ABSTRACT
The X-ray crystal structure data of 12-α-fluoro-3ß-hy-droxy-olean-28,13ß-olide methanol hemisolvate, 2C30H47FO3·CH3OH, (1), and 12-α-fluoro-3ß-hy-droxy-taraxer-28,14ß-olide methanol hemisolvate, 2C30H47FO3·CH3OH, (2), are described. The fluoro-lactonization of oleanolic acid using SelectfluorTM yielded a mixture of the six-membered δ-lactone (1) and the unusual seven-membered γ-lactone (2) following a 1,2-shift of methyl C-27 from C-14 to C-13.
ABSTRACT
Computational simulation methods based on machine learned potentials (MLPs) promise to revolutionise shape prediction of flexible molecules in solution, but their widespread adoption has been limited by the way in which training data is generated. Here, we present an approach which allows the key conformational degrees of freedom to be properly represented in reference molecular datasets. MLPs trained on these datasets using a global descriptor scheme are generalisable in conformational space, providing quantum chemical accuracy for all conformers. These MLPs are capable of propagating long, stable molecular dynamics trajectories, an attribute that has remained a challenge. We deploy the MLPs in obtaining converged conformational free energy surfaces for flexible molecules via well-tempered metadynamics simulations; this approach provides a hitherto inaccessible route to accurately computing the structural, dynamical and thermodynamical properties of a wide variety of flexible molecular systems. It is further demonstrated that MLPs must be trained on reference datasets with complete coverage of conformational space, including in barrier regions, to achieve stable molecular dynamics trajectories.
ABSTRACT
This report seeks to discuss sequelae of chronic cellulitis that is commonly treated in the ambulatory setting, as exacerbated by the conditions of living outside. Further we hope to identify etiologic factors that contribute to complication development. Additionally, this article will touch on unique treatment plan considerations for unhoused patients with the intention to educate providers and reduce mortality and morbidity relating to pedal skin and soft tissue infections in this population. This piece examines the case of a 52-year-old man with a history of chronic diseases, substance use disorder, and recurrent cellulitis. We highlight systemic issues in healthcare delivery for unhoused patients, including inadequate discharge planning, limited access to medication, and challenges in shelter placement. The discussion section emphasizes the importance of accurate diagnosis and tailored treatment plans for cellulitis in houseless individuals, the importance of a multidisciplinary approach incorporating social work services, and addressing chronic illnesses, substance use disorder, and housing issues. The report advocates for heightened awareness of bilateral cellulitis in unhoused populations, emphasizing the need for comprehensive, individualized treatment plans.
Subject(s)
Cellulitis , Humans , Cellulitis/etiology , Cellulitis/therapy , Male , Middle Aged , Chronic Disease , Substance-Related Disorders/complications , Substance-Related Disorders/therapy , Anti-Bacterial Agents/therapeutic use , HousingABSTRACT
Traditional medicines have reportedly treated SARS-CoV-2 infection. Substantial evidence shows that fish oil supplements promote human immune function, suggesting they may lessen susceptibility to SARS-CoV-2 infection and suppress viral replication by inducing interferon. Fish oil was subjected to partition chromatography and separated into two compounds (EP01 and DH01). Isolated compounds were purified and characterized using UV, FTIR, NMR, and mass spectrometry to confirm their identity. Molecular docking was studied on the SARS CoV-2 variants of concern; SARS CoV-2 WT (PDB: 6VXX), SARS CoV-2 Alpha variant (PDB: 7LWS), SARS CoV-2 Delta variant (PDB: 7TOU), SARS CoV-2 Gamma variant (PDB: 7V78), SARS CoV-2 Kappa variant (PDB: 7VX9), and SARS CoV-2 Omicron variant (PDB: 7QO7) and TMPRSS2 (PDB: 7Y0E). Further selected protein-ligand complexes were subjected to 100 ns MD simulations to predict their biological potential in the SARS-CoV-2 treatment. In-vitro biological studies were carried out to support in-silico findings. Isolated compounds EP01 and DH01 were identified as 5-Tridecyltetrahydro-2H-pyran-2-one and 5-Heptadecyltetrahydro-2H-pyran-2-one, respectively. The compound EP01 significantly reduced (93.24 %) the viral RNA copy number with an IC50 of ~8.661 µM. EP01 proved to be a potent antiviral by in-vitro method against the SARS-CoV-2 clinical isolate, making it a promising antiviral candidate, with a single dose capable of preventing viral replication.
