Drug resistance mutations in HIV-2 patients failing raltegravir and influence on dolutegravir response

Producción CientíficaBackground: A broader extent of amino acid substitutions in the integrase of HIV-2 compared with HIV-1 might enable greater cross-resistance between raltegravir and dolutegravir in HIV-2 infection. Few studies have examined the virological response to dolutegravir in HIV-2 patients that failed raltegravir. Methods: All patients recorded in the HIV-2 Spanish cohort were examined. The integrase coding region was sequenced in viraemic patients. Changes associated with resistance to raltegravir and dolutegravir in HIV-1 were recorded. Results: From 319 HIV-2-infected patients recorded in the HIV-2 Spanish cohort, 53 integrase sequences from 30 individuals were obtained (20 raltegravir naive and 10 raltegravir experienced). Only one secondary mutation (E138A) was found in one of the 20 raltegravir-naive HIV-2 patients. For raltegravir-experienced individuals, the resistance mutation profile in 9 of 10 viraemic patients was as follows: N155H + A153G/S (four); Y143G + A153S (two); Q148R + G140A/S (two); and Y143C + Q91R (one). Of note, all patients with Y143G and N155H developed a rare non-polymorphic mutation at codon 153. Rescue therapy with dolutegravir was given to 5 of these 10 patients. After >6 months on dolutegravir therapy, three patients with baseline N155H experienced viral rebound. In two of them N155H was replaced by Q148K/R and in another by G118R. Conclusions: A wide repertoire of resistance mutations in the integrase gene occur in HIV-2-infected patients failing on raltegravir. Although dolutegravir may allow successful rescue in most HIV-2 raltegravir failures, we report and characterize three cases of dolutegravir resistance in HIV-2 patients, emerging variants Q148K and Q148R and a novel change G118R.Fondo de Investigación Sanitaria-Fondos FEDER (FIS, PI13/01574; ICI14/0274, CES12/003, FI14/00264, CD14/00243

Emergence of Anti-Cancer Drug Resistance: Exploring the Importance of the Microenvironmental Niche via a Spatial Model

Practically, all chemotherapeutic agents lead to drug resistance. Clinically, it is a challenge to determine whether resistance arises prior to, or as a result of, cancer therapy. Further, a number of different intracellular and microenvironmental factors have been correlated with the emergence of drug resistance. With the goal of better understanding drug resistance and its connection with the tumor microenvironment, we have developed a hybrid discrete-continuous mathematical model. In this model, cancer cells described through a particle-spring approach respond to dynamically changing oxygen and DNA damaging drug concentrations described through partial differential equations. We thoroughly explored the behavior of our self-calibrated model under the following common conditions: a fixed layout of the vasculature, an identical initial configuration of cancer cells, the same mechanism of drug action, and one mechanism of cellular response to the drug. We considered one set of simulations in which drug resistance existed prior to the start of treatment, and another set in which drug resistance is acquired in response to treatment. This allows us to compare how both kinds of resistance influence the spatial and temporal dynamics of the developing tumor, and its clonal diversity. We show that both pre-existing and acquired resistance can give rise to three biologically distinct parameter regimes: successful tumor eradication, reduced effectiveness of drug during the course of treatment (resistance), and complete treatment failure

_M. tuberculosis_ interactome analysis unravels potential pathways to drug resistance

Drug resistance is a major problem for combating tuberculosis. Lack of understanding of how resistance emerges in bacteria upon drug treatment limits our ability to counter resistance. By analysis of the _Mycobacterium tuberculosis_ interactome network, along with drug-induced expression data from literature, we show possible pathways for the emergence of drug resistance. To a curated set of resistance related proteins, we have identified sets of high propensity paths from different drug targets. Many top paths were upregulated upon exposure to anti-tubercular drugs. Different targets appear to have different propensities for the four resistance mechanisms. Knowledge of important proteins in such pathways enables identification of appropriate _'co-targets'_, which when simultaneously inhibited with the intended target, is likely to help in combating drug resistance. RecA, Rv0823c, Rv0892 and DnaE1 were the best examples of co-targets for combating tuberculosis. This approach is also inherently generic, likely to significantly impact drug discovery

Genomic introgression mapping of field-derived multiple-anthelmintic resistance in Teladorsagia circumcincta

Preventive chemotherapy has long been practiced against nematode parasites of livestock, leading to widespread drug resistance, and is increasingly being adopted for eradication of human parasitic nematodes even though it is similarly likely to lead to drug resistance. Given that the genetic architecture of resistance is poorly understood for any nematode, we have analyzed multidrug resistant Teladorsagia circumcincta, a major parasite of sheep, as a model for analysis of resistance selection. We introgressed a field-derived multiresistant genotype into a partially inbred susceptible genetic background (through repeated backcrossing and drug selection) and performed genome-wide scans in the backcross progeny and drug-selected F2 populations to identify the major genes responsible for the multidrug resistance. We identified variation linking candidate resistance genes to each drug class. Putative mechanisms included target site polymorphism, changes in likely regulatory regions and copy number variation in efflux transporters. This work elucidates the genetic architecture of multiple anthelmintic resistance in a parasitic nematode for the first time and establishes a framework for future studies of anthelmintic resistance in nematode parasites of humans

Molecular mechanisms of drug resistance in natural Leishmania populations vary with genetic background

The evolution of drug-resistance in pathogens is a major global health threat. Elucidating the molecular basis of pathogen drug-resistance has been the focus of many studies but rarely is it known whether a drug-resistance mechanism identified is universal for the studied pathogen; it has seldom been clarified whether drug-resistance mechanisms vary with the pathogen's genotype. Nevertheless this is of critical importance in gaining an understanding of the complexity of this global threat and in underpinning epidemiological surveillance of pathogen drug resistance in the field. This study aimed to assess the molecular and phenotypic heterogeneity that emerges in natural parasite populations under drug treatment pressure. We studied lines of the protozoan parasite Leishmania (L.) donovani with differential susceptibility to antimonial drugs; the lines being derived from clinical isolates belonging to two distinct genetic populations that circulate in the leishmaniasis endemic region of Nepal. Parasite pathways known to be affected by antimonial drugs were characterised on five experimental levels in the lines of the two populations. Characterisation of DNA sequence, gene expression, protein expression and thiol levels revealed a number of molecular features that mark antimonial-resistant parasites in only one of the two populations studied. A final series of in vitro stress phenotyping experiments confirmed this heterogeneity amongst drug-resistant parasites from the two populations. These data provide evidence that the molecular changes associated with antimonial-resistance in natural Leishmania populations depend on the genetic background of the Leishmania population, which has resulted in a divergent set of resistance markers in the Leishmania populations. This heterogeneity of parasite adaptations provides severe challenges for the control of drug resistance in the field and the design of molecular surveillance tools for widespread applicability

Customizing the therapeutic response of signaling networks to promote antitumor responses by drug combinations

Drug resistance, de novo and acquired, pervades cellular signaling networks (SNs) from one signaling motif to another as a result of cancer progression and/or drug intervention. This resistance is one of the key determinants of efficacy in targeted anti-cancer drug therapy. Although poorly understood, drug resistance is already being addressed in combination therapy by selecting drug targets where SN sensitivity increases due to combination components or as a result of de novo or acquired mutations. Additionally, successive drug combinations have shown low resistance potential. To promote a rational, systematic development of combination therapies, it is necessary to establish the underlying mechanisms that drive the advantages of combination therapies, and design methods to determine drug targets for combination regimens. Based on a joint systems analysis of cellular SN response and its sensitivity to drug action and oncogenic mutations, we describe an in silico method to analyze the targets of drug combinations. Our method explores mechanisms of sensitizing the SN through a combination of two drugs targeting vertical signaling pathways. We propose a paradigm of SN response customization by one drug to both maximize the effect of another drug in combination and promote a robust therapeutic response against oncogenic mutations. The method was applied to customize the response of the ErbB/PI3K/PTEN/AKT pathway by combination of drugs targeting HER2 receptors and proteins in the down-stream pathway. The results of a computational experiment showed that the modification of the SN response from hyperbolic to smooth sigmoid response by manipulation of two drugs in combination leads to greater robustness in therapeutic response against oncogenic mutations determining cancer heterogeneity. The application of this method in drug combination co-development suggests a combined evaluation of inhibition effects together with the capability of drug combinations to suppress resistance mechanisms before they become clinically manifest

Genetic and genomic approaches for the discovery of parasite genes involved in antimalarial drug resistance

The biggest threat to the war on malaria is the continued evolution of drug resistance by the parasite. Resistance to almost all currently available antimalarials now exists in Plasmodium falciparum which causes the most suffering among all human malaria parasites. Monitoring of antimalarial efficacy and the development and subsequent spread of resistance has become an important part in the treatment and control of malaria. With recent reports of reduced efficacy of artemisinin, the current recommended treatment for uncomplicated malaria, there is urgent need for better methods to recognize and monitor drug resistance for effective treatment. Molecular markers have become a welcome addition to complement the more laborious and costly in vitro and in vivo methods that have traditionally been used to monitor drug resistance. However, there are currently no molecular markers for resistance to some antimalarials. This review highlights the role of the various genetic and genomic approaches that have been used in identifying the molecular markers that underlie drug resistance in P. falciparum. These approaches include; candidate genes, genetic linkage and genome-wide association studies. We discuss the requirements and limitations of each approach and use various examples to illustrate their contributions in identifying genomic regions of the parasite associated with antimalarial drug responses

Aurora kinase A drives the evolution of resistance to third-generation EGFR inhibitors in lung cancer.

Although targeted therapies often elicit profound initial patient responses, these effects are transient due to residual disease leading to acquired resistance. How tumors transition between drug responsiveness, tolerance and resistance, especially in the absence of preexisting subclones, remains unclear. In epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma cells, we demonstrate that residual disease and acquired resistance in response to EGFR inhibitors requires Aurora kinase A (AURKA) activity. Nongenetic resistance through the activation of AURKA by its coactivator TPX2 emerges in response to chronic EGFR inhibition where it mitigates drug-induced apoptosis. Aurora kinase inhibitors suppress this adaptive survival program, increasing the magnitude and duration of EGFR inhibitor response in preclinical models. Treatment-induced activation of AURKA is associated with resistance to EGFR inhibitors in vitro, in vivo and in most individuals with EGFR-mutant lung adenocarcinoma. These findings delineate a molecular path whereby drug resistance emerges from drug-tolerant cells and unveils a synthetic lethal strategy for enhancing responses to EGFR inhibitors by suppressing AURKA-driven residual disease and acquired resistance

Treatment of tuberculosis in a region with high drug resistance: Outcomes, drug resistance amplification and re-infection

Introduction: Emerging antituberculosis drug resistance is a serious threat for tuberculosis (TB) control, especially in Eastern European countries. Methods: We combined drug susceptibility results and molecular strain typing data with treatment outcome reports to assess the influence of drug resistance on TB treatment outcomes in a prospective cohort of patients from Abkhazia (Georgia). Patients received individualized treatment regimens based on drug susceptibility testing (DST) results. Definitions for antituberculosis drug resistance and treatment outcomes were in line with current WHO recommendations. First and second line DST, and molecular typing were performed in a supranational laboratory for Mycobacterium tuberculosis (MTB) strains from consecutive sputum smear-positive TB patients at baseline and during treatment. Results: At baseline, MTB strains were fully drug-susceptible in 189/326 (58.0%) of patients. Resistance to at least H or R (PDR-TB) and multidrug-resistance (MDR-TB) were found in 69/326 (21.2%) and 68/326 (20.9%) of strains, respectively. Three MDR-TB strains were also extensively resistant (XDR-TB). During treatment, 3/189 (1.6%) fully susceptible patients at baseline were re-infected with a MDR-TB strain and 2/58 (3.4%) PDR-TB patients became MDR-TB due to resistance amplification. 5/ 47 (10.6%) MDR- patients became XDR-TB during treatment. Treatment success was observed in 161/189 (85.2%), 54/69 (78.3%) and 22/68 (32.3%) of patients with fully drug susceptible, PDR- and MDR-TB, respectively. Development of ofloxacin resistance was significantly associated with a negative treatment outcome. Conclusion: In Abkhazia, a region with high prevalence of drug resistant TB, the use of individualized MDR-TB treatment regimens resulted in poor treatment outcomes and XDR-TB amplification. Nosocomial transmission of MDR-TB emphasizes the importance of infection control in hospitals

Metabolomics to unveil and understand phenotypic diversity between pathogen populations

Visceral leishmaniasis is caused by a parasite called Leishmania donovani, which every year infects about half a million people and claims several thousand lives. Existing treatments are now becoming less effective due to the emergence of drug resistance. Improving our understanding of the mechanisms used by the parasite to adapt to drugs and achieve resistance is crucial for developing future treatment strategies. Unfortunately, the biological mechanism whereby Leishmania acquires drug resistance is poorly understood. Recent years have brought new technologies with the potential to increase greatly our understanding of drug resistance mechanisms. The latest mass spectrometry techniques allow the metabolome of parasites to be studied rapidly and in great detail. We have applied this approach to determine the metabolome of drug-sensitive and drug-resistant parasites isolated from patients with leishmaniasis. The data show that there are wholesale differences between the isolates and that the membrane composition has been drastically modified in drug-resistant parasites compared with drug-sensitive parasites. Our findings demonstrate that untargeted metabolomics has great potential to identify major metabolic differences between closely related parasite strains and thus should find many applications in distinguishing parasite phenotypes of clinical relevance