Dietary toxins in carcinogenesis: Mechanisms utilized

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Dr. Grace Akinyi Odongo

Dietary toxins: Mycotoxins

• Mycotoxins are toxins naturally produced by fungi (mould). Common mycotoxins include aflatoxins which are produced by Aspergillus species of fungi, fumonisins produced by Fusarium species and ochratoxins produced by Aspergillus species and Penicillium species.

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• These toxins contaminate food products especially grains such as maize, nuts and wheat.

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• Aflatoxins B1 (AFB1) exposure has been reported to increase the risk of hepatocellular carcinoma (liver cancer) development in the presence of Hepatitis B or C virus infection Zhu Q et al., 2021 and Chu Y et al., 2018.

International Agency for Research on cancer classification of mycotoxins based their carcinogenicity to humans

Effects mycotoxins exposure

• Mycotoxins or Aflatoxin B1 can contribute to carcinogenesis through impacting genes or proteins that play a role in cancer development.

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• In our recent studies we have shown that Aflatoxin B1 and related toxins cause deregulation and methylation changes in gene CCL22 and TGFBI thereby promoting cancer development (carcinogenesis) Odongo G.A. et al., 2024 and Manara F. et al., 2022.

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• CCL22 (C-C motif Chemokine ligand 22) also known as macrophage derived chemokine. It is a pro-inflammatory cytokine that plays a role in immunity. It can suppress anti-tumour activity.

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• TGFBI (Transforming growth factor beta-induced gene) plays in a role of promoting development of several cancer types such as colon, gastric, bladder, and breast cancer. TGFBI play a role in cancer cell proliferation, angiogenesis and apoptosis. It facilitates invasion and metastasis (Wang B et al., 2019 and Wang H et al., 2024).

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Mechanisms used by mycotoxins in carcinogenesis

Mycotoxins and EBV exposure increase CCL22 gene expression

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(A) CCL22 relative mRNA expression levels in Louckes and primary B cells exposed to aflatoxin B1 (AFB1) 50 µM and B2 (AFB2) 50 µM. (B) CCL22 protein levels detected in presence and absence of aflatoxin exposure (50 µM) by Western Blot using total cell extract (Left) and immunoprecipitated (IP) CCL22 from cell supernatant (Right). (C and D) RT-qPCR quantification of CCL22 mRNA levels in cells exposed to AFB1 (50 µM), aflatoxicol (AFL) at 25 µM, sterigmatocystin (STC) at 3.13 µM and combination of both (AFL+STC) for 48 h only or infected by EBV 24 h after treatment. (E) The RT-qPCR analyses of CCR4 mRNA levels in Louckes and primary B cells exposed to AFB1 (50 µM) and EBV. DMSO was used as solvent control in all experiments. The histograms represent data mean ± SD and significance level calculated by ANOVA test (P *≤ 0.05, or P** ≤ 0.01, or P*** ≤ 0.001 or P**** ≤ 0.0001), n = 3. (F) Representative images of immunohistochemistry staining for CCL22 performed on EBV-positive (n = 8) and EBV-negative (n = 6) Burkitt Lymphomas.

Published PNAS

AFB1 and EBV stimulate CCL22 via the activation of NF-kB pathway

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(A) RT-qPCR analysis of CCL22 mRNA expression levels in Louckes cells exposed to NF-kB inhibitor (Bay11; used at 1 µM or 10 µM) under conditions of AFB1 treatment (50 µM) for 48 h, EBV for 24 h, or a combination of both EBV and AFB1 with nonexposed cells (/) as control. (B) RT-qPCR quantification of RelA/p65 (key subunit of NF-kB) mRNA expression levels in exposed Louckes cells as (A) and transfected with siRelA/p65 or scramble control (siCtrl) (Left). RT-qPCR relative quantification of CCL22 mRNA in exposed cells transfected with siCtrl or siRelA/p65 (Right). Data are mean ± SD (n = 3) and significance level calculated by ANOVA test (P* ≤ 0.05, or P** ≤ 0.01, or P*** ≤ 0.001 or P**** ≤ 0.0001).

Published PNAS

CCL22 enhances EBV infection through activation of PI3K pathway

(A) qPCR quantification of viral DNA levels in EBV exposed primary B cells treated with CCL22 neutralizing antibody (CCL22 ab) or isotype antibody (isotype). (B) RT-qPCR analysis of CCL22 gene silencing efficiency in EBV infected B cells (Left) and FACS analysis data indicating the percentage of green fluorescence protein EBV-positive B cells (%GFP+ B cells) in siCCL22 (siRNA against CCL22) versus siCtrl (scramble control) treated B cells infected with EBV (Right). (C) qPCR quantification of viral DNA levels in EBV exposed primary B cells treated with human recombinant CCL22 (RhCCL22) or phosphate buffered saline (Pbs). (D) Same as in (B). Mock infected cells were used as controls in all EBV infection experiments. (E) Viral quantification results by FACS in siCCL22 treated cells exposed to AFB1 50 µM (Up) and infected by EBV together with western blot results of CCL22 protein detection in treated cells (Down). (F) Viral DNA level by qPCR in exposed B cells treated with a PI3K inhibitor (Wortmannin) or untreated, exposure of cells was with either EBV, or EBV plus RhCCL22, or EBV plus AFB1. Dimethyl sulfoxide (DMSO) was used as solvent control in aflatoxins exposures. Histograms represent mean ± SD, n = 3, and significance level calculated by Student’s t test (P* ≤ 0.05, or P** ≤ 0.01, or P*** ≤ 0.001 or P**** ≤ 0.0001).

