Differential sensitivity of ERBB2 kinase domain mutations towards lapatinib

Background

Overexpression of the ERBB2 kinase is observed in about one-third of breast cancer patients and the dual ERBB1/ERBB2 kinase inhibitor lapatinib was recently approved for the treatment of advanced ERBB2-positive breast cancer. Mutations in the ERBB2 receptor have recently been reported in breast cancer at diagnosis and also in gastric, colorectal and lung cancer. These mutations may have an impact on the clinical responses achieved with lapatinib in breast cancer and may also have a potential impact on the use of lapatinib in other solid cancers. However, the sensitivity of lapatinib towards clinically observed ERBB2 mutations is not known.

Methodology/Principal Findings

We cloned a panel of 8 clinically observed ERBB2 mutations, established stable cell lines and characterized their sensitivity towards lapatinib and alternative ERBB2 inhibitors. Both lapatinib-sensitive and lapatinib-resistant ERBB2 mutations were observed. Interestingly, we were able to generate lapatinib resistance mutations in wt-ERBB2 cells incubated with lapatinib for prolonged periods of time. This indicates that these resistance mutations may also cause secondary resistance in lapatinib-treated patients. Lapatinib-resistant ERBB2 mutations were found to be highly resistant towards AEE788 treatment but remained sensitive towards the dual irreversible inhibitors CL-387785 and WZ-4002.

Conclusions/Significance

Patients harbouring certain ERBB2 kinase domain mutations at diagnosis may not benefit from lapatinib treatment. Moreover, secondary lapatinib resistance may develop due to kinase domain mutations. Irreversible ERBB2 inhibitors may offer alternative treatment options for breast cancer and other solid tumor patients harbouring lapatinib resistance mutations. In addition, these inhibitors may be of interest in the scenario of secondary lapatinib resistance.     

The role of compensatory mutations in the emergence of drug resistance

Pathogens that evolve resistance to drugs usually have reduced fitness. However, mutations that largely compensate for this reduction in fitness often arise. We investigate how these compensatory mutations affect population-wide resistance emergence as a function of drug treatment. Using a model of gonorrhea transmission dynamics, we obtain generally applicable, qualitative results that show how compensatory mutations lead to more likely and faster resistance emergence. We further show that resistance emergence depends on the level of drug use in a strongly nonlinear fashion. We also discuss what data need to be obtained to allow future quantitative predictions of resistance emergence.     

Modeling the Dynamics of Heterogeneity of Solid Tumors in Response to Chemotherapy

In this paper, we extend the model of the dynamics of drug resistance in a solid tumor that was introduced by Lorz et al. (Bull Math Biol 77:1–22, 2015). Similarly to the original, radially symmetric model, the quantities we follow depend on a phenotype variable that corresponds to the level of drug resistance. The original model is modified in three ways: (i) We consider a more general growth term that takes into account the sensitivity of resistance level to high drug dosage. (ii) We add a diffusion term in space for the cancer cells and adjust all diffusion terms (for the nutrients and for the drugs) so that the permeability of the resource and drug is limited by the cell concentration. (iii) We add a mutation term with a mutation kernel that corresponds to mutations that occur regularly or rarely. We study the dynamics of the emerging resistance of the cancer cells under continuous infusion and on–off infusion of cytotoxic and cytostatic drugs. While the original Lorz model has an asymptotic profile in which the cancer cells are either fully resistant or fully sensitive, our model allows the emergence of partial resistance levels. We show that increased drug concentrations are correlated with delayed relapse. However, when the cancer relapses, more resistant traits are selected. We further show that an on–off drug infusion also selects for more resistant traits when compared with a continuous drug infusion of identical total drug concentrations. Under certain conditions, our model predicts the emergence of a heterogeneous tumor in which cancer cells of different resistance levels coexist in different areas in space.     

Mapping and manipulating the Mycobacterium tuberculosis transcriptome using a transcription factor overexpression-derived regulatory network

Background

Mycobacterium tuberculosis is characterized by a low mutation rate and a lack of genetic recombination. Yet, the rise of extensively resistant strains paints a picture of a microbe with an impressive adaptive potential. Here we describe the first documented case of extensively drug-resistant tuberculosis evolved from a susceptible ancestor within a single patient.

