Discovery and Optimization of Potent, Efficacious and Selective Inhibitors Targeting EGFR Exon20 Insertion Mutations.

Herein, we report the identification and optimization of a series of potent inhibitors of EGFR Exon20 insertions with significant selectivity over wild-type EGFR. A strategically designed HTS campaign, multiple iterations of structure-based drug design (SBDD), and tactical linker replacement led to a potent and wild-type selective series of molecules and ultimately the discovery of 36. Compound 36 is a potent and selective inhibitor of EGFR Exon20 insertions and has demonstrated encouraging efficacy in NSCLC EGFR CRISPR-engineered H2073 xenografts that carry an SVD Exon20 insertion and reduced efficacy in a H2073 wild-type EGFR xenograft model compared to CLN-081 (5), indicating that 36 may have lower EGFR wild-type associated toxicity.

Targeting Cytotoxic Agents through EGFR-Mediated Covalent Binding and Release.

A major drawback of cytotoxic chemotherapy is the lack of selectivity toward noncancerous cells. The targeted delivery of cytotoxic drugs to tumor cells is a longstanding goal in cancer research. We proposed that covalent inhibitors could be adapted to deliver cytotoxic agents, conjugated to the ß-position of the Michael acceptor, via an addition-elimination mechanism promoted by covalent binding. Studies on model systems showed that conjugated 5-fluorouracil (5FU) could be released upon thiol addition in relevant time scales. A series of covalent epidermal growth factor receptor (EGFR) inhibitors were synthesized as their 5FU derivatives. Achieving the desired release of 5FU was demonstrated to depend on the electronics and geometry of the compounds. Mass spectrometry and NMR studies demonstrated an anilinoquinazoline acrylate ester conjugate bound to EGFR with the release of 5FU. This work establishes that acrylates can be used to release conjugated molecules upon covalent binding to proteins and could be used to develop targeted therapeutics.

Spatial predictions of tree density and tree height across Mexico forests using ensemble learning and forest inventory data.

The National Forestry Commission of Mexico continuously monitors forest structure within the country's continental territory by the implementation of the National Forest and Soils Inventory (INFyS). Due to the challenges involved in collecting data exclusively from field surveys, there are spatial information gaps for important forest attributes. This can produce bias or increase uncertainty when generating estimates required to support forest management decisions. Our objective is to predict the spatial distribution of tree height and tree density in all Mexican forests. We performed wall-to-wall spatial predictions of both attributes in 1-km grids, using ensemble machine learning across each forest type in Mexico. Predictor variables include remote sensing imagery and other geospatial data (e.g., mean precipitation, surface temperature, canopy cover). Training data is from the 2009 to 2014 cycle (n > 26,000 sampling plots). Spatial cross validation suggested that the model had a better performance when predicting tree height r 2 = .35 [.12, .51] (mean [min, max]) than for tree density r 2 = .23 [.05, .42]. The best predictive performance when mapping tree height was for broadleaf and coniferous-broadleaf forests (model explained ~50% of variance). The best predictive performance when mapping tree density was for tropical forest (model explained ~40% of variance). Although most forests had relatively low uncertainty for tree height predictions, e.g., values <60%, arid and semiarid ecosystems had high uncertainty, e.g., values >80%. Uncertainty values for tree density predictions were >80% in most forests. The applied open science approach we present is easily replicable and scalable, thus it is helpful to assist in the decision-making and future of the National Forest and Soils Inventory. This work highlights the need for analytical tools that help us exploit the full potential of the Mexican forest inventory datasets.

Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling.

