Research ArticleExperimental Studies

Novel Prognostic Implications of Methylated RNA and Demethylases in Resected HCC and Background Liver Tissue

NOBUHIKO NAKAGAWA, KATSUHITO TANAKA, FUMINORI SONOHARA, RAJU KANDIMALLA, YUKI SUNAGAWA, YOSHIKUNI INOKAWA, HIDEKI TAKAMI, MASAMICHI HAYASHI, SUGURU YAMADA, MITSURO KANDA, CHIE TANAKA, GORO NAKAYAMA, MASAHIKO KOIKE and YASUHIRO KODERA
Anticancer Research December 2020, 40 (12) 6665-6676; DOI: https://doi.org/10.21873/anticanres.14690

Abstract

Background/Aim: N6-Methyladenosine (m6A), the most abundant internal modification of RNA, plays a critical role in cancer development. However, the clinical implications of m6A in hepatocellular carcinoma (HCC) remain unclear. Materials and Methods: We analyzed 177 HCC and paired noncancerous liver tissues from patients who underwent hepatectomy according to global m6A quantification and expression of m6A demethylases fat mass and obesity-associated protein (FTO) and alpha-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5). Results: The global m6A quantification revealed no significant difference between HCC and non-cancerous tissue. The expression of m6A demethylases FTO and ALKBH5, was significantly lower in HCC than in non-cancerous tissues (both p<0.001). Furthermore, low ALKBH5 expression in non-cancerous tissues was significantly correlated with worse recurrence-free survival (median of 16.3 vs. 38.9 months, p=0.001). Conclusion: m6A in HCC and its demethylase in surrounding non-cancerous liver tissues might be involved in inherent mechanisms for HCC development and affect malignant potential after HCC resection.

Key Words:

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. It represents the fifth most common malignancy and the second most common cause of cancer-related death worldwide (1). Although the guidelines recommend several treatment options for HCC (2-4), surgical resection is deemed as the most effective therapy to prolong patient survival. Generally, HCC is accompanied by background chronic hepatitis caused by viral infection and alcoholic or nonalcoholic fatty liver disease. Due to these background disorders, the possibility of postoperative recurrence including metachronous disease is relatively high, and the survival rate for patients with HCC following surgery is less than 50% (5). Therefore, further understanding of the molecular mechanism of HCC initiation and progression from the viewpoint not only of the malignant potential of HCC itself but also of the background liver disorders is warranted.

Epigenetic changes such as DNA methylation (6), chromatin remodeling (7), histone modification (8) and regulation by non-coding RNA (9) that do not involve changes to the underlying DNA sequence have been extensively studied in the context of carcinogenesis and cancer progression. Currently, DNA methylation is one of the most broadly studied and well-characterized epigenetic mechanisms in cancer development (10). RNA methylation has been recognized since the 1970s (11, 12). However, unlike DNA methylation, the role of RNA methylation in biological processes has only recently been uncovered. Among various types of post-transcriptional mRNA modifications, methylation of N6 adenosine (m6A) is the most abundant form in the mRNA of many eukaryotic species (13, 14). m6A methylation is involved in mRNA splicing, degradation and translation; lower m6A methylation is correlated with cell pluripotency and m6A increases during differentiation (15, 16). Recent studies demonstrate abnormal m6A to be found in many malignancies such as gastric, prostate, breast and pancreatic cancer, as well as leukemia (17-21). However, reflecting the diverse role of the m6A methylation, its association with prognosis may differ depending on the type of cancer.

The regulation of m6A methylation is determined by the interplay among m6A methyltransferases, binding proteins, demethylases (22-24) and m6A methylation itself. Of late, there has been a growing interest in these m6A-associated systems in terms of human malignancies (25). Notably, demethylases such as fat mass and obesity-associated protein (FTO) and alpha-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5) were recently found to have roles in m6A methylation and, additionally, in carcinogenesis (26, 27).

In the current study, we assessed the expression of these m6A demethylases and the level of global m6A methylation both in resected HCC tissues and paired non-cancerous liver tissues collected from patients who underwent curative HCC surgery. We also sought to discover novel prognostic implications of m6A methylation that might be used to predict prognosis in patients with HCC.

Materials and Methods

Patients and samples. A total of 177 frozen tumor specimens and the paired para-tumoral non-cancerous tissues were collected from patients with HCC who underwent surgery at Nagoya University Hospital between January 1998 and April 2014. All fresh tissues were immediately frozen in liquid nitrogen and stored at −80°C until required. Patient characteristics are summarized in Table I. After surgery, all patients were monitored by performing blood examinations, ultrasonography, and computed tomography. Angiography was performed for further information whenever recurrence was suspected. The median follow-up duration of cases overall was 48.8 months (range=0.3 to 191 months). A total of 92 (52.0%) patients died and 123 (69.4%) patients had recurrence. This study and all procedures were approved by the Institutional Review Board at Nagoya University (approval number 2013-0295) and all patients provided written informed consent. All clinical investigations were conducted in accordance with the principles of the Declaration of Helsinki.

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Table I.

Characteristics of patients with hepatocellular carcinoma (n=177).