Results

Genome sequences of nine serial M. tuberculosis isolates from the same patient uncovered a dramatic turnover of competing lineages driven by the emergence, and subsequent fixation or loss of single nucleotide polymorphisms. For most drugs, resistance arose through independent emergence of mutations in more than one clone, of which only one ultimately prevailed as the clone carrying it expanded, displacing the other clones in the process. The vast majority of mutations identified over 3.5 years were either involved in drug resistance or hitchhiking in the genetic background of these. Additionally, RNA-sequencing of isolates grown in the absence of drug challenge revealed that the efflux-associated iniBAC operon was up-regulated over time, whereas down-regulated genes include those involved in mycolic acid synthesis.

Conclusions

We observed both rapid acquisitions of resistance to antimicrobial compounds mediated by individual mutations as well as a gradual increase in fitness in the presence of antibiotics, likely driven by stable gene expression reprogramming. The rapid turnover of resistance mutations and hitchhiking neutral mutations has major implications for inferring tuberculosis transmission events in situations where drug resistance evolves within transmission chains.     

Dynamics of Preferential Substrate Recognition in HIV-1 Protease: Redefining the Substrate Envelope

Human immunodeficiency virus type 1 (HIV-1) protease (PR) permits viral maturation by processing the gag and gag-pro-pol polyproteins. HIV-1 PR inhibitors (PIs) are used in combination antiviral therapy but the emergence of drug resistance has limited their efficacy. The rapid evolution of HIV-1 necessitates consideration of drug resistance in novel drug design. Drug-resistant HIV-1 PR variants no longer inhibited efficiently, continue to hydrolyze the natural viral substrates. Though highly diverse in sequence, the HIV-1 PR substrates bind in a conserved three-dimensional shape we termed the substrate envelope. Earlier, we showed that resistance mutations arise where PIs protrude beyond the substrate envelope, because these regions are crucial for drug binding but not for substrate recognition. We extend this model by considering the role of protein dynamics in the interaction of HIV-1 PR with its substrates. We simulated the molecular dynamics of seven PR-substrate complexes to estimate the conformational flexibility of the bound substrates. Interdependence of substrate-protease interactions might compensate for variations in cleavage-site sequences and explain how a diverse set of sequences are recognized as substrates by the same enzyme. This diversity might be essential for regulating sequential processing of substrates. We define a dynamic substrate envelope as a more accurate representation of PR-substrate interactions. This dynamic substrate envelope, described by a probability distribution function, is a powerful tool for drug design efforts targeting ensembles of resistant HIV-1 PR variants with the aim of developing drugs that are less susceptible to resistance.     

On the contribution of the rodent model Plasmodium chabaudi for understanding the genetics of drug resistance in malaria

Malaria is a devastating disease that still claims over half a million lives every year, mostly in sub–Saharan Africa. One of the main barriers to malaria control is the evolution and propagation of drug-resistant mutant parasites. Knowing the genes and respective mutations responsible for drug resistance facilitates the design of drugs with novel modes of action and allows predicting and monitoring drug resistance in natural parasite populations in real-time. The best way to identify these mutations is to experimentally evolve resistance to the drug in question and then comparing the genomes of the drug-resistant mutants to that of the sensitive progenitor parasites. This simple evolutive concept was the starting point for the development of a paradigm over the years, based on the use of the rodent malaria parasite Plasmodium chabaudi to unravel the genetics of drug resistance in malaria. It involves the use of a cloned parasite isolate (P. chabaudi AS) whose genome is well characterized, to artificially select resistance to given drugs through serial passages in mice under slowly increasing drug pressure. The end resulting parasites are cloned and the genetic mutations are then discovered through Linkage Group Selection, a technique conceived by Prof. Richard Carter and his group, and/or Whole Genome Sequencing. The precise role of these mutations can then be interrogated in malaria parasites of humans through allelic replacement experiments and/or genotype-phenotype association studies in natural parasite populations. Using this paradigm, all the mutations underlying resistance to the most important antimalarial drugs were identified, most of which were pioneering and later shown to also play a role in drug resistance in natural infections of human malaria parasites. This supports the use of P. chabaudi a fast-track predictive model to identify candidate genetic markers of resistance to present and future antimalarial drugs and improving our understanding of the biology of resistance.     