Forest carbon is a large and uncertain component of the global carbon cycle. An important source of complexity is the spatial heterogeneity of vegetation vertical structure and extent, which results from variations in climate, soils, and disturbances and influences both contemporary carbon stocks and fluxes. Recent advances in remote sensing and ecosystem modeling have the potential to significantly improve the characterization of vegetation structure and its resulting influence on carbon. Here, we used novel remote sensing observations of tree canopy height collected by two NASA spaceborne lidar missions, Global Ecosystem Dynamics Investigation and ICE, Cloud, and Land Elevation Satellite 2, together with a newly developed global Ecosystem Demography model (v3.0) to characterize the spatial heterogeneity of global forest structure and quantify the corresponding implications for forest carbon stocks and fluxes. Multiple-scale evaluations suggested favorable results relative to other estimates including field inventory, remote sensing-based products, and national statistics. However, this approach utilized several orders of magnitude more data (3.77 billion lidar samples) on vegetation structure than used previously and enabled a qualitative increase in the spatial resolution of model estimates achievable (0.25° to 0.01°). At this resolution, process-based models are now able to capture detailed spatial patterns of forest structure previously unattainable, including patterns of natural and anthropogenic disturbance and recovery. Through the novel integration of new remote sensing data and ecosystem modeling, this study bridges the gap between existing empirically based remote sensing approaches and process-based modeling approaches. This study more generally demonstrates the promising value of spaceborne lidar observations for advancing carbon modeling at a global scale.

Discovery of a Potent and Orally Bioavailable Zwitterionic Series of Selective Estrogen Receptor Degrader-Antagonists.

Herein, we report the optimization of a meta-substituted series of selective estrogen receptor degrader (SERD) antagonists for the treatment of ER+ breast cancer. Structure-based design together with the use of modeling and NMR to favor the bioactive conformation led to a highly potent series of basic SERDs with promising physicochemical properties. Issues with hERG activity resulted in a strategy of zwitterion formation and ultimately in the identification of 38. This compound was shown to be a highly potent SERD capable of effectively degrading ERα in both MCF-7 and CAMA-1 cell lines. The low lipophilicity and zwitterionic nature led to a SERD with a clean secondary pharmacology profile and no hERG activity. Favorable physicochemical properties resulted in good oral bioavailability in preclinical species and potent in vivo activity in a mouse xenograft model.

C(sp3)-C(sp3) coupling of non-activated alkyl-iodides with electron-deficient alkenes via visible-light/silane-mediated alkyl-radical formation.

Here, we present a remarkably mild and general initiation protocol for alkyl-radical generation from non-activated alkyl-iodides. An interaction between a silane and an alkyl iodide is excited by irradiation with visible light to trigger carbon-iodide bond homolysis and form the alkyl radical. We show how this method can be developed into an operationally simple and general Giese addition reaction that can tolerate a range of sensitive functionalities not normally explored in established approaches to this strategically important transformation. The new method requires no photocatalyst or other additives and uses only commerical tris(trimethylsilyl)silane and visible light to effectively combine a broad range of alkyl halides with activated alkenes to form C(sp3)-C(sp3) bonds embedded within complex frameworks.

Discovery of a Series of 7-Azaindoles as Potent and Highly Selective CDK9 Inhibitors for Transient Target Engagement.

Optimization of a series of azabenzimidazoles identified from screening hit 2 and the information gained from a co-crystal structure of the azabenzimidazole-based lead 6 bound to CDK9 led to the discovery of azaindoles as highly potent and selective CDK9 inhibitors. With the goal of discovering a highly selective and potent CDK9 inhibitor administrated intravenously that would enable transient target engagement of CDK9 for the treatment of hematological malignancies, further optimization focusing on physicochemical and pharmacokinetic properties led to azaindoles 38 and 39. These compounds are highly potent and selective CDK9 inhibitors having short half-lives in rodents, suitable physical properties for intravenous administration, and the potential to achieve profound but transient inhibition of CDK9 in vivo.

Development of autotaxin inhibitors: A series of tetrazole cinnamides.

A series of inhibitors of Autotaxin (ATX) have been developed from a high throughput screening hit, 1a, which shows an alternative binding mode to known catalytic site inhibitors. Selectivity over the hERG channel and microsomal clearance were dependent on the lipophilicity of the compounds, and this was optimised by reduction of clogD whilst maintaining high affinity ATX inhibition. Compound 15a shows good oral exposure, and concentration dependent inhibition of formation of LPA in vivo, as shown in pharmacokinetic-pharmacodynamic (PK/PD) experiments.