RNA isolation and reverse transcription quantitative polymerase chain reaction (RT-qPCR). Total RNA was extracted from tissue samples using a Qiagen miRNeasy mini-kit (Qiagen, Hilden, Germany) (28). We used DNase in extracting total RNA and RNA quality was analyzed by NanoDrop (Thermo Scientific Fisher, Waltham, MA, USA). Total RNA was converted to complementary DNA by reverse-transcription with Moloney murine leukemia virus reverse transcriptase (Invitrogen, Carlsbad, CA, USA). This total cDNA was used as a template for the next step of quantitative PCR. PCR was performed using SYBR Premix Ex Taq II (Takara Clontech, Kyoto, Japan) under the following conditions: denaturation at 95°C for 10 s, 40 cycles of denaturation at 95°C for 5 s, and annealing/extension at 60°C for 30 s. The SYBR Green signal was detected in real-time using StepOne Plus Real-Time PCR System (Life Technologies, Carlsbad, CA, USA). The relative quantification method was used and expression of each gene was determined relative to the expression of the target gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) for each sample. The relative gene-expression levels were determined using comparative threshold cycle (2−ΔCT) method (29).

The PCR primers used in the current study for the 57 base-pair fragment of FTO were sense: 5’-TATAGCTGTGAAGGCCCTGAA-3’ and antisense: 5’-CCTGCCTTCGAGATGAGAGTC-3’; and for the 57 base pairs fragment of ALKBH5 were sense, 5’-GTGCTCAG TGGATATGCTGC-3’ and antisense: 5’-GATGTCCTGAGGCCG TATGC-3’. GAPDH (sense: 5’-GAGTCCACTGGCGTCTTCAC-3’; antisense: 5’-GTTCACACCCATGACGAACA-3’) expression was quantified in each sample in order to perform the normalization. All primers for qPCR were intron-spanning. All RT-qPCR assays were performed in duplicate, including the template-omitted negative controls.

Publicly available dataset. The Cancer Genome Atlas (TCGA) RNA-sequencing data for HCC were downloaded from the Broad GDAC Firehose (http://gdac.broadinstitute.org/, accessed on January 1st, 2019). This dataset included 360 HCC cases including seven HCCs mixed with hepatocholangiocarcinoma and two cases with fibrolamellar carcinoma. Of the 360 cases, 266 cases had information on recurrence-free survival (RFS) and 336 cases on overall survival (OS).

Global m6A quantification. The relative content of m6A in the total RNA was measured using EpiQuik m6A RNA Methylation Quantification Kit (Colorimetric) (P-9005; Epigentek, NY, USA) as per the manufacturer’s instructions. Briefly, 200 ng RNA were coated onto assay wells. Capture antibody solution and detection antibody solution were then added to assay wells separately in a suitably diluted concentration following the manufacturer’s instructions. The m6A levels were quantified colorimetrically by reading the absorbance of each well at a wavelength of 450 nm, and then calculations were performed based on the standard curve.

Statistical analysis. Continuous variables are expressed as median (range) and expression of each target gene was compared by a Wilcoxon signed-rank test. Categorical variables were compared using the chi-squared or Fisher’s exact tests, as appropriate. Correlation between expression of each gene and global m6A level was analyzed with Spearman’s rank correlation coefficient. RFS was defined as the time between curative resection of HCC and confirmation of recurrence. Overall survival (OS) was defined as the time between surgery and all-cause death. OS and RFS rate at each point of the follow-up time were estimated using the Kaplan–Meier method and compared using a log-rank test. The Cox proportional hazard regression model was used to perform univariate and multivariate analysis for OS and RFS. Variables with p<0.05 in univariate analysis and conventional risk factors for HCC were selected for multivariate analysis. All statistical analyses were performed using R version 3.5.3 (http//www.r-project.org/) and statistical significance was set at p<0.05, which was obtained using two-tailed tests.

Results

Global m6A quantification in resected specimens from patients with HCC. Resected HCC cases in this study included 41 hepatitis B virus (23%), 106 hepatitis C virus (60%), and 30 non-viral hepatitis cases (17%). Among 177 cases, 91 were used for global m6A quantification. The relative content of m6A in total RNA from HCC and background normal tissues was examined. The m6A quantification revealed no significant difference in the amount of m6A between HCC and the corresponding noncancerous tissues (p=0.79, Figure 1A). The cases were then stratified by the median m6A amount in HCC and background non-cancerous tissues, and survival analyses were performed. There was no significant difference in survival when patients were stratified by the m6A content in non-cancerous liver tissues (Figure 1B). However, patients with high m6A in HCC tissues tended to have inferior RFS, which translated into significantly inferior OS [RFS, median survival time (MST)=31 vs. 14 months, p=0.13; OS, MST=not reached vs. 32 months, p=0.009, Figure 1C].

Figure 1.
Figure 1.

Global N6-methyladenosine (m6A) levels in individual (upper panel) and paired (lower panel) hepatocellular carcinoma tissues (T) and non-cancerous adjacent tissue (N) (A). Analysis of recurrence free survival (RFS) and overall survival (OS) using Kaplan–Meier curves for 91 patients with hepatocellular carcinoma based on global m6A levels in non-cancerous tissues (B) and tumor tissues (C).

FTO and ALKBH5 expression levels and correlation with HCC prognosis in a publicly available dataset. Considering their potential importance in HCC development, we focused on m6A demethylases for further analyses in this study. We analyzed the expression levels of FTO and ALKBH5 in HCC and non-cancerous tissues using the TCGA RNA-sequence dataset. This analysis revealed that expression of FTO and ALKBH5 were significantly lower in HCC tumor tissues when compared with non-cancerous tissues (FTO, p<0.001; ALKBH5, p=0.02, Figure 2A). In addition, we confirmed the prognostic impact of FTO and ALKBH5 expression on resected HCC cases using the same TCGA dataset. Based on the normalized RNA-sequencing data, HCC cases were divided into two groups by the median value of FTO and ALKBH5 expression in HCC tissues. This analysis revealed that the cases with low ALKBH5 expression tended to have worse RFS (MST=636 vs. 893 days, p=0.09; Figure 2B) while FTO expression was not associated with RFS (MST=1,032 vs. 658 days, p=0.66; Figure 2C). In this HCC dataset, there was no significant difference in OS according to expression of ALKBH5 and FTO (ALKBH5: MST=1,624 vs. 2,131 days, p=0.23; FTO: MST=1,694 vs. 1,791 days, p=0.88).