Subject(s)
Antiviral Agents , Fish Oils , Molecular Docking Simulation , Pyrones , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , SARS-CoV-2/drug effects , Humans , Spike Glycoprotein, Coronavirus/metabolism , Spike Glycoprotein, Coronavirus/chemistry , Antiviral Agents/pharmacology , Antiviral Agents/chemistry , Binding Sites , Fish Oils/pharmacology , Fish Oils/chemistry , Pyrones/pharmacology , Pyrones/chemistry , Linoleic Acid/chemistry , Linoleic Acid/pharmacology , COVID-19 Drug Treatment , Molecular Dynamics Simulation , COVID-19/virologyABSTRACT
The ability to conduct effective high throughput screening (HTS) campaigns in drug discovery is often hampered by the detection of false positives in these assays due to small colloidally aggregating molecules (SCAMs). SCAMs can produce artifactual hits in HTS by nonspecific inhibition of the protein target. In this work, we present a new computational prediction tool for detecting SCAMs based on their 2D chemical structure. The tool, called the boosted aggregation detection (BAD) molecule filter, employs decision tree ensemble methods, namely, the CatBoost classifier and the light gradient-boosting machine, to significantly improve the detection of SCAMs. In developing the filter, we explore models trained on individual data sets, a consensus approach using these models, and, third, a merged data set approach, each tailored for specific drug discovery needs. The individual data set method emerged as most effective, achieving 93% sensitivity and 90% specificity, outperforming existing state-of-the-art models by 20 and 5%, respectively. The consensus models offer broader chemical space coverage, exceeding 90% for all testing sets. This feature is an important aspect particularly for early stage medicinal chemistry projects, and provides information on applicability domain. Meanwhile, the merged data set models demonstrated robust performance, with a notable sensitivity of 79% in the comprehensive 10-fold cross-validation test set. A SHAP analysis of model features indicates the importance of hydrophobicity and molecular complexity as primary factors influencing the aggregation propensity. The BAD molecule filter is readily accessible for the public usage on https://molmodlab-aau.com/Tools.html. This filter provides a new, more robust tool for aggregate prediction in the early stages of drug discovery to optimize hit rates and reduce associated testing and validation overheads.
Subject(s)
Drug Discovery , Drug Discovery/methods , Colloids/chemistry , High-Throughput Screening Assays , Small Molecule Libraries/chemistryABSTRACT
Small colloidally aggregating molecules (SCAMs) can be problematic for biological assays in drug discovery campaigns. However, the self-associating properties of SCAMs have potential applications in drug delivery and analytical biochemistry. Consequently, the ability to predict the aggregation propensity of a small organic molecule is of considerable interest. Chemoinformatics-based filters such as ChemAGG and Aggregator Advisor offer rapid assessment but are limited by the assay quality and structural diversity of their training set data. Complementary to these tools, we explore here the ability of molecular dynamics (MD) simulations as a physics-based method capable of predicting the aggregation propensity of diverse chemical structures. For a set of 32 molecules, using simulations of 100 ns in explicit solvent, we find a success rate of 97% (one molecule misclassified) as opposed to 75% by Aggregator Advisor and 72% by ChemAGG. These short timescale MD simulations are representative of longer microsecond trajectories and yield an informative spectrum of aggregation propensities across the set of solutes, capturing the dynamic behaviour of weakly aggregating compounds. Implicit solvent simulations using the generalized Born model were less successful in predicting aggregation propensity. MD simulations were also performed to explore structure-aggregation relationships for selected molecules, identifying chemical modifications that reversed the predicted behaviour of a given aggregator/non-aggregator compound. While lower throughput than rapid cheminformatics-based SCAM filters, MD-based prediction of aggregation has potential to be deployed on the scale of focused subsets of moderate size, and, depending on the target application, provide guidance on removing or optimizing a compound's aggregation propensity.
