Current Colorectal Cancer Reports

, Volume 8, Issue 1, pp 66–81

Epigenetics Offer New Horizons for Colorectal Cancer Prevention

Open AccessMolecular Epidemiology (MJ Wargovich, Section Editor)

DOI: 10.1007/s11888-011-0116-z

Cite this article as:
Schnekenburger, M. & Diederich, M. Curr Colorectal Cancer Rep (2012) 8: 66. doi:10.1007/s11888-011-0116-z

Abstract

In recent years, colorectal cancer (CRC) incidence has been increasing to become a major cause of morbidity and mortality worldwide from cancers, with high rates in westernized societies and increasing rates in developing countries. Epigenetic modifications including changes in DNA methylation, histone modifications, and non-coding RNAs play a critical role in carcinogenesis. Epidemiological data suggest that, in comparison to other cancers, these alterations are particularly common within the gastrointestinal tract. To explain these observations, environmental factors and especially diet were suggested to both prevent and induce CRC. Epigenetic alterations are, in contrast to genetic modifications, potentially reversible, making the use of dietary agents a promising approach in CRC for the development of chemopreventive strategies targeting epigenetic mechanisms. This review focuses on CRC-related epigenetic alterations as a rationale for various levels of prevention strategies and their potential modulation by natural dietary compounds.

Keywords

Colorectal cancerEpigeneticDNA methylationHistone modificationNon-codingmicroRNACancer preventionEarly detectionBiomarkerPredictive markerPrognostic markerChemopreventionMolecular epidemiology

Introduction

Colon and rectal cancers (colorectal cancer, CRC) represent globally, in terms of frequency, the third leading cause of cancer-related mortality (ie, after lung and breast cancer). Nevertheless, CRC incidence and mortality rates vary over 10-fold worldwide. Lowest incidence rates are observed in Africa and Asia and highest ones are found in Australia/New Zealand, North America, and Western Europe with a mortality rate of approximately 30%. Although incidence rates in developed countries are stabilizing, they are severely increasing in both developing countries and several areas historically at low risk [1]. Since the 1970s, CRC incidence in USA has continuously increased in the African-American population to become more frequent in this population than in Caucasians or other ethnic groups [2]. Similarly, data from migration population studies revealed that some ethnic groups are showing increased CRC incidence rate while they are migrating from low-risk to high-risk areas, to finally reach rates comparable to the host country [35]. Despite genetic variation, these epidemiological data strongly suggest a role of environmental and lifestyle factors deeply contributing to the etiology of CRC.

Although it is well accepted that genetic factors and inflammatory bowel disease place certain individuals at increased risk [6], various modifiable lifestyle factors have been identified related to CRC pathogenesis. Significant lifestyle risk factors are represented by sedentarity and changes in dietary habits, from a moderate to a Western-like enriched diet associated with high consumption of unsaturated fats and red meat, high intake of alcohol, and smoking.

Epigenetic mechanisms are fundamental to tightly regulated cellular processes. Epigenetic aberrations governing tumor suppressor gene (TSG) inactivation, oncogene activation, and chromosomal instability play a fundamental role in tumorigenesis including CRC. Epigenetic events are involved in all critical pathways and steps of carcinogenesis including tumor initiation, and some events are usually detectable before neoplastic transformation [7, 8, 9•, 10]. Nonetheless, it is well accepted that environmental and dietary factors greatly influence epigenetic events. Moreover, the reversibility of epigenetic alterations stimulates the development of novel therapeutic approaches with an open field for development in cancer chemoprevention. Taking together, these observations suggest that improved early detection and dietary intervention are preventive approaches of choice to decrease CRC incidence.

In this review, we focus on epigenetic alterations associated with CRC, which offer promising novel biomarkers for early detection, with an emphasis on how these alterations can potentially be modulated by dietary compounds for preventive interventions.

Colorectal Carcinogenesis and Cancer Prevention

The vast majority of CRCs are a multistep-associated adenoma-carcinoma progression associated with successive clinico-histopathological stages. This transformation initially starts with a premalignant lesion, called aberrant crypt foci (ACF), rising from normal colonic mucosa, progressing to a premalignant lesion (ie, adenoma), and finally evolving to invasive adenocarcinoma and metastasis (Fig. 1). The tumor-node-metastasis (TNM) system stages CRCs depending on the extent of invasion of the intestinal wall (T), the degree of lymphatic node involvement (N), and whether there is presence of metastasis (M). Based on this system, CRC is ranked from 0 (in situ tumor confined to mucosa) to stage IV (presence of metastasis). Thus, an increasing ranking correlates to a more advanced cancer and likely a worse outcome [11].
https://static-content.springer.com/image/art%3A10.1007%2Fs11888-011-0116-z/MediaObjects/11888_2011_116_Fig1_HTML.gif
Fig. 1

Colorectal cancer (CRC) progression as a model for epigenetic alteration cascade and prevention strategies. CRC development is initially starting by a premalignant lesion, called aberrant crypt foci (ACF), rising from normal colonic mucosa, progressing to a premalignant lesion (adenoma) and then to invasive adenocarcinoma, and finally evolving to metastatic adenocarcinoma. Epigenetic alterations are largely contributing to CRC initiation and adenoma-carcinoma progression. These alterations are characterized by global genomic DNA hypomethylation leading to genomic instability and oncogene activation concomitantly to an increase of CpG island promoter hypermethylation-mediated silencing of tumor suppressor genes. These changes are accompanied by an increase of aberrant histone modification profiles and miRNA signatures reinforcing oncogenic activation and tumor suppressor loss associated with CRC progression. Consequently, epigenetic alterations represent promising targets for CRC prevention. Early epigenetic aberrations represent interesting targets for primary prevention, especially through chemoprevention by dietary epigenetic modulators, as well as for secondary prevention as early biomarkers of CRC initiation. Modifications occurring at later stages may be targeted by chemotherapeutic interventions as well as chemopreventive agents to limit or block disease progression (secondary and tertiary prevention activities)

Although most CRCs occur sporadically, the importance of inheritance associated with a family history of the disease is evaluated to approximately 25% [12]. Some well-defined syndromes associated with CRC pathobiology have been identified: hereditary non-polyposis CRC (HNPCC), familial adenomatous polyposis (FAP), and MUTYH-associated polyposis (MAP), which are caused by germline mutations in DNA mismatch repair (MMR) genes, adenomatous polyposis coli (APC) TSG, and MUTYH gene, respectively; plus a number of relatively rare polyposis syndromes [13].