Figure 2.
Figure 2.

Relative expression of alkB homolog 5 (ALKBH5) and fat mass and obesity-associated protein (FTO) in The Cancer Genome Atlas dataset paired hepatocellular carcinoma tissues (T) and non-cancerous adjacent tissue (N) (A). Survival analysis using Kaplan–Meier curves for recurrence free survival (RFS) of The Cancer Genome Atlas dataset based on ALKBH5 (B) and FTO (C) expression.

FTO and ALKBH5 in resected specimens from patients with HCC. Next, expression analyses of m6A demethylases were conducted with our surgically resected specimens. The expression levels of ALKBH5 and FTO were measured by qPCR. The expression of both FTO and ALKBH5 were significantly lower in tumor tissues than in non-cancerous tissues (p<0.001, Figure 3). Thus, FTO and ALKBH5 in HCC tissues were significantly down-regulated both in TCGA dataset and in our resected cases.

Figure 3.
Figure 3.

Relative expression of alkB homolog 5 (ALKBH5) and fat mass and obesity-associated protein (FTO) in individual (A) and paired (B) hepatocellular carcinoma tissues (T) and non-cancerous adjacent tissue (N).

FTO and ALKBH5 stratified by clinical features are shown in Table II. In non-cancerous tissues, low FTO expression was significantly associated with lower prothrombin time (23% vs. 1%) and poor differentiation (13% vs. 3%), while low ALKBH5 expression was associated with younger age (58% vs. 40%), and higher stage (45% vs. 29%). In HCC tissues, low FTO expression was significantly associated with male sex (89% vs. 74%), larger tumor size (93% vs. 77%), higher alpha-fetoprotein (AFP) (56% vs. 35%), positive septal formation (78% vs. 60%) and higher stage (45% vs. 28%); low ALKBH5 expression was also significantly associated with male sex (92% vs. 75%), larger tumor size (91% vs. 78%), higher AFP (55% vs. 35%), positive septal formation (77% vs. 62%) and higher stage (45% vs. 27%), as well as portal or hepatic vein invasion (35% vs. 19%). Briefly, lower expression of FTO and ALKBH5 both in HCC and in non-cancerous tissues tended to be associated with a higher proportion of worse HCC features such as large tumor size, venous invasion, high serum AFP, and worse stage.

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Table II.

Clinical features stratified by expression of methylated N6 adenosine demethylases.

Prognostic significance of FTO and ALKBH5 in resected HCC cases. Based on the results obtained by the qPCR, the 177 HCC cases were divided into two groups by the median value of FTO and ALKBH5 expression in tumor tissues and in non-cancerous tissues. The effects of the expression levels on RFS and OS were then evaluated. In non-cancerous tissues, low ALKBH5 expression correlated significantly with shorter RFS (MST=16.3 vs. 38.9 months, p=0.001, Figure 4A). A similar tendency (p=0.09) was observed for low ALKBH5 expression in non-cancerous tissues (MST=64.1 vs. 136.2 months, Figure 4A). FTO expression in non-cancerous tissues was not significantly correlated with RFS or OS (RFS: MST=25.2 vs. 20.1 months; Figure 4B). In tumor tissues, survival was not significantly correlated with FTO expression nor ALKBH5 expression (FTO: RFS: MST=31.3 vs. 19.3 months; OS: MST=98.4 vs. 88.5 months; ALKBH5: RFS: MST=23.7 vs. 24.8 months; OS: MST=66.3 vs. 119 months, Figure 4C and D).

Figure 4.
Figure 4.

Kaplan–Meier analysis of RFS (A) and OS (B) for 177 patients with hepatocellular carcinoma (HCC) based on alkB homolog 5 (ALKBH5) and fat mass and obesity-associated protein (FTO) expression in hepatocellular carcinoma tissues (T) and non-cancerous adjacent tissue (N).

Cox regression analysis for survival in HCC. Since survival curves showed that ALKBH5 expression levels in noncancerous tissues and global m6A level in tumor tissues were correlated with survival, we performed Cox proportional-hazards analyses to further investigate the prognostic value of ALKBH5 and global m6A. Multivariate analysis identified indocyanine green 15-minute clearance rate (ICG-R15) [hazard ratio (HR)=1.88, 95% confidence interval (CI)=1.10-3.22], liver cirrhosis (HR=1.99, 95% CI=1.27-3.12), portal or hepatic vein invasion (HR=2.00, 95% CI=1.17-3.43), and ALKBH5 expression in non-cancerous tissues (HR=2.07, 95% CI=1.31-3.26) as significant independent factors for RFS (Table III) and hepatitis C virus infection (HR=2.14, 95% CI=1.09-4.18), serum AFP (HR=2.10, 95% CI=1.10-4.02), poor differentiation (HR=3.93, 95% CI=1.33-11.6), portal vein invasion (HR=2.46, 95% CI=1.21-4.99), and positive surgical margin (HR=2.81, 95% CI=1.18-6.70) as significant (p<0.05) independent factors for OS (Table IV). Consequently, low expression of ALKBH5 in non-cancerous liver tissues was significantly associated with recurrence after HCC surgery.

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Table III.

