Liver safety assessment: required data elements and best practices for data collection and standardization in clinical trials.

A workshop was convened to discuss best practices for the assessment of drug-induced liver injury (DILI) in clinical trials. In a breakout session, workshop attendees discussed necessary data elements and standards for the accurate measurement of DILI risk associated with new therapeutic agents in clinical trials. There was agreement that in order to achieve this goal the systematic acquisition of protocol-specified clinical measures and lab specimens from all study subjects is crucial. In addition, standard DILI terms that address the diverse clinical and pathologic signatures of DILI were considered essential. There was a strong consensus that clinical and lab analyses necessary for the evaluation of cases of acute liver injury should be consistent with the US Food and Drug Administration (FDA) guidance on pre-marketing risk assessment of DILI in clinical trials issued in 2009. A recommendation that liver injury case review and management be guided by clinicians with hepatologic expertise was made. Of note, there was agreement that emerging DILI signals should prompt the systematic collection of candidate pharmacogenomic, proteomic and/or metabonomic biomarkers from all study subjects. The use of emerging standardized clinical terminology, CRFs and graphic tools for data review to enable harmonization across clinical trials was strongly encouraged. Many of the recommendations made in the breakout session are in alignment with those made in the other parallel sessions on methodology to assess clinical liver safety data, causality assessment for suspected DILI, and liver safety assessment in special populations (hepatitis B, C, and oncology trials). Nonetheless, a few outstanding issues remain for future consideration.

HIV-1 coreceptor usage and CXCR4-specific viral load predict clinical disease progression during combination antiretroviral therapy

Background: Although combination antiretroviral therapy (cART) dramatically reduces rates of AIDS and death, a minority of patients experience clinical disease progression during treatment. <p>Objective: To investigate whether detection of CXCR4(X4)-specific strains or quantification of X4-specific HIV-1 load predict clinical outcome. Methods: From the Swiss HIV Cohort Study, 96 participants who initiated cART yet subsequently progressed to AIDS or death were compared with 84 contemporaneous, treated nonprogressors. A sensitive heteroduplex tracking assay was developed to quantify plasma X4 and CCR5 variants and resolve HIV-1 load into coreceptor-specific components. Measurements were analyzed as cofactors of progression in multivariable Cox models adjusted for concurrent CD4 cell count and total viral load, applying inverse probability weights to adjust for sampling bias. Results: Patients with X4 variants at baseline displayed reduced CD4 cell responses compared with those without X4 strains (40 versus 82 cells/mu l; P= 0.012). The adjusted multivariable hazard ratio (HR) for clinical progression was 4.8 [95% confidence interval (Cl) 2.3-10.0] for those demonstrating X4 strains at baseline. The X4-specific HIV-1 load was a similarly independent predictor, with HR values of 3.7(95%Cl, 1.2-11.3) and 5.9 (95% Cl, 2.2-15.0) for baseline loads of 2.2-4.3 and > 4.3 log(10)copies/ml, respectively, compared with < 2.2 log(10)copies/ml. Conclusions: HIV-1 coreceptor usage and X4-specific viral loads strongly predicted disease progression during cART, independent of and in addition to CD4 cell count or total viral load. Detection and quantification of X4 strains promise to be clinically useful biomarkers to guide patient management and study HIV-1 pathogenesis.

Immunoregulation in human malaria: the challenge of understanding asymptomatic infection

Asymptomatic Plasmodium infection carriers represent a major threat to malaria control worldwide as they are silent natural reservoirs and do not seek medical care. There are no standard criteria for asymptomaticPlasmodium infection; therefore, its diagnosis relies on the presence of the parasite during a specific period of symptomless infection. The antiparasitic immune response can result in reducedPlasmodium sp. load with control of disease manifestations, which leads to asymptomatic infection. Both the innate and adaptive immune responses seem to play major roles in asymptomatic Plasmodiuminfection; T regulatory cell activity (through the production of interleukin-10 and transforming growth factor-β) and B-cells (with a broad antibody response) both play prominent roles. Furthermore, molecules involved in the haem detoxification pathway (such as haptoglobin and haeme oxygenase-1) and iron metabolism (ferritin and activated c-Jun N-terminal kinase) have emerged in recent years as potential biomarkers and thus are helping to unravel the immune response underlying asymptomatic Plasmodium infection. The acquisition of large data sets and the use of robust statistical tools, including network analysis, associated with well-designed malaria studies will likely help elucidate the immune mechanisms responsible for asymptomatic infection.

Serum sCD163 levels are associated with type 2 diabetes mellitus and are influenced by coffee and wine consumption: results of the Di@bet.es study.