Addition of Fluorine and a Late-Stage Functionalization (LSF) of the Oral SERD AZD9833.

Herein we describe our efforts using a late stage functionalization together with more traditional synthetic approaches to generate fluorinated analogues of the clinical candidate AZD9833. The effects of the addition of fluorine on the lipophilicity, permeability, and metabolism are discussed. Many of these changes were tolerated in terms of pharmacology and resulted in high quality molecules which reached advanced stages of profiling in the testing cascade.

Discovery of AZD9833, a Potent and Orally Bioavailable Selective Estrogen Receptor Degrader and Antagonist.

Herein we report the optimization of a series of tricyclic indazoles as selective estrogen receptor degraders (SERD) and antagonists for the treatment of ER+ breast cancer. Structure based design together with systematic investigation of each region of the molecular architecture led to the identification of N-[1-(3-fluoropropyl)azetidin-3-yl]-6-[(6S,8R)-8-methyl-7-(2,2,2-trifluoroethyl)-6,7,8,9-tetrahydro-3H-pyrazolo[4,3-f]isoquinolin-6-yl]pyridin-3-amine (28). This compound was demonstrated to be a highly potent SERD that showed a pharmacological profile comparable to fulvestrant in its ability to degrade ERα in both MCF-7 and CAMA-1 cell lines. A stringent control of lipophilicity ensured that 28 had favorable physicochemical and preclinical pharmacokinetic properties for oral administration. This, combined with demonstration of potent in vivo activity in mouse xenograft models, resulted in progression of this compound, also known as AZD9833, into clinical trials.

Sustained Progression-Free Survival Benefit of Rituximab Maintenance in Patients With Follicular Lymphoma: Long-Term Results of the PRIMA Study.

PURPOSE: The PRIMA study (ClinicalTrials.gov identifier: NCT00140582) established that 2 years of rituximab maintenance after first-line immunochemotherapy significantly improved progression-free survival (PFS) in patients with follicular lymphoma compared with observation. Here, we report the final PFS and overall survival (OS) results from the PRIMA study after 9 years of follow-up and provide a final overview of safety. METHODS: Patients (> 18 years of age) with previously untreated high-tumor-burden follicular lymphoma were nonrandomly assigned to receive one of three immunochemotherapy induction regimens. Responding patients were randomly assigned (stratified by induction regimen, response to induction treatment, treatment center, and geographic region) 1:1 to receive 2 years of rituximab maintenance (375 mg/m2, once every 8 weeks), starting 8 weeks after the last induction treatment, or observation (no additional treatment). All patients in the extended follow-up provided their written informed consent (data cutoff: December 31, 2016). RESULTS: In total, 1,018 patients completed induction treatment and were randomly assigned to rituximab maintenance (n = 505) or observation (n = 513). Consent for the extended follow-up was provided by 607 patients (59.6%) of 1,018 (rituximab maintenance, n = 309; observation, n = 298). After data cutoff, median PFS was 10.5 years in the rituximab maintenance arm compared with 4.1 years in the observation arm (hazard ratio, 0.61; 95% CI, 0.52 to 0.73; P < .001). No OS difference was seen in patients randomly assigned to rituximab maintenance or observation (hazard ratio, 1.04; 95% CI, 0.77 to 1.40; P = .7948); 10-year OS estimates were approximately 80% in both study arms. No new safety signals were observed. CONCLUSION: Rituximab maintenance after induction immunochemotherapy provides a significant long-term PFS, but not OS, benefit over observation.

The Laser Vegetation Detecting Sensor: A Full Waveform, Large-Footprint, Airborne Laser Altimeter for Monitoring Forest Resources.