Subject(s)
Drug Discovery , Molecular Dynamics Simulation , Solvents/chemistry , SolutionsABSTRACT
Excessive or aberrant NLRP3 inflammasome activation has been implicated in the progression and initiation of many inflammatory conditions; however, currently no NLRP3 inflammasome inhibitors have been approved for therapeutic use in the clinic. Here we have identified that the natural product brazilin effectively inhibits both priming and activation of the NLRP3 inflammasome in cultured murine macrophages, a human iPSC microglial cell line and in a mouse model of acute peritoneal inflammation. Through computational modeling, we predict that brazilin can adopt a favorable binding pose within a site of the NLRP3 protein which is essential for its conformational activation. Our results not only encourage further evaluation of brazilin as a therapeutic agent for NLRP3-related inflammatory diseases, but also introduce this small-molecule as a promising scaffold structure for the development of derivative NLRP3 inhibitor compounds.
ABSTRACT
Molecular simulations have become a key tool in molecular and materials design. Machine learning (ML)-based potential energy functions offer the prospect of simulating complex molecular systems efficiently at quantum chemical accuracy. In previous work, we have introduced the ML-based PairF-Net approach to neural network potentials, that adopts a pairwise interatomic scheme to predicting forces within a molecular system. Here, we further develop the PairF-Net model to intrinsically incorporate energy conservation and couple the model to a molecular mechanical (MM) environment within the OpenMM package. The updated PairF-Net model yields energy and force predictions and dynamical distributions in good agreement with the rMD17 dataset of ten small organic molecules in the gas-phase. We further show that these in vacuo ML models of small molecules can be applied to force predictions in aqueous solution via hybrid ML/MM simulations. We present a new benchmark dataset for these ten molecules in solution, obtained from QM/MM simulations, which we denote as rMD17-aq (https://zenodo.org/records/10048644); and assess the ability of PairF-Net to reproduce the molecular energy, atomic forces and dynamical distributions of these solution conformations via ML/MM simulations.
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Graphene-cellulose interactions have considerable potential in the development of new materials. In previous computational work (Biomacromolecules2016, 16, 1771), we predicted that the model 100 hydrophobic surface of cellulose interacted favourably with pristine graphene in aqueous solution molecular dynamics simulations; conversely, a model of the hydrophilic 010 surface of cellulose exhibited progressive rearrangement to present a more hydrophobic face with the graphene, with weakened hydrogen bonds between cellulose chains and partial permeation of water. Here, we extend this work by simulating the interaction in aqueous solution of the amphiphilic 110 surface of a cellulose Iß microfibril model, comprising 36 chains of 40 glucosyl residues, with an infinite sheet of pristine graphene. This face of the microfibril is of intermediate hydrophilicity and progressively associates with graphene over replicate simulations. As cellulose chains adhere to the graphene surface, forming interactions via its CH and OH groups, we observe a degree of local and global untwisting of the microfibril. Complementary rippling of the graphene surface is also observed, as it adapts to interaction with the microfibril. This adsorption process is accompanied by increased exclusion of water between cellulose and graphene although some water localises between chains at the immediate interface. The predicted propensity of a cellulose microfibril to adsorb spontaneously on the graphene surface, with mutual structural accommodation, highlights the amphiphilic nature of cellulose and the types of interactions that can be harnessed to design new graphene-carbohydrate biopolymer materials.
Subject(s)
Graphite , Water , Water/chemistry , Microfibrils , Cellulose/chemistry , Molecular Dynamics SimulationABSTRACT
The NLRP3 inflammasome is currently an exciting target for drug discovery due to its role in various inflammatory diseases; however, to date, no NLRP3 inhibitors have reached the clinic. Several studies have used natural products as hit compounds to facilitate the design of novel selective NLRP3 inhibitors. Here, we review selected natural products reported in the literature as NLRP3 inhibitors, with a particular focus on those targeting gout. To complement this survey, we also report a virtual screen of the ZINC20 natural product database, predicting favored chemical features that can aid in the design of novel small molecule NLRP3 inhibitors.