OBJECTIVE Serum levels of soluble TNF-like weak inducer of apoptosis (sTWEAK) and its scavenger receptor CD163 (sCD163) have been linked to insulin resistance. We analysed the usefulness of these cytokines as biomarkers of type 2 diabetes in a Spanish cohort, together with their relationship to food consumption in the setting of the Di@bet.es study. RESEARCH DESIGN AND METHODS This is a cross-sectional, matched case-control study of 514 type 2 diabetes subjects and 517 controls with a Normal Oral Glucose Tolerance Test (NOGTT), using data from the Di@bet.es study. Study variables included clinical and demographic structured survey, food frequency questionnaire and physical examination. Serum concentrations of sTWEAK and sCD163 were measured by ELISA. Linear regression analysis determined which variables were related to sTWEAK and sCD163 levels. Logistic regression analysis was used to estimate odd ratios of presenting type 2 diabetes. RESULTS sCD163 concentrations and sCD163/sTWEAK ratio were 11.0% and 15.0% higher, respectively, (P<0.001) in type 2 diabetes than in controls. Following adjustment for various confounders, the OR for presenting type 2 diabetes in subjects in the highest vs the lowest tertile of sCD163 was [(OR), 2,01 (95%CI, 1,46-2,97); P for trend <0.001]. Coffee and red wine consumption was negatively associated with serum levels of sCD163 (P = 0.0001 and; P = 0.002 for coffee and red wine intake, respectively). CONCLUSIONS High circulating levels of sCD163 are associated with type 2 diabetes in the Spanish population. The association between coffee and red wine intake and these biomarkers deserves further study to confirm its potential role in type 2 diabetes.

Colorectal Cancer Classification and Cell Heterogeneity: A Systems Oncology Approach.

Colorectal cancer is a heterogeneous disease that manifests through diverse clinical scenarios. During many years, our knowledge about the variability of colorectal tumors was limited to the histopathological analysis from which generic classifications associated with different clinical expectations are derived. However, currently we are beginning to understand that under the intense pathological and clinical variability of these tumors there underlies strong genetic and biological heterogeneity. Thus, with the increasing available information of inter-tumor and intra-tumor heterogeneity, the classical pathological approach is being displaced in favor of novel molecular classifications. In the present article, we summarize the most relevant proposals of molecular classifications obtained from the analysis of colorectal tumors using powerful high throughput techniques and devices. We also discuss the role that cancer systems biology may play in the integration and interpretation of the high amount of data generated and the challenges to be addressed in the future development of precision oncology. In addition, we review the current state of implementation of these novel tools in the pathological laboratory and in clinical practice.

A combined molecular clinical predictor of survival validated with the rtog-0525 cohort

For glioblastoma (GBM), survival classification has primarily relied on clinical criteria, exemplified by the Radiation Therapy Oncology Group (RTOG) recursive partitioning analysis (RPA). We sought to improve tumor classification by combining tumor biomarkers with the clinical RPA data. To accomplish this, we first developed 4 molecular biomarkers derived from gene expression profiling, a glioma CpG island methylator phenotype, a novel MGMT promoter methylation assay, and IDH1 mutations. A molecular predictor (MP) model was created with these 4 biomarkers on a training set of 220 retrospectively collected archival GBMtumors. ThisMPwas further combined with RPA classification to develop a molecular-clinical predictor (MCP). The median survivals for the combined, 4-class MCP were 65 months, 31 months, 13 months, and 9 months, which was significantly improved when compared with the RPA alone. The MCP was then applied to 725 samples from the RTOG-0525 cohort, showing median survival for each risk group of NR, 26 months, 16 months, and 11 months. The MCP was significantly improved over the RPA at outcome prediction in the RTOG 0525 cohort with a 33%increase in explained variation with respect to survival, validating the result obtained in the training set. To illustrate the benefit of the MCP for patient stratification, we examined progression-free survival (PFS) for patients receiving standard-dose temozolomide (SD-TMZ) vs. dose-dense TMZ (DD-TMZ) in RPA and MCP risk groups. A significant difference between DD-TMZ and SD-TMZ was observed in the poorest surviving MCP risk group with a median PFS of 6 months vs. 3 months (p ¼ 0.048, log-rank test). This difference was not seen using the RPA classification alone. In summary, we have developed a combined molecular-clinical predictor that appears to improve outcome prediction when compared with clinical variables alone. This MCP may serve to better identify patients requiring intensive treatments beyond the standard of care.

Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort.

