Number Of Active Drugs Research Articles

Characterization of liver cancer-targeted doxorubicin coupling segmented copolymer nanomicelles and its inhibitory effect on hepatocellular carcinoma HepG2 and Huh7 cells

Objective To investigate the characterization of doxorubicin (DOX) coupling segmented copolymer nanomicelles with dual effects of passive and active targeting to liver cancer and its antineoplastic function in vitro. Methods DOX was covalently conjugated to a terminal hydroxyl group of poly lactic-co-glycolic acid-poly ethylene glycol (PLGA-PEG) diblock copolymer to form DOX-PLGA-PEG. The formation of amido bond was determined by using fourier transform infrared spectroscopy (FTIR) and magnetic resonance method. Amphiphatic diblock copolymer DOX-PLGA-PEG could self-assemble to form nanomicelles in an aqueous phase by dialysis method. The DOX-PLGA-PEG targeted micelles decorated with liver cancer HAb18 F (ab')2 specific antibody were prepared by using physical bonding method. The size and the scattering scope of nanomicelles was determined by using granulometer and dynamic light scattering (DLS). Micelle morphology was examined by using scanning electron microscopy (SEM). The drug loading rate and entrapment rate of DOX-PLGA-PEG micelles or targeted micelles were measured by using ultraviolet spectrophotometry method, and stimulated release in vitro experiment was done. After administration of 2 mg/ml DOX-PLGA-PEG or targeted micelles, cell morphology change of liver cancer HepG2 and Huh7 was observed by using the phase-contrast photomicrography. After administration of 1 mg/ml DOX-PLGA-PEG or targeted micelles, cell survival was analyzed by using plate clone formation assay. Results The spectrum peak was around 1 575 cm-1 under the observation of FTIR, which was accord with the location of the peak of amido bond. Activating with p-nitrophenyl chloroformate, DOX was covalently conjugated to PLGA-PEG to produce DOX-PLGA-PEG via a carbamate linkage between the primary amine group in DOX and the terminal hydroxyl group in PLGA-PEG. DLS measurements showed that the diameter of DOX-PLGA-PEG micelles and targeted micelles was (55.0±6.3) nm and (87.6±9.3) nm, respectively, and polydispersity index was 0.098 and 0.142, respectively. SEM micrographs revealed that these nanomicelles had a spherical morphology and relatively smooth surface. Drug loading rate of DOX-PLGA-PEG micelles and targeted micelles was (2.4±0.2)% and (2.2±1.9)%, and the entrapment rate was (91.7±5.3)% and (87.5±4.8)%, respectively. The drug release curve in vitro of DOX-PLGA-PEG micelles and targeted micelles exhibited a biphasic pattern characterized by a fast initial release, followed by a slower and continuous release. The amount of the drug release rate was about 30% within 5 d, and 25% within 6 h. After 2 mg/ml DOX-PLGA-PEG micelles and targeted micelles, the cell morphology of liver cancer HepG2 and Huh7 had the impaired change, and the part of the cells were dead, the clonality decreased. The effect of targeted micelles was more significant compared with DOX-PLGA-PEG micelles. After DOX-PLGA-PEG micelles and targeted micelles, the survival rates of HepG2 and Huh7 cells were decreased with time, and the effect of targeted micelles was more effective compared with DOX-PLGA-PEG micelles (all P < 0.05). The 50% effective inhibition of the targeted micelles and DOX-PLGA-PEG micelles was obtained in 2.4 d and 5.5 d, respectively for Huh7 cells. At these time points, DOX concentration was 1.15 μg/ml and 1.24 μg/ml, respectively. The 50% effective inhibition of targeted micelles and DOX-PLGA-PEG micelles was obtained in 3.3 d and 7.4 d, respectively for HepG2 cells. At these time points, DOX concentration was 1.20 μg/ml and 1.31 μg/ml. Conclusion DOX nanomicelles with dual effects of passive and active targeting can release a large number of active drugs in vitro, which plays an obvious inhibitory role in the cell proliferation of liver cancer HepG2 and Huh7 cells. Key words: Liver neoplasms; Doxorubicin; Drug delivery systems; Molecular targeted therapy; Targeted micelles