Mechanisms underlying the adenoma-carcinoma sequence have been identified for their contribution to CRC pathogenesis in relation to alterations of TSG and oncogene functions. Among these mechanisms, genomic instability represented by two “genotypic” subtypes pathways associated with somatic mutations are frequently identified: chromosomal instability (CIN) and microsatellite instability (MSI) [9•, 13]. Although CIN is observed in approximately 85% of CRC cases, the initiating mechanism is still poorly understood. The most common cytogenic abnormalities observed in CIN are mutations of APC gene, which occur in the majority of sporadic CRCs and also very early in adenoma development, and chromosome aberrations such as loss of heterozygosity of 5, 17p, and 18q. The latter contains the deleted in colorectal cancer (DCC) TSG. MSI is characterized by the inactivation of genes implicated in mismatch repair (MMR) system leading to subsequent mutations in the microsatellite repeat sequences of genes linked to tumor progression [13]. In addition to somatic mutations, epigenetic alterations are also particularly common in CRC. Epigenetics is defined as the heritable changes in gene expression patterns that occur without a change in the primary DNA sequence. This field encompasses DNA methylation, histone modifications and chromatin remodeling, and non-coding RNA-mediated interference [9•, 10, 13].

After years of research it appears that the best way to avoid the burden of cancer might be prevention. Under the general concept of prevention, several levels of approaches are encompassed [14]. Avoiding exposure to potential carcinogens or life risk factors is associated with the primary level of prevention. However, preemptive behavior prevention is not limited to this aspect. Indeed, chemoprevention, ie, the use of natural agents in healthy individuals without signs of premalignancy, falls also in this category. Secondary prevention corresponds to early detection of tumor-related abnormal changes aiming to prevent cancer development. Screening tests are included in this category, which require robust clinical biomarkers for early diagnosis. Finally, tertiary prevention consists to control cancer development to a more advanced-stage or reoccurrence after treatment and reduce adverse health effects.

Given the fact that epimutations are potentially reversible, the major field of applications regarding epigenetics might be cancer prevention. Accordingly, epimutations represent secondary prevention biomarkers by their precocity in carcinogenesis processes (ie, before neoplastic transformation). Primary to tertiary prevention may be achieved through chemoprevention, with dietary agents controlling epigenetic (re)programming, to either prevent or reverse premalignant stem cell phenotypes (Fig. 1).

Epimutations in CRC: Biomarkers and Targets for Prevention

DNA Methylation in CRC

In humans, DNA methylation occurs at the 5′ position of the pyrimidine ring of the cytosine residues within CpG dinucleotides through addition of a methyl moiety to form 5-methylcytosines. This process is catalyzed by three DNA methyltransferases (DNMT1, DNMT3A, and DNMT3B) using the cofactor S-adenosyl-methionine (SAM). Although CpG dinucleotides represent approximately 1% of the human genome, they are unequally distributed across the genome and are clustered in small DNA stretches. These CpG-rich regions, called CpG islands (CGIs), are usually present near promoters and exogenic regions. CGIs are usually unmethylated in normal differentiated cells, whereas CpGs located in intergenic regions are methylated [8, 15].

In cancer, promoter CGI of numerous TSGs are found to be densely methylated, which results in transcriptional silencing. Interestingly, these epimutations may be cancer type-specific and tumor stage-specific. Thus, methylation patterns can be considered as biomarkers for diagnosis, prognosis, as well as prediction and monitoring of therapy response [8, 10, 15, 16]. Therefore, the identification of these cancer-associated methylation signatures is really critical for cancer prevention purposes.

Recent studies show that CRC is strongly associated with aberrant DNA methylation profiles, which has been linked to the origin and progression of the disease. The list of epimutations is growing quickly with the use of developing technologies allowing genome studies. To date, a long list of TSGs involved in numerous signalization pathways and cellular processes were found frequently methylated in CRC (Table 1). Noteworthy, a widespread contribution of DNA methylation participates in the disruption of β-catenin–dependent Wnt signaling pathway, which plays an important role in colorectal tumor development [9•, 13]. Moreover, methylation can affect coding and non-coding genes (eg, microRNA, miRNA) participating in loss of tumor suppressor functions. Remarkably, most of these methylated genes are investigated as potential biomarkers for preventive or therapeutic purposes. However, the methylation prevalence varies substantively depending on the considered genes as well as between studies regarding a same gene. The discrepancy between studies, like the case of CDKN2A (p16), for which methylation ranged from 10% to 58% depending on reports [1719], could be explained by the phenotype of patients constituting these cohorts as well as how clinical parameters were included in these analyses. Indeed, certain genes are found frequently methylated in specific CRC subgroups, such as AXIN2 found preferentially associated with MSI tumors [20].
Table 1

Epimutations associated with colorectal cancer based on experimental data from patientsa

Epigenetic event

Name

Locus

Function/targets

Noteb

Comments

Hypermethylation

ADAMTS5

21q22.1-q22

Protease

NA

Increase of methylation level in CRC

 

ADHFE1

8q12.3

Alcohol dehydrogenase

NA

Increase of methylation level in CRC

 

ALX4

11p11.2

Homeobox gene

85/64

Adenoma vs CRC

 

APBA1

9q13-q21

Intracellular signaling

16–28

 
 

APBA2

15q11-q12

Intracellular signaling

22/26

Stage I + III vs IV

 

APC

5q22.2

Wnt signaling

21

 
 

APC2

19p13.3

Wnt signaling

100

 
 

AXIN2

17q24.1

Wnt signaling

29

Associated with MSI tumors

 

B4GALNT1

12q13.3

Lipid metabolism

100

 
 

B4GALNT2

17q21.3

Lipid metabolism

50

Correlated with EBV-associated gastric carcinomas

 

BARX1

9q12

Homeobox gene

56

 
 

BMP3

4q21.21

Bone and cartilage formation

72/60

Adenoma vs CRC

 

BNIP3

10q26.3

Apoptosis

66

 
 

BOLL

2q33.1

Development

NA

Increase of methylation level in CRC

 

CACNA1G

17q22

Calcium metabolism

39

 
 

CASR

3q21.1

Calcium metabolism

9/69/90

Adenoma vs CRC vs lymph node metastatic tissues

 

CCNA1

13q13.3

Cell cycle

100

 
 

CD109

6q13

Complement system

33

 
 

CDH1

16q22.1

Cell adhesion

51

 
 

CDH13

16q23.3

Cell adhesion

32–66

Poor prognosis

 

CDH2

18q12.1

Cell adhesion

45

 
 

CDH4

20q13.3

Cell adhesion

78

 
 

CDKN2A (p14)

9p21.3

Cell cycle

34

 
 

CDKN2A (p16)

9p21.3

Cell cycle

10–58

 
 

CDKN2B (p15)

9p21.3

Cell cycle

68

 
 

CDX1

5q33.1

Homeobox gene

100

 
 

CHFR

12q24.33

Cell cycle

26–63

Associated with disease recurrence

 

CNRIP1

2p14

G protein-coupled receptor

91/94

Adenoma vs CRC

 

