hunter; Douglas F Easton; Wei Zheng
Journal:  Cancer Causes Control       Date:  2016-04-06       Impact factor: 2.506

Review 2.  Single nucleotide polymorphisms of the FTO gene and cancer risk: an overview.

Authors:  Marta Elena Hernández-Caballero; José Alfredo Sierra-Ramírez
Journal:  Mol Biol Rep       Date:  2014-11-12       Impact factor: 2.316

3.  Operating characteristics of a rank correlation test for publication bias.

Authors:  C B Begg; M Mazumdar
Journal:  Biometrics       Date:  1994-12       Impact factor: 2.571

4.  Association study of susceptibility loci with specific breast cancer subtypes in Chinese women.

Authors:  Bo Zhang; Yang Li; Longnian Li; Mengyun Chen; Cuicui Zhang; Xian-bo Zuo; Fu-sheng Zhou; Bo Liang; Jun Zhu; Pan Li; Zhong-lian Huang; Han Xuan; Wei Li; Zhen-dong Chen
Journal:  Breast Cancer Res Treat       Date:  2014-07-10       Impact factor: 4.872

5.  Regulation of Fto/Ftm gene expression in mice and humans.

Authors:  George Stratigopoulos; Stephanie L Padilla; Charles A LeDuc; Elizabeth Watson; Andrew T Hattersley; Mark I McCarthy; Lori M Zeltser; Wendy K Chung; Rudolph L Leibel
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2008-02-06       Impact factor: 3.619

6.  Association of type 2 diabetes susceptibility variants with advanced prostate cancer risk in the Breast and Prostate Cancer Cohort Consortium.

Authors:  Mitchell J Machiela; Sara Lindström; Naomi E Allen; Christopher A Haiman; Demetrius Albanes; Aurelio Barricarte; Sonja I Berndt; H Bas Bueno-de-Mesquita; Stephen Chanock; J Michael Gaziano; Susan M Gapstur; Edward Giovannucci; Brian E Henderson; Eric J Jacobs; Laurence N Kolonel; Vittorio Krogh; Jing Ma; Meir J Stampfer; Victoria L Stevens; Daniel O Stram; Anne Tjønneland; Ruth Travis; Walter C Willett; David J Hunter; Loic Le Marchand; Peter Kraft
Journal:  Am J Epidemiol       Date:  2012-11-28       Impact factor: 4.897

7.  Association of FTO Mutations with Risk and Survival of Breast Cancer in a Chinese Population.

Authors:  Xianxu Zeng; Zhenying Ban; Jing Cao; Wei Zhang; Tianjiao Chu; Dongmei Lei; Yanmin Du
Journal:  Dis Markers       Date:  2015-06-04       Impact factor: 3.434

8.  Variation in FTO contributes to childhood obesity and severe adult obesity.

Authors:  Christian Dina; David Meyre; Sophie Gallina; Emmanuelle Durand; Antje Körner; Peter Jacobson; Lena M S Carlsson; Wieland Kiess; Vincent Vatin; Cecile Lecoeur; Jérome Delplanque; Emmanuel Vaillant; François Pattou; Juan Ruiz; Jacques Weill; Claire Levy-Marchal; Fritz Horber; Natascha Potoczna; Serge Hercberg; Catherine Le Stunff; Pierre Bougnères; Peter Kovacs; Michel Marre; Beverley Balkau; Stéphane Cauchi; Jean-Claude Chèvre; Philippe Froguel
Journal:  Nat Genet       Date:  2007-05-13       Impact factor: 38.330

Review 9.  The FTO gene rs9939609 polymorphism predicts risk of cardiovascular disease: a systematic review and meta-analysis.

Authors:  Chibo Liu; Sihua Mou; Chunqin Pan
Journal:  PLoS One       Date:  2013-08-19       Impact factor: 3.240

Review 10.  FTO gene variant and risk of overweight and obesity among children and adolescents: a systematic review and meta-analysis.

Authors:  Chibo Liu; Sihua Mou; Yangqun Cai
Journal:  PLoS One       Date:  2013-11-22       Impact factor: 3.240

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2.  Fat mass and obesity-associated gene polymorphisms, pre-diagnostic plasma adipokine levels and the risk of colorectal cancer: The Japan Public Health Center-based Prospective Study.

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Review 3.  The Potential Role of N6-Methyladenosine (m6A) Demethylase Fat Mass and Obesity-Associated Gene (FTO) in Human Cancers.

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4.  The association between fat mass and obesity-associated (FTO) genotype and serum vitamin D level in breast cancer patients.

Authors:  Maryam Gholamalizadeh; Zohreh Mokhtari; Saeid Doaei; Vahideh Jalili; Sayed Hossein Davoodi; Mona Jonoush; Mohammad Esmail Akbari; Azadeh Hajipour; Bojlul Bahar; Ghasem Azizi Tabesh; Saeed Omidi; Seyed Alireza Mosavi Jarrahi
Journal:  J Cell Mol Med       Date:  2021-09-06       Impact factor: 5.310

Review 5.  RNA N6-methyladenosine modification in solid tumors: new therapeutic frontiers.

Authors:  Laleh Melstrom; Jianjun Chen
Journal:  Cancer Gene Ther       Date:  2020-01-20       Impact factor: 5.987

Review 6.  The dual role of N6-methyladenosine modification of RNAs is involved in human cancers.

Authors:  Liujia He; Jiangfeng Li; Xiao Wang; Yufan Ying; Haiyun Xie; Huaqing Yan; Xiangyi Zheng; Liping Xie
Journal:  J Cell Mol Med       Date:  2018-07-24       Impact factor: 5.310

Review 7.  Critical Enzymatic Functions of FTO in Obesity and Cancer.

Authors:  Xiaolan Deng; Rui Su; Savanna Stanford; Jianjun Chen
Journal:  Front Endocrinol (Lausanne)       Date:  2018-07-30       Impact factor: 5.555

8.  Postmenopausal estrogen receptor positive breast cancer and obesity associated gene variants.

Authors:  Asuman Özgöz; Fadime Mutlu Içduygu; Aysegül Yükseltürk; Hale Samli; Kuyas Hekimler Öztürk; Zuhal Baskan; Ilknur Tütüncü
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