Univariate and multivariate Cox proportional-hazard regression analyses of recurrence-free survival.

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Table IV.

Univariate and multivariate Cox proportional-hazard regression analyses of overall survival.

Discussion

In this study, we primarily evaluated the clinical implications of RNA methylation and RNA demethylases on resected HCC cases. HCC is generally associated with chronic hepatitis induced by viral infection, alcoholic hepatitis, and non-alcoholic steatohepatitis. Based on the nature of the background inflammatory condition, HCC can easily cause heterochronic intrahepatic recurrence even after complete resection of primary HCC. We firstly evaluated the global m6A amount in our resected HCC specimens and our findings suggested that this was not significantly different between HCC tissues and non-cancerous liver tissues. Survival analysis according to the amount of global m6A showed that a high level of global m6A in HCC tissue was associated with worse RFS and OS. Then we further analyzed the expression of m6A demethylase genes which might play key roles in regulating m6A methylation. The expression of ALKBH5 and FTO was found to be significantly lower in HCC tissues, implying that a high amount of m6A methylation in HCC was caused by down-regulation of these demethylases. However, despite our expectation, we found only a low correlation between the global m6A amount and expression of these demethylases in both HCC and non-cancerous tissues. High expression of de-methylases might not simply contribute to the increase of methylation and there might be a potential feedback mechanism in m6A methylation. Furthermore, prognostic analysis stratified by expression of these two demethylases revealed that low expression of ALKBH5 in non-cancerous liver tissues was associated with worse prognosis. Thus, m6A in HCC and its demethylase in surrounding non-cancerous liver tissues might be inherent mechanisms for HCC carcinogenesis and influence the long-term outcome after HCC resection.

The evidence of RNA methylation and other epigenetic mechanisms in humans in the context of cancer development and progression has been accumulating. Recent functional studies revealed that knockdown of the key methyltransferase methyltransferase-like 3 (METTL3) in glioblastoma stem-like cells led to increased cell proliferation and tumorigenesis, while overexpression of this enzyme inhibited tumor growth in in vivo xenograft models (30). Change in mRNA m6A enrichment was also found to cause altered mRNA expression of genes involved in critical pathways. On the other hand, another study revealed that silencing of m6A demethylase ALKBH5 suppressed proliferation of glioblastoma stem-like cells (31). Hypoxia in breast cancer was shown to increase the expression of ALKBH5, which stabilized NANOG mRNA and promoted tumor formation (32). A recent report about acute myeloid leukemia indicated that mutations and copy number variations in m6A regulators led to poor disease-free and OS (33). Furthermore, several studies have shown that the progression of HCC is associated with abnormal m6A modifications (34-36). Our findings revealed that high m6A levels in tumor tissues were associated with poor prognosis. However, the present study quantified m6A in total RNA including non-coding RNA such as ribosomal, RNA, and small nuclear RNA. Because m6A methylation also occurs in non-coding RNA, our results cannot be directly interpreted as the abundance of methylation in coding RNA. Although the detailed mechanism of m6A modifications in HCC remain to be unraveled, RNA methylation including m6A may be potentially considered as a novel HCC biomarker and treatment target in further studies.

In 2011, RNA demethylase FTO was the first m6A RNA demethylase to be identified (37). Li et al. reported that FTO was up-regulated in HCC tissue and cells and that the overexpression of FTO was correlated with poor prognosis of patients with HCC (38). On the other hand, Zhuang et al. reported that FTO suppressed clear-cell renal cell carcinoma (39). Our results on FTO were opposite to those of Li et al. but several individual results showed that FTO expression in non-cancerous tissue was lower than that in tumor tissues. The total number of patients were larger in our study and might have led to different result from previous reports. ALKBH5 was identified as the second RNA demethylase by Zheng et al. in 2013 (40). To the best of our knowledge, there are no studies revealing the association between ALKBH5 and clinical features of HCC. To our knowledge, we are the first to demonstrate that ALKBH5 expression in background liver tissue is a significant independent risk factor for RFS. In patients with HCC, background liver factors are generally associated with heterochronic intrahepatic recurrence and expression of ALKBH5 in background liver tissue may associated with carcinogenesis of newly developed HCC in remnant liver tissue after surgery. M6A related genes also include ‘writers’ which catalyze methylation and ‘readers’ which recognize the m6A sites. To discover the function of abnormal m6A modification, further study of these genes is needed.

Although our study successfully uncovered important aspects of m6A methylation and associated demethylases, there are some inherent limitations. Firstly, before considering the actual clinical utility of m6A and associated genes as new biomarkers or treatment targets, detailed molecular mechanisms through which m6A methylation enhances HCC development and progression need to be discovered. Secondly, as we used total RNA, which includes coding mRNA and non-coding RNA such as ribosome RNA, transfer RNA and small nuclear RNA, for m6A quantification, further study for m6A in mRNA is needed. mRNA isolation and study is one of the ways to clarify the function of m6A in coding RNA. Methylated RNA sequencing is another way which may be useful to identify specific methylated regions in RNA. In addition, in vitro study with hepatocytes may be required to reveal the detailed function of m6A in HCC development. Thirdly, in the clinical setting, non-invasive tests are preferred to predict and monitor tumor recurrence or metastasis before and after treatment. From this point of view, the relevance of alteration of methylated RNA in serum or urine will need to be assessed. Hence much further investigation is necessary before considering the clinical utility of our findings.

In conclusion, our study revealed that a high global m6A level in HCC tissues was associated with worse prognosis and ALKBH5 expression in HCC background tissues related to cancer recurrence. Our results may pave the way for discovering the clinical utility of m6A methylation and associated genes in HCC therapy.

Acknowledgements

This work was partly supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant-in-Aid for Scientific Research (C) number 18H06176 and 19K18110 to Fuminori Sonohara. We would like to thank Yoko Nishikawa for technical assistance with the experiments and Editage (www.editage.com) for English language editing.

Footnotes

  • ↵* These Authors contributed equally to this study.

  • Authors’ Contributions

    Conception and design: NN, FS, RK; Financial support: FS, YK; Administrative support: SY, YK; Provision of study materials and patients: SY, FS, YS, YI, HT, MH, MK, DK, CT, GN, MK; Collection and assembly of data: NN, FS, KT, YS; qPCR data analysis and interpretation: NN, KT; Article writing: NN, KT, FS, YK; Final approval of article: all Authors.

  • Conflicts of Interest

    The Authors have no conflicts of interest to declare.

  • Received October 6, 2020.
  • Revision received October 17, 2020.
  • Accepted October 23, 2020.

References

  1. ↵
    1. Torre LA,
    2. Bray F,
    3. Siegel RL,
    4. Ferlay J,
    5. Lortet-Tieulent J and
    6. Jemal A
    : Global cancer statistics, 2012. CA Cancer J Clin 65(2): 87-108, 2015. PMID: 25651787. DOI: 10.3322/caac.21262.
    OpenUrlCrossRef
  2. ↵
    EASL clinical practice guidelines: Management of hepatocellular carcinoma. J Hepatol 69(1): 182-236, 2018. PMID: 29628281. DOI: 10.1016/j.jhep.2018.03.019
    OpenUrlCrossRefPubMed
    1. Marrero JA,
    2. Kulik LM,
    3. Sirlin CB,
    4. Zhu AX,
    5. Finn RS,
    6. Abecassis MM,
    7. Roberts LR and
    8. Heimbach JK
    : Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases. Hepatology 68(2): 723-750, 2018. PMID: 29624699. DOI: 10.1002/hep.29913
    OpenUrlCrossRefPubMed
  4. ↵
    1. Kokudo N,
    2. Hasegawa K,
    3. Akahane M,
    4. Igaki H,
    5. Izumi N,
    6. Ichida T,
    7. Uemoto S,
    8. Kaneko S,
    9. Kawasaki S,
    10. Ku Y,
    11. Kudo M,
    12. Kubo S,
    13. Takayama T,
    14. Tateishi R,
    15. Fukuda T,
    16. Matsui O,
    17. Matsuyama Y,
    18. Murakami T,
    19. Arii S,
    20. Okazaki M and
    21. Makuuchi M
    : Evidence-based clinical practice guidelines for hepatocellular carcinoma: The Japan Society of Hepatology 2013 update (3rd JSH-HCC guidelines). Hepatol Res 45(2), 2015. PMID: 25625806. DOI: 10.1111/hepr.12464
    OpenUrlCrossRef
  5. ↵
    1. Qiang L,
    2. Huikai L,
    3. Butt K,
    4. Wang PP and
    5. Hao X
    : Factors associated with disease survival after surgical resection in Chinese patients with hepatocellular carcinoma. World J Surg 30(3): 439-445, 2006. PMID: 16479331. DOI: 10.1007/s00268-005-0608-6
    OpenUrlCrossRefPubMed
  6. ↵
    1. Kulis M and
    2. Esteller M
    : Dna methylation and cancer. Adv Genet 70: 27-56, 2010. PMID: 20920744. DOI: 10.1016/B978-0-12-380866-0.60002-2
    OpenUrlCrossRefPubMed
  7. ↵
    1. Zhang C,
    2. Lu J and
    3. Zhang P
    : The roles of chromatin remodeling proteins in cancer. Curr Protein Pept Sci 17(5): 446-454, 2016. PMID: 26796304. DOI: 10.2174/1389203717666160122120713
    OpenUrlCrossRef
  8. ↵
    1. Wang R,
    2. Xin M,
    3. Li Y,
    4. Zhang P and
    5. Zhang M
    : The functions of histone modification enzymes in cancer. Curr Protein Pept Sci 17(5): 438-445, 2016. PMID: 26796305. DOI: 10.2174/1389203717666160122120521
    OpenUrlCrossRef
  9. ↵
    1. Kondo Y,
    2. Shinjo K and
    3. Katsushima K
    : Long non-coding RNAs as an epigenetic regulator in human cancers. Cancer Sci 108(10): 1927-1933, 2017. PMID: 28776911. DOI: 10.1111/cas.13342
    OpenUrlCrossRef
  10. ↵
    1. Das PM and
    2. Singal R
    : DNA methylation and cancer. J Clin Oncol 22(22): 4632-4642, 2004. PMID: 15542813. DOI: 10.1200/JCO.2004.07.151
    OpenUrlAbstract/FREE Full Text
  11. ↵
    1. Desrosiers R,
    2. Friderici K and
    3. Rottman F
    : Identification of methylated nucleosides in messenger RNA from Novikoff hepatoma cells. Proc Natl Acad Sci USA 71(10): 3971-3975, 1974. PMID: 4372599. DOI: 10.1073/pnas.71.10.3971
    OpenUrlAbstract/FREE Full Text
  12. ↵
    1. Wei CM,
    2. Gershowitz A and
    3. Moss B