CNTFR

9p13.3

Cytokine signaling

22

 
 

CPAMD8

19p13.12

Innate immunity

90

 
 

CXCL12

10q11.21

Cytokine signaling

62

 
 

DAPK1

9q21.33

Apoptosis

43

 
 

DCC

18q21.2

Putative TSG

81/83

Adenoma vs CRC (20% in normal)

 

DFNA5

7p15.3

Unknown

65

 
 

DKK1

10q21.1

Wnt signaling

13–35

Associated with MSI tumors

 

DKK2

4q25

Wnt signaling

65

 
 

DKK3

11p15.3

Wnt signaling

35

 
 

DKK4

8p11.2-p11.1

Wnt signaling

20

 
 

DLC1-i4

8p22

Putative TSG

100

 
 

DLEC1

3p22.2

Putative TSG

38

Poor prognosis

 

EFEMP1

2p16.1

Cell migration

39

Poor prognosis

 

EGFR

7p11.2

Cytokine signaling

58

Poor prognosis

 

EN1

2q13-q21

Homeobox gene

33

 
 

EphA1

7q32-q34

Intercellular signaling

49

Poor prognosis

 

EphA5

4q13.1

Intercellular signaling

53

 
 

EphA7

6q16.1

Intercellular signaling

49

More frequent in moderately differentiated adenocarcinomas

 

EPHB2

1p36.12

Intercellular signaling

53

 
 

ESR1

6q25.1

Hormonal signaling

31

 
 

EVL

14q32.32

Cell migration

60

 
 

EYA2

20q13.1

Development

44/51

Adenoma vs CRC

 

EYA4

6q23

Development

70

 
 

FAM127A

Xq26

Unknown

58

 
 

FBN1

15q21.1

ECM component

69/79

Adenoma vs CRC

 

FBN2

5q23.3

ECM component

90

 
 

FLNC

7q32.1

Cell migration

30

 
 

FOXL2

3q23

Transcription factor

50

 
 

GAS7

17p13.1

Development

NA

Increase of methylation level in CRC

 

GATA4

8p23.1

Transcription factor

70

Independent of clinicopathologic features

 

GATA5

20q13.33

Transcription factor

79

Independent of clinicopathologic features

 

GPNMB

7p15

Development

100

 
 

GPR101

Xq25-q27.1

G protein-coupled receptor

40

 
 

GRID1

10q22

Glutamate receptor

60

 
 

GRIN2A

16p13.2

Glutamate receptor

82

 
 

GSPT2

Xp11.22

GTPase

21

 
 

GUCY1A2

11q21-q22

Intercellular signaling

50

 
 

HACE1

6q16.3

Stress response

28

 
 

HIC1

17p13.3

Transcriptional repressor

35/42

Adenoma vs CRC

 

HLTF

3q24

Transcription factor

18–34

 
 

HOXB13

17q21.32

Homeobox gene

40

 
 

HRK

12q24.23

Apoptosis

36

 
 

HUS1

7p12.3

Cell cycle

22

 
 

ID4

6p22.3

Transcription factor

46

 
 

IGF2

11p15.5

Development

22

 
 

IGFBP3

7p12.3

Hormonal signaling

25

 
 

IGFBP7

4q12

Hormonal signaling

18/23

Adenoma vs CRC

 

IKZF1

7p12.2

Transcriptional activator

30–82

% increase with Duke’s stages

 

INA

10q24.33

Development

35/65

Adenoma vs CRC

 

INHBB

2q14.2

Inhibin

30

 
 

IRF8

16q24.1

Transcription factor

43

 
 

ITGA4

2q31.3

Cell adhesion

75/92

Adenoma vs CRC

 

KCNK12

2p16.3

Potential potassium channel

41

 
 

KLF4

9q31.2

Transcription factor

25

 
 

LAMA1

18p11.31

Cell migration

100

 
 

LRRC3B

3p24.1

Putative TSG

77

 
 

MAL

2q11.1

Proteolipids

84/91

Adenoma vs CRC

 

MGMT

10q26.3

DNA repair

20–60

 
 

miR-1-1

20q13.33

Translational repression

50

 
 

miR-9-1

1q22

Translational repression

50

Associated with the presence of lymph node metastasis

 

miR-34a

1p36.22

Translational repression

74

 
 

miR-34b/c

11q23.1

Translational repression

99

 
 

miR-124-1

8p23.1

Translational repression

75

 
 

miR-129-2

11p11.2

Translational repression

83

 
 

miR-137

1p21.3

Translational repression

100

 
 

miR-148

NA

Translational repression

65

 
 

miR-342

14q32.2

Translational repression

67/86

Adenoma vs CRC

 

miR-345

14q32.2

Translational repression

87

 
 

miR-373

19q13.42

Translational repression

88

 
 

MLH1

3p22.2

DNA repair

18–22

Poor prognosis

 

MMP2

16q12.2

Protease

95

 
 

MYOD1

11p15.1

Transcription factor

69

 
 

NDRG2

14q11.2

Putative TSG

27

 
 

NDRG4

16q21

Putative TSG

70–86

 
 

NEURL

10q25.1

Putative TSG

31

 
 

NEUROG1

5q31.1

Putative TSG

36

 
 

NPY

7p15.1

Putative TSG

NA

Increase of methylation level in CRC

 

NRCAM

7q31.1

Cell adhesion

50

 
 

NTNG1

1p13.3

Development

70

 
 

NTRK2

9q21.33

Differentiation

100

 
 

OSMR

5p13.1

Cytokine signaling

55/89/90

Mucosa adjacent to CRC vs colorectal polyps vs carcinoma

 

PAPSS2

10q23.2

Development

100

 
 

PDLIM4

5q31.1

Development

85/70

Adenoma vs CRC

 

PPM1E

17q23.2

Phosphatase

55

 
 

PRKD1

14q12

Kinase

20

 
 

PROM1

4p15.32

Putative TSG

62

 
 

PTGIS

20q13.1-q13.3

Prostaglandin signaling

30/44

Adenoma vs CRC

 

PTGS2

1p25.2-3

Inflammation

72

 
 

PTPRD

9p23

Phosphatase

50

 
 

RAB32

6q24.3

Ras signaling

56

MSI tumors

 

RARβ

3p24.2

Hormonal signaling

33–85

 
 

RASSF1A

3p21.2

Ras signaling

41/57

Stage I/III vs IV

 

RASSF2

20p13

Ras signaling

42

 
 

RASSF5

1q32.1

Ras signaling

NA

Increase of methylation level in CRC

 

RECK

9p13.3

Putative TSG

44

 
 

RUNX3

1p36.11

Transcription factor

27–63

Poor prognosis

 

SCTR

2q14.1

G protein-coupled receptor

81

 
 