Abstract LB-069: Identification of personalized active agents in pediatric medulloblastoma through high-throughput drug screening in matching pairs of patient derived orthotopic xenograft neurosphere and monolayer cells

Abstract Objective: Glioblastoma and Medulloblastoma are deadliest brain tumors both in adults and children. While next-generation sequencing rapidly identifies whole exome/genome gene mutations, the efficacy of targeting mutated genes/pathways has not been systematically analyzed. Additionally, it remains unknown if neurospheres (enriched with cancer stem cells) and non-stem monolayer tumor cells will respond equally to the same target therapies. Methods: Matching pairs of neurosphere and monolayer cell cultures from 4 molecularly characterized PDOX mouse models established from distinct clinical stages of pediatric GBM and MB were treated with 7,913 drugs (mostly in clinical use or trials) at 4 doses (0-10 uM) for 3 and 7 days. Dose-response curves and active area under the curve were constructed to identify active drugs and correlate with model-specific gene mutations. Results: Relatively long-term treatment (7 day screening) was achieved for high-throughput drug screening and revealed time- and dose-dependent effects in most of the 4,629 compounds that were active in at least one culture at one time point. When gene mutations were druggable, not all inhibitors of the same family were active. In IC-4687GBM (a treatment-naïve GBM), high NF1 mutation (&amp;gt;76-99% allele) frequency was found in patient tumor, xenografts, and cultured cells, but only 3/17 MEK inhibitors were active in neurospheres and 2/17 in monolayer cells (GDC0980 and PI-103 were active in both) on day 7. In IC-R0315GBM (from an autopsied terminal GBM) that carried PI3KCA mutation (allele frequency 22-27%), 5/33 PI3K inhibitors were active in neurospheres and 8/33 in monolayer cells (only Tremetinib was active in both) after 7 days. In IC-3752GBM (recurrent GBM) and ICb-1127AA (radiation-induced anaplastic astrocytoma), no druggable mutations were detected. The number of active drugs on day 7 was 366 in IC-4768GBM, 406 in IC-3752GBM, 284 in IC-R0315GBM, and 305 in ICb-1277AA. When the 4 matching pairs of neurospheres and monolayers were compared, the agents active in both cultures ranged from 36% to 60%, active only in neurosphere from 10.3% to 25%, and active only in monolayer cells from 14.8% to 53%. The response of MB to the drugs is on the way for analysis. Conclusion: We showed that long-term treatment is feasible for high-throughput drug screening. Targeting druggable mutations can be achieved but only by a fraction of specific agents. Neurospheres and monolayer cells do not always respond equally toward the same drugs, and effective targeting of both subpopulations is needed to generate prolonged animal survival times. Citation Format: Lin Qi, Yuchen Du, Goeun Bae, Mari Mari, Frank Braun, Holly Lindsay, Huiyuan Zhang, Sibo Zhao, Sarah Injac, Patricia Baxter, Jack Su, Michael Mancini, Oliver Hampton, William Parsons, Mural Chintagumpala, Clifford Stephan, Peter Davies, Xiaonan Li. Identification of personalized active agents in pediatric medulloblastoma through high-throughput drug screening in matching pairs of patient derived orthotopic xenograft neurosphere and monolayer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-069.

Abstract 4214: Identification of personalized active agents in pediatric gliomas through high-throughput drug screening in matching pairs of patient derived orthotopic xenograft (PDOX) neurosphere and monolayer cells