The use of satellite-borne large-footprint LiDAR (light detection and ranging) systems allows for the acquisition of forest monitoring data. This paper mainly describes the design, use, operating principles, installation and data properties of the new Laser Vegetation Detecting Sensor (LVDS), a LiDAR system designed and developed at the Academy of Forest Inventory and Planning (AFIP) and the Beijing Institute of Telemetry (BIT). Data from LVDS were used to calculate the mean height of forest trees on sample plots using data collected in the Hunan province of China. The results show that the full waveform data obtained by LVDS has the ability to accurately characterize forest height. The mean absolute percentage error of mean forest height per plot in flat areas was 6.8%, with a mean absolute deviation of 0.78 m. The airborne LVDS system provides prototype data sets and a platform for instrument proof-of-concept studies for China's Terrestrial Ecosystem Carbon Monitoring (TECM) mission, which is an Earth remote sensing satellite due for launch in 2020. The information produced by LVDS allows for forest structure studies with high accuracy and coverage of large areas.

Tricyclic Indazoles-A Novel Class of Selective Estrogen Receptor Degrader Antagonists.

Herein, we report the identification and synthesis of a series of tricyclic indazoles as a novel class of selective estrogen receptor degrader antagonists. Replacement of a phenol, present in our previously reported tetrahydroisoquinoline scaffold, with an indazole group led to the removal of a reactive metabolite signal in an in vitro glutathione trapping assay. Further optimization, guided by X-ray crystal structures and NMR conformational work, varied the alkyl side chain and pendant aryl group and resulted in compounds with low turnover in human hepatocytes and enhanced chemical stability. Compound 9 was profiled as a representative of the series in terms of pharmacology and demonstrated the desired estrogen receptor α degrader-antagonist profile and demonstrated activity in a xenograft model of breast cancer.

Synthesis of a Novel Type of 2,3'-BIMs via Platinum-Catalysed Reaction of Indolylallenes with Indoles.

Optimisation, scope and mechanism of the platinum-catalysed addition of indoles to indolylallenes is reported here to give 2,3'-BIMs with a novel core structure very relevant for pharmaceutical industry. The reaction is modulated by the electronic properties of the substituents on both indoles, with the 2,3'-BIMs favoured when electron donating groups are present. Although simple at first, a complex mechanism has been uncovered that explains the different behaviour of these systems with platinum when compared with other metals (e.g. gold). Detailed labelling studies have shown Pt-catalysed 6-endo-trig cyclisation of the indollylallene as the first step of the reaction and the involvement of two cyclic vinyl-platinum intermediates in equilibrium through a platinum carbene, as the key intermediates of the catalytic cycle towards the second nucleophilic attack and formation of the BIMs.

Precision and cost considerations for two-stage sampling in a panelized forest inventory design.

Due to the relatively high cost of measuring sample plots in forest inventories, considerable attention is given to sampling and plot designs during the forest inventory planning phase. A two-stage design can be efficient from a field work perspective as spatially proximate plots are grouped into work zones. A comparison between subsampling with units of unequal size (SUUS) and a simple random sample (SRS) design in a panelized framework assessed the statistical and economic implications of using the SUUS design for a case study in the Northeastern USA. The sampling errors for estimates of forest land area and biomass were approximately 1.5-2.2 times larger with SUUS prior to completion of the inventory cycle. Considerable sampling error reductions were realized by using the zones within a post-stratified sampling paradigm; however, post-stratification of plots in the SRS design always provided smaller sampling errors in comparison. Cost differences between the two designs indicated the SUUS design could reduce the field work expense by 2-7 %. The results also suggest the SUUS design may provide substantial economic advantage for tropical forest inventories, where remote areas, poor access, and lower wages are typically encountered.

Integrating LIDAR and forest inventories to fill the trees outside forests data gap.

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all "nonforest" Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6%, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47% increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.

Avoiding treatment bias of REDD+ monitoring by sampling with partial replacement.