Subject(s)
Biological Products , Gout , Biological Products/pharmacology , Humans , Inflammasomes , Interleukin-1beta , NLR Family, Pyrin Domain-Containing 3 ProteinABSTRACT
The NLRP3 inflammasome is a cytoplasmic complex that regulates the activation of inflammatory cytokines and, given its implication in a range of diseases, is an important therapeutic target. The cofactor ATP and the centrosomal kinase NEK7 are important for NLRP3 activation. Here we have constructed and simulated computational models of full-length monomeric NLRP3 to shed light on the importance of NEK7 and cofactor interactions for its conformation and dynamics in aqueous solution. We find that molecular dynamics simulation reproduces well the features of the recently published cryo-EM structure of the ADP-bound NLRP3-NEK7 complex; on the removal of NEK7, the NLRP3 molecule adopts a more compact closed form during simulations. Replacement of ADP by ATP promotes a rearrangement of hydrogen-bonding interactions, domain interfaces, and a degree of opening of the NLRP3 conformation. We also examine the dynamics of an acidic loop of the LRR domain of NLRP3, which samples in a region observed in the NEK7-bound cryo-EM structure but not in an oligomeric form of inactive NLRP3. During the molecular dynamics simulations of NLRP3, we find some plasticity in its topology that suggests access routes for ATP to the cofactor pocket not immediately evident from the existing NEK7-bound cryo-EM structure. These computed dynamical trajectories of NLRP3 provide insight into coordinates of deformation that may be key for cofactor binding and inflammasome activation.
Subject(s)
Inflammasomes , NIMA-Related Kinases , NLR Family, Pyrin Domain-Containing 3 Protein , Adenosine Diphosphate , Adenosine Triphosphate , Computer Simulation , Cytokines/metabolism , Hydrogen , Inflammasomes/chemistry , Inflammasomes/metabolism , NIMA-Related Kinases/metabolism , NLR Family, Pyrin Domain-Containing 3 Protein/metabolismABSTRACT
Pyranose ring pucker is a key coordinate governing the structure, interactions and reactivity of carbohydrates. We assess the ability of the machine learning potentials, ANI-1ccx and ANI-2x, and the GFN2-xTB semiempirical quantum chemical method, to model ring pucker conformers of five monosaccharides and oxane in the gas phase. Relative to coupled-cluster quantum mechanical calculations, we find that ANI-1ccx most accurately reproduces the ring pucker energy landscape for these molecules, with a correlation coefficient r2 of 0.83. This correlation in relative energies lowers to values of 0.70 for ANI-2x and 0.60 for GFN2-xTB. The ANI-1ccx also provides the most accurate estimate of the energetics of the 4 C1 -to-1 C4 minimum energy pathway for the six molecules. All three models reproduce chair more accurately than non-chair geometries. Analysis of small model molecules suggests that the ANI-1ccx model favors puckers with equatorial hydrogen bonding substituents; that ANI-2x and GFN2-xTB models overstabilize conformers with axially oriented groups; and that the endo-anomeric effect is overestimated by the machine learning models and underestimated via the GFN2-xTB method. While the pucker conformers considered in this study correspond to a gas phase environment, the accuracy and computational efficiency of the ANI-1ccx approach in modeling ring pucker in vacuo provides a promising basis for future evaluation and application to condensed phase environments.
Subject(s)
Carbohydrates , Quantum Theory , Carbohydrates/chemistry , Hydrogen Bonding , Machine Learning , Monosaccharides/chemistryABSTRACT
Background: Although one of the fastest-growing populations in the USA, Latinx individuals remain underrepresented in research. In this study, we aimed to identify how Latina/Latinx participants of the Environment, Leiomyomas, Latinas, and Adiposity Study (ELLAS) learned about the research study and what motivated them to participate. Materials and Methods: Using a standardized survey tool, bilingual staff interviewed participants and asked them, 1) how they heard about ELLAS and 2) to identify and rank their top three reasons for participating in ELLAS. Results: "Word of mouth" through a friend or relative was the most common method of learning about ELLAS (49.0%), followed by a "community outreach event" (29.3%). The three most common reasons for participating in ELLAS were "to learn more about women's health" (83.3%), "to receive a free health assessment" (79.4%), and "to contribute to scientific knowledge" (59.5%). Correlation between demographic and socioeconomic characteristics and participant responses indicated that there are different reasons for participation based on these factors. Conclusions: Community engagement and word of mouth are vital to the successful recruitment of Latina/Latinx participants to research studies. Latinx participants are most motivated to participate by health benefits and health education, as well as altruistic aspects of research studies. Therefore, establishing mutually beneficial relationships within Latinx communities and appealing to motivations for research participation with close attention to the demographics of participants can both expand and allow for targeted recruitment efforts for this underrepresented group in research studies.