Environmental mutagens may be implicated in the emergence of drug-resistant microorganisms

The emergence of drug-resistant microorganisms is an important medical and social problem. Drug-resistant microorganisms are thought to grow selectively in the presence of antibiotics. Most clinically isolated drug-resistant microorganisms have mutations in the target genes for the drugs. While any of the many mutagens in the environment may cause such genetic mutations, no reports have yet described whether these mutagens can confer drug resistance to clinically important microorganisms. We investigated how environmental mutagens might be implicated in acquired resistance to antibiotics in clinically important microorganisms, which causes human diseases. We selected mutagens found in the environment, in cigarette smoke, or in drugs, and then exposed Pseudomonas aeruginosa to them. After exposure, the incidence of rifampicin- and ciprofloxacin-resistant P. aeruginosa strains markedly increased, and we found mutations in genes for the antibiotic-target molecule. These mutations were similar to those found in drug-resistant microorganisms isolated from clinical samples. Our findings show that environmental mutagens, and an anticancer drug, are capable of inducing drug-resistant P. aeruginosa similar to strains found in clinical settings.     

Structural analyses of 2015-updated drug-resistant mutations in HIV-1 protease: an implication of protease inhibitor cross-resistance

Background

Strategies to control HIV for improving the quality of patient lives have been aided by the Highly Active Anti-Retroviral Therapy (HAART), which consists of a cocktail of inhibitors targeting key viral enzymes. Numerous new drugs have been developed over the past few decades but viral resistances to these drugs in the targeted viral enzymes are increasingly reported. Nonetheless the acquired mutations often reduce viral fitness and infectivity. Viral compensatory secondary-line mutations mitigate this loss of fitness, equipping the virus with a broad spectrum of resistance against these drugs. While structural understanding of the viral protease and its drug resistance mutations have been well established, the interconnectivity and development of structural cross-resistance remain unclear. This paper reports the structural analyses of recent clinical mutations on the drug cross-resistance effects from various protease and protease inhibitors (PIs) complexes.

Methods

Using the 2015 updated clinical HIV protease mutations, we constructed a structure-based correlation network and a minimum-spanning tree (MST) based on the following features: (i) topology of the PI-binding pocket, (ii) allosteric effects of the mutations, and (iii) protease structural stability.

Results and conclusion

Analyis of the network and the MST of dominant mutations conferring resistance to the seven PIs (Atazanavir-ATV, Darunavir-DRV, Indinavir-IDV, Lopinavir-LPV, Nelfinavir-NFV, Saquinavir-SQV, and Tipranavir-TPV) showed that cross-resistance can develop easily across NFV, SQV, LPV, IDV, and DRV, but not for ATV or TPV. Through estimation of the changes in vibrational entropies caused by each reported mutation, some secondary mutations were found to destabilize protease structure. Our findings provide an insight into the mechanism of PI cross-resistance and may also be useful in guiding the selection of PI in clinical treatment to delay the onset of cross drug resistance.

     

Identification of Novel Mutations Responsible for Resistance to MK-2048, a Second-Generation HIV-1 Integrase Inhibitor