SFRP1

8p11.21

Wnt signaling

95–100

 
 

SFRP4

7p14.1

Wnt signaling

100

 
 

SH3TC1

4p16.1

Putative TSG

40

 
 

SLC5A8

12q23.1

Solute carrier

80

 
 

SLC6A15

12q21.31

Solute carrier

NA

Increase of methylation level in CRC

 

SLIT2

4p15.2

Cell migration

72

 
 

SMO

7q32.1

G protein-coupled receptor

21

 
 

SNCA

4q21.3-q22

Dopamine signaling

53/66

Adenoma vs CRC

 

SOCS1

16p13.13

Cytokine signaling

22

 
 

SOX17

8q11.23

Transcription factor

86/89–100

Adenoma vs CRC

 

SPARC

5q33.1

ECM component

100

 
 

SPG20

13q13.3

Putative TSG

78/89

Adenoma vs CRC

 

SST

3q28

Hormonal signaling

90

 
 

ST3GAL6

3q12.2

Putative TSG

44

Correlated with EBV-associated gastric carcinomas

 

STARD8

Xq13.1

Putative TSG

55

 
 

SYNE1

6q25.2

Putative TSG

95

 
 

SYT6

1p13.2

Calcium metabolism

64

 
 

TAC1

7q21.3

Hormonal signaling

95

 
 

TCERG1L

10q26.3

Putative TSG

100

 
 

TFPI2

7q22

ECM component

NA

Increase of methylation level in CRC

 

TIMP3

22q12–13

ECM component

23

 
 

TMEFF2

2q32.3-q33

Cell proliferation

77

 
 

TP73

1p36.33

Cell cycle control (G1-S)

63

 
 

TUBG2

17q21

Cell migration

71

 
 

TUSC3

8p22

Putative TSG

66

Associated with ulcerative colitis

 

TWIST1

7p21.1

Transcription factor

NA

Increase of methylation level in CRC

 

UNC5C

4q22.3

Development

64/76

Adenoma vs CRC

 

VIM

10p13

Cell migration

91/77

Adenoma vs CRC

 

WIF-1

12q13.13

WIF-1

100

Very limited number of samples

 

WNT5a

3p14.3

Wnt signaling

20

Associated with MSI and BRAF V600E mutation

 

WRN

8p12

DNA repair

29

 
 

WT1

11p13

Transcription factor

58

 
 

ZNF569

19q13.12

Transcription factor

40

 

Hypomethylation

C7orf50

7p22.3

Unknown

NA

 
 

CARD14

17q25.3

NF-κB signaling

NA

 
 

CCDC116

22q11.21

Transcriptional regulator

NA

 
 

CDH3

16q22.1

Cell adhesion

77

 
 

CSRP1

1q32.1

Development

NA

 
 

EPHX4

1p22.1

Cell detoxification

NA

 
 

GPR109A

12q24.31

G protein-coupled receptor

NA

 
 

GPSM1

9q34.3

G protein signaling

NA

 
 

GRAP

17p11.2

Intracellular signaling

NA

 
 

H19

11p15.5

Putative TSG

18

 
 

HIST1H2BO

6p22.1

Histone

NA

 
 

IGF2

11p15.5

Development

35

Poor prognosis

 

L1CAM

Xq28

Cell adhesion

NA

 
 

LAMB1

7q22

ECM component

NA

 
 

LILRA4

19q13.4

Cytokine signaling

NA

 
 

LINE1

NA

Retrotransposon

NA

Associated with MSI and CIMP tumors

 

MAEL

1q24.1

piRNA system

NA

 
 

MIRLET7BHG

22q13.31

Long non-coding RNA

NA

 
 

NRXN1

2p16.3

Cell adhesion

NA

 
 

NUP50

22q13.3

Macromolecule trafficking

NA

 
 

S100A4

1q21.3

Cell cycle

NA

 
 

S1PR4

19p13.3

G protein-coupled receptor

NA

 
 

SFT2D3

2q14.3

Transport and trafficking

NA

 
 

SLC39A4

8q24.3

Solute carrier

NA

 
 

SLC6A18

5p15.33

Solute carrier

NA

 
 

SLC6A6

3p25.1

Solute carrier

NA

 
 

TIAM1

21q22.1

Cell migration

NA

Associated with metastasis

miRNA

let-7 family

NA

DLD-1, c-Myc, K-RAS

Poor prognosis

 

miR-1-1

20q13.33

TAGLN2

 
 

miR-9-1

1q22

 

 
 

miR-10b

2q31.1

 

 
 

miR-15b

3q25.33

 

+

 
 

miR-16

NA

Wip1

 
 

miR-17

13q31.3

E2F1

+

Poor prognosis, MSS tumors

 

miR-18a

13q31.3

K-RAS

+

Without lymph node metastasis

 

miR-18b

Xq26.2

 

+

Without lymph node metastasis

 

miR-19a

13q31.3

PTEN

+

Without lymph node metastasis

 

miR-19b

NA

 

+

 
 

miR-20a

13q31.3

BNIP2

+

MSI

 

miR-21

17q23.1

Cdc25A, MSH2, PTEN, RECK, TIMP3

+

Poor prognosis, decrease of chemotherapy response, MSI tumors

 

mir-24

NA

DHFR

 
 

miR-25

7q22.1

 

+

 
 

miR-26b

2q35

EphA2

 
 

miR-29a

7q32.3

 

+

 
 

miR-29b

NA

 

+

 
 

miR-30a

6q13

Beclin 1

 
 

miR-30c

NA

 

 
 

miR-31

9p21.3

FIH-1

+

Poor prognosis

 

miR-32

9q31.3

 

+

 
 

miR-33a

22q13.2

 

+

 
 

miR-34a

1p36.22

Bcl2, CDK4/6, E2F3, MET, SIRT1

 
 

miR-34b/c

11q23.1

Tp53

 
 

miR-92a

NA

 

+

MSS tumors

 

miR-93

7q22.1

 

+

 
 

miR-95

4

SNX1

+

 
 

miR-96

7q32.2

 

+

 
 

miR-99a

21q21.1

 

 
 

miR-101

NA

COX-2

MSI tumors

 

miR-106a

Xq26.2

E2F1

+

 
 

miR-106b

7q22.1

CDKN1A (p21)

+

Without lymph node metastasis

 

miR-124-1

8p23.1

 

 
 

miR-125a

19q13.41

 

 
 

miR-125b

NA

 

+

Poor prognosis

 

miR-126

9q34.3

p85β

Associated with metastasis

 

miR-127

14q32.2

 

 
 

miR-129-2

11p11.2

 

 
 

miR-103b

NA

 

+

 
 

miR-133a

NA

 