    : Methylated nucleotides block 5’ terminus of HeLa cell messenger RNA. Cell 4(4): 379-386, 1975. PMID: 164293. DOI: 10.1016/0092-8674(75)90158-0
    OpenUrlCrossRefPubMed
  13. ↵
    1. Wang X,
    2. Lu Z,
    3. Gomez A,
    4. Hon GC,
    5. Yue Y,
    6. Han D,
    7. Fu Y,
    8. Parisien M,
    9. Dai Q,
    10. Jia G,
    11. Ren B,
    12. Pan T and
    13. He C
    : N6-methyladenosine-dependent regulation of messenger RNA stability. Nature 505(7481): 117-120, 2014. PMID: 24284625. DOI: 10.1038/nature12730
    OpenUrlCrossRefPubMed
  14. ↵
    1. Yue Y,
    2. Liu J and
    3. He C
    : RNA N6-methyladenosine methylation in post-transcriptional gene expression regulation. Genes Dev 29(13): 1343-1355, 2015. PMID: 26159994. DOI: 10.1101/gad.262766.115
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. Bertero A,
    2. Brown S,
    3. Madrigal P,
    4. Osnato A,
    5. Ortmann D,
    6. Yiangou L,
    7. Kadiwala J,
    8. Hubner NC,
    9. de Los Mozos IR,
    10. Sadee C,
    11. Lenaerts AS,
    12. Nakanoh S,
    13. Grandy R,
    14. Farnell E,
    15. Ule J,
    16. Stunnenberg HG,
    17. Mendjan S and
    18. Vallier L
    : The smad2/3 interactome reveals that TGFbeta controls m(6)a mRNA methylation in pluripotency. Nature 555(7695): 256-259, 2018. PMID: 29489750. DOI: 10.1038/nature25784
    OpenUrlCrossRefPubMed
  16. ↵
    1. Lee H,
    2. Bao S,
    3. Qian Y,
    4. Geula S,
    5. Leslie J,
    6. Zhang C,
    7. Hanna JH and
    8. Ding L
    : Stage-specific requirement for METTL3-dependent m. Nat Cell Biol 21(6): 700-709, 2019. PMID: 31061465. DOI: 10.1038/s41556-019-0318-1
    OpenUrlCrossRef
  17. ↵
    1. Liu T,
    2. Yang S,
    3. Sui J,
    4. Xu SY,
    5. Cheng YP,
    6. Shen B,
    7. Zhang Y,
    8. Zhang XM,
    9. Yin LH,
    10. Pu YP and
    11. Liang GY
    : Dysregulated N6-methyladenosine methylation writer METTL3 contributes to the proliferation and migration of gastric cancer. J Cell Physiol 235(1): 548-562, 2020. PMID: 31232471. DOI: 10.1002/jcp.28994
    OpenUrlCrossRef
    1. Li J,
    2. Meng S,
    3. Xu M,
    4. Wang S,
    5. He L,
    6. Xu X,
    7. Wang X and
    8. Xie L
    : Downregulation of N(6)-methyladenosine binding YTHDF2 protein mediated by mir-493-3p suppresses prostate cancer by elevating N(6)-methyladenosine levels. Oncotarget 9(3): 3752-3764, 2018. PMID: 29423080. DOI: 10.18632/oncotarget.23365
    OpenUrlCrossRef
    1. Wu L,
    2. Wu D,
    3. Ning J,
    4. Liu W and
    5. Zhang D
    : Changes of N6-methyladenosine modulators promote breast cancer progression. BMC Cancer 19(1): 326, 2019. PMID: 30953473. DOI: 10.1186/s12885-019-5538-z
    OpenUrlCrossRef
    1. He Y,
    2. Hu H,
    3. Wang Y,
    4. Yuan H,
    5. Lu Z,
    6. Wu P,
    7. Liu D,
    8. Tian L,
    9. Yin J,
    10. Jiang K and
    11. Miao Y
    : Alkbh5 inhibits pancreatic cancer motility by decreasing long non-coding RNA KCNK15-AS1 methylation. Cell Physiol Biochem 48(2): 838-846, 2018. PMID: 30032148. DOI: 10.1159/000491915
    OpenUrlCrossRef
  21. ↵
    1. Li Z,
    2. Weng H,
    3. Su R,
    4. Weng X,
    5. Zuo Z,
    6. Li C,
    7. Huang H,
    8. Nachtergaele S,
    9. Dong L,
    10. Hu C,
    11. Qin X,
    12. Tang L,
    13. Wang Y,
    14. Hong GM,
    15. Wang X,
    16. Chen P,
    17. Gurbuxani S,
    18. Arnovitz S,
    19. Li Y,
    20. Li S,
    21. Strong J,
    22. Neilly MB,
    23. Larson RA,
    24. Jiang X,
    25. Zhang P,
    26. Jin J,
    27. He C and
    28. Chen J
    : FTO plays an oncogenic role in acute myeloid leukemia as a N(6)-methyladenosine RNA demethylase. Cancer Cell 31(1): 127-141, 2017. PMID: 28017614. DOI: 10.1016/j.ccell.2016.11.017
    OpenUrlCrossRefPubMed
  22. ↵
    1. Bokar JA,
    2. Rath-Shambaugh ME,
    3. Ludwiczak R,
    4. Narayan P and
    5. Rottman F
    : Characterization and partial purification of mRNA N6-adenosine methyltransferase from hela cell nuclei. Internal mRNA methylation requires a multisubunit complex. J Biol Chem 269(26): 17697-17704, 1994. PMID: 8021282.
    OpenUrlAbstract/FREE Full Text
    1. Chen M,
    2. Wei L,