MK-2048 represents a prototype second-generation integrase strand transfer inhibitor (INSTI) developed with the goal of retaining activity against viruses containing mutations associated with resistance to first-generation INSTIs, raltegravir (RAL) and elvitegravir (EVG). Here, we report the identification of mutations (G118R and E138K) which confer resistance to MK-2048 and not to RAL or EVG. These mutations were selected in vitro and confirmed by site-specific mutagenesis. G118R, which appeared first in cell culture, conferred low levels of resistance to MK-2048. G118R also reduced viral replication capacity to approximately 1% that of the isogenic wild-type (wt) virus. The subsequent selection of E138K partially restored replication capacity to ≈13% of wt levels and increased resistance to MK-2048 to ≈8-fold. Viruses containing G118R and E138K remained largely susceptible to both RAL and EVG, suggesting a unique interaction between this second-generation INSTI and the enzyme may be defined by these residues as a potential basis for the increased intrinsic affinity and longer “off” rate of MK-2048. In silico structural analysis suggests that the introduction of a positively charged arginine at position 118, near the catalytic amino acid 116, might decrease Mg²⁺ binding, compromising enzyme function and thus leading to the significant reduction in both integration and viral replication capacity observed with these mutations.Selective pressure exerted by antiretroviral drugs, in conjunction with high viral mutation rates, promotes the inevitable emergence of drug-resistant HIV-1 variants. This necessitates an ongoing search for novel antiretroviral compounds that either have novel mechanisms and inhibit different stages of viral replication or inhibit targets that have acquired resistance to existing drugs. In the latter case, such newer next-generation agents should ideally display resistance profiles which are distinct and nonoverlapping with those of the first-generation drugs.Integration of viral cDNA into the host cell genome is a distinct feature of retroviral replication, and inhibitors of HIV-1 integrase have recently been added to the arsenal of clinically approved antiretroviral drugs. Raltegravir (RAL) was the first integrase strand transfer inhibitor (INSTI) to be approved by the U.S. Food and Drug Administration (FDA) after clinical trials showed that this drug promoted a rapid and sustained antiviral effect (13). Elvitegravir (EVG), another integrase inhibitor, is currently in phase III clinical trials (27). Resistance mutations common to both of these first-generation integrase inhibitors have been reported and can result in high levels of drug resistance (26). Mutations which engender cross-resistance between RAL and EVG have been reported in clinical trials, cell culture studies, and biochemical assays (9, 26). This has prompted the search for second-generation integrase inhibitors that might display novel patterns of resistance, allowing their use in patients who have failed therapy with RAL or EVG. MK-2048 (28) is a prototype second-generation INSTI that retains potency against viruses containing common single and double mutations observed in the clinic with first-generation agents with a 95% inhibitory concentration (IC₉₅) in the nM range. MK-2048 has been previously reported to be active against viruses resistant to RAL and EVG (28, 29). Given common mechanisms of action among INSTIs and a lack of structural information on integrase inhibitor complexes with resistance mutations, an understanding of resistance to second-generation agents such as MK-2048 is important.This article describes the selection of resistance to MK-2048 in tissue culture and the characterization of mutations associated with such resistance, G118R and E138K. The identification of distinct mutations which appear to confer resistance to MK-2048 and not to either RAL or EVG has potential implications for understanding the structural basis for the second-generation profile of this compound as well as future drug discovery and development efforts focused on this mechanism.     

Comparative genomics study of multi-drug-resistance mechanisms in the antibiotic-resistant Streptococcus suis R61 strain

Background

Streptococcus suis infections are a serious problem for both humans and pigs worldwide. The emergence and increasing prevalence of antibiotic-resistant S. suis strains pose significant clinical and societal challenges.

Results

In our study, we sequenced one multi-drug-resistant S. suis strain, R61, and one S. suis strain, A7, which is fully sensitive to all tested antibiotics. Comparative genomic analysis revealed that the R61 strain is phylogenetically distinct from other S. suis strains, and the genome of R61 exhibits extreme levels of evolutionary plasticity with high levels of gene gain and loss. Our results indicate that the multi-drug-resistant strain R61 has evolved three main categories of resistance.

Conclusions

Comparative genomic analysis of S. suis strains with diverse drug-resistant phenotypes provided evidence that horizontal gene transfer is an important evolutionary force in shaping the genome of multi-drug-resistant strain R61. In this study, we discovered novel and previously unexamined mutations that are strong candidates for conferring drug resistance. We believe that these mutations will provide crucial clues for designing new drugs against this pathogen. In addition, our work provides a clear demonstration that the use of drugs has driven the emergence of the multi-drug-resistant strain R61.     

Reverse Chemical Genetics: Comprehensive Fitness Profiling Reveals the Spectrum of Drug Target Interactions

The emergence and prevalence of drug resistance demands streamlined strategies to identify drug resistant variants in a fast, systematic and cost-effective way. Methods commonly used to understand and predict drug resistance rely on limited clinical studies from patients who are refractory to drugs or on laborious evolution experiments with poor coverage of the gene variants. Here, we report an integrative functional variomics methodology combining deep sequencing and a Bayesian statistical model to provide a comprehensive list of drug resistance alleles from complex variant populations. Dihydrofolate reductase, the target of methotrexate chemotherapy drug, was used as a model to identify functional mutant alleles correlated with methotrexate resistance. This systematic approach identified previously reported resistance mutations, as well as novel point mutations that were validated in vivo. Use of this systematic strategy as a routine diagnostics tool widens the scope of successful drug research and development.     