 
 

miR-133b

6p12.2

c-Met

+

 
 

miR-135a

NA

APC

+

 
 

miR-135b

1q32.1

APC

+

Without lymph node metastasis

 

miR-137

1p21.3

Cdc42, LSD-1

 
 

miR-139

11q13.4

β–Catenin

 
 

miR-140

16q22.1

HDAC4

 
 

miR-141

12p13.31

TGF-β1

+

 
 

miR-142

17q22

 

MSS tumors

 

miR-143

5q32

DNMT3A, Erk5, K-RAS

Decrease of chemotherapy response, associated with metastasis

 

miR-145

5q32

FLI1, IRS1, STAT1, YES

MSI tumors

 

miR-146b

10q24.32

 

MSS tumors

 

miR-155

21q21.3

MLH1, MSH2, MSH6

+

With lymph node metastasis

 

miR-181b

NA

 

+

Decrease of chemotherapy response

 

miR-182

7q32.2

 

+

 
 

miR-183

7q32.2

Klf4, Sox2, BMI1

+

 
 

miR-191

3p21.31

 

 
 

miR-192

11q13.1

DHFR, TS, TYMS

Decrease of chemotherapy response

 

miR-195

17p13.1

Bcl-2

 
 

mir-196a

NA

AKT

Increase metastasis potential

 

mir-196b

7p15.2

 

+

Without lymph node metastasis

 

miR-200a

1p36.33

ZEB1, ZEB2, MLH1, MSH2

+

Associated with metastasis

 

miR-200b

1p36.33

MLH1, MSH2

+

Associated with metastasis

 

miR-200c

12p13.31

TGF-β2, ZEB1, ZEB2, BMI1, PTPN12

+

Poor prognosis, associated with metastasis

 

miR-203

14q32.33

Klf4, Sox2, BMI1

+

 
 

miR-212

17p13.3

 

MSS

 

miR-215

1q41

DHFR, TS, TYMS

Decrease of chemotherapy response

 

miR-217

2p16.1

 

MSS

 

miR-223

Xq12

 

+

 
 

miR-224

Xq28

 

+

Without lymph node metastasis

 

miR-301b

22q11.21

 

+

Without lymph node metastasis

 

miR-320

8p21.3

 

Poor prognosis

 

miR-328

16q22.1

 

 
 

miR-335

7q32.2

 

+

Without lymph node metastasis

 

miR-342

14q32.2

DNMT1

 
 

miR-345

14q32.2

BAG3

 
 

miR-373

19q13.42

LATS2, CD44, RAB22A

 
 

miR-374a

Xq13.2

 

+

Without lymph node metastasis

 

miR-378

5q32

 

Without lymph node metastasis

 

miR-378*

5q32

 

Without lymph node metastasis

 

miR-422a

15q22.31

 

 
 

miR-424

Xq26.3

 

+

Without lymph node metastasis

 

miR-432*

14q32.2

 

+

MSI tumors

 

miR-451

17q11.2

MIF

Poor prognosis

 

miR-455

9q32

 

MSI tumors

 

miR-484

16p13.11

 

MSI tumors

 

miR-486

8p11.21

 

 
 

miR-492

12q22

 

+

MSI tumors

 

miR-497

17p13.1

 

 
 

miR-498

19q13.42

 

Poor prognosis

 

miR-510

Xq27.3

 

+

MSS tumors

 

miR-513

NA

 

+

MSS tumors

 

miR-542

Xq26.3

 

+

 
 

miR-552

1p34.3

 

+

 
 

miR-592

7q31.33

 

+

MSS tumors

 

miR-675

11p15.5

Rb

+

 

CIMP, CpG island methylator phenotype; ECM, extracellular matrix; MSI, microsatellite instability; MSS, microsatellite stable; TSG, tumor suppressor gene.

aOnly hypermethylated genes with methylation prevalence ≥ 20% in CRC patients and ≤ 10% in normal mucosa were reported. Gene symbols and chromosome location are in accordance with www.genecards.org.

bFor DNA hypermethylation/hypomethylation, number represent prevalence (%) in CRC; for miRNAs, - and + mean down-regulated and up-regulated in CRC compared to normal mucosa, respectively; NA means “not applicable.”

Besides its diagnostic potential, methylated genes are associated with a number of clinical features correlated with poor prognosis (DLEC1, EFEMP1, EphA1, EGFR, MLH1, CDH13) [19, 2124], Epstein-Barr virus–associated gastric carcinomas (B4GALNT2, ST3GAL6) [25]. In contrast, some methylated genes (GATA4, GATA5) are found methylated independently of clinicopathologic features [26].

Some genes are not, at least alone, good biomarkers for CRC since they are frequently methylated in other cancer types such CDKN2A (p16), found methylated across various tumors [10, 16]. In contrast, APC2, B4GALNT1, CCNA1, CDX1, GPNMB, LAMA1, NTRK2, PAPSS2, TCERG1L, and SFRP4 genes are found methylated near 100% of patients tested [19, 2729]. Therefore, these genes could represent promising CRC biomarkers, similarly to the methylation of detoxification enzyme GSTP1, which is a hallmark of prostate cancer, even though data suggest it may also occur in other cancers [16, 30]. Nevertheless, it confirms that epigenetic silencing is far more common than mutations (see for review of mutation frequencies [13]). Interestingly, numerous genes are gradually methylated during colorectal carcinogenesis. By example, CASR is found methylated at 9%, 69%, and 90% in adenoma, carcinoma, and lymph node metastatic tissues, respectively [31]. Intriguingly, some CRC patients accumulate methylation abnormalities in a large number of genes. This CRC subset is defined with CpG island methylator (CIMP) phenotype characterized by clinicopathological and genetic (chromosomal instability) features, which are the consequence of hypermethylation-mediated TSG silencing involved in the malignant transformation of colonic tissue [32]. In sporadic MSI tumors, hypermethylation-mediated silencing of MMR genes such as MLH1 is common [19, 23, 24].

Concomitant with DNA promoter CGI hypermethylation-mediated silencing, global genomic hypomethylation is observed in CRC. This hypomethylation is usually associated with oncogene activation and genetic instability. Accordingly, an increasing list of genes were identified as hypomethylated in CRC patients, such as CCDC116, SFT2D3, MAEL, and H19/IGF2, which could also be used as biomarkers to reinforce CRC detection [33••, 34]. Furthermore, a recent study suggests that long interspersed nuclear element-1 (LINE-1) hypomethylation could be used as a predictive biomarker of chemotherapy response to fluoropyrimidines in CRC patients [35].

Finally, DNMT expression might also be used as a marker, since overexpression of DNMT1 mRNA was reported in 42% of CRC [36].