Published PNAS

Published cancers

Methylation signatures of Burkitt’s Lymphoma (BL), EBV, and AFB1

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(a) Heatmap of differentially methylated positions (DMPs) in the genome of EBV(+) and EBV(-) BL-derived cell lines, primary B cells, and lymphoblastoid cells (LCL). (b) Genes commonly affected by methylation changes identified from the comparative analysis of methylomes associated with the conditions previously illustrated in (a) with AFB1 exposure. The Venn Diagram illustrates the intersection of DMPs associated respectively with aflatoxin B1 exposure condition (“AFB1 in vivo”) provided by a publicly available dataset (Vargas et al., 2015), with the eBL-specific ones (“BL EBV+”) identified in a previous study (Vargas et al., 2017) and, ultimately, with the specific signature of B cell transformation state (“BL”). (c) TGFBI gene diagram (modified from UCSC Genome Browser) in which the CGs showing differential methylation are highlighted in red boxes.

TGFBI cancer related gene affected by methylation changes caused by AFB1, EBV +/- Burkitt’s lymphoma.

EBV and AFB1-induced hypermethylation of TGFBI promoter

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(a) Pyrosequencing-based quantification of methylation levels within the TGFBI CpG sites previously identified-CG21, CG11, and CG00–in primary human B cell s and EBV(+) BL derived cell lines (b) and in eBL samples (n = 20) vs. healthy patients’ lymph nodes. Statistical significance was determined by Student’s t test (* p  <  0.05). Error bars in the graphs represent the standard deviation. (c,d) Pyrosequencing analysis of the methylation levels within the same CpG sites in EBV(-) BL cells in vitro treated with AFB1 for 48 h; n = 2.

Published cancers

Published cancers

EBV and AFB1 share a common pathway to regulate TGFBI

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(a) Schematic representation of the in vitro combined AFB1-exposure and EBV-infection-mediated primary B cells immortalization experiment. (b) qPCR quantification of TGFBI mRNA expression levels in LCL obtained as explained in (a) (* p  <  0.05). (c) Heatmap of CG methylation levels in B cells at different stages of EBV-mediated immortalization, in presence or absence of concomitant AFB1 in vitro exposure. Independent experiments from different B cells donors. (d) pyrosequencing-based analysis of TGFBI methylation levels within the three CpGs of interest at different time points of EBV-induced B cells immortalization with concurrent AFB1/DMSO treatment. (e) Immunoblotting quantification of Phospho-IκBα (PIKBA) and IκBα (IKBA) levels in Louckes vs. Louckes-EBV treated or not with AFB1 50 µM. (f) The enzymatic assays-based measure of DNMTs activity (left graph (OD/h/mg)) and DNMT1 quantity in the nucleus (right graph (ng/mg)) in RPMI-LMP1 vs. RPMI-pLXSN cell lines treated with AFB1/DMSO and with Bay11/DMSO

Published environment International

Longitudinal effects of AFB1 exposure and EBV infection on the histone code

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(A) Volcano plots showing differentially abundant histone modifications over time. Significant changes (adjusted p < 0.05) are highlighted in red. Comparisons include DMSO+ vs. DMSO (top left), AFB1+ vs. DMSO+ (top right), AFB1 vs. DMSO (bottom left), and AFB1+ vs. AFB1 (bottom right). (B, C) Box plots depicting temporal changes in histone acetylation levels for H3.1K27me3 (B) and H3.3K27me3 (C) in AFB1-treated cells compared to DMSO controls. (D, E) Box plots showing temporal dynamics of H4K12ac (D) and H4K16ac (E) in EBV-infected cells following treatment with AFB1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Changes seen in H3.1K27me3 and H3.3K27me3

(Histone 3 tri methylation of lysine 27)

Conclusion

• B cells exposure to AFB1 and EBV synergistically stimulated CCL22 secretion via the activation of Nuclear Factor-kappa B pathway.

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• CCL22 overexpression resulting from AFB1-exposure in vitro increased EBV (oncogenic virus) infection through the activation of phosphoinositide-3-kinase pathway.

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• Genome-wide DNA methylation profiling identified an EBV–AFB1 common signature within the TGFBI locus, which encodes for a putative tumour suppressor often altered in cancer. Subsequent mechanistic analyses confirmed a DNA-methylation-dependent transcriptional silencing of TGFBI involving the recruitment of DNMT1 methyltransferase that is associated with an activation of the NF-κB pathway. Results reveal a potential common mechanism of B cell transformation shared by the main risk factors of endemic BL (EBV and AFB1).

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• We observed alterations in histone methylation and acetylation patterns over time in all cells. Specifically, AFB1 exposure induced an increase in H3K27me3 levels, which in the case of EBV infected cells, counteracts the decrease observed at baseline compared to uninfected cells. Additionally, changes in acetylation patterns of H4 N-tail residues and key regulatory proteins suggest potential disruptions in chromatin accessibility and transcriptional regulation

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• These findings unravel new mechanisms that may underpin endemic Burkitt’s lymphoma development and identify novel pathways that can be targeted in drug development.

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Acknowledgement

Special Thanks

Dr. Zdenko Herceg

Dr. Rita Khoueiry

Dr. Francesca Manara

Dr. Tarik Gheit

EGM branch members

Collaborators

Prof. Dr. Sarah De Saeger

Prof. Dr. Marthe De Borvre

Dr. Thanos M. Michailidis

Ghent team members

Dr. Henry Gruffat

Dr. Mohamed Ali Maroui

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