Quantitative Assessment of the Impact of Crohn\u27s Disease on Protein Abundance of Human Intestinal Drug-Metabolising Enzymes and Transporters

Crohn\u27s disease affects the mucosal layer of the intestine, predominantly ileum and colon segments, with the potential to affect the expression of intestinal enzymes and transporters, and consequently, oral drug bioavailability. We carried out a quantitative proteomic analysis of inflamed and non-inflamed ileum and colon tissues from Crohn\u27s disease patients and healthy donors. Homogenates from samples in each group were pooled and protein abundance determined by liquid chromatography–mass spectrometry (LC-MS). In inflamed Crohn\u27s ileum, CYP3A4, CYP20A1, CYP51A1, ADH1B, ALPI, FOM1, SULT1A2, SULT1B1 and ABCB7 showed ≥10-fold reduction in abundance compared with healthy baseline. By contrast, only MGST1 showed ≥10 fold reduction in inflamed colon. Ileal UGT1A1, MGST1, MGST2, and MAOA levels increased by ≥2 fold in Crohn\u27s patients, while only ALPI showed ≥2 fold increase in the colon. Counter-intuitively, non-inflamed ileum had a higher magnitude of fold change than inflamed tissue when compared with healthy tissue. Marked but non-uniform alterations were observed in the expression of various enzymes and transporters in ileum and colon compared with healthy samples. Modelling will allow improved understanding of the variable effects of Crohn\u27s disease on bioavailability of orally administered drugs

Paracetamol self-poisoning: when oral N-acetylcysteine saves life? a case report

Paracetamol is the most widely drug involved in accidental paediatric exposures and deliberate self-poisoning cases because of its availability. Nacetyl cystein is the main treatment for this poisoning. We report a case of a 24-year-old Arab female who has deliberately ingested 100 tablets of 500 mg paracetamol each (50g). Her first examination was normal. She has received oral N-acetyl cystein (NAC) 6 hours after the ingestion. Serum paracetamol level done 18 hours post ingestion was 900 mg/l. On review the next days, she did not develop any symptoms of liver failure. However, due to the massive paracetamol ingestion associated with high serum paracetamol levels, oral NAC was continued for 3 days. The patient was discharged well on the fifth day of hospitalization. Our patient has ingested one of the highest paracetamol overdose (50g) with the highest paracetamol blood levels ever reported in medical literature. She was treated, six hours after ingestion, with oral NAC for 3 days without any side effects

Quantitative Proteomics of Hepatic Drug-Metabolizing Enzymes and Transporters in Patients With Colorectal Cancer Metastasis

The impact of liver cancer metastasis on protein abundance of 22 drug-metabolizing enzymes (DMEs) and 25 transporters was investigated using liquid chromatography-tandem accurate mass spectrometry targeted proteomics. Microsomes were prepared from liver tissue taken from 15 healthy individuals and 18 patients with cancer (2 primary and 16 metastatic). Patient samples included tumors and matching histologically normal tissue. The levels of cytochrome P450 (CYPs 2B6, 2D6, 2E1, 3A4, and 3A5) and uridine 5′-diphospho-glucuronosyltransferases (UGTs 1A1, 1A6, 1A9, 2B15, 2B4, and 2B7) were lower in histologically normal tissue from patients relative to healthy controls (up to 6.6-fold) and decreased further in tumors (up to 21-fold for CYPs and 58-fold for UGTs). BSEP and MRPs were also suppressed in histologically normal (up to 3.1-fold) and tumorous tissue (up to 6.3-fold) relative to healthy individuals. Abundance of OCT3, OAT2, OAT7, and OATPs followed similar trends (up to 2.9-fold lower in histologically normal tissue and up to 16-fold lower in tumors). Abundance of NTCP and OCT1 was also lower (up to 9-fold). Interestingly, monocarboxylate transporter MCT1 was more abundant (3.3-fold) in tumors, the only protein target to show this pattern. These perturbations could be attributed to inflammation. Interindividual variability was substantially higher in patients with cancer. Proteomics-informed physiologically-based pharmacokinetic (PBPK) models of 50 drugs with different attributes and hepatic extraction ratios (Simcyp) showed substantially lower drug clearance with cancer-specific parameters compared with default parameters. In conclusion, this study provides values for decreased abundance of DMEs and transporters in liver cancer, which enables using population-specific abundance for these patients in PBPK modeling