All together, these events may represent powerful biomarkers for secondary prevention and risk stratification in CRC. Accordingly, these markers represent promising targets for therapeutic/chemopreventive interventions.

miRNA in CRC

MiRNA pathway is an additional epigenetic mechanism implicated in the regulation of tightly regulated biological processes. MiRNAs are endogenous short non-coding RNAs (~22 nucleotides) that post-transcriptionally regulate mRNA expression levels in a sequence-specific manner. MiRNAs bind sequences located essentially in 5′ and 3′ untranslated regions of target genes degrading mRNA or blocking translation. Increasing amount of evidence reveals that miRNA expression signature dysregulations are associated with carcinogenesis, suggesting miRNAs might act as a novel class of oncogenes or TSGs [8, 10, 37].

An increasing number of reports indicate that miRNA dysregulations are important in colorectal carcinogenesis. Table 1 summarizes these alterations based on experimental data from patients. MiRNome signatures revealed that miRNA affected many tumor-suppressive and oncogenic pathways implicated in CRC pathobiology, including β-catenin/Wnt signaling (miR-135a, -135b, -139, -145) [38•, 39, 40], apoptosis (miR-34a, -133b, -195) [38•, 41], differentiation (miR-141, -200c) [4244], p53 signaling (miR-34b/c) [45], proliferation (K-RAS signaling: let7 family, miR-18a, -143, -200c) [38•, 41, 46], cell cycle control (miR-34a, -192, -215, -675) [38•, 41, 47], and migration, invasion, and metastasis (miR-126, -143, -196a, -200a, -200b, -200c, -373, -520c) [38•, 41, 44]. MiRNA pathway may also modulate DNA methylation (miR-143, -342) [48, 49].

In addition, miRNA alterations are correlated to a number of clinicopathologic features and outcomes related to CRC pathogenesis. MiR-21 is a representative example, since high levels of expression are associated with lymph node positivity, increased metastasis propensity and advanced tumor stages associated with worse overall survival [50, 51]. Additional miRNAs, including miR-17, -31, -125b, -126, -143, -196a, -200c, -320, -451, and -498, were identified as associated to an increase of metastasis potential, a decrease of disease-free survival, and a poor prognosis [38•, 4042, 44, 46, 52, 53].

Several studies have identified miRNA expression signatures associated with MSS or MSI CRC phenotypes. These include miR-17, -92, -142, -146b, -212, -217, -510, -513, and -592 associated with MSS, whereas miR-20a, -101, -145, -432*, -455, -484, -492, and -625 were higher in MSI-H tumors [39, 52, 54]. Furthermore, four miRNAs (miR-31, -224, -552, and -592) were identified as able to discriminate between MMR-proficient and MMR-defective adenocarcinomas [40].

All together, these data suggest that CRC-specific miRNA expression signatures are common events, which are representative of CRC-related genetic instability and may be a key event for tumor onset and development. Accordingly, miRNA expression signatures have great and valuable potential for diagnostic and prognostic purposes.

For the past decades, 5-fluorouracil (5-FU) has been and still is the most commonly used chemotherapeutic agent in CRC treatments. However, a significant fraction of patients are refractory or become resistant to 5-FU–based chemotherapies. A growing body of evidence is revealing the importance of miRNA alterations in the modulation of tumor response to 5-FU treatments. For instance, miR-92, -143, and -215, by impairing 5-FU–induced apoptosis [55], could be implicated in the resistance to 5-FU developed by CRC patients presenting low level of expression of miR-92, -143, and -215 [38•, 41]. In addition, miR-21, which plays a central role in colon cancer pathogenesis by targeting many TSGs with elevated expression in advanced tumor stages, was described as an independent predictive marker associated with poor survival and for which overexpression predicts a poor response to therapy [50, 51]. Finally, a recent study suggests that miRNA SNPs rs7372209 and rs1834306 in miR-26-a-1 and miR-100 genes, respectively, affect the clinical outcome of 5-FU–treated CRC patients [56]. These data suggest that miRNA signatures have a potential as marker to predict chemotherapy response.

It has been suggested that, in addition to DNA hypermethylation-mediated silencing of miRNAs (Table 1) [45, 53, 57, 58••, 5961], alterations of proteins involved in miRNA processing is observed in CRC. Indeed, Papachristou et al. [62] reported that the nuclear ribonuclease Drosha and the cytoplasmic ribonucleases Dicer and Ago2 are possibly implicated in colorectal carcinogenesis and that Dicer could influence tumor progression to advanced stages.

Taken together, these findings demonstrate that miRNome alterations represent promising candidates to develop specific and sensitive biomarkers in CRC pathology with opportunities for primary to tertiary prevention levels.

Histones and Histone-Modifying Enzymes in CRC

An additional layer of epigenetic regulation of gene expression is represented by histone tail post-translational covalent modifications. Core histone (H2A, H2B, H3, H4) N-termini are modified by phosphorylation, acetylation, methylation, ubiquitylation, sumoylation, citrullination, β-N-acetylglucosamination, deimination, and ADP-ribosylation. Altogether, these dynamic and reversible modifications establish a “histone code” regulating chromatin structure and activity. The better understood modifications are acetylation of lysine and methylation of arginine and lysine residues. The acetylation/deacetylation reactions are catalyzed by histone acetyl transferases (HATs) and histone deacetylases (HDACs), respectively. Similarly, methylation/demethylation processes are driven by histone methyltransferase (HMTs) and histone demethylases (HDM). While acetylation occurs as a single addition, methylation exists at various levels on the same residue (ie, mono-, di-, and tri-methylation) [63, 64].

There is now clear evidence that aberrant histone modification profiles are closely connected to tumorigenesis. Indeed, dysregulated activity or expression of histone-modifying enzymes as well as their aberrant recruitment by cytogenetic alterations (eg, leukemia-associated fusion proteins) participate in cancer development by inducing aberrant regulation of oncogenes and/or TSGs, and affecting genome stability and/or chromosome segregation [10, 64, 65]. Although our knowledge about histone code and histone-modifying enzymes is incomplete, some data suggest their implications in CRC. A study from Weichert et al. [66] revealed that HDAC1, HDAC2, and HDAC3 are overexpressed in 36.4%, 57.9%, and 72.9% of CRC cases, respectively. Interestingly, the expression was significantly enhanced in strongly proliferating and poorly differentiated tumors. Thus, high HDAC expression levels are associated with reduced patient survival, with in addition, HDAC2 expression being a prognostic factor for survival [66]. HDAC2 overexpression is accompanied by H4K12 and H3K18 acetylation and correlates with adenoma-carcinoma progression [67]. HDAC1 increase was confirmed in another study reporting an upregulation of two HATs: K(lysine) acetyltransferase 2B (KAT2B, CBP) and p300. KAT2B overexpression was associated with long-term survival, whereas p300 overexpression was correlated with a poor prognosis [68]. Interestingly, the class III HDAC sirtuin 1 is overexpressed in 37% of CRC patients and is mainly associated with MSI and CIMP-high phenotypes [69•]. Finally, it was demonstrated that the expression of the cell-cycle regulator p21 is lower in CRC associated with widespread histone H3 hypo-acetylation in chromatin. These observations were connected to the development and progression of CRC but not with tumor biological behaviors [70].

