Metabolic activation of WHO-congeners PCB28, 52, and 101 by human CYP2A6: evidence from in vitro and in vivo experiments.

Despite extensive research on the metabolism of polychlorinated biphenyls (PCBs), knowledge gaps persist regarding their isoform-specific biotransformation pathways. This study aimed to elucidate the role of different cytochrome P450 enzymes in PCB metabolism, focusing on WHO-congeners 2,4,4'-trichlorobiphenyl (PCB28), 2,2',5,5'-tetrachlorobiphenyl (PCB52), and 2,2',4,5,5'-pentachlorobiphenyl (PCB101). Utilizing engineered HEK293 cell lines, we investigated the in vitro metabolism of these PCBs by CYP1A2, CYP2C8, CYP2C9, CYP3A4, CYP2A6, and CYP2E1, revealing robust production of hydroxylated metabolites. Our results show that CYP2A6 plays a major role in the metabolism of these congeners responsible for predominant formation of para-position hydroxylated metabolites, with concentrations reaching up to 1.61 µg/L (5,89 nM) for PCB28, 316.98 µg/L (1,03 µM) for PCB52, and 151.1 µg/L (441 nM) for PCB101 from a 20 µM parent PCB concentration. Moreover, concentration-dependent cytotoxic and cytostatic effects induced by reactive intermediates of the PCB hydroxylation pathway were observed in HEK293CYP2A6 cells, for all three congeners tested. CYP2A6 was specifically capable of activating PCBs 28 and 101 to genotoxic metabolites which produced genetic defects which were propagated to subsequent generations, potentially contributing to carcinogenesis. In a clinical study examining CYP2A6 enzyme activity in formerly exposed individuals with elevated internal PCB levels, a participant with increased enzyme activity showed a direct association between the phenotypic activity of CYP2A6 and the metabolism of PCB28, confirming the role of CYP2A6 in the in vivo metabolism of PCB28 also in humans. These results altogether reinforce the concept that CYP2A6 plays a pivotal role in PCB congener metabolism and suggest its significance in human health, particularly in the metabolism of lower chlorinated, volatile PCB congeners.

In silico and biological analyses of missense variants of the human biliary efflux transporter ABCC2: effects of novel rare missense variants.

BACKGROUND AND PURPOSE: The ATP-dependent biliary efflux transporter ABCC2, also known as multidrug resistance protein 2 (MRP2), is essential for the cellular disposition and detoxification of various xenobiotics including drugs as well as endogenous metabolites. Common functionally relevant ABCC2 genetic variants significantly alter drug responses and contribute to side effects. The aim of this study was to determine functional consequences of rare variants identified in subjects with European ancestry using in silico tools and in vitro analyses. EXPERIMENTAL APPROACH: Targeted next-generation sequencing of the ABCC2 gene was used to identify novel variants in European subjects (n = 143). Twenty-six in silico tools were used to predict functional consequences. For biological validation, transport assays were carried out with membrane vesicles prepared from cell lines overexpressing the newly identified ABCC2 variants and estradiol ß-glucuronide and carboxydichlorofluorescein as the substrates. KEY RESULTS: Three novel rare ABCC2 missense variants were identified (W227R, K402T, V489F). Twenty-five in silico tools predicted W227R as damaging and one as potentially damaging. Prediction of functional consequences was not possible for K402T and V489F and for the common linked variants V1188E/C1515Y. Characterisation in vitro showed increased function of W227R, V489F and V1188E/C1515Y for both substrates, whereas K402T function was only increased for carboxydichlorofluorescein. CONCLUSION AND IMPLICATIONS: In silico tools were unable to accurately predict the substrate-dependent increase in function of ABCC2 missense variants. In vitro biological studies are required to accurately determine functional activity to avoid misleading consequences for drug therapy.

A Semi-Mechanistic Population Pharmacokinetic Model of Noscapine in Healthy Subjects Considering Hepatic First-Pass Extraction and CYP2C9 Genotypes.

INTRODUCTION: Noscapine is a commonly used cough suppressant, with ongoing research on its anti-inflammatory and anti-tumor properties. The drug has a pronounced pharmacokinetic variability. OBJECTIVE: This evaluation aims to describe the pharmacokinetics of noscapine using a semi-mechanistic population pharmacokinetic model and to identify covariates that could explain inter-individual pharmacokinetic variability. METHODS: Forty-eight healthy volunteers (30 men and 18 women, mean age 33 years) were enrolled in a randomized, two-period, two-stage, crossover bioequivalence study of noscapine in two different liquid formulations. Noscapine plasma concentrations following oral administration of noscapine 50 mg were evaluated by a non-compartmental analysis and by a population pharmacokinetic model separately. RESULTS: Compared to the reference formulation, the test formulation exhibited ratios (with 94.12% confidence intervals) of 0.784 (0.662-0.929) and 0.827 (0.762-0.925) for peak plasma concentrations and area under the plasma concentration-time curve, respectively. Significant differences in p values (< 0.01) were both observed when comparing peak plasma concentrations and area under the plasma concentration-time curve between CYP2C9 genotype-predicted phenotypes. A three-compartmental model with zero-order absorption and first-order elimination process best described the plasma data. The introduction of a liver compartment was able to describe the profound first-pass effect of noscapine. Total body weight and the CYP2C9 genotype-predicted phenotype were both identified as significant covariates on apparent clearance, which was estimated as 958 ± 548 L/h for extensive metabolizers (CYP2C9*1/*1 and *1/*9), 531 ± 304 L/h for intermediate metabolizers with an activity score of 1.5 (CYP2C9*1/*2), and 343 ± 197 L/h for poor metabolizers and intermediate metabolizers with an activity score of 1.0 (CYP2C9*1/*3, *2/*3, and*3/*3). CONCLUSION: The current work is expected to facilitate the future pharmacokinetic/pharmacodynamic development of noscapine. This study was registered prior to starting at "Deutsches Register Klinischer Studien" under registration no. DRKS00017760.

Genetic associations of cardiovascular risk genes in European patients with coronary artery spasm.

BACKGROUND: Coronary artery spasm (CAS) is a frequent finding in patients presenting with angina pectoris. Although the pathogenesis of CAS is incompletely understood, previous studies suggested a genetic contribution. Our study aimed to elucidate genetic variants in a cohort of European patients with angina and unobstructed coronary arteries who underwent acetylcholine (ACh) provocation testing. METHODS: A candidate association analysis of 208 genes previously associated with cardiovascular conditions was performed using genotyped and imputed variants in patients grouped in epicardial (focal, diffuse) CAS (n = 119) and microvascular CAS (n = 87). Patients with a negative ACh test result (n = 45) served as controls. RESULTS: We found no association below the genome-wide significance threshold of p < 5 × 10-8, thus not confirming variants in ALDH2, NOS3, and ROCK2 previously reported in CAS patients of Asian ancestry. However, the analysis identified suggestive associations (p < 10-05) for the groups of focal epicardial CAS (CDH13) and diffuse epicardial CAS (HDAC9, EDN1). Downstream analysis of the potential EDN1 risk locus showed that CAS patients have significantly increased plasma endothelin-1 levels (ET-1) compared to controls. An EDN1 haplotype comprising rs9349379 and rs2070698 was significantly associated to ET-1 levels (p = 0.01). CONCLUSIONS: In summary, we suggest EDN1 as potential genetic risk loci for patients with diffuse epicardial CAS, and European ancestry. Plasma ET-1 levels may serve as a potential cardiac marker.

Analysis of the immunological markers BTLA, TIM-3, and PD-L1 at the invasion front and tumor center in clear cell renal cell carcinoma.

PURPOSE: Immune checkpoint inhibitors (ICI) are then backbone in the therapy of metastatic renal cell carcinoma (RCC). The aim of this analysis was to explore the different expression of the ICI PD-L1, BTLA, and TIM-3 at the different tumor locations of the invasion front and the tumor center. METHODS: Large-area sections of the tumor center and invasion front of 44 stage pT1-4 clear cell RCCs were examined immunohistochemically using antibodies against BTLA, TIM-3, and PD-L1 and subsequently correlated with clinicopathologic data. RESULTS: TIM-3 was most strongly expressed at the invasion front (mean ± SD: 84.1 ± 46.6, p = 0.094). BTLA expression was highest in normal tissue, with weak staining in the tumor center and at the invasion front [110.2 vs. 18.6 (p < 0.001) vs. 32.2 (p = 0.248)]. PD-L1 was weakly expressed at the tumor center (n = 5/44) and at the invasion front (n = 5/44). Correlation with clinicopathological parameters revealed significantly higher BTLA expression in ≥ T3 tumors compared to T1/2 tumors (tumor center p = 0.009; invasion front p = 0.005). BTLA-positive tumors at the tumor center correlated with worse CSS (median 48.46 vs. 68.91 months, HR 4.43, p = 0.061). PD-L1 expression was associated with worse CSS (median 1.66 vs. 4.5 years, HR 1.63, p = 0.652). For TIM-3, there were no significant associations with clinicopathological parameters and survival. CONCLUSION: The present results show heterogeneous intratumoral and intertumoral expression of the investigated checkpoint receptors PD-L1, BTLA, and TIM-3. In the clinical practice tumor sampling should include different tumor locations, and multiple inhibition of different checkpoint receptors seems reasonable to increase the therapeutic success.

Nutrimetric Validation of Solanidine as Dietary-Derived CYP2D6 Activity Marker In Vivo.

CYP2D6 is involved in the metabolism of many drugs. Its activity is affected by pharmacogenetic variability leading to highly polymorphic phenotypes between individuals, affecting safety and efficacy of drugs. Recently, solanidine, a steroidal alkaloid from potatoes, and its metabolites, has been identified as a dietary-derived activity marker for CYP2D6. The intraday variability in plasma within individuals has not been studied yet in healthy subjects. As part of a CYP phenotyping cocktail study with 20 healthy participants, plasma concentrations of solanidine, 4-OH-solanidine and 3,4-secosolanidine-3,4-dioic acid (SSDA) were determined using a sensitive liquid chromatography-mass spectrometry method in urine and in plasma at timepoints 0, 2.5, 5, 8, and 24 hours after intake of test substances. The participants were phenotyped for CYP2D6 with oral metoprolol (12.5 mg) with 15 plasma sampling points over 24 hours (DRKS00028922). Metabolic ratios (MRs) of metabolite to parent plasma concentrations were formed from single timepoints and the area under the curve (AUC). All participants were genotyped for CYP2D6. The intra-individual variability of the CYP2D6 metabolite SSDA was highly stable with a median SD of 11.62% over 24 hours. MR SSDA/solanidine was more variable (median SD 31.90%) but correlated significantly at all measured timepoints with AUC MR α-OH-metoprolol/metoprolol. The AUC MR SSDA/solanidine showed a significant linear relationship with the genetically predicted CYP2D6 activity score. This study substantiates the MR SSDA/solanidine as CYP2D6 activity marker. The high correlation with metoprolol MR indicates a valid prediction of the CYP2D6 phenotype at any timepoint during the study day.

Circulating Biomarkers Instead of Genotyping to Establish Metabolizer Phenotypes.

Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the genetic information of absorption, distribution, metabolism, and excretion (ADME) targets such as drug-metabolizing enzymes or transporters to predict differences in the patient's phenotype. However, there is evidence that the phenotype-genotype concordance is limited. Thus, we discuss different phenotyping strategies using exogenous xenobiotics (e.g., drug cocktails) or endogenous compounds for phenotype prediction. In particular, minimally invasive approaches focusing on liquid biopsies offer great potential to preemptively determine metabolic and transport capacities. Early studies indicate that ADME phenotyping using exosomes released from the liver is reliable. In addition, pharmacometric modeling and artificial intelligence improve phenotype prediction. However, further prospective studies are needed to demonstrate the clinical utility of individualized treatment based on phenotyping strategies, not only relying on genetics. The present review summarizes current knowledge and limitations.

Novel drug transporter substrates identification: An innovative approach based on metabolomic profiling, in silico ligand screening and biological validation.

Solute carrier (SLC) transport proteins are fundamental for the translocation of endogenous compounds and drugs across membranes, thus playing a critical role in disease susceptibility and drug response. Because only a limited number of transporter substrates are currently known, the function of a large number of SLC transporters is elusive. Here, we describe the proof-of-concept of a novel strategy to identify SLC transporter substrates exemplarily for the proton-coupled peptide transporter (PEPT) 2 (SLC15A2) and multidrug and toxin extrusion (MATE) 1 transporter (SLC47A1), which are important renal transporters of drug reabsorption and excretion, respectively. By combining metabolomic profiling of mice with genetically-disrupted transporters, in silico ligand screening and in vitro transport studies for experimental validation, we identified nucleobases and nucleoside-derived anticancer and antiviral agents (flucytosine, cytarabine, gemcitabine, capecitabine) as novel drug substrates of the MATE1 transporter. Our data confirms the successful applicability of this new approach for the identification of transporter substrates in general, which may prove particularly relevant in drug research.

Platelet miRNAs: differential expression in coronary artery disease and associations with course of left ventricular systolic function.

BACKGROUND: MicroRNAs are paramount in post transcriptional gene regulation. We investigated platelet miRNAs in patients with CAD and examined potential associations with course of left ventricular ejection fraction (LVEF%). MATERIALS AND METHODS: In a first cohort, 62 MiRNAs were measured in platelets of 100 patients suffering from CAD. Expression profiles of individuals with chronic coronary syndrome (CCS) and MI were compared (CCS n = 67, MI n = 33). Also, associations between miRNA profiles and change in left ventricular ejection fraction (LVEF%) were investigated. In a second cohort of patients suffering from CCS (n = 10), MI (n = 11) or no CAD (n = 13), we measured miRNA expression in platelets, platelet supernatant and serum. This was carried out before and after in vitro platelet activation with CRP. RESULTS: Platelet miRNAs 103a-3p and 155-5p demonstrated higher expression in patients with CCS then in individuals with MI. Furthermore, multiple miRNAs were significantly higher expressed in matched controls compared to MI patients. 8 miRNAs showed higher expression in patients with improving LVEF% after a 1-year follow-up. In our second cohort, we found higher concentrations of 6 miRNAs in the platelet supernatant of patients with CCS, MI and no CAD after in vitro platelet activation. Most of these miRNAs showed a higher abundance in serum of MI patients as compared to CCS. CONCLUSION: Several miRNAs show higher expression in platelets of CCS compared to MI. After in vitro platelet activation, a release of multiple miRNAs out of the thrombocyte was observed. Furthermore, upregulation of serum miRNAs was found in MI patients when compared to CCS patients and individuals without CAD. Hence, platelets could present a source of upregulated circulating miRNAs in MI and additionally affect course of LVEF%.

A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study.

BACKGROUND: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed. METHODS: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants. FINDINGS: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54-0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61-0·79]; p <0·0001). INTERPRETATION: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe. FUNDING: European Union Horizon 2020.

Cross-Ancestry Genome-Wide Association Study Defines the Extended CYP2D6 Locus as the Principal Genetic Determinant of Endoxifen Plasma Concentrations.

The therapeutic efficacy of tamoxifen is predominantly mediated by its active metabolites 4-hydroxy-tamoxifen and endoxifen, whose formation is catalyzed by the polymorphic cytochrome P450 2D6 (CYP2D6). Yet, known CYP2D6 polymorphisms only partially determine metabolite concentrations in vivo. We performed the first cross-ancestry genome-wide association study with well-characterized patients of European, Middle-Eastern, and Asian descent (n = 497) to identify genetic factors impacting active and parent metabolite formation. Genome-wide significant variants were functionally evaluated in an independent liver cohort (n = 149) and in silico. Metabolite prediction models were validated in two independent European breast cancer cohorts (n = 287, n = 189). Within a single 1-megabase (Mb) region of chromosome 22q13 encompassing the CYP2D6 gene, 589 variants were significantly associated with tamoxifen metabolite concentrations, particularly endoxifen and metabolic ratio (MR) endoxifen/N-desmethyltamoxifen (minimal P = 5.4E-35 and 2.5E-65, respectively). Previously suggested other loci were not confirmed. Functional analyses revealed 66% of associated, mostly intergenic variants to be significantly correlated with hepatic CYP2D6 activity or expression (ρ = 0.35 to -0.52), and six hotspot regions in the extended 22q13 locus impacting gene regulatory function. Machine learning models based on hotspot variants (n = 12) plus CYP2D6 activity score (AS) increased the explained variability (~ 9%) compared with AS alone, explaining up to 49% (median R2 ) and 72% of the variability in endoxifen and MR endoxifen/N-desmethyltamoxifen, respectively. Our findings suggest that the extended CYP2D6 locus at 22q13 is the principal genetic determinant of endoxifen plasma concentration. Long-distance haplotypes connecting CYP2D6 with adjacent regulatory sites and nongenetic factors may account for the unexplained portion of variability.

Chemotherapy-related hyperbilirubinemia in pediatric acute lymphoblastic leukemia: a genome-wide association study from the AIEOP-BFM ALL study group.

BACKGROUND: Characterization of clinical phenotypes in context with tumor and host genomic information can aid in the development of more effective and less toxic risk-adapted and targeted treatment strategies. To analyze the impact of therapy-related hyperbilirubinemia on treatment outcome and to identify contributing genetic risk factors of this well-recognized adverse effect we evaluated serum bilirubin levels in 1547 pediatric patients with acute lymphoblastic leukemia (ALL) and conducted a genome-wide association study (GWAS). PATIENTS AND METHODS: Patients were treated in multicenter trial AIEOP-BFM ALL 2000 for pediatric ALL. Bilirubin toxicity was graded 0 to 4 according to the Common Toxicity Criteria (CTC) of the National Cancer Institute. In the GWAS discovery cohort, including 650 of the 1547 individuals, genotype frequencies of 745,895 single nucleotide variants were compared between 435 patients with hyperbilirubinemia (CTC grades 1-4) during induction/consolidation treatment and 215 patients without it (grade 0). Replication analyses included 224 patients from the same trial. RESULTS: Compared to patients with no (grade 0) or moderate hyperbilirubinemia (grades 1-2) during induction/consolidation, patients with grades 3-4 had a poorer 5-year event free survival (76.6 ± 3% versus 87.7 ± 1% for grades 1-2, P = 0.003; 85.2 ± 2% for grade 0, P < 0.001) and a higher cumulative incidence of relapse (15.6 ± 3% versus 9.0 ± 1% for grades 1-2, P = 0.08; 11.1 ± 1% for grade 0, P = 0.007). GWAS identified a strong association of the rs6744284 variant T allele in the UGT1A gene cluster with risk of hyperbilirubinemia (allelic odds ratio (OR) = 2.1, P = 7 × 10- 8). TT-homozygotes had a 6.5-fold increased risk of hyperbilirubinemia (grades 1-4; 95% confidence interval (CI) = 2.9-14.6, P = 7 × 10- 6) and a 16.4-fold higher risk of grade 3-4 hyperbilirubinemia (95% CI 6.1-43.8, P = 2 × 10- 8). Replication analyses confirmed these associations with joint analysis yielding genome-wide significance (allelic OR = 2.1, P = 6 × 10- 11; 95% CI 1.7-2.7). Moreover, rs6744284 genotypes were strongly linked to the Gilbert's syndrome-associated UGT1A1*28/*37 allele (r2 = 0.70), providing functional support for study findings. Of clinical importance, the rs6744284 TT genotype counterbalanced the adverse prognostic impact of high hyperbilirubinemia on therapy outcome. CONCLUSIONS: Chemotherapy-related hyperbilirubinemia is a prognostic factor for treatment outcome in pediatric ALL and genetic variation in UGT1A aids in predicting the clinical impact of hyperbilirubinemia. TRIAL REGISTRATION: http://www. CLINICALTRIALS: gov ; #NCT00430118.

Prediction of Drug-Drug-Gene Interaction Scenarios of (E)-Clomiphene and Its Metabolites Using Physiologically Based Pharmacokinetic Modeling.

Clomiphene, a selective estrogen receptor modulator (SERM), has been used for the treatment of anovulation for more than 50 years. However, since (E)-clomiphene ((E)-Clom) and its metabolites are eliminated primarily via Cytochrome P450 (CYP) 2D6 and CYP3A4, exposure can be affected by CYP2D6 polymorphisms and concomitant use with CYP inhibitors. Thus, clomiphene therapy may be susceptible to drug-gene interactions (DGIs), drug-drug interactions (DDIs) and drug-drug-gene interactions (DDGIs). Physiologically based pharmacokinetic (PBPK) modeling is a tool to quantify such DGI and DD(G)I scenarios. This study aimed to develop a whole-body PBPK model of (E)-Clom including three important metabolites to describe and predict DGI and DD(G)I effects. Model performance was evaluated both graphically and by calculating quantitative measures. Here, 90% of predicted Cmax and 80% of AUClast values were within two-fold of the corresponding observed value for DGIs and DD(G)Is with clarithromycin and paroxetine. The model also revealed quantitative contributions of different CYP enzymes to the involved metabolic pathways of (E)-Clom and its metabolites. The developed PBPK model can be employed to assess the exposure of (E)-Clom and its active metabolites in as-yet unexplored DD(G)I scenarios in future studies.

Dendritic Cells or Macrophages? The Microenvironment of Human Clear Cell Renal Cell Carcinoma Imprints a Mosaic Myeloid Subtype Associated with Patient Survival.

Since their initial description by Elie Metchnikoff, phagocytes have sparked interest in a variety of biologic disciplines. These important cells perform central functions in tissue repair and immune activation as well as tolerance. Myeloid cells can be immunoinhibitory, particularly in the tumor microenvironment, where their presence is generally associated with poor patient prognosis. These cells are highly adaptable and plastic, and can be modulated to perform desired functions such as antitumor activity, if key programming molecules can be identified. Human clear cell renal cell carcinoma (ccRCC) is considered immunogenic; yet checkpoint blockades that target T cell dysfunction have shown limited clinical efficacy, suggesting additional layers of immunoinhibition. We previously described "enriched-in-renal cell carcinoma" (erc) DCs that were often found in tight contact with dysfunctional T cells. Using transcriptional profiling and flow cytometry, we describe here that ercDCs represent a mosaic cell type within the macrophage continuum co-expressing M1 and M2 markers. The polarization state reflects tissue-specific signals that are characteristic of RCC and renal tissue homeostasis. ErcDCs are tissue-resident with increasing prevalence related to tumor grade. Accordingly, a high ercDC score predicted poor patient survival. Within the profile, therapeutic targets (VSIG4, NRP1, GPNMB) were identified with promise to improve immunotherapy.

A novel molecular signature identifies mixed subtypes in renal cell carcinoma with poor prognosis and independent response to immunotherapy.

BACKGROUND: Renal cell carcinoma (RCC) is a heterogeneous disease comprising histologically defined subtypes. For therapy selection, precise subtype identification and individualized prognosis are mandatory, but currently limited. Our aim was to refine subtyping and outcome prediction across main subtypes, assuming that a tumor is composed of molecular features present in distinct pathological subtypes. METHODS: Individual RCC samples were modeled as linear combination of the main subtypes (clear cell (ccRCC), papillary (pRCC), chromophobe (chRCC)) using computational gene expression deconvolution. The new molecular subtyping was compared with histological classification of RCC using the Cancer Genome Atlas (TCGA) cohort (n = 864; ccRCC: 512; pRCC: 287; chRCC: 65) as well as 92 independent histopathologically well-characterized RCC. Predicted continuous subtypes were correlated to cancer-specific survival (CSS) in the TCGA cohort and validated in 242 independent RCC. Association with treatment-related progression-free survival (PFS) was studied in the JAVELIN Renal 101 (n = 726) and IMmotion151 trials (n = 823). CSS and PFS were analyzed using the Kaplan-Meier and Cox regression analysis. RESULTS: One hundred seventy-four signature genes enabled reference-free molecular classification of individual RCC. We unambiguously assign tumors to either ccRCC, pRCC, or chRCC and uncover molecularly heterogeneous tumors (e.g., with ccRCC and pRCC features), which are at risk of worse outcome. Assigned proportions of molecular subtype-features significantly correlated with CSS (ccRCC (P = 4.1E - 10), pRCC (P = 6.5E - 10), chRCC (P = 8.6E - 06)) in TCGA. Translation into a numerical RCC-R(isk) score enabled prognosis in TCGA (P = 9.5E - 11). Survival modeling based on the RCC-R score compared to pathological categories was significantly improved (P = 3.6E - 11). The RCC-R score was validated in univariate (P = 3.2E - 05; HR = 3.02, 95% CI: 1.8-5.08) and multivariate analyses including clinicopathological factors (P = 0.018; HR = 2.14, 95% CI: 1.14-4.04). Heterogeneous PD-L1-positive RCC determined by molecular subtyping showed increased PFS with checkpoint inhibition versus sunitinib in the JAVELIN Renal 101 (P = 3.3E - 04; HR = 0.52, 95% CI: 0.36 - 0.75) and IMmotion151 trials (P = 0.047; HR = 0.69, 95% CI: 0.48 - 1). The prediction of PFS significantly benefits from classification into heterogeneous and unambiguous subtypes in both cohorts (P = 0.013 and P = 0.032). CONCLUSION: Switching from categorical to continuous subtype classification across most frequent RCC subtypes enables outcome prediction and fosters personalized treatment strategies.

Challenges and opportunities associated with rare-variant pharmacogenomics.

Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.

Hepatic solute carrier transporters and drug therapy: Regulation of expression and impact of genetic variation.

Organic cation transporters (OCT), organic anion transporting polypeptides (OATP) and organic anion transporters (OAT) from the solute carrier (SLC) family play an essential role in the uptake of endogenous compounds and drugs into the hepatocytes and other cell types. The well-documented interindividual variability of expression and activity of these transporters translates into interindividual variability in drug pharmacokinetics and drug response. It is therefore important to elucidate mechanisms affecting membrane transporter expression and function. These mechanisms include transcriptional regulation, disease-dependent regulation and genetic variation. In this review, we will summarize the current knowledge of the molecular functions and substrate profiles of cloned hepatic OCTs, OATPs and OATs and discuss recent advances in understanding variable expression and function. Finally, the role of genetic variation in these transporters on drug exposure will be presented with implications for individual drug response.

A Molecularly Characterized Preclinical Platform of Subcutaneous Renal Cell Carcinoma (RCC) Patient-Derived Xenograft Models to Evaluate Novel Treatment Strategies.

Renal cell carcinoma (RCC) is a kidney cancer with an onset mainly during the sixth or seventh decade of the patient's life. Patients with advanced, metastasized RCC have a poor prognosis. The majority of patients develop treatment resistance towards Standard of Care (SoC) drugs within months. Tyrosine kinase inhibitors (TKIs) are the backbone of first-line therapy and have been partnered with an immune checkpoint inhibitor (ICI) recently. Despite the most recent progress, the development of novel therapies targeting acquired TKI resistance mechanisms in advanced and metastatic RCC remains a high medical need. Preclinical models with high translational relevance can significantly support the development of novel personalized therapies. It has been demonstrated that patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In the present project, we established and molecularly characterized a comprehensive panel of subcutaneous RCC PDX models with well-conserved molecular and pathological features over multiple passages. Drug screening towards four SoC drugs targeting the vascular endothelial growth factor (VEGF) and PI3K/mTOR pathway revealed individual and heterogeneous response profiles in those models, very similar to observations in patients. As unique features, our cohort includes PDX models from metastatic disease and multi-tumor regions from one patient, allowing extended studies on intra-tumor heterogeneity (ITH). The PDX models are further used as basis for developing corresponding in vitro cell culture models enabling advanced high-throughput drug screening in a personalized context. PDX models were subjected to next-generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in RCC. In summary, we report a newly established and molecularly characterized panel of RCC PDX models with high relevance for translational preclinical research.