Proteomics of Colorectal Cancer Liver Metastasis: a Quantitative Focus on Drug Elimination and Pharmacodynamics Effects

AIMS: This study aims to quantify drug‐metabolising enzymes, transporters, receptor tyrosine kinases (RTKs) and protein markers (involved in pathways affected in cancer) in pooled healthy, histologically normal and matched cancerous liver microsomes from colorectal cancer liver metastasis (CRLM) patients. METHODS: Microsomal fractionation was performed and pooled microsomes were prepared. Global and accurate mass and retention time liquid chromatography–mass spectrometry proteomics were used to quantify proteins. A QconCAT (KinCAT) for the quantification of RTKs was designed and applied for the first time. Physiologically based pharmacokinetic (PBPK) simulations were performed to assess the contribution of altered abundance of drug‐metabolising enzymes and transporters to changes in pharmacokinetics. RESULTS: Most CYPs and UGTs were downregulated in histologically normal relative to healthy samples, and were further reduced in cancer samples (up to 54‐fold). The transporters, MRP2/3, OAT2/7 and OATP2B1/1B3/1B1 were downregulated in CRLM. Application of abundance data in PBPK models for substrates with different attributes indicated substantially lower (up to 13‐fold) drug clearance when using cancer‐specific instead of default parameters in cancer population. Liver function markers were downregulated, while inflammation proteins were upregulated (by up to 76‐fold) in cancer samples. Various pharmacodynamics markers (e.g. RTKs) were altered in CRLM. Using global proteomics, we examined proteins in pathways relevant to cancer (such as metastasis and desmoplasia), including caveolins and collagen chains, and confirmed general over‐expression of such pathways. CONCLUSION: This study highlights impaired drug metabolism, perturbed drug transport and altered abundance of cancer markers in CRLM, demonstrating the importance of population‐specific abundance data in PBPK models for cancer

Proteomic quantification of perturbation to pharmacokinetic target proteins in liver disease

Model-based assessment of drug pharmacokinetics in liver disease requires quantification of abundance and disease-related changes in hepatic enzymes and transporters. This study aimed to assess performance of three label-free methods [high N (HiN), intensity-based absolute quantification (iBAQ) and total protein approach (TPA)] against QconCAT-based targeted data in healthy and diseased (cancer and cirrhosis) liver tissue. Measurements were compared across methods and disease-to-control ratios provided a ‘disease perturbation factor’ (DPF) for each protein. Mean label-free measurements of targets correlated well (Pearson\u27s coefficient, r = 0.91–0.98 p \u3c 0.001) and with targeted data (r = 0.65–0.95, p \u3c 0.001). Concordance with targeted data was generally moderate (Lin\u27s concordance coefficient, ρc = 0.46–0.92), depending on methodology. Moderate precision and accuracy were observed for label-free methods (average fold error, AFE = 1.44–1.68; absolute average fold error, AAFE = 2.44–3.23). The DPF reconciled the data and indicated downregulated expression in cancer and cirrhosis, consistent with an inflammatory effect. HiN estimated perturbation consistently with targeted data (AFEHiN = 1.07, AAFEHiN = 1.57), whereas iBAQ overestimated (AFEiBAQ = 0.81, AAFEiBAQ = 1.67) and TPA underestimated (AFETPA = 1.37, AAFETPA = 1.65) disease effect. Progression from mild to severe cirrhosis was consistent with progressive decline in expression, reproduced by HiN but overestimated by iBAQ and underestimated by TPA (AFEHiN = 0.98, AFEiBAQ = 0.60, AFETPA = 1.24). DPF data confirmed non-uniform disease effect on drug-elimination pathways and progressive impact of disease severity