The Expression Profiles of ADME Genes in Human Cancers and Their Associations with Clinical Outcomes

Abstract

ADME genes are a group of genes that are involved in drug absorption, distribution, metabolism, and excretion (ADME). The expression profiles of ADME genes within tumours is proposed to impact on cancer patient survival; however, this has not been systematically examined. In this study, our comprehensive analyses of pan-cancer datasets from the Cancer Genome Atlas (TCGA) revealed differential intratumoral expression profiles for ADME genes in 21 different cancer types. Most genes also showed high interindividual variability within cancer-specific patient cohorts. Using Kaplan-Meier plots and logrank tests, we showed that intratumoral expression levels of twenty of the thirty-two core ADME genes were associated with overall survival (OS) in these cancers. Of these genes, five showed significant association with unfavourable OS in three cancers, including SKCM (ABCC2, GSTP1), KIRC (CYP2D6, CYP2E1), PAAD (UGT2B7); sixteen showed significant associations with favourable OS in twelve cancers, including BLCA (UGT2B15), BRCA (CYP2D6), COAD (NAT1), HNSC (ABCB1), KIRC (ABCG2, CYP3A4, SLC22A2, SLC22A6), KIRP (SLC22A2), LIHC (CYP2C19, CYP2C8, CYP2C9, CYP3A5, SLC22A1), LUAD (SLC15A2), LUSC (UGT1A1), PAAD (ABCB1), SARC (ABCB1), and SKCM (ABCB1, DYPD). Overall, these data provide compelling evidence supporting ADME genes as prognostic biomarkers and potential therapeutic targets. We propose that intratumoral expression of ADME genes may impact cancer patient survival by multiple mechanisms that can include metabolizing/transporting anticancer drugs, activating anticancer drugs, and metabolizing/transporting a variety of endogenous molecules involved in metabolically fuelling cancer cells and/or controlling pro-growth signalling pathways.

PXR Modulates the Prostate Cancer Cell Response to Afatinib by Regulating the Expression of the Monocarboxylate Transporter SLC16A1

“…We identified for the first time a PXR-mediated role of SLC16A1 in the transport of afatinib and the sensitivity of prostate cancer cells to this ErBb family blocker. Our study further strengthens the implication of ADME genes in the clinical outcome of various cancers [ 55 ] and highlights the importance of PXR as a potential biomarker of response to anticancer treatments in prostate cancers, in particular kinase inhibitors that are still the object of many clinical trials for castration-resistant tumors.…”

Identification and validation of ADME genes as prognosis and therapy markers for hepatocellular carcinoma patients

“…The samples were from Japanese individuals [ 17 ]. A set of ADME-related genes ( n =298) was acquired from previous literature [ 14 ].…”

“…Previous studies have explored the role of ADME genes as prognostic cancer biomarkers and therapeutic targets. Hu et al (14) reported that about half of ADME genes are expressed in 21 cancers and they have prognostic value in these cancers. In addition, most ADME genes are highly expressed in HCC.…”

The Expression Profiles and Deregulation of UDP-Glycosyltransferase (UGT) Genes in Human Cancers and Their Association with Clinical Outcomes

“…As a varying number of UGT genes were expressed in different cancer types (Table S1), the number of independent logrank tests performed varied among different cancers, ranging from 20 tests in LIHC to 3 tests in UVM. To control false-positive discovery rates, we adjusted the logrank p-values for each cancer type using Bonferroni correction, the most stringent test for multiple testing correction as recently reported [41]. A Bonferroni-corrected cutoff logrank p-value of <0.05 was considered statistically significant.…”

“…The Cancer Genome Atlas (TCGA) project analysed over 20,000 primary cancer patients from 33 different cancer types and provides freely-accessible databases for genomewide molecular profiles (e.g., RNAseq datasets) as well as clinicopathological data (e.g., survival times) for cancer patients (https://gdc.cancer.gov, accessed on 20 June 2021) [40]. Using the RNAseq and clinical datasets from the TCGA project, we recently reported the expression profiles of core ADME genes and their association with patient survival in 21 different TCGA cancer types [41]. Through analyses of the RNAseq and clinical datasets from the TCGA project, the present study defines the expression profiles of all UGT genes in 33 different TCGA cancer types and reports a subset of UGT genes that are significantly associated with survival rates in specific cancers.…”