Dysregulation of enzymes involved in histone methylation is also observed in CRC. Indeed, the HMT suppressor of variegation 3–9 homolog 1 (SUV39H1) is overexpressed in 25% of CRC patients and its expression is significantly associated with DNMT1 expression [36]. Furthermore, the histone H3 lysine 4-specific HMT suppressor of variegation, enhancer of zeste, and trithorax (SET)1 is over-expressed in colon tumor cells, where its expression promotes cell proliferation and survival [71]. Moreover, the multiple myeloma SET domain (MMSET) HMT and putative oncoprotein is overexpressed in CRC patients with a worse 5-year survival. Recently, MMSET expression was associated with a good prognostic value in colon cancer and is more pronounced in early stages of colon carcinogenesis (dysplasia) than in adenocarcinomas [72]. Noteworthy, the histone H3 lysine 9-specific HDM, Jumonji domain containing 1A (JMJD1A) was reported as a useful biomarker for hypoxic tumor cells [73]. In humans, enhancer of zeste homolog 2 (EZH2) overexpression-mediated gene silencing has been identified in numerous tumor types associated with H3K27me3 widespread high levels in chromatin. Recent evidence demonstrated that EZH2 overexpression is a common feature of CRC (observed in 87% of cases) [74]. Finally, it was suggested that oncogenic RAS pathways could modulate histone modifications to influence the expression of target genes involved in the regulation of cell proliferation [75]. Accordingly, overexpression of the HMT SET and MYND domain-containing protein 3 (SMYD3) has been reported in mutated K-RAS CRC patients [76].

Taken together these data suggest that histone modification profiles and histone-modifying enzymes could be used as marker as well as therapeutic/chemopreventive targets in CRC and therefore play a role in CRC prevention.

Chemoprevention, Epigenetics, and CRC

Epigenetic mechanisms by their potential reversibility represent interesting targets in CRC for chemopreventive approaches using dietary agents. Accumulating evidence suggests that natural molecules/nutrients present in our diet might modulate epigenetic events in humans. Table 2 summarizes compounds identified in various in vitro and in vivo tumor models that may exert their chemopreventive potential by targeting epigenetic mechanism(s). The current knowledge about some naturally occurring compounds, which may play a significant role in CRC chemoprevention related to epigenetic modulation, is discussed below.
Table 2

Compounds present in diet acting as epigenetic modulators

Dietary agent

Food source

Potential epigenetic target

3,3′-diindolylmethane

Broccoli, cauliflower (indole-3-carbinol metabolite)

Histone modifications, miRNAs

6-methoxy-2E,9E-humuladien-8-one

Ginger

Histone modifications

Allicin

Garlic

Histone modifications

Allyl mercaptan

Garlic

Histone modifications

Anacardic acid

Cashew nuts

Histone modifications

Apigenin

Parsley, celery

DNA methylation

Biochanin A

Soy

Histone modifications

Butein

Toxicodendron vernicifluum

Histone modifications

Butyrate

Gut flora–mediated fermentation of dietary fiber

Histone modifications

Caffeic acid

Coffea

Histone modifications

Catechin

Green tea

Histone modifications

Chlorogenic acid

Coffea

Histone modifications

Cinnamic acid

Cinnamon

Histone modifications

Coumaric acid

Cinnamon

Histone modifications

Curcumin (diferuloylmethane)

Turmeric

Histone modifications, miRNAs

Daidzein

Soy

Histone modifications

Delphinidin

Cranberries, Concord grapes, pomegranates

Histone modifications

Diallyl disulfide

Garlic

Histone modifications

Dihydrocoumarin

Sweet clover (Meliotus officinalis)

Histone modifications

(-)-Epigallocatechin gallate

Green tea

DNA methylation, histone modifications, miRNAs

Equol

Soy

Histone modifications

Fisetin

Strawberries

DNA methylation

Flavone

Mandarin

Histone modifications

Folate

Leafy vegetables, beans, peas, lentils, eggs, liver

DNA methylation, histone modifications

Garcinol, isogarcinol

Garcinia indica

Histone modifications

Genistein

Soybean

DNA methylation, histone modifications, miRNAs

Hesperidin

Citrus

DNA methylation

Isoliquiritigenin

Licorice

Histone modifications

Isothiocyanates

Broccoli

Histone modifications, miRNAs

Kaempferol

Apples, nuts, tea, onions

Histone modifications

Luteolin

Celery, parsley

Histone modifications

Lycopene

Tomatoes and various fruits

DNA methylation

MCP30

Bitter melon

Histone modifications

Myricetin

Walnuts and various berries, fruits, and vegetables

DNA methylation

Naringenin

Citrus

DNA methylation

Phloretin

Apples

DNA methylation

Piceatannol

Grapes (resveratrol metabolite)

Histone modifications

Polyphenon B

Green and black tea

Histone modifications

Pomiferin

Maclura pomifera

Histone modifications

Protocatechuric acid

Olives

DNA methylation

Quercetin

Apples, tea, onion, nuts, berries

DNA methylation, histone modifications

Resveratrol

Grapes

Histone modifications

Rosmarinic acid

Rosemary

DNA methylation

S-allylmercaptocysteine

Garlic

Histone modifications

Sanguinarine

Opium poppy

Histone modifications

Silibinin

Milk thistle

Histone modifications

Sinapinic acid

Sinapis (mustard)

DNA methylation

Sulforaphane

Broccoli

DNA methylation, histone modifications

Syringic acid

Red grapes

DNA methylation

Theophylline

Green and black tea

Histone modifications

Ursolic acid

Basil

Histone modifications

Selenium

Nuts, cereals, meat, fish, eggs, kidney

DNA methylation, histone modifications

Curcumin is well recognized for its chemopreventive and therapeutic properties in vitro and in vivo against many tumor types. Curcumin decreases inflammation cell proliferation, invasion, and angiogenesis, triggers apoptosis, and sensitizes tumor cells to cancer therapies [7779]. These protective properties could be, at least partially, mediated by a modulation of epigenetic events. While no study was performed in colon cells, curcumin is a well-known inhibitor of p300/ KAT2B HAT activity [80]. Furthermore, it was shown that curcumin modulates the miRNA pathway. Specifically, curcumin inhibits miR-21 expression via AP-1 leading to a decreased proliferation and metastasis potential in CRC [81].