Fitness trade-offs in the evolution of dihydrofolate reductase and drug resistance in Plasmodium falciparum

Background

Patterns of emerging drug resistance reflect the underlying adaptive landscapes for specific drugs. In Plasmodium falciparum, the parasite that causes the most serious form of malaria, antifolate drugs inhibit the function of essential enzymes in the folate pathway. However, a handful of mutations in the gene coding for one such enzyme, dihydrofolate reductase, confer drug resistance. Understanding how evolution proceeds from drug susceptibility to drug resistance is critical if new antifolate treatments are to have sustained usefulness.

Methodology/Principal Findings

We use a transgenic yeast expression system to build on previous studies that described the adaptive landscape for the antifolate drug pyrimethamine, and we describe the most likely evolutionary trajectories for the evolution of drug resistance to the antifolate chlorcycloguanil. We find that the adaptive landscape for chlorcycloguanil is multi-peaked, not all highly resistant alleles are equally accessible by evolution, and there are both commonalities and differences in adaptive landscapes for chlorcycloguanil and pyrimethamine.

Conclusions/Significance

Our findings suggest that cross-resistance between drugs targeting the same enzyme reflect the fitness landscapes associated with each particular drug and the position of the genotype on both landscapes. The possible public health implications of these findings are discussed.     

Sequence signatures involved in targeting the male-specific lethal complex to X-chromosomal genes in Drosophila melanogaster

Background

Drug resistance in the malaria parasite Plasmodium falciparum severely compromises the treatment and control of malaria. A knowledge of the critical mutations conferring resistance to particular drugs is important in understanding modes of drug action and mechanisms of resistances. They are required to design better therapies and limit drug resistance. A mutation in the gene (pfcrt) encoding a membrane transporter has been identified as a principal determinant of chloroquine resistance in P. falciparum, but we lack a full account of higher level chloroquine resistance. Furthermore, the determinants of resistance in the other major human malaria parasite, P. vivax, are not known. To address these questions, we investigated the genetic basis of chloroquine resistance in an isogenic lineage of rodent malaria parasite P. chabaudi in which high level resistance to chloroquine has been progressively selected under laboratory conditions.

Results

Loci containing the critical genes were mapped by Linkage Group Selection, using a genetic cross between the high-level chloroquine-resistant mutant and a genetically distinct sensitive strain. A novel high-resolution quantitative whole-genome re-sequencing approach was used to reveal three regions of selection on chr11, chr03 and chr02 that appear progressively at increasing drug doses on three chromosomes. Whole-genome sequencing of the chloroquine-resistant parent identified just four point mutations in different genes on these chromosomes. Three mutations are located at the foci of the selection valleys and are therefore predicted to confer different levels of chloroquine resistance. The critical mutation conferring the first level of chloroquine resistance is found in aat1, a putative aminoacid transporter.

Conclusions

Quantitative trait loci conferring selectable phenotypes, such as drug resistance, can be mapped directly using progressive genome-wide linkage group selection. Quantitative genome-wide short-read genome resequencing can be used to reveal these signatures of drug selection at high resolution. The identities of three genes (and mutations within them) conferring different levels of chloroquine resistance generate insights regarding the genetic architecture and mechanisms of resistance to chloroquine and other drugs. Importantly, their orthologues may now be evaluated for critical or accessory roles in chloroquine resistance in human malarias P. vivax and P. falciparum.     

Using Aspergillus nidulans To Identify Antifungal Drug Resistance Mutations

Systemic fungal infections contribute to at least 10% of deaths in hospital settings. Most antifungal drugs target ergosterol (polyenes) or its biosynthetic pathway (azoles and allylamines), or beta-glucan synthesis (echinocandins). Antifungal drugs that target proteins are prone to the emergence of resistant strains. Identification of genes whose mutations lead to targeted resistance can provide new information on those pathways. We used Aspergillus nidulans as a model system to exploit its tractable sexual cycle and calcofluor white as a model antifungal agent to cross-reference our results with other studies. Within 2 weeks from inoculation on sublethal doses of calcofluor white, we isolated 24 A. nidulans adaptive strains from sectoring colonies. Meiotic analysis showed that these strains had single-gene mutations. In each case, the resistance was specific to calcofluor white, since there was no cross-resistance to caspofungin (echinocandin). Mutation sites were identified in two mutants by next-generation sequencing. These were confirmed by reengineering the mutation in a wild-type strain using a gene replacement strategy. One of these mutated genes was related to cell wall synthesis, and the other one was related to drug metabolism. Our strategy has wide application for many fungal species, for antifungal compounds used in agriculture as well as health care, and potentially during protracted drug therapy once drug resistance arises. We suggest that our strategy will be useful for keeping ahead in the drug resistance arms race.     