Abstract Objective: Glioblastoma (GBM) is one of the deadliest brain tumors both in adults and children. While next-generation sequencing rapidly identifies whole exome/genome gene mutations, the efficacy of targeting mutated genes/pathways has not been systematically analyzed. Additionally, it remains unknown if neurospheres (enriched with cancer stem cells) and non-stem monolayer tumor cells will respond equally to the same target therapies. Methods: Matching pairs of neurosphere and monolayer cell cultures from 4 molecularly characterized PDOX mouse models established from distinct clinical stages of pediatric glioma (treatment-naïve, early recurrent, terminal, and radiation-induced) were treated with 7,913 drugs (mostly in clinical use or trials) at 4 doses (0-10 uM) for 3 and 7 days. Dose-response curves and active area under the curve (AAUC) were constructed to identify active drugs and correlate with model-specific gene mutations. Results: Relatively long-term treatment (7 day screening) was achieved for high-throughput drug screening and revealed time- and dose-dependent effects in most of the 4,629 compounds that were active in at least one culture at one time point. When gene mutations were druggable, not all inhibitors of the same family were active. In IC-4687GBM (a treatment-naïve GBM), high NF1 mutation (&amp;gt;76-99% allele) frequency was found in patient tumor, xenografts, and cultured cells, but only 3/17 MEK inhibitors were active in neurospheres and 2/17 in monolayer cells (GDC0980 and PI-103 were active in both) on day 7. In IC-R0315GBM (from an autopsied terminal GBM) that carried PI3KCA mutation (allele frequency 22-27%), 5/33 PI3K inhibitors were active in neurospheres and 8/33 in monolayer cells (only Tremetinib was active in both) after 7 days. In IC-3752GBM (recurrent GBM) and ICb-1127AA (radiation-induced anaplastic astrocytoma), no druggable mutations were detected. The number of active drugs on day 7 was 366 in IC-4768GBM, 406 in IC-3752GBM, 284 in IC-R0315GBM, and 305 in ICb-1277AA. When the 4 matching pairs of neurospheres and monolayers were compared, the agents active in both cultures ranged from 36% to 60%, active only in neurosphere from 10.3% to 25%, and active only in monolayer cells from 14.8% to 53%. Subsequent in vivo validation using MLN8327 in IC-4687GBM and IC-R0315GBM showed that effective targeting of both neurosphere and monolayer was required for significantly-improved animal survival times. Conclusion: We showed that long-term treatment is feasible for high-throughput drug screening. Targeting druggable mutations can be achieved but only by a fraction of specific agents. Neurospheres and monolayer cells do not always respond equally toward the same drugs, and effective targeting of both subpopulations is needed to generate prolonged animal survival times. Citation Format: Lin Qi, Yuchen Du, Mari Kogiso, Goeun Bae, Frank Braun, Holly Lindsay, Huiyuan Zhang, Sibo Zhao, Sarah Injac, Patricia Baxter, Jack Su, Michael Mancini, Oliver Hampton, William Parsons, Murali Chintagumpala, Clifford Stephan, Peter Davies, Xiao-Nan Li, Xiao-Nan Li. Identification of personalized active agents in pediatric gliomas through high-throughput drug screening in matching pairs of patient derived orthotopic xenograft (PDOX) neurosphere and monolayer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4214. doi:10.1158/1538-7445.AM2017-4214

Tuberculosis in Liver Transplant Recipients: A Report of Eight Cases During a Five Year Period.

Tuberculosis incidence in Portugal ranged from 20 to 22 cases per 100 000 inhabitants between 2010 and 2014.Tuberculosis incidence in liver transplant recipients is not precisely known, but it is estimated to be higher than among the generalpopulation. Tuberculosis in liver transplant recipients is particularly challenging because of the atypical clinical presentation and sideeffects of the antibacillary drugs and their potential interactions with immunosuppressive therapies. We retrospectively reviewed the clinical records of liver transplant recipients with post-transplant tuberculosisoccurring from January 2010 to December 2014 at a liver transplantation unit in Lisbon, Portugal. Demographic data, baseline andclinical features, as well as treatment regimen, toxicities and outcomes, were analyzed. Among 1005 recipients, active tuberculosis was diagnosed in eight patients between January 2010 and December 2014(frequency = 0.8%). Late onset tuberculosis was more frequent than early tuberculosis. Mycobacterium tuberculosis complex wasisolated from cultures in almost every case (7; 87.5%). Extra-pulmonary involvement and disseminated tuberculosis were frequent. Twopatients developed rejection without allograft loss. Crude mortality was 37.5%, with 2 deaths being related to tuberculosis. Despite the uncertainty regarding treatment duration in liver transplant recipients, disease severity, as well as number ofactive drugs against TB infection, should be taken into account. There was a need for a rifampin-free regimen and immunosuppressionadjustment in patients who experienced acute graf rejection. Although the number of cases of tuberculosis is low, its post-transplant frequency is significant and the observed mortalityrate is not to be neglected. The cases of hepatotoxicity and graft rejection seen in this case series demonstrate the challengesassociated with tuberculosis diagnosis in liver transplant recipients and management of the interactions between immunosuppressorsand rifampin. This study strengthens the recommendation of latent tuberculosis infection screening and treatment in liver transplantcandidates or recipients.

Detection of potential drug-drug interactions in prescriptions dispensed in hospital pharmacy

This prospective observational study examined the severity, type and frequency of potential drug-drug interactions (PDDIs) in prescriptions dispensed in the hospital pharmacies of M.S. Ramaiah Memorial Hospital and M.S. Ramaiah Hospital, Bangalore, Karnataka. A total of 500 prescriptions were collected over a period of 5 months. PDDIs were identified and analysed using Micromedex database. The frequency of PDDIs was 71.8%, with at least one interacting combination with major (14.20%), moderate (72.70%) and minor (13.09%) interactions. Out of the total PDDIs identified, 60% were pharmacodynamic interactions, 38% were pharmacokinetic interactions and 2% had interaction of unknown mechanism. The largest number of active drugs prescribed with major PDDIs were related to the cardiovascular system (32.63%), central nervous system (22.28%), gastrointestinal tract and drug metabolism (13.37%).The results of the present study showed a high frequency of PDDIs in prescriptions received at hospital pharmacies.

Are There Strategies to Integrate the Continuum of Care for Metastatic Colorectal Cancer When Resources Are Limited?

Colorectal cancer is one of the most frequent neoplasias worldwide, affecting both men and women. Patients with inoperable or metastatic colorectal cancer (CRC) are candidates for palliative treatment with chemotherapy, which can significantly prolong survival. The number of active drugs has progressively increased over the past years, as well as available techniques directed towards resection or ablation of metastasis. Consequently, patients are able to live longer, with better quality of life. As new technologies become available, the treatments are becoming increasingly complicated, and the cost has increased in a proportion that most health systems can hardly afford. While the price of new therapies poses a challenge in more economically developed countries, it has a much greater impact in emerging and underdeveloped economies. In this article, we will discuss some strategies that could help dealing with this major problem, while reasonably maintaining the benefits of newer drugs and technologies to patient treatment.

Similar Efficacy of Raltegravir When Used With or Without a Protease Inhibitor in Treatment-Experienced Patients

Background: Patients with multiclass-resistant HIV-1 have limited treatment options. Raltegravir, an inhibitor of integrase, has shown excellent efficacy when used with protease inhibitors (Pis) in patients with drug-resistant HIV-1. Limited data are available however about the outcomes when using raltegravir without Pis in this population. Methods: Medical records of subjects who received raltegravir as part of the Merck EAP study 0518 were reviewed and abstracted at participating sites. Eligibility criteria included HIV positivity, age ≥16 years, limited or no treatment options due to resistance or intolerance to multiple antiretroviral regimens, detectable viremia on current treatment regimen, and documented resistance to at least one drug in each antiretroviral class (PI, NNRTI, and nucleoside analogue). Demographic, clinical, and laboratory data were collected locally using a standardized collection form. Genotypic susceptibility scores (GSS) were determined from the most recent genotypic resistance test available prior to the initiation of raltegravir. The main objective was to compare virologic results in patients who received raltegravir with a PI versus those who received raltegravir without a PI. Results: Four hundred forty-two subjects were evaluated from the respective sites in the EAP trial, of whom 340 were evaluable. The baseline mean HIV RNA was 4.6 log copies/ mL, and the mean CD4 cell count was 159 cells/μL. The median number of total and new antiretroviral agents in the background regimen was 4 and 2, respectively. Among the 254 patients who received a PI, the most common PI used was darunavir (89%). Etra-virine was commonly used in both groups: 39% of the PI group and 67% of the non-PI group. At week 12, 67% of PI patients and 64% of non-PI patients achieved HIV RNA <75 copies/mL and 85% and 86%, respectively, achieved HIV RNA <400 copies/mL GSS, which was similar in both groups at baseline, predicted achieving an HIV RNA of <400 and 75 copies/mL at week 12 (P < .05). Conclusions: In treatment-experienced patients, the combination of raltegravir with a regimen not containing a PI (used with etravirine in two-thirds of patients) had similar virologic activity when compared to more standard regimens using raltegravir with a PI. The main determinant of efficacy was the number of active drugs as measured by GSS. These data expand the potential utility of raltegravir in patients with multidrug-resistant HIV.

Costs to Achieve Undetectable HIV RNA with Darunavir-Containing Highly Active Antiretroviral Therapy in Highly Pretreated Patients

Very few studies have evaluated the cost of highly active antiretroviral therapy (HAART) per successful treatment in HIV-infected patients. To evaluate the cost of achieving undetectable plasma HIV-RNA levels in highly treatment-experienced, HIV-1-infected adults receiving darunavir/ritonavir (DRV/r 600 mg/100 mg twice a day) or control protease inhibitor (PI)-based HAART. The mean annual per-patient cost of DRV/r and control PI-based HAART was determined from the proportional use of antiretroviral agents in the DRV/r and control PI arms of the pooled POWER 1 and 2 trials, applying drug acquisition costs for 13 healthcare settings. The mean annual cost per patient of achieving undetectable plasma HIV-RNA levels (<50 copies/mL) was calculated by dividing the cost of each treatment by the proportion of patients with undetectable plasma HIV-RNA levels after 48 weeks in the DRV/r (45%) and control PI (10%) arms of the POWER trials. Whereas absolute costs of treatment were 1-19% higher with DRV/r versus control PI-based HAART depending on the healthcare setting, the mean annual per-patient cost of achieving undetectable plasma HIV-RNA levels was 73-78% lower. These cost savings were maintained in the sensitivity analyses, adjusting for control PI and enfuvirtide use, and the number of active drugs in the background regimen. The incremental annual cost per additional patient achieving undetectable plasma HIV-RNA levels with DRV/r versus control PI-based HAART in POWER 1 and 2 (£4148) compared favourably with that determined for enfuvirtide (£137, 740; TORO trials) and tipranavir/ritonavir (£32,176; RESIST) versus control therapy. DRV/r-based HAART provided consistent reductions in the cost of achieving undetectable plasma HIV-RNA levels compared with control PI-based therapy in highly treatment-experienced patients across various healthcare settings. The incremental cost per additional patient achieving undetectable plasma HIV-RNA levels with DRV/r versus control PI-based HAART was also lower than that calculated for other treatment options in this population. These results suggest that DRV/r is an economically viable option for highly treatment-experienced patients.

Historical resistance profile helps to predict salvage failure

This study compared the predictive value for treatment failure of extended resistance detected in the current genotype resistance test (GRT) versus those from GRT history in patients with multiple combination antiretroviral therapy (cART) failures. Patients who underwent three GRT between 1999 and 2007 were included. Extended resistance at genotypic sensitivity score (GSS) using the Rega 7.1 interpretation system compared with a non-standard definition (defined as class-wide resistance [CWR] on the basis of International AIDS Society-USA mutations) was assessed both for current and historical GRTs (a combination of mutations was detected in all three tests). The predictive role of extended resistance for treatment failure was evaluated with an adjusted Cox proportional hazard model. Overall, 177 patients were included. The historical GRT increased the number of patients with extended resistance to all three major drug classes by 25% in comparison with the current GRT. Using the GSS method, the absence of detection of any active drug in any drug class was predictive of failure with both the current and historical GRTs. Similarly, the number of active drugs in the cART regimen after the third resistance test, used as continuous variable, was also predictive of failure. Using both GSS approaches, current genotype had a higher effect than historical genotype on risk of treatment failure. Using the non-standard definition (CWR), historical resistance predicted failure better than current resistance. Our results provide an epidemiological demonstration that analysis of a combined latest and historical GRT, which also considers archived mutations, might better identify of the more virologically impaired patients in order to assess the best salvage treatment.

Darunavir Inhibitory Quotient Predicts the 48-Week Virological Response to Darunavir-Based Salvage Therapy in Human Immunodeficiency Virus-Infected Protease Inhibitor-Experienced Patients

The aim of this study was to evaluate the relationship between the virological response to darunavir-based salvage antiretroviral therapy and the darunavir genotypic and virtual inhibitory quotients (gIQ and vIQ, respectively). Thirty-seven HIV-infected patients failing protease inhibitor-based antiretroviral regimens who started salvage therapy containing darunavir-ritonavir were prospectively studied. The primary outcome of the study was a viral load (VL) of <50 copies/ml at week 48. The trough concentrations of darunavir in plasma, the number of darunavir resistance mutations, the change in the 50% inhibitory concentration (IC(50)) of darunavir in the virtual phenotype, and the darunavir gIQ and vIQ were correlated with the virological outcome in regression analyses adjusted by the number of active drugs in the background regimen. The VL was <50 copies/ml in 56.8% of patients at week 48. Changes in the VL were not significantly associated with the darunavir concentration (P = 0.304), the number of darunavir resistance mutations (P = 0.695), or the change in the IC(50) (P = 0.750). However, patients with darunavir vIQs of >or=1.5 had a 12-fold greater chance of achieving a >or=1 log(10) reduction in the VL (odds ratio [OR], 12.7; 95% confidence interval [95% CI], 1.9 to 81.6; P = 0.007), and a 5-fold greater chance of achieving a VL of <50 copies/ml (OR, 5.4; 95% CI, 1.2 to 24.5; P = 0.028), at week 48 than patients with darunavir vIQs of <1.5. The positive and negative predictive values of this darunavir vIQ cutoff for achieving a VL of <50 copies/ml at week 48 were 70% and 69%, respectively. The darunavir vIQ predicts virological response to darunavir-based salvage therapy better than the darunavir trough concentration or resistance mutations alone. We suggest targeting a darunavir vIQ of 1.5 for achieving long-term viral suppression.

Resampling‐Based Multiple Testing Methods with Covariate Adjustment: Application to Investigation of Antiretroviral Drug Susceptibility

Identifying genetic mutations that cause clinical resistance to antiretroviral drugs requires adjustment for potential confounders, such as the number of active drugs in a HIV-infected patient's regimen other than the one of interest. Motivated by this problem, we investigated resampling-based methods to test equal mean response across multiple groups defined by HIV genotype, after adjustment for covariates. We consider construction of test statistics and their null distributions under two types of model: parametric and semiparametric. The covariate function is explicitly specified in the parametric but not in the semiparametric approach. The parametric approach is more precise when models are correctly specified, but suffer from bias when they are not; the semiparametric approach is more robust to model misspecification, but may be less efficient. To help preserve type I error while also improving power in both approaches, we propose resampling approaches based on matching of observations with similar covariate values. Matching reduces the impact of model misspecification as well as imprecision in estimation. These methods are evaluated via simulation studies and applied to a data set that combines results from a variety of clinical studies of salvage regimens. Our focus is on relating HIV genotype to viral susceptibility to abacavir after adjustment for the number of active antiretroviral drugs (excluding abacavir) in the patient's regimen.