BACKGROUND: Implementing REDD+ renders the development of a measurement, reporting and verification (MRV) system necessary to monitor carbon stock changes. MRV systems generally apply a combination of remote sensing techniques and in-situ field assessments. In-situ assessments can be based on 1) permanent plots, which are assessed on all successive occasions, 2) temporary plots, which are assessed only once, and 3) a combination of both. The current study focuses on in-situ assessments and addresses the effect of treatment bias, which is introduced by managing permanent sampling plots differently than the surrounding forests. Temporary plots are not subject to treatment bias, but are associated with large sampling errors and low cost-efficiency. Sampling with partial replacement (SPR) utilizes both permanent and temporary plots. RESULTS: We apply a scenario analysis with different intensities of deforestation and forest degradation to show that SPR combines cost-efficiency with the handling of treatment bias. Without treatment bias permanent plots generally provide lower sampling errors for change estimates than SPR and temporary plots, but do not provide reliable estimates, if treatment bias occurs, SPR allows for change estimates that are comparable to those provided by permanent plots, offers the flexibility to adjust sample sizes in the course of time, and allows to compare data on permanent versus temporary plots for detecting treatment bias. Equivalence of biomass or carbon stock estimates between permanent and temporary plots serves as an indication for the absence of treatment bias while differences suggest that there is evidence for treatment bias. CONCLUSIONS: SPR is a flexible tool for estimating emission factors from successive measurements. It does not entirely depend on sample plots that are installed at the first occasion but allows for the adjustment of sample sizes and placement of new plots at any occasion. This ensures that in-situ samples provide representative estimates over time. SPR offers the possibility to increase sampling intensity in areas with high degradation intensities or to establish new plots in areas where permanent plots are lost due to deforestation. SPR is also an ideal approach to mitigate concerns about treatment bias.

Results of a trial of PET-directed therapy for early-stage Hodgkin's lymphoma.

BACKGROUND: It is unclear whether patients with early-stage Hodgkin's lymphoma and negative findings on positron-emission tomography (PET) after three cycles of chemotherapy with doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) require radiotherapy. METHODS: Patients with newly diagnosed stage IA or stage IIA Hodgkin's lymphoma received three cycles of ABVD and then underwent PET scanning. Patients with negative PET findings were randomly assigned to receive involved-field radiotherapy or no further treatment; patients with positive PET findings received a fourth cycle of ABVD and radiotherapy. This trial assessing the noninferiority of no further treatment was designed to exclude a difference in the 3-year progression-free survival rate of 7 or more percentage points from the assumed 95% progression-free survival rate in the radiotherapy group. RESULTS: A total of 602 patients (53.3% male; median age, 34 years) were recruited, and 571 patients underwent PET scanning. The PET findings were negative in 426 of these patients (74.6%), 420 of whom were randomly assigned to a study group (209 to the radiotherapy group and 211 to no further therapy). At a median of 60 months of follow-up, there had been 8 instances of disease progression in the radiotherapy group, and 8 patients had died (3 with disease progression, 1 of whom died from Hodgkin's lymphoma); there had been 20 instances of disease progression in the group with no further therapy, and 4 patients had died (2 with disease progression and none from Hodgkin's lymphoma). In the radiotherapy group, 5 of the deaths occurred in patients who received no radiotherapy. The 3-year progression-free survival rate was 94.6% (95% confidence interval [CI], 91.5 to 97.7) in the radiotherapy group and 90.8% (95% CI, 86.9 to 94.8) in the group that received no further therapy, with an absolute risk difference of -3.8 percentage points (95% CI, -8.8 to 1.3). CONCLUSIONS: The results of this study did not show the noninferiority of the strategy of no further treatment after chemotherapy with regard to progression-free survival. Nevertheless, patients in this study with early-stage Hodgkin's lymphoma and negative PET findings after three cycles of ABVD had a very good prognosis either with or without consolidation radiotherapy. (Funded by Leukaemia and Lymphoma Research and others; RAPID ClinicalTrials.gov number, NCT00943423.).

Risk of premature menopause after treatment for Hodgkin's lymphoma.

BACKGROUND: Modern treatment of Hodgkin's lymphoma (HL) has transformed its prognosis but causes late effects, including premature menopause. Cohort studies of premature menopause risks after treatment have been relatively small, and knowledge about these risks is limited. METHODS: Nonsurgical menopause risk was analyzed in 2127 women treated for HL in England and Wales at ages younger than 36 years from 1960 through 2004 and followed to 2003 through 2012. Risks were estimated using Cox regression, modified Poisson regression, and competing risks. All statistical tests were two-sided. RESULTS: During follow-up, 605 patients underