Population pharmacokinetic analyses for belzutifan to inform dosing considerations and labeling.

Belzutifan (Welireg, Merck & Co., Inc., Rahway, NJ, USA) is an oral, potent inhibitor of hypoxia-inducible factor 2α, approved for the treatment of certain patients with von Hippel-Lindau (VHL) disease-associated renal cell carcinoma (RCC), central nervous system hemangioblastomas, and pancreatic neuroendocrine tumors. It is primarily metabolized by the polymorphic uridine 5'-diphospho-glucuronosyltransferase (UGT) 2B17 and cytochrome (CYP) 2C19. A population pharmacokinetic (PK) model was built, using NONMEM version 7.3, based on demographics/PK data from three clinical pharmacology (food effect, formulation bridging, and genotype/race effect) and two clinical studies (phase I dose escalation/expansion in patients with RCC and other solid tumors; phase II in patients with VHL). Median (range) age for the combined studies was 55 years (19-84) and body weight was 73.6 kg (42.1-165.8). Belzutifan plasma PK was well-characterized by a linear two-compartment model with first-order absorption and elimination. For patients with VHL, the predicted geometric mean (% coefficient of variation) apparent clearance was 7.3 L/h (51%), apparent total volume of distribution was 130 L (35%), and half-life was 12.39 h (42%). There were no clinically relevant differences in belzutifan PK based on the individual covariates of age, sex, ethnicity, race, body weight, mild/moderate renal impairment, or mild hepatic impairment. In this model, dual UGT2B17 and CYP2C19 poor metabolizers (PMs) were estimated to have a 3.2-fold higher area under the plasma concentration-time curve compared to UGT2B17 extensive metabolizer and CYP2C19 non-PM patients. This population PK analysis enabled an integrated assessment of PK characteristics with covariate effects in the overall population and subpopulations for belzutifan labeling.

A statistical perspective on baseline adjustment in pharmacogenomic genome-wide association studies of quantitative change.

In pharmacogenetic (PGx) studies, drug response phenotypes are often measured in the form of change in a quantitative trait before and after treatment. There is some debate in recent literature regarding baseline adjustment, or inclusion of pre-treatment or baseline value as a covariate, in PGx genome-wide association studies (GWAS) analysis. Here, we provide a clear statistical perspective on this baseline adjustment issue by running extensive simulations based on nine statistical models to evaluate the influence of baseline adjustment on type I error and power. We then apply these nine models to analyzing the change in low-density lipoprotein cholesterol (LDL-C) levels with ezetimibe + simvastatin combination therapy compared with simvastatin monotherapy therapy in the 5661 participants of the IMPROVE-IT (IMProved Reduction of Outcomes: Vytroin Efficacy International Trial) PGx GWAS, supporting the conclusions drawn from our simulations. Both simulations and GWAS analyses consistently show that baseline-unadjusted models inflate type I error for the variants associated with baseline value if the baseline value is also associated with change from baseline (e.g., when baseline value is a mediator between a variant and change from baseline), while baseline-adjusted models can control type I error in various scenarios. We thus recommend performing baseline-adjusted analyses in PGx GWASs of quantitative change.

An Exploratory Study Using Electronic Medical Records to Assess the Feasibility of Establishing Cohorts of Patients with Genetic Causes of Parkinson's Disease.

BACKGROUND: More efficient screening methods are needed to improve the ability to identify and follow genetic cohorts in Parkinson's disease (PD). OBJECTIVE: To explore the use of the electronic medical records (EMRs) to identify participants with PD. METHODS: Using an algorithm previously developed in collaboration with Maccabi Healthcare Services (MHS), approximately 5,200 participants with PD were identified, more than 3,200 were screened, and 837 participants were enrolled and genotyped for leucine-rich repeat kinase 2 (LRRK2) and beta-glucocerebrosidase (GBA) variants. Questionnaires were completed to ascertain Ashkenazi Jewish (AJ) ancestry and family history of PD. RESULTS: Among 837 participants with PD, 82% were 65 years and older and 72% had a family history of AJ ancestry. Among those with AJ ancestry, 15.6% reported having relatives with PD. The frequency of observed mutations for LRRK2 and GBA genes combined was approximately 15.4%. The frequency of observed LRRK2 mutation was 6.1% overall and 7.2% from those with AJ ancestry; and for GBA mutation was 9.3% overall and 11.2% from those with AJ ancestry. CONCLUSION: Although the frequency of observed mutations in this study was lower than anticipated, mutation carriers were enriched among those with a family history of AJ ancestry increasing nearly 2-3-fold, from 3% -7% (LRRK2) and 4% -11% (GBA). The identification (and selection) of PD patients through EMRs prior to genotyping is a viable approach, to establish a genetically defined cohort of patients with PD for clinical research.

Germline HLA landscape does not predict efficacy of pembrolizumab monotherapy across solid tumor types.

We evaluated the impact of class I and class II human leukocyte antigen (HLA) genotypes, heterozygosity, and diversity on the efficacy of pembrolizumab. Seventeen pembrolizumab clinical trials across eight tumor types and one basket trial in patients with advanced solid tumors were included (n > 3,500 analyzed). Germline DNA was genotyped using a custom genotyping array. HLA diversity (measured by heterozygosity and evolutionary divergence) across class I loci was not associated with improved response to pembrolizumab, either within each tumor type evaluated or across all patients. Similarly, HLA heterozygosity at each class I and class II gene was not associated with response to pembrolizumab after accounting for the number of tests conducted. No conclusive association between HLA genotype and response to pembrolizumab was identified in this dataset. Germline HLA genotype or diversity alone is not an important independent determinant of response to pembrolizumab and should not be used for clinical decision-making in patients treated with pembrolizumab.

Current challenges and opportunities for pharmacogenomics: perspective of the Industry Pharmacogenomics Working Group (I-PWG).

Pharmaceutical companies have increasingly utilized genomic data for the selection of drug targets and the development of precision medicine approaches. Most major pharmaceutical companies routinely collect DNA from clinical trial participants and conduct pharmacogenomic (PGx) studies. However, the implementation of PGx studies during clinical development presents a number of challenges. These challenges include adapting to a constantly changing global regulatory environment, challenges in study design and clinical implementation, and the increasing concerns over patient privacy. Advances in the field of genomics are also providing new opportunities for pharmaceutical companies, including the availability of large genomic databases linked to patient health information, the growing use of polygenic risk scores, and the direct sequencing of clinical trial participants. The Industry Pharmacogenomics Working Group (I-PWG) is an association of pharmaceutical companies actively working in the field of pharmacogenomics. This I-PWG perspective will provide an overview of the steps pharmaceutical companies are taking to address each of these challenges, and the approaches being taken to capitalize on emerging scientific opportunities.

Global Landscape of Clostridioides Difficile Phylogeography, Antibiotic Susceptibility, and Toxin Polymorphisms by Post-Hoc Whole-Genome Sequencing from the MODIFY I/II Studies.

INTRODUCTION: Clostridioides (Clostridium) difficile infection, the leading cause of healthcare-associated diarrhea, represents a significant burden on global healthcare systems. Despite being a global issue, information on C. difficile from a global perspective is lacking. The aim of this study is to model the global phylogeography of clinical C. difficile. METHODS: Using samples collected from the MODIFY I and II studies (NCT01241552, NCT01513239), we performed whole-genome sequencing of 1501 clinical isolates including 37 novel sequence types (STs), representing the largest worldwide collection to date. RESULTS: Our data showed ribotypes, multi-locus sequence typing clades, and whole-genome phylogeny were in good accordance. The clinical C. difficile genome was found to be more conserved than previously reported (61% core genes), and modest recombination rates of 1.4-5.0 were observed across clades. We observed a significant continent distribution preference among five C. difficile clades (Benjamini-Hochberg corrected Fisher's exact test P < 0.01); moreover, weak association between geographic and genetic distance among ribotypes suggested sources beyond healthcare-related transmission. Markedly different trends of antibiotic susceptibility among lineages and regions were identified, and three novel mutations (in pyridoxamine 5'-phosphate oxidase family protein: Tyr130Ser, Tyr130Cys, and a promoter SNP) associated with metronidazole-reduced susceptibility were discovered on a nim-related gene and its promotor by genome-wide association study. Toxin gene polymorphisms were shown to vary within and between prevalent ribotypes, and novel severe mutations were found on the tcdC toxin regulator protein. CONCLUSION: Our systematic characterization of a global set of clinical trial C. difficile isolates from infected individuals demonstrated the complexity of the genetic makeup of this pathogenic organism. The geographic variability of clades, variability in toxin genes, and mutations associated with antibiotic susceptibility indicate a highly complex interaction of C. difficile between host and environment. This dataset will provide a useful resource for validation of findings and future research of C. difficile.

Genetic Association Reveals Protection against Recurrence of Clostridium difficile Infection with Bezlotoxumab Treatment.

Bezlotoxumab is a human monoclonal antibody against Clostridium difficile toxin B, indicated to prevent recurrence of C. difficile infection (rCDI) in high-risk adults receiving antibacterial treatment for CDI. An exploratory genome-wide association study investigated whether human genetic variation influences bezlotoxumab response. DNA from 704 participants who achieved initial clinical cure in the phase 3 MODIFY I/II trials was genotyped. Single nucleotide polymorphisms (SNPs) and human leukocyte antigen (HLA) imputation were performed using IMPUTE2 and HIBAG, respectively. A joint test of genotype and genotype-by-treatment interaction in a logistic regression model was used to screen genetic variants associated with response to bezlotoxumab. The SNP rs2516513 and the HLA alleles HLA-DRB1*07:01 and HLA-DQA1*02:01, located in the extended major histocompatibility complex on chromosome 6, were associated with the reduction of rCDI in bezlotoxumab-treated participants. Carriage of a minor allele (homozygous or heterozygous) at any of the identified loci was related to a larger difference in the proportion of participants experiencing rCDI versus placebo; the effect was most prominent in the subgroup at high baseline risk for rCDI. Genotypes associated with an improved bezlotoxumab response showed no association with rCDI in the placebo cohort. These data suggest that a host-driven, immunological mechanism may impact bezlotoxumab response. Trial registration numbers are as follows: NCT01241552 (MODIFY I) and NCT01513239 (MODIFY II).IMPORTANCEClostridium difficile infection is associated with significant clinical morbidity and mortality; antibacterial treatments are effective, but recurrence of C. difficile infection is common. In this genome-wide association study, we explored whether host genetic variability affected treatment responses to bezlotoxumab, a human monoclonal antibody that binds C. difficile toxin B and is indicated for the prevention of recurrent C. difficile infection. Using data from the MODIFY I/II phase 3 clinical trials, we identified three genetic variants associated with reduced rates of C. difficile infection recurrence in bezlotoxumab-treated participants. The effects were most pronounced in participants at high risk of C. difficile infection recurrence. All three variants are located in the extended major histocompatibility complex on chromosome 6, suggesting the involvement of a host-driven immunological mechanism in the prevention of C. difficile infection recurrence.

Bezlotoxumab for prevention of Clostridium difficile infection recurrence: Distinguishing relapse from reinfection with whole genome sequencing.

BACKGROUND: Bezlotoxumab has been shown to prevent Clostridium difficile infection recurrence (rCDI) in high-risk patients. METHODS: We used whole genome sequencing to estimate the impact of bezlotoxumab on same-strain relapse or new-strain reinfection in MODIFY I/II trials. Reinfection with a new strain and relapse with the same strain were differentiated by the comparison of ribotype (RT) and pair-wise single-nucleotide whole genome sequencing (WGS) variations (PWSNV). Relapse was assigned if the baseline RT and the RT isolated during rCDI were the same, and if PWSNVs were ≤ 2. Reinfection was assigned if the baseline RT and the RT isolated during rCDI were different, or if the RT was the same but PWSNVs were > 10. Unknown status was assigned if the RT was the same but PWSNVs were 3-10. RESULTS: 259 rCDI events were evaluable (50 [19.3%] reinfection; 198 [76.4%] relapse). The proportion of relapses was higher for ribotype 027 (84.5%) compared with other ribotypes (74.1%). Cumulative incidence of relapse was significantly lower for bezlotoxumab versus no bezlotoxumab (p < 0.0001), with a non-significant trend towards reduction for reinfection (p = 0.14). CONCLUSION: Bezlotoxumab treatment significantly reduced the rate of CDI relapse versus a regimen without bezlotoxumab. (NCT01241552/NCT01513239).

Impact of ADCY9 Genotype on Response to Anacetrapib.

BACKGROUND: Exploratory analyses of previous randomized trials generated a hypothesis that the clinical response to cholesteryl ester transfer protein (CETP) inhibitor therapy differs by ADCY9 genotype, prompting the ongoing dal-GenE trial in individuals with a particular genetic profile. The randomized placebo-controlled REVEAL trial (Randomized Evaluation of the Effects of Anacetrapib through Lipid-Modification) demonstrated the clinical efficacy of the CETP inhibitor anacetrapib among patients with preexisting atherosclerotic vascular disease. In the present study, we examined the impact of ADCY9 genotype on response to anacetrapib in the REVEAL trial. METHODS: Individuals with stable atherosclerotic vascular disease who were treated with intensive atorvastatin therapy received either anacetrapib 100 mg daily or matching placebo. Cox proportional hazards models, adjusted for the first 5 principal components of ancestry, were used to estimate the effects of allocation to anacetrapib on major vascular events (a composite of coronary death, myocardial infarction, coronary revascularization, or presumed ischemic stroke) and the interaction with ADCY9 rs1967309 genotype. RESULTS: Among 19 210 genotyped individuals of European ancestry, 2504 (13.0%) had a first major vascular event during 4 years median follow-up: 1216 (12.6%) among anacetrapib-allocated participants and 1288 (13.4%) among placebo-allocated participants. Proportional reductions in the risk of major vascular events with anacetrapib did not differ significantly by ADCY9 genotype: hazard ratio (HR) = 0.92 (95% CI, 0.81-1.05) for GG; HR = 0.94 (95% CI, 0.84-1.06) for AG; and HR = 0.93 (95% CI, 0.76-1.13) for AA genotype carriers, respectively; genotypic P for interaction = 0.96. Furthermore, there were no associations between ADCY9 genotype and the proportional reductions in the separate components of major vascular events or meaningful differences in lipid response to anacetrapib. CONCLUSIONS: The REVEAL trial is the single largest study to date evaluating the ADCY9 pharmacogenetic interaction. It provides no support for the hypothesis that ADCY9 genotype is materially relevant to the clinical effects of the CETP inhibitor anacetrapib. The ongoing dal-GenE study will provide direct evidence as to whether there is any specific pharmacogenetic interaction with dalcetrapib. CLINICAL TRIAL REGISTRATION: URL: https://www. CLINICALTRIALS: gov. Unique identifier: NCT01252953. URL: http://www.isrctn.com. Unique identifier: ISRCTN48678192. URL: https://www.clinicaltrialsregister.eu. Unique identifier: 2010-023467-18.

The pharmacogenetics of OATP1B1 variants and their impact on the pharmacokinetics and efficacy of elbasvir/grazoprevir.

Aim: To evaluate the effect of SLCO1B1 genetic variants on grazoprevir pharmacokinetics and efficacy. Methods: A retrospective analysis of 1578 hepatitis C virus-infected participants from ten Phase II/III clinical trials. Results: Relative to noncarriers of the risk allele, geometric mean ratios (95% CI) of grazoprevir area under curve (AUC)0-24 were: rs4149056 (risk allele C), one copy, 1.13 (1.06-1.21), two copies, 1.43 (1.16-1.77); and rs11045819 (risk allele A), one copy, 0.93 (0.87-1.00); two copies, 0.78 (0.61-1.00). The rs2306283 variant was not associated with grazoprevir exposure. None of the SLCO1B1 variants were associated with sustained virologic response. Conclusion: Genetic variants in SLCO1B1 were associated with modest changes in grazoprevir pharmacokinetics, but not with meaningful differences in efficacy.

Pharmacogenetic Analysis of OATP1B1, UGT1A1, and BCRP Variants in Relation to the Pharmacokinetics of Letermovir in Previously Conducted Clinical Studies.

The cytomegalovirus (CMV) viral terminase inhibitor letermovir is indicated for prevention of CMV infection in CMV-seropositive allogeneic hematopoietic stem cell transplant recipients. In this analysis, functional variants in solute carrier organic anion transporter family member 1B1 (SLCO1B1), uridine diphosphate-glucuronosyltransferase 1A1 (UGT1A1), and breast cancer resistance protein (BCRP) were assessed for effects on letermovir pharmacokinetics (PK) using pooled genetic information from 296 participants in 12 phase 1 studies. Letermovir area under the plasma concentration-time curve (AUC) was increased in carriers of the SLCO1B1 variant rs4149056 C allele relative to noncarriers with a geometric mean ratio (GMR) of 1.18 (95% confidence interval [CI], 1.06-1.30) for carriers of 1 copy and 1.42 (1.10-1.84) for carriers of 2 copies of the risk allele C compared with noncarriers. The SLCO1B1 variant rs4149032 T allele was associated with a decrease in letermovir AUC with GMR (95%CI) of 0.93 (0.85-1.02) and 0.82 (0.73-0.92) for carriers of 1 and 2 copies of the risk allele T, respectively, compared with noncarriers. The UGT1A1*6 variant rs4148323 A allele was present predominantly in Asian participants and was associated with an increase in letermovir AUC compared with noncarriers (GMR, 1.36; 95%CI, 1. 1.07-1.74). SLCO1B1 variant rs2306283, UGT1A1*28 TA promoter repeat, and BCRP variant rs2231142 had no effect on letermovir PK. Together, these data suggest that variants of enzymes and transporters that are involved in the disposition of letermovir in vitro may account for some variability in letermovir PK, but do not affect exposure to a clinically relevant extent.

Effect of tildrakizumab (MK-3222), a high affinity, selective anti-IL23p19 monoclonal antibody, on cytochrome P450 metabolism in subjects with moderate to severe psoriasis.

AIMS: Tildrakizumab, an interleukin (IL)-23 inhibitor, is indicated for the treatment of moderate to severe chronic plaque psoriasis. Although tildrakizumab is not metabolized by, and does not alter, cytochrome P450 (CYP) expression in vitro, clinically significant pharmacokinetic effects through changes in systemic inflammation, which alters CYP metabolism, have been well documented. At the time of study conduct, the effect of modulation of inflammation/cytokines, including IL-23 inhibition with tildrakizumab, on CYP metabolism, and therefore the potential for disease-drug interactions, in psoriasis patients was unknown. We therefore assessed whether tildrakizumab alters CYP metabolism in subjects with moderate to severe psoriasis. METHODS: This was an open-label, fixed-sequence, two-period trial. In Period 1 (Day 1), subjects received an oral CYP probe cocktail of up to five drugs (midazolam 2 mg [3A4], caffeine 200 mg [1A2], warfarin 10 mg [2C9], omeprazole 40 mg [2C19] and dextromethorphan 30 mg [2D6]), followed by a 7-day washout. In Period 2, subjects received tildrakizumab 200 mg subcutaneously on Days 1 and 29 and a second CYP probe cocktail on Day 57. Substrate or metabolite pharmacokinetics, safety and changes in Psoriasis Severity Area Index (PASI), interleukin-6 (IL-6) and high-sensitivity C-reactive protein (hs-CRP), were assessed. RESULTS: Twenty subjects (13 men, 7 women) were enrolled. Tildrakizumab had no clinically relevant effect on the pharmacokinetics of any of the probe substrates tested. On Day 57 of Period 2, the median percentage decrease from baseline in PASI score following tildrakizumab was ~93%. There were no clinically relevant changes in IL-6 or hs-CRP. Treatment with tildrakizumab was generally well tolerated. CONCLUSION: In subjects with moderate to severe psoriasis, tildrakizumab 200 mg did not have a discernible effect on CYP metabolism. The potential for clinically significant drug-drug interactions (DDIs) with tildrakizumab in patients with psoriasis is low. The difference in the occurrence of DDIs seen with anti-inflammatory agents in rheumatoid arthritis patients compared with psoriasis patients may be due to the much greater extent of systemic inflammation in rheumatoid arthritis as compared to psoriasis.

The combination of MK-5172, peginterferon, and ribavirin is effective in treatment-naive patients with hepatitis C virus genotype 1 infection without cirrhosis.

BACKGROUND & AIMS: MK-5172 is an inhibitor of the hepatitis C virus (HCV) nonstructural protein 3/4A protease; MK-5172 is taken once daily and has a higher potency and barrier to resistance than licensed protease inhibitors. We investigated the efficacy and tolerability of MK-5172 with peginterferon and ribavirin (PR) in treatment-naive patients with chronic HCV genotype 1 infection without cirrhosis. METHODS: We performed a multicenter, double-blind, randomized, active-controlled, dose-ranging, response-guided therapy study. A total of 332 patients received MK-5172 (100, 200, 400, or 800 mg) once daily for 12 weeks in combination with PR. Patients in the MK-5172 groups received PR for an additional 12 or 36 weeks, based on response at week 4. Patients in the control group (n = 66) received a combination of boceprevir and PR, dosed in accordance with boceprevir's US product circular. RESULTS: At 24 weeks after the end of therapy, sustained virologic responses were achieved in 89%, 93%, 91%, and 86% of the patients in the groups given the combination of PR and MK-5172 (100, 200, 400, or 800 mg), respectively, vs 61% of controls. In the MK-5172 group receiving 100 mg, 91% of patients had undetectable levels of HCV RNA at week 4 and qualified for the short duration of therapy. The combination of MK-5172 and PR generally was well tolerated. Transient increases in transaminase levels were noted in the MK-5172 groups given 400 and 800 mg, at higher frequencies than in the MK-5172 groups given 100 or 200 mg, or control groups. CONCLUSIONS: Once-daily MK-5172 (100 mg) with PR for 24 or 48 weeks was highly effective and well tolerated among treatment-naive patients with HCV genotype 1 infection without cirrhosis. Studies are underway to evaluate interferon-free MK-5172-based regimens. ClinicalTrials.gov number: NCT01353911.

Mobilizing pharmacogenomic analyses during clinical trials in drug development.

The utilization of pharmacogenomics (PGx) in drug development is increasing as pharmaceutical companies and regulatory agencies work to understand variation in response to medications. The implementation of PGx in clinical trials requires a number of considerations that begin early at the point of program development for a compound. This article will discuss the issues involved in mobilizing a PGx study during the conduct of a clinical trial, including the development of a PGx hypothesis, the identification of genetic markers for analysis, PGx platform selection and assay development, as well as challenges that arise in relation to global laws and regulations related to genetic research and logistical/timeline concerns in the execution of a PGx analysis.

Quantifying factors for the success of stratified medicine.

Co-developing a drug with a diagnostic to create a stratified medicine - a therapy that is targeted to a specific patient population on the basis of a clinical characteristic such as a biomarker that predicts treatment response - presents challenges for product developers, regulators, payers and physicians. With the aim of developing a shared framework and tools for addressing these challenges, here we present an analysis using data from case studies in oncology and Alzheimer's disease, coupled with integrated computational modelling of clinical outcomes and developer economic value, to quantify the effects of decisions related to key issues such as the design of clinical trials. This illustrates how such analyses can aid the coordination of diagnostic and drug development, and the selection of optimal development and commercialization strategies. It also illustrates the impact of the interplay of these factors on the economic feasibility of stratified medicine, which has important implications for public policy makers.

DLK1-DIO3 genomic imprinted microRNA cluster at 14q32.2 defines a stemlike subtype of hepatocellular carcinoma associated with poor survival.

Hepatocellular carcinoma (HCC) is a heterogeneous and highly aggressive malignancy, for which there are no effective cures. Identification of a malignant stemlike subtype of HCC may offer patients with a dismal prognosis a potential targeted therapy using c-MET and Wnt pathway inhibitors. MicroRNAs (miRNAs) show promise as diagnostic and prognostic tools for cancer detection and stratification. Using a TRE-c-Met-driven transgenic HCC mouse model, we identified a cluster of 23 miRNAs that is encoded within the Dlk1-Gtl2 imprinted region on chromosome 12qF1 overexpressed in all of the isolated liver tumors. Interestingly, this region is conserved among mammalian species and maps to the human DLK1-DIO3 region on chromosome 14q32.2. We thus examined the expression of the DLK1-DIO3 miRNA cluster in a cohort of 97 hepatitis B virus-associated HCC patients and identified a subgroup (n = 18) of patients showing strong coordinate overexpression of miRNAs in this cluster but not in other cancer types (breast, lung, kidney, stomach, and colon) that were tested. Expression levels of imprinted gene transcripts from neighboring loci in this 14q32.2 region and from a subset of other imprinted sites were concomitantly elevated in human HCC. Interestingly, overexpression of the DLK1-DIO3 miRNA cluster was positively correlated with HCC stem cell markers (CD133, CD90, EpCAM, Nestin) and associated with a high level of serum α-fetoprotein, a conventional biomarker for liver cancer, and poor survival rate in HCC patients. In conclusion, our findings suggest that coordinate up-regulation of the DLK1-DIO3 miRNA cluster at 14q32.2 may define a novel molecular (stem cell-like) subtype of HCC associated with poor prognosis.

Predictive genes in adjacent normal tissue are preferentially altered by sCNV during tumorigenesis in liver cancer and may rate limiting.

BACKGROUND: In hepatocellular carcinoma (HCC) genes predictive of survival have been found in both adjacent normal (AN) and tumor (TU) tissues. The relationships between these two sets of predictive genes and the general process of tumorigenesis and disease progression remains unclear. METHODOLOGY/PRINCIPAL FINDINGS: Here we have investigated HCC tumorigenesis by comparing gene expression, DNA copy number variation and survival using ∼250 AN and TU samples representing, respectively, the pre-cancer state, and the result of tumorigenesis. Genes that participate in tumorigenesis were defined using a gene-gene correlation meta-analysis procedure that compared AN versus TU tissues. Genes predictive of survival in AN (AN-survival genes) were found to be enriched in the differential gene-gene correlation gene set indicating that they directly participate in the process of tumorigenesis. Additionally the AN-survival genes were mostly not predictive after tumorigenesis in TU tissue and this transition was associated with and could largely be explained by the effect of somatic DNA copy number variation (sCNV) in cis and in trans. The data was consistent with the variance of AN-survival genes being rate-limiting steps in tumorigenesis and this was confirmed using a treatment that promotes HCC tumorigenesis that selectively altered AN-survival genes and genes differentially correlated between AN and TU. CONCLUSIONS/SIGNIFICANCE: This suggests that the process of tumor evolution involves rate-limiting steps related to the background from which the tumor evolved where these were frequently predictive of clinical outcome. Additionally treatments that alter the likelihood of tumorigenesis occurring may act by altering AN-survival genes, suggesting that the process can be manipulated. Further sCNV explains a substantial fraction of tumor specific expression and may therefore be a causal driver of tumor evolution in HCC and perhaps many solid tumor types.

Prospective-retrospective biomarker analysis for regulatory consideration: white paper from the industry pharmacogenomics working group.

One approach to delivering cost-effective healthcare requires the identification of patients as individuals or subpopulations that are more likely to respond to an appropriate dose and/or schedule of a therapeutic agent, or as subpopulations that are less likely to develop an adverse event (i.e., personalized or stratified medicine). Biomarkers that identify therapeutically relevant variations in human biology are often only uncovered in the later stage of drug development. In this article, the Industry Pharmacogenomics Working Group provides, for regulatory consideration, its perspective on the rationale for the conduct of what is commonly referred to as the prospective-retrospective analysis (PRA) of biomarkers. Reflecting on published proposals and materials presented by the US FDA, a decision tree for generating robust scientific data from samples collected from an already conducted trial to allow PRA is presented. The primary utility of the PRA is to define a process that provides robust scientific evidence for decision-making in situations where it is not necessary, nor practical or ethical to conduct a new prospective clinical study.

The value of banked samples for oncology drug discovery and development.

To gain insights into human biology and pathobiology, ready access to banked human tissue samples that encompass a representative cross section of the population is required. For optimal use, the banked human tissue needs to be appropriately consented, collected, annotated, and stored. If any of these elements are missing, the studies using these samples are compromised. These elements are critical whether the research is for academic or pharmaceutical industry purposes. An additional temporal element that adds enormous value to such banked samples is treatment and outcome information from the people who donated the tissue. To achieve these aims, many different groups have to work effectively together, not least of which are the individuals who donate their tissue with appropriate consent. Such research is unlikely to benefit the donors but others who succumb to the same disease. The development of a large accessible human tissue bank resource (National Cancer Institute's Cancer HUman Biobank [caHUB]) that provides an ongoing supply of human tissue for all working toward the common goal of understanding human health and disease has a number of advantages. These include, but are not limited to, access to a broad cross section of healthy and diseased populations beyond what individual collections may achieve for understanding disease pathobiology, therapeutic target discovery, as well as a source of material for diagnostic assay validation. Models will need to be developed to enable fair access to caHUB under terms that enable appropriate intellectual property protection and ultimate data sharing to ensure that the biobank successfully distributes samples to a broad range of researchers.