ABSTRACT
The featureless interface formed by protein-protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.
Subject(s)
Proteins , Binding Sites , Ligands , Protein Binding , Proteins/metabolismABSTRACT
A set of meta-substituted 3-arylisoquinolinones have been identified that show substantial cytotoxicity in breast, liver, lung and colon cancer cell lines; these are up to 700-fold more active than the corresponding para analogues. These compounds were initially proposed as inhibitors of N-ribosyl dihydronicotinamide (NRH): quinone oxidoreductase 2 (NQO2) but were found to be inactive against the enzyme. Instead, COMPARE analysis suggested that 6-fluoro-3-(meta-fluorophenyl)isoquinolin-1(2H)-one (4) could mimic colchicine and interact with microtubules, a recognized target for cancer therapy. Subsequent docking, molecular dynamics simulations, and free energy analysis further suggested that compound 4 bound well into the colchicine-binding pocket of tubulin. Indeed, 4 suppressed tubulin polymerization, caused G2/M cell cycle arrest, and induced apoptosis. Also, 4 inhibited the formation of endothelial cell capillary-like tubes and further disrupted the structure of preestablished tubes; the effects were not observed with para analogue 5. In accordance with this, the computed free energy of binding of 5 to tubulin was lower in magnitude than that for 4 and appeared to arise in part from the inability of the para substituent to occupy a tubulin subpocket, which is possible in the meta orientation. In conclusion, the antiproliferative potential of the novel 3-arylisoquinolinones is markedly influenced by a subtle change in the structure (meta versus para). The meta-substituted isoquinolinone 4 is a microtubule-destabilizing agent with potential tumor-selectivity and antiangiogenic and vascular disrupting features.
Subject(s)
Antineoplastic Agents , Tubulin , Antineoplastic Agents/chemistry , Cell Line, Tumor , Cell Proliferation , Colchicine/metabolism , Drug Screening Assays, Antitumor , Microtubules , Molecular Structure , Structure-Activity Relationship , Tubulin/metabolism , Tubulin Modulators/chemistryABSTRACT
PURPOSE: HER2 mutations (HER2mut) induce endocrine resistance in estrogen receptor-positive (ER+) breast cancer. PATIENTS AND METHODS: In this single-arm multi-cohort phase II trial, we evaluated the efficacy of neratinib plus fulvestrant in patients with ER+/HER2mut, HER2 non-amplified metastatic breast cancer (MBC) in the fulvestrant-treated (n = 24) or fulvestrant-naïve cohort (n = 11). Patients with ER-negative (ER-)/HER2mut MBC received neratinib monotherapy in an exploratory ER- cohort (n = 5). RESULTS: The clinical benefit rate [CBR (95% confidence interval)] was 38% (18%-62%), 30% (7%-65%), and 25% (1%-81%) in the fulvestrant-treated, fulvestrant-naïve, and ER- cohorts, respectively. Adding trastuzumab at progression in 5 patients resulted in three partial responses and one stable disease ≥24 weeks. CBR appeared positively associated with lobular histology and negatively associated with HER2 L755 alterations. Acquired HER2mut were detected in 5 of 23 patients at progression. CONCLUSIONS: Neratinib and fulvestrant are active for ER+/HER2mut MBC. Our data support further evaluation of dual HER2 blockade for the treatment of HER2mut MBC.