BACKGROUND Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers. METHODS To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort. RESULTS A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis. CONCLUSION Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.

Prognosis Relevance of Serum Cytokines in Pancreatic Cancer.

The overall survival of patients with pancreatic ductal adenocarcinoma is extremely low. Although gemcitabine is the standard used chemotherapy for this disease, clinical outcomes do not reflect significant improvements, not even when combined with adjuvant treatments. There is an urgent need for prognosis markers to be found. The aim of this study was to analyze the potential value of serum cytokines to find a profile that can predict the clinical outcome in patients with pancreatic cancer and to establish a practical prognosis index that significantly predicts patients' outcomes. We have conducted an extensive analysis of serum prognosis biomarkers using an antibody array comprising 507 human cytokines. Overall survival was estimated using the Kaplan-Meier method. Univariate and multivariate Cox's proportional hazard models were used to analyze prognosis factors. To determine the extent that survival could be predicted based on this index, we used the leave-one-out cross-validation model. The multivariate model showed a better performance and it could represent a novel panel of serum cytokines that correlates to poor prognosis in pancreatic cancer. B7-1/CD80, EG-VEGF/PK1, IL-29, NRG1-beta1/HRG1-beta1, and PD-ECGF expressions portend a poor prognosis for patients with pancreatic cancer and these cytokines could represent novel therapeutic targets for this disease.

Response to Infliximab in Crohn's Disease: Genetic Analysis Supporting Expression Profile.

Substantial proportion of Crohn's disease (CD) patients shows no response or a limited response to treatment with infliximab (IFX) and to identify biomarkers of response would be of great clinical and economic benefit. The expression profile of five genes (S100A8-S100A9, G0S2, TNFAIP6, and IL11) reportedly predicted response to IFX and we aimed at investigating their etiologic role through genetic association analysis. Patients with active CD (350) who received at least three induction doses of IFX were included and classified according to IFX response. A tagging strategy was used to select genetic polymorphisms that cover the variability present in the chromosomal regions encoding the identified genes with altered expression. Following genotyping, differences between responders and nonresponders to IFX were observed in haplotypes of the studied regions: S100A8-S100A9 (rs11205276* G/rs3014866* C/rs724781* C/rs3006488* A; P = 0.05); G0S2 (rs4844486* A/rs1473683* T; P = 0.15); TNFAIP6 (rs11677200* C/rs2342910* A/rs3755480* G/rs10432475* A; P = 0.10); and IL11 (rs1126760* C/rs1042506* G; P = 0.07). These differences were amplified in patients with colonic and ileocolonic location for all but the TNFAIP6 haplotype, which evidenced significant difference in ileal CD patients. Our results support the role of the reported expression signature as predictive of anti-TNF outcome in CD patients and suggest an etiological role of those top-five genes in the IFX response pathway.

Proadrenomedullin: An effective prognostic biomarker in septic patients

Background: Measurement of biomarkers is a potential approach to early prediction of mortality in septic patients. The purpose of this study was to asses the prognostic value of proadrenomedullin (pADM) in adult patients with sepsis with a single measurement in the first 24 hours after the onset of severe sepsis or septic shock. Conclusions: The protein pADM is an important prognostic biomarker of survival when measured on admission of septic patients to the ICU.

C-reactive protein, procalcitonin, lactate and score apache II in septic patients' prognosis.

Background: APACHE-II IS a score, based on several clinical and analytical measurements within 24 hours of admission in Intensive Care Unit (ICU). C-Reactive Protein (CRP), Lactate and recently Procalcitonin (PCT), also are biomarkers for the assessment of septic patients. The aim of this study was to find out if CRP, lactate and PCT during the first 24 hours from severe sepsis or septic shock onset, improved prediction of the APACHE II in terms of prognosis. Conclusions: CRP improves the prediction of patients with sepsis used in conjunction with the APACHE II score in severe sepsis and, lactate along with the CRP are the best precictors of survival in the cases of septic shock. The PCT did not show any predictive value.

The rationale of retinal endovascular fibrinolysis in the treatment of retinal vein occlusion : from experimental data to clinical application.

PURPOSE: : We describe a retinal endovascular fibrinolysis technique to directly reperfuse experimentally occluded retinal veins using a simple micropipette. METHODS: : Retinal vein occlusion was photochemically induced in 12 eyes of 12 minipigs: after intravenous injection of 10% fluorescein (1-mL bolus), the targeted retinal vein segment was exposed to thrombin (50 units) and to Argon laser (100-200 mW) through a pars plana approach. A beveled micropipette with a 30-μm-diameter sharp edge was used for micropuncture of the occluded vein and endovascular microinjection of tissue plasminogen activator (50 μg/mL) in 11 eyes. In one control eye, balanced salt solution was injected. The lesion site was examined histologically. RESULTS: : Retinal vein occlusion was achieved in all cases. Endovascular microinjection of tissue plasminogen activator or balanced salt solution led to reperfusion of the occluded retinal vein in all cases. Indicative of successful reperfusion were the following: continuous endovascular flow, unaffected collateral circulation, no optic disk ischemia, and no venous wall bleeding. However, balanced salt solution injection was accompanied by thrombus formation at the punctured site, whereas no thrombus was observed with tissue plasminogen activator injection. CONCLUSION: : Retinal endovascular fibrinolysis constitutes an efficient method of micropuncture and reperfusion of an experimentally occluded retinal vein. Thrombus formation at the punctured site can be prevented by injection of tissue plasminogen activator.

New insights into the role of the immune microenvironment in breast carcinoma.

Recently, immune edition has been recognized as a new hallmark of cancer. In this respect, some clinical trials in breast cancer have reported imppressive outcomes related to laboratory immune findings, especially in the neoadjuvant and metastatic setting. Infiltration by tumor infiltrating lymphocytes (TIL) and their subtypes, tumor-associated macrophages (TAM) and myeloid-derived suppressive cells (MDSC) seem bona fide prognostic and even predictive biomarkers, that will eventually be incorporated into diagnostic and therapeutic algorithms of breast cancer. In addition, the complex interaction of costimulatory and coinhibitory molecules on the immune synapse and the different signals that they may exert represent another exciting field to explore. In this review we try to summarize and elucidate these new concepts and knowledge from a translational perspective focusing on breast cancer, paying special attention to those aspects that might have more significance in clinical practice and could be useful to design successful therapeutic strategies in the future.

Genome-wide association study identifies two loci strongly affecting transferrin glycosylation.

Polysaccharide sidechains attached to proteins play important roles in cell-cell and receptor-ligand interactions. Variation in the carbohydrate component has been extensively studied for the iron transport protein transferrin, because serum levels of the transferrin isoforms asialotransferrin + disialotransferrin (carbohydrate-deficient transferrin, CDT) are used as biomarkers of excessive alcohol intake. We conducted a genome-wide association study to assess whether genetic factors affect CDT concentration in serum. CDT was measured in three population-based studies: one in Switzerland (CoLaus study, n = 5181) and two in Australia (n = 1509, n = 775). The first cohort was used as the discovery panel and the latter ones served as replication. Genome-wide single-nucleotide polymorphism (SNP) typing data were used to identify loci with significant associations with CDT as a percentage of total transferrin (CDT%). The top three SNPs in the discovery panel (rs2749097 near PGM1 on chromosome 1, and missense polymorphisms rs1049296, rs1799899 in TF on chromosome 3) were successfully replicated , yielding genome-wide significant combined association with CDT% (P = 1.9 × 10(-9), 4 × 10(-39), 5.5 × 10(-43), respectively) and explain 5.8% of the variation in CDT%. These allelic effects are postulated to be caused by variation in availability of glucose-1-phosphate as a precursor of the glycan (PGM1), and variation in transferrin (TF) structure.

Circulating insulin-like growth factor-I in pregnancy and maternal risk of breast cancer.

BACKGROUND: Elevated serum concentrations of insulin-like growth factor (IGF)-1 have been associated with increased risk of breast cancer. Previously, we reported a similar association in samples obtained during pregnancy. The current study was conducted to further characterize the association of IGF-1 during pregnancy with maternal breast cancer risk. METHODS: A case-control study was nested within the Finnish Maternity Cohort. The study was limited to primiparous women less than 40 years of age, who donated blood samples during early (median, 12 weeks) pregnancy and delivered a single child at term. Seven hundred and nineteen women with invasive breast cancer were eligible. Two controls (n = 1,434) were matched to each case on age and date at blood donation. Serum IGF-1 concentration was measured using an Immulite 2000 analyzer. Conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI).RESULTS: No significant associations were observed between serum IGF-1 concentrations and breast cancer risk in both the overall analysis (OR 1.08 (95% CI 0.80-1.47) and in analyses stratified by histological subtype, lag-time to cancer diagnosis, age at pregnancy or age at diagnosis.CONCLUSIONS: There was no association between IGF-1 and maternal breast cancer risk during early pregnancy in this large nested case-control study.Impact:Serum IGF-1 concentrations during early pregnancy may not be related to maternal risk of breast cancer.