    3. Law CT,
    4. Tsang FH,
    5. Shen J,
    6. Cheng CL,
    7. Tsang LH,
    8. Ho DW,
    9. Chiu DK,
    10. Lee JM,
    11. Wong CC,
    12. Ng IO and
    13. Wong CM
    : RNA N6-methyladenosine methyltransferase-like 3 promotes liver cancer progression through YTHDF2-dependent posttranscriptional silencing of SOCS2. Hepatology 67(6): 2254-2270, 2018. PMID: 29171881. DOI: 10.1002/hep.29683
    OpenUrlCrossRefPubMed
  24. ↵
    1. Zou S,
    2. Toh JD,
    3. Wong KH,
    4. Gao YG,
    5. Hong W and
    6. Woon EC
    : N(6)-Methyladenosine: A conformational marker that regulates the substrate specificity of human demethylases FTO and ALKBH5. Sci Rep 6: 25677, 2016. PMID: 27156733. DOI: 10.1038/srep25677
    OpenUrlCrossRefPubMed
  25. ↵
    1. Kandimalla R,
    2. Gao F,
    3. Li Y,
    4. Huang H,
    5. Ke J,
    6. Deng X,
    7. Zhao L,
    8. Zhou S,
    9. Goel A and
    10. Wang X
    : Rnamethypro: A biologically conserved signature of N6-methyladenosine regulators for predicting survival at pan-cancer level. NPJ Precis Oncol 3: 13, 2019. PMID: 31069256. DOI: 10.1038/s41698-019-0085-2
    OpenUrlCrossRef
  26. ↵
    1. Niu Y,
    2. Lin Z,
    3. Wan A,
    4. Chen H,
    5. Liang H,
    6. Sun L,
    7. Wang Y,
    8. Li X,
    9. Xiong XF,
    10. Wei B,
    11. Wu X and
    12. Wan G
    : RNA N6-methyladenosine demethylase FTO promotes breast tumor progression through inhibiting BNIP3. Mol Cancer 18(1): 46, 2019. PMID: 30922314. DOI: 10.1186/s12943-019-1004-4
    OpenUrlCrossRef
  27. ↵
    1. Zhang S,
    2. Zhao BS,
    3. Zhou A,
    4. Lin K,
    5. Zheng S,
    6. Lu Z,
    7. Chen Y,
    8. Sulman EP,
    9. Xie K,
    10. Bögler O,
    11. Majumder S,
    12. He C and
    13. Huang S
    : M(6)a demethylase ALKBH5 maintains tumorigenicity of glioblastoma stem-like cells by sustaining FOXM1 expression and cell proliferation program. Cancer Cell 31(4): 591-606.e596, 2017. PMID: 28344040. DOI: 10.1016/j.ccell.2017.02.013
    OpenUrlCrossRefPubMed
  28. ↵
    1. Sonohara F,
    2. Inokawa Y,
    3. Hayashi M,
    4. Yamada S,
    5. Sugimoto H,
    6. Fujii T,
    7. Kodera Y and
    8. Nomoto S
    : Prognostic value of long noncoding RNA HULC and MALAT1 following the curative resection of hepatocellular carcinoma. Sci Rep 7(1): 16142, 2017. PMID: 29170515. DOI: 10.1038/s41598-017-16260-1
    OpenUrlCrossRef
  29. ↵
    1. Hur K,
    2. Toiyama Y,
    3. Schetter AJ,
    4. Okugawa Y,
    5. Harris CC,
    6. Boland CR and
    7. Goel A
    : Identification of a metastasis-specific microRNA signature in human colorectal cancer. J Natl Cancer Inst 107(3): dju492, 2015. PMID: 25663689. DOI: 10.1093/jnci/dju492
    OpenUrlCrossRefPubMed
  30. ↵
    1. Cui Q,
    2. Shi H,
    3. Ye P,
    4. Li L,
    5. Qu Q,
    6. Sun G,
    7. Lu Z,
    8. Huang Y,
    9. Yang CG,
    10. Riggs AD,
    11. He C and
    12. Shi Y
    : m 6 A RNA methylation regulates the self-renewal and tumorigenesis of glioblastoma stem cells. Cell Rep 18(11): 2622-2634, 2017. PMID: 28297667. DOI: 10.1016/j.celrep.2017.02.059
    OpenUrlCrossRefPubMed
  31. ↵
    1. Zhang S,
    2. Zhao BS,
    3. Zhou A,
    4. Lin K,
    5. Zheng S,
    6. Lu Z,
    7. Chen Y,
    8. Sulman EP,
    9. Xie K,
    10. Bögler O,
    11. Majumder S,
    12. He C and
    13. Huang S
    : m 6 A demethylase ALKBH5 maintains tumorigenicity of glioblastoma stem-like cells by sustaining FOXM1 expression and cell proliferation program. Cancer Cell 31(4): 591-606, 2017. PMID: 28344040. DOI: 10.1016/j.ccell.2017.02.013
    OpenUrlCrossRefPubMed
  32. ↵
    1. Zhang C,
    2. Zhi WI,
    3. Lu H,
    4. Samanta D,
    5. Chen I,
    6. Gabrielson E and
    7. Semenza GL
    : Hypoxia-inducible factors regulate pluripotency factor expression by ZNF217- and ALKBH5-mediated modulation of RNA methylation in breast cancer cells. Oncotarget 7(40): 64527-64542, 2016. PMID: 27590511. DOI: 10.18632/oncotarget.11743
    OpenUrlCrossRef
  33. ↵
    1. Kwok CT,
    2. Marshall AD,
    3. Rasko JE and
    4. Wong JJ