Subject(s)
Breast Neoplasms , Antineoplastic Combined Chemotherapy Protocols/adverse effects , Breast Neoplasms/drug therapy , Breast Neoplasms/genetics , Breast Neoplasms/pathology , Female , Fulvestrant , Humans , Quinolines , Receptor, ErbB-2/genetics , Receptor, ErbB-2/therapeutic useABSTRACT
BACKGROUND: Uterine leiomyomas, commonly known as fibroids, are benign tumors in postmenarchal females. By the age of 35 years, approximately 30% of females will have fibroids, and by the age of 50 years, the prevalence approaches 70% with some studies reporting >85% prevalence in African American females. Previous studies evaluating the prevalence of fibroids have largely relied on self-reported fibroid diagnoses, which could have falsely underestimated prevalence because many females with fibroids are asymptomatic. Despite known differences in fibroid prevalence by race, there are very limited data on fibroid prevalence by ethnicity. The Latino population is the largest ethnic minority in the United States, yet there is no large study that utilizes ultrasound to confirm the presence of fibroids in Latina/Latinx females. In addition, fibroids have been associated with obesity and with diabetes mellitus, but the data have been inconsistent and at times conflicting. OBJECTIVE: The Environment, Leiomyomas, Latinas, and Adiposity Study was designed to quantify the prevalence of uterine fibroids among Latina/Latinx females and understand the relationships between obesity, glucose dysregulation, and fibroid prevalence and growth. This article presents the study's design and reports early enrollment data. STUDY DESIGN: The Environment, Leiomyomas, Latinas, and Adiposity Study is a 5-year longitudinal cohort study based in Southeast Michigan with the goal of recruiting 600 Latina/Latinx females between the ages of 21 and 50 years. Given the recruitment goals, developing a respectful, transparent, and trusting relationship between the study investigators and the community was a major priority. Thus, a community-engaged research approach was utilized in the design of the Environment, Leiomyomas, Latinas, and Adiposity Study. A community advisory board containing community leaders, largely from the Latinx community, provided input and direction during the entirety of the Environment, Leiomyomas, Latinas, and Adiposity Study design and rollout process. A minimum of 3 visits (orientation and consent, baseline, follow-up) will be conducted for each participant, with baseline and follow-up visits approximately 18 to 30 months apart. At each visit, interviewer and self-administered surveys will assess sociodemographic factors, health behaviors, health history, and social determinants of health. In addition, participants undergo a pelvic ultrasound examination and biologic samples are collected. RESULTS: Using community-engaged approaches, we have successfully enrolled 633 Latina/Latinx females. The mean participant age is 37.5±7.04 years. The mean body mass index is 30.0±6.54 kg/m2. First study visits have been initiated. CONCLUSION: The objective of the Environment, Leiomyomas, Latinas, and Adiposity Study is to address the knowledge gap regarding uterine fibroids in the Latina/Latinx population. The Environment, Leiomyomas, Latinas, and Adiposity Study will generate ultrasound-confirmed evidence of the prevalence and growth patterns of uterine fibroids in this specific population while also examining the associations between obesity and laboratory-confirmed glucose dysregulation with uterine fibroid prevalence and growth patterns.