Genotypic and phenotypic resistance testing of HIV-1 in routine clinical care

Data on genotypic and phenotypic resistance testing of HIV-1 in the routine clinical setting are lacking. In a retrospective single-center study, all patients (n = 102) for whom genotypic resistance typing (GRT) and phenotypic resistance typing (PRT) were performed during the calendar year 2002 were examined. GRT and PRT results were concordant for 79% of the drugs, being highest for nevirapine (92%) and lowest for didanosine (57%). Concordance of results for protease inhibitors was lowest for lopinavir (78%) and highest for indinavir (88%). Discordant results for lamivudine were observed in 16% of patients; 90% of these results corresponded to high-level resistance by PRT and susceptibility by GRT. Overall, HIV loads were lower and CD4+ cell counts higher after therapy following resistance testing, but a significant association with the number of active drugs as predicted by GRT or PRT could not be identified. In a subgroup of 43 patients with virological failure under antiretroviral therapy and sufficient follow-up data, HIV loads were significantly lower after 3 and 6 months. More patients with HIV loads <400/ml had 2 or more active drugs according to PRT (21/29 [75%]) than according to GRT ([15/29 [52%]; p = 0.109. This was also found for HIV loads <50/ml (PRT 16/22 [72%], GRT 10/22 [42%]; p = 0.103), although the differences were not statistically significant. There was no discernable difference between GRT and PRT in the clinic-based population, but the numbers of resistance tests performed are not sufficient to draw definitive conclusions.

Selection of Antiretroviral Therapy Guided by Genotypic or Phenotypic Resistance Testing

The phenotype/genotype (PhenGen) open-label, randomized, multicenter study evaluated the genotype/virtual phenotype (vPt) and real phenotype (rPt) for choosing a new highly active antiretroviral therapy regimen at failure. Patients with a plasma viral load (pVL) between 2000 and 200,000 copies/mL and a CD4 cell count >200/microL, failing > or =2 regimens (<6 drugs), were randomized for vPt or rPt. Three hundred three patients were enrolled: 111 and 108 patients received a new treatment in the vPt and rPt arms, respectively. The 2 groups were comparable for baseline patient characteristics and treatment history. The new therapy was in agreement with expert advice in 58.5% of cases. After 6 months, no statistical differences were found in the mean absolute change from baseline CD4 cells (+55 and +46 cells/muL; P = 0.7), mean pVL log decrease (-1.35 and -1.37; P = 0.8), or proportion of patients with a pVL <400 copies/mL (54.8% in vPt arm and 52.6% in rPt arm; P = 0.9). At multivariate analysis, variables independently associated with failure of the new regimen were: pVL at baseline (odds ratio [OR] = 1.81; P < 0.021), number of nucleoside reverse transcriptase inhibitor-associated mutations (OR = 1.21; P = 0.001), number of protease mutations (OR = 1.15; P < 0.001), and recycling of indinavir (OR = 4.63; P = 0.019). Patients' adherence to the prescribed regimen (OR = 0.23; P < 0.001), number of active drugs in the new regimen (OR = 0.55; P = 0.001), and adherence to expert advice (OR = 0.37; P < 0.001) predicted virologic response. The vPt is as predictive of treatment outcome as the rPT. Use of expert advice significantly improved the response to therapy.

Baseline Resistance and Virological Outcome in Patients with Virological Failure who Start a Regimen Containing Abacavir: Eurosida Study

To investigate the ability of several HIV-1 drug-resistance interpretation systems, as well as the number of pre-specified combinations of abacavir-related mutations, to predict virological response to abacavir-containing regimens in antiretroviral therapy-experienced, abacavir-naive patients starting an abacavir-containing regimen in the EuroSIDA cohort. A total of 100 HIV-infected patients with viral load (VL) >500 copies/ml who had a plasma sample available at the time of starting abacavir (baseline) were included. Resistance to abacavir was interpreted by using eight different commonly used systems that consisted of rules-based algorithms or tables of mutations. Correlation between baseline abacavir-resistance mutations and month 6 virological response was performed on this population using a multivariable linear regression model accounting for censored data. The baseline VL was 4.36 log10 RNA copies/ml [interquartile range (IQR): 3.65-4.99 log10 RNA copies/ml] and the median CD4 cell count was 210 cells/microl (IQR: 67-305 cells/microl). Our patients were pre-exposed to a median of seven antiretrovirals (2-12) before starting abacavir therapy. The median (range) number of abacavir mutations (according to the International AIDS Society-USA) detected at baseline was 3.5 (0-8). Overall, the Kaplan-Meier estimate of the median month 6 VL decline was 0.86 log10 RNA copies/ml [95% confidence intervals (95% CI): 0.45-1.24]. The VL in those patients (n=31) who intensified treatment by adding only abacavir decreased by a median 0.20 log10 RNA copies/ml (95% CI: -0.18; +0.94). The proportion of patients who harboured viruses fully resistant to abacavir among the eight genotypic resistance interpretation algorithms ranged from 12% [Agence Nationale de Recherches sur le SIDA (ANRS)] to 79% [Stanford HIV RT and PR Sequence Database (HIVdb)]. Some interpretation systems showed statistically significant associations between the predicted resistance status and the virological response while others showed no consistent association. The number of active drugs in the regimen was associated with greater virological suppression (additional month 6 VL reduction per additional sensitive drug=0.51, 95% CI: 0.15-0.88, P=0.006); baseline VL was also weakly associated (additional month 6 VL reduction per log10 higher=0.30, 95% CI: -0.02; +0.62, P=0.06). In contrast, the number of drugs previously received was associated with diminished viral reduction (additional month 6 VL reduction per additional drug=-0.14, 95% CI: -0.28; 0.00, P=0.05). Our results revealed a high degree of variability among several genotypic resistance interpretation algorithms currently in use for abacavir. Therefore, the interpretation of genotypic resistance for predicting response to regimens containing abacavir remains a major challenge.

Assessing resistance costs of antiretroviral therapies via measures of future drug options.

The emergence of drug-resistant human immunodeficiency virus (HIV) type 1 in the setting of antiretroviral therapy failure limits the number of drugs available for use in subsequent therapy regimens. To quantify the relative HIV-1-resistance costs associated with various antiretroviral therapy strategies, we developed 2 related measures of future drug options (FDOs) by use of rule-based genotype-interpretation systems. The FDO1 metric assesses the number of drug classes that remain useful; the FDO2 metric assesses the number of drug classes that remain useful and the number of active drugs within each class. Application of these methods is illustrated with data from a randomized study of 3 therapy regimens in nucleoside analog-experienced patients. Each therapy regimen resulted in a unique pattern of drug-resistance (and cross-resistance) mutations. The regimen with the highest virologic failure rate preserved greater future drug options. Quantification of future drug options as an outcome of antiretroviral therapy trials may complement traditional clinical, virologic, and immunologic end points, thereby providing novel insights.

Progress in the systemic treatment of cancer.Concepts, trials, drugs, and biologics

The effective treatment of systemic cancer began in the 1950s on two fronts, i.e., childhood leukemia and choriocarcinoma. These two diseases were successfully treated as a direct result of the use of antifolate methotrexate. The demonstration of complete durable remissions in these diseases quickly led to development of other anticancer drugs, tested using the prospective clinical trials. In the 1960s as the number of active drugs increased, combination chemotherapy was introduced. Other systemic cancers, such as Hodgkin's, large cell lymphoma, and testicular cancer, became curable in the 1970s. For the common low-growth fraction solid tumors, the curability of systemic disease remained elusive until the introduction of adjuvant therapy to treat micrometastases. The past decade of the 1980s has seen improvement in the outcomes for breast cancer, osteosarcoma, and possible colon cancer utilizing adjunctive chemotherapy. The 1980s also saw the introduction of biologic therapies that have further improved the outcomes of several leukemias and produced consistent responses in patients with renal cell and melanoma. The 1990s will undoubtedly see more improvements as the effects of current drugs will be enhanced not only by improved integration of systemic and local therapies but also by utilizing cytokines and biologic response modifiers in concert with cytotoxics. Moreover, as we understand more about the process of cancer induction, promotion, and progression, more specific anti-cancer approaches will be developed to control cancer even before clinical cancer is diagnosed. Underlying and facilitating the improvement in cancer therapy have been not only the experimental results of many laboratory scientists but also the outcomes from many controlled clinical trials, the laboratory of clinical scientists.