Butyrate is an essential short-chained fatty acid (SCFA) for the colon epithelia formed from bacteria-fermented dietary fibers. Butyrate triggers growth arrest, differentiation, and/or apoptosis in many in vitro and in vivo precancerous and tumor cell models including CRC cell lines [8284]. These biological effects leading to carcinogenesis suppression have been proposed to account for the chemopreventive properties of butyrate and to be mediated by HDAC inhibition–induced histone hyperacetylation [83, 84]. Furthermore, butyrate was identified as the most potent HDAC inhibitor among various SCFAs tested in colon carcinoma cells. In the same study, cinnamic acid, coumaric acid, and caffeic acid also showed HDAC inhibitory activities [85].

(-)-Epigallocatechin gallate (EGCG), the major polyphenol in green tea, has been extensively studied both in vitro and in animal models of carcinogenesis and is well recognized for its chemopreventive properties. EGCG seems to have DNA-demethylating properties since it can induce the reactivation of some methylation-silenced TSGs in various tumor models including human colon cancer cells, limiting their proliferation and invasiveness [86, 87].

Isothiocyanates such as sulforaphane (SFN) are sulfur phytonutrients abundant in broccoli reported to present chemopreventive properties in CRC. SFN has been initially found to inhibit in vitro HDAC activity in human colon cancer cells and then in numerous other models [88, 89]. In vivo, a study demonstrated that APCmin/+ mice with SFN-enriched diet have reduced tumor development associated with an increased histone acetylation and p21 expression [90]. Remarkably, in humans, consumption of 68 g broccoli resulted in a significant inhibition of blood HDAC activity 3 h following intake [91]. Furthermore, prolonged exposure to SFN induces a decrease of various class I and selected class II HDAC proteins and especially HDAC3 [92].

3,3′-diindolylmethane (DIM) is a digestive metabolite of indole-3-carbinol, which is found in vegetables such as broccoli or cauliflower. DIM strongly decreases the expression of the anti-apoptotic protein survivin and enhances the effect of butyrate on both apoptosis in colon cancer cells and prevention of FAP in APCmin/+ mice. These effects were accompanied by a drastic decrease of HDAC1, HDAC2, and HDAC3 expression [93], which could be explained by selective DIM-induced proteasomal degradation of class I HDACs (HDAC1–3, and 8), leading to p21 and p27 overexpression. These data may account for DIM’s capability to trigger G2-cell cycle arrest and apoptosis [94].

Garlic-derived sulfur compounds such as diallyl disulphide (DADS) or allyl mercaptan (AM) are known for their HDAC inhibitory potential. Thus, these compounds induce total histone hyperacetylation in colon cancer cells as well as CDKN1A promoter-associated histone hyperacetylation, which is responsible for p21 overexpression and correlated with a G2/M-cell cycle arrest [89, 95]. Remarkably, epidemiological data suggest that garlic consumption decreases risks of CRC. Thus, it is believed that the effect of these sulfur compounds on HDAC account for their anticarcinogenic and chemopreventive properties.

Quercetin has been shown to activate the class III HDAC sirtuin 1 (SIRT1) and to be a potent antitumor agent by decreasing proliferation, and triggering G2/M-cell cycle arrest and apoptosis in cancer cells [96, 97]. In addition, a study revealed that quercetin demethylates CDKN2A promoter in colon cells [98]. Therefore, quercetin might present protective properties against CRC.

Finally, folate and selenium are common nutrients reported to influence epigenetic events. Epidemiological studies support the link between low folate concentrations and increased CRC risk [99]. Folate is the main source of methyl group necessary for the production of SAM, a universal cofactor in methylation reactions. Thus, defects in folate metabolism or intake lead to hypomethylation of genomic DNA or proto-oncogene and alterations of histone methylation patterns associated with genomic instability in colon cells [83]. Selenium has also been reported to alter epigenetic mechanisms, providing a rationale for its potential chemopreventive efficacy. Indeed, it was shown that colon DNA from rats fed a selenium-rich diet was hypomethylated, whereas low-selenium diet increases DNA methylation of the TSG von Hippel-Lindau [100]. These data were linked to selenium propensity to inhibit DNMT1 activity and protein expression in colon cells [101]. Furthermore, organoselenium metabolites of Se-methyl-L-selenocysteine and L-selenomethionine methylselenopyruvate induce HDAC inhibition–dependent histone H3 acetylation in colon cancer cells associated with an induction of p21 expression, which could account for G2/M cell cycle arrest and apoptosis [102]. Therefore, unbalanced and improper consumption of these nutrients might have an injurious impact on colorectal carcinogenesis.

Conclusions and Perspectives

Since epigenetic alterations are reversible, they were initially considered as interesting targets for chemotherapy using DNMT and HDAC inhibitors such as 5-aza-2′-deoxycytidine (decitabine) and suberoylanilide hydroxamic acid (SAHA, vorinostat), respectively. These compounds induce pleiotropic biological effects including regulation of cell growth, differentiation, autophagy, senescence, and apoptosis. Additionally, they sensitize cells to classical chemotherapeutic agents and they mostly act synergistically as antitumor agents against cancer cells [10, 63, 103, 104]. Nonetheless, the use of such pharmacological epigenetic modulators is associated with some dose-limiting toxicities such as neutropenia and thrombocytopenia observed with SAHA or nonspecific cytotoxic effects observed with nucleoside analogues DNA demethylating agents inherent to their incorporation into DNA. In the perspective to reduce these drawbacks, natural compounds might represent a good alternative to identify safer epigenetic modulators. Accordingly, increasing evidence about the impact of environment on epigenetics as well as early occurrence of epimutations in carcinogenesis make us reconsider epigenetic events as promising preventive targets. However, to reach these attractive perspectives, we need to improve our current knowledge of CRC-associated early epigenetic changes, for early detection and to define promising epigenetic targets for chemoprevention. In addition, a clear impact of such chemopreventive strategies is needed, which requires a better rationale of studies to determine detail mechanisms, and assess safety and efficient doses for humans. Nevertheless, epigenetics and chemoprevention by dietary modulators is well associated with targeted therapy and personalized oncology and should ultimately aid to decrease CRC incidence and mortality rate.

Acknowledgments

Research at the Laboratoire de Biologie Moléculaire et Cellulaire du Cancer (LBMCC) is financially supported by the “Recherche Cancer et Sang” foundation, “Recherches Scientifiques Luxembourg,” the “Een Häerz fir Kriibskrank Kanner” association, the Action Lions “Vaincre le Cancer” Luxembourg, and Televie Luxembourg. MS is recipient of a Télévie Luxembourg fellowship. Editing and print costs were covered by the Fonds National de la Recherche (FNR), Luxembourg.

Disclosure

No potential conflicts of interest relevant to this article were reported.

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Authors and Affiliations

  1. 1.Laboratoire de Biologie Moléculaire et Cellulaire de CancerLuxembourgLuxembourg