    : Genetic alterations of m6A regulators predict poorer survival in acute myeloid leukemia. J Hematol Oncol 10(1): 39, 2017. PMID: 28153030. DOI: 10.1186/s13045-017-0410-6
    OpenUrlCrossRef
  34. ↵
    1. Ma JZ,
    2. Yang F,
    3. Zhou CC,
    4. Liu F,
    5. Yuan JH,
    6. Wang F,
    7. Wang TT,
    8. Xu QG,
    9. Zhou WP and
    10. Sun SH
    : METTL14 suppresses the metastatic potential of hepatocellular carcinoma by modulating N(6)-methyladenosine-dependent primary microRNA processing. Hepatology 65(2): 529-543, 2017. PMID: 27774652. DOI: 10.1002/hep.28885
    OpenUrlCrossRef
    1. Lan T,
    2. Li H,
    3. Zhang D,
    4. Xu L,
    5. Liu H,
    6. Hao X,
    7. Yan X,
    8. Liao H,
    9. Chen X,
    10. Xie K,
    11. Li J,
    12. Liao M,
    13. Huang J,
    14. Yuan K,
    15. Zeng Y and
    16. Wu H
    : KIAA1429 contributes to liver cancer progression through N6-methyladenosine-dependent post-transcriptional modification of GATA3. Mol Cancer 18(1): 186, 2019. PMID: 31856849. DOI: 10.1186/s12943-019-1106-z
    OpenUrlCrossRef
  36. ↵
    1. Hou J,
    2. Zhang H,
    3. Liu J,
    4. Zhao Z,
    5. Wang J,
    6. Lu Z,
    7. Hu B,
    8. Zhou J,
    9. Feng M,
    10. Shen B,
    11. Huang X,
    12. Sun B,
    13. He C and
    14. Xia Q
    : YTHDF2 reduction fuels inflammation and vascular abnormalization in hepatocellular carcinoma. Mol Cancer 18(1): 163, 2019. PMID: 31735169. DOI: 10.1186/s12943-019-1082-3
    OpenUrlCrossRef
  37. ↵
    1. Jia G,
    2. Fu Y,
    3. Zhao X,
    4. Dai Q,
    5. Zheng G,
    6. Yang Y,
    7. Yi C,
    8. Lindahl T,
    9. Pan T,
    10. Yang YG and
    11. He C
    : N6-Methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat Chem Biol 7(12): 885-887, 2011. PMID: 22002720. DOI: 10.1038/nchembio.687
    OpenUrlCrossRefPubMed
  38. ↵
    1. Li J,
    2. Zhu L,
    3. Shi Y,
    4. Liu J,
    5. Lin L and
    6. Chen X
    : m6A Demethylase FTO promotes hepatocellular carcinoma tumorigenesis via mediating PKM2 demethylation. Am J Transl Res 11(9): 6084-6092, 2019. PMID: 31632576.
    OpenUrl
  39. ↵
    1. Zhuang C,
    2. Luo X,
    3. Huang X,
    4. Yao L,
    5. Li J,
    6. Li Y,
    7. Xiong T,
    8. Ye J,
    9. Zhang F and
    10. Gui Y
    : N6-methyladenosine demethylase FTO suppresses clear cell renal cell carcinoma through a novel FTO -PGC-1alpha signalling axis. J Cell Mol Med 23(3): 2163-2173, 2019. PMID: 30648791. DOI: 10.1111/jcmm.14128
    OpenUrlCrossRef
  40. ↵
    1. Zheng G,
    2. Dahl JA,
    3. Niu Y,
    4. Fedorcsak P,
    5. Huang CM,
    6. Li CJ,
    7. Vågbø CB,
    8. Shi Y,
    9. Wang WL,
    10. Song SH,
    11. Lu Z,
    12. Bosmans RP,
    13. Dai Q,
    14. Hao YJ,
    15. Yang X,
    16. Zhao WM,
    17. Tong WM,
    18. Wang XJ,
    19. Bogdan F,
    20. Furu K,
    21. Fu Y,
    22. Jia G,
    23. Zhao X,
    24. Liu J,
    25. Krokan HE,
    26. Klungland A,
    27. Yang YG and
    28. He C
    : ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol Cell 49(1): 18-29, 2013. PMID: 23177736. DOI: 10.1016/j.molcel.2012.10.015
    OpenUrlCrossRefPubMed
    1. Liver Cancer Study Group of Japan
    : General Rules for the Clinical and Pathological Study of Primary Liver Cancer. Third English Edition Kanehara and Co., Ltd., Tokyo, 2010.
    1. Kudo M,
    2. Kitano M,
    3. Sakurai T and
    4. Nishida N
    : General Rules for the Clinical and Pathological Study of Primary Liver Cancer, Nationwide Follow-Up Survey and Clinical Practice Guidelines: The outstanding achievements of the Liver Cancer Study Group of Japan. Dig Dis 33(6): 765-770, 2015. PMID: 26488173. DOI: 10.1159/000439101
    OpenUrlCrossRefPubMed
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Novel Prognostic Implications of Methylated RNA and Demethylases in Resected HCC and Background Liver Tissue
NOBUHIKO NAKAGAWA, KATSUHITO TANAKA, FUMINORI SONOHARA, RAJU KANDIMALLA, YUKI SUNAGAWA, YOSHIKUNI INOKAWA, HIDEKI TAKAMI, MASAMICHI HAYASHI, SUGURU YAMADA, MITSURO KANDA, CHIE TANAKA, GORO NAKAYAMA, MASAHIKO KOIKE, YASUHIRO KODERA
Anticancer Research Dec 2020, 40 (12) 6665-6676; DOI: 10.21873/anticanres.14690
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