Leishmania: role of P glycoprotein in drug resistance and reversion strategies

Protozoan parasites are important causative agents of morbidity and mortality throughout the world--a problem further complicated by the emergence of drug resistance in these parasites. Mechanisms of drug resistance include the following: decreased uptake of the drug into the cell, loss of drug activation, alterations in the drug target, and over-expression of a well-known multiple drug transporter proteins. In this review, two critical components of resistance are stressed: (1) the role of ATP binding cassette proteins, such as P-glycoproteins, in mediating drug resistance in Leishmania and other protozoans, followed by development of cross-resistance to many structurally and functionally unrelated drugs, and (2) some concepts concerning the reversal mechanism of multidrug resistance by drugs and natural products. Several modulators or chemosensitizers alter the capacity of P-glycoproteins to maintain subtoxic intracellular drug concentrations. Calcium channel blockers such as verapamil act in this mode; however, high concentrations are required for an efficient and effective inhibition and, in addition, produce undesirable side effects. The discovery of new, natural product modulators of P-glycoproteins is stressed. This category of modulators offer potentially improved efficacy and lowered toxicity for the mammalian host.     

Understanding the Basis of Drug Resistance of the Mutants of αβ-Tubulin Dimer via Molecular Dynamics Simulations

The vital role of tubulin dimer in cell division makes it an attractive drug target. Drugs that target tubulin showed significant clinical success in treating various cancers. However, the efficacy of these drugs is attenuated by the emergence of tubulin mutants that are unsusceptible to several classes of tubulin binding drugs. The molecular basis of drug resistance of the tubulin mutants is yet to be unraveled. Here, we employ molecular dynamics simulations, protein-ligand docking, and MMPB(GB)SA analyses to examine the binding of anticancer drugs, taxol and epothilone to the reported point mutants of tubulin - T274I, R282Q, and Q292E. Results suggest that the mutations significantly alter the tubulin structure and dynamics, thereby weaken the interactions and binding of the drugs, primarily by modifying the M loop conformation and enlarging the pocket volume. Interestingly, these mutations also affect the tubulin distal sites that are associated with microtubule building processes.     

Dose-Dependent Mutation Rates Determine Optimum Erlotinib Dosing Strategies for EGFR Mutant Non-Small Cell Lung Cancer Patients

Background

The advent of targeted therapy for cancer treatment has brought about a paradigm shift in the clinical management of human malignancies. Agents such as erlotinib used for EGFR-mutant non-small cell lung cancer or imatinib for chronic myeloid leukemia, for instance, lead to rapid tumor responses. Unfortunately, however, resistance often emerges and renders these agents ineffective after a variable amount of time. The FDA-approved dosing schedules for these drugs were not designed to optimally prevent the emergence of resistance. To this end, we have previously utilized evolutionary mathematical modeling of treatment responses to elucidate the dosing schedules best able to prevent or delay the onset of resistance. Here we expand on our approaches by taking into account dose-dependent mutation rates at which resistant cells emerge. The relationship between the serum drug concentration and the rate at which resistance mutations arise can lead to non-intuitive results about the best dose administration strategies to prevent or delay the emergence of resistance.

Methods

We used mathematical modeling, available clinical trial data, and different considerations of the relationship between mutation rate and drug concentration to predict the effectiveness of different dosing strategies.

Results

We designed several distinct measures to interrogate the effects of different treatment dosing strategies and found that a low-dose continuous strategy coupled with high-dose pulses leads to the maximal delay until clinically observable resistance. Furthermore, the response to treatment is robust against different assumptions of the mutation rate as a function of drug concentration.

Conclusions

For new and existing targeted drugs, our methodology can be employed to compare the effectiveness of different dose administration schedules and investigate the influence of changing mutation rates on outcomes.