Subject(s)
Leiomyoma , Uterine Neoplasms , Adiposity , Adult , Ethnicity , Female , Hispanic or Latino , Humans , Leiomyoma/epidemiology , Longitudinal Studies , Middle Aged , Minority Groups , Obesity/epidemiology , Uterine Neoplasms/epidemiology , Young AdultABSTRACT
PURPOSE: Neratinib, an irreversible pan-HER tyrosine kinase inhibitor, has demonstrated systemic efficacy and intracranial activity in various stages of HER2+breast cancer. NALA was a phase III randomized trial that assessed the efficacy and safety of neratinib+capecitabine (N+C) against lapatinib+capecitabine (L+C) in HER2+ metastatic breast cancer (mBC) patients who had received ≥ 2 HER2-directed regimens. Descriptive analysis results of the Asian subgroup in the NALA study are reported herein. METHODS: 621 centrally assessed HER2+ mBC patients were enrolled, 202 of whom were Asian. Those with stable, asymptomatic brain metastases (BM) were eligible for study entry. Patients were randomized 1:1 to N (240 mg qd) + C (750 mg/m2 bid, day 1-14) with loperamide prophylaxis or to L (1250 mg qd) + C (1000 mg/m2 bid, day 1-14) in 21-day cycles. Co-primary endpoints were centrally assessed progression-free survival (PFS) and overall survival (OS). Secondary endpoints included time to intervention for central nervous system (CNS) disease, objective response rate, duration of response (DoR), clinical benefit rate, and safety. RESULTS: 104 and 98 Asian patients were randomly assigned to receive N+C or L+C, respectively. Median PFS of N+C and L+C was 7.0 and 5.4 months (P = 0.0011), respectively. Overall cumulative incidence of intervention for CNS disease was lower with N+C (27.9 versus 33.8%; P = 0.039). Both median OS (23.8 versus 18.7 months; P = 0.185) and DoR (11.1 versus 4.2 months; P < 0.0001) were extended with N+C, compared to L+C. The incidences of grade 3/4 treatment emergent adverse events (TEAEs) and TEAEs leading to treatment discontinuation were mostly comparable between the two arms. Diarrhea and palmar-plantar erythrodysesthesia were the most frequent TEAEs in both arms, similar to the overall population in incidence and severity. CONCLUSION: Consistent with the efficacy profile observed in the overall study population, Asian patients with HER2+ mBC, who had received ≥ 2 HER2-directed regimens, may also benefit from N+C. No new safety signals were noted. CLINICAL TRIAL REGISTRATION: NCT01808573.
Subject(s)
Breast Neoplasms , Antineoplastic Combined Chemotherapy Protocols/adverse effects , Breast Neoplasms/drug therapy , Breast Neoplasms/genetics , Capecitabine/therapeutic use , Female , Humans , Lapatinib/therapeutic use , Quinolines , Receptor, ErbB-2/genetics , Treatment OutcomeABSTRACT
PURPOSE: Neratinib plus capecitabine (N+C) demonstrated significant progression-free survival (PFS) benefit in NALA (NCT01808573), a randomized phase III trial comparing N+C with lapatinib + capecitabine (L+C) in 621 patients with HER2-positive (HER2+) metastatic breast cancer (MBC) who had received ≥2 prior HER2-directed regimens in the metastatic setting. We evaluated correlations between exploratory biomarkers and PFS. PATIENTS AND METHODS: Somatic mutations were evaluated by next-generation sequencing on primary or metastatic samples. HER2 protein expression was evaluated by central IHC, H-score, and VeraTag/HERmark. p95 expression (truncated HER2) was measured by VeraTag. HRs were estimated using unstratified Cox proportional hazards models. RESULTS: Four hundred and twenty samples had successful sequencing: 34.0% had PIK3CA mutations and 5.5% had HER2 (ERBB2) mutations. In the combined patient populations, PIK3CA mutations trended toward shorter PFS [wild-type vs. mutant, HR = 0.81; 95% confidence interval (CI), 0.64-1.03], whereas HER2 mutations trended toward longer PFS [HR = 1.69 (95% CI, 0.97-3.29)]. Higher HER2 protein expression was associated with longer PFS [IHC 3+ vs. 2+, HR = 0.67 (0.54-0.82); H-score ≥240 versus <240, HR = 0.77 (0.63-0.93); HERmark positive vs. negative, HR = 0.76 (0.59-0.98)]. Patients whose tumors had higher HER2 protein expression (any method) derived an increased benefit from N+C compared with L+C [IHC 3+, HR = 0.64 (0.51-0.81); H-score ≥ 240, HR = 0.54 (0.41-0.72); HERmark positive, HR = 0.65 (0.50-0.84)], as did patients with high p95 [p95 ≥2.8 relative fluorescence (RF)/mm2, HR = 0.66 (0.50-0.86) vs. p95 < 2.8 RF/mm2, HR = 0.91 (0.61-1.36)]. CONCLUSIONS: PIK3CA mutations were associated with shorter PFS whereas higher HER2 expression was associated with longer PFS. Higher HER2 protein expression was also associated with a greater benefit for N+C compared with L+C.