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Capecitabine is a chemotherapeutic drug that is widely used as a monotherapy option in advanced cancer patients. After administration, it is converted into its active metabolite 5-fluorouracil (5-FU), a cytotoxic compound that may also induce adverse side effects in the gastrointestinal (GI) tract. Although these side effects can interfere with the continuation of the chemotherapy, diagnostic tools to detect early onset and prevention strategies are not available. In this explorative case study, we aim to identify differentially expressed genes (DEGs) that provide insight into the molecular mechanisms of toxicity induced by 5-FU in healthy colon tissue of breast cancer patients receiving capecitabine. Gene expression responses observed in patients were compared with those established in an in vitro model of healthy colon organoids. Colon biopsies from two patients with advanced breast cancer were collected before and after the treatment with capecitabine and used for RNA sequencing to determine transcriptomic responses. Differential expression analysis resulted in 31 affected genes, showing that the most affected pathways were transport of small molecules, cellular responses to stress, folate metabolism, NF-kB signalling pathway and immune system responses. The most biologically relevant genes were haemoglobin subunits encoding genes, involved in several processes; ATP12A, SLC26A3 and AQP8, involved in the transport of ions and water; TRIM31, a regulator of NF-kB signalling pathway; MST1P2 and MST1L, stimulators of macrophages. Comparison of human in vitro and in vivo responses showed that the gene expression of TRIM31 was similarly altered in the colon organoids exposed to 5-FU. Therefore, this gene constitutes a potential biomarker of colon toxicity that might be used in future in vitro drug safety design and screening., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systematic genome-wide study was designed to address the impact of multiple important single nucleotide polymorphisms (SNPs) related to As exposure on the methylome of drinking water As-exposed rural subjects from Pakistan. Urinary As levels were used to stratify subjects into low, medium and high exposure groups. Genome-wide DNA methylation was investigated using MeDIP in combination with NimbleGen 2.1 M Deluxe Promotor arrays. Transcriptome levels were measured using Agilent 8 × 60 K expression arrays. Genotyping of selected SNPs (As3MT, DNMT1a, ERCC2, EGFR and MTHFR) was measured and an integrated genetic risk factor for each respondent was calculated by assigning a specific value to the measured genotypes based on known risk allele numbers. To select a representative model related to As exposure we compared 9 linear mixed models comprising of model 1 (including the genetic risk factor), model 2 (without the genetic risk factor) and models with individual SNPs incorporated into the methylome data. Pathway analysis was performed using ConsensusPathDB. Model 1 comprising the integrated genetic risk factor disclosed biochemical pathways including muscle contraction, cardio-vascular diseases, ATR signaling, GPCR signaling, methionine metabolism and chromatin modification in association with hypo- and hyper-methylated gene targets. A unique pathway (direct P53 effector) was found associated with the individual DNMT1a polymorphism due to hyper-methylation of CSE1L and TRRAP. Most importantly, we provide here the first evidence of As-associated DNA methylation in relation with gene expression of ATR, ATF7IP, TPM3, UBE2J2. We report the first evidence that integrating SNPs data with methylome data generates a more representative epigenome profile and discloses a better insight in disease risks of As-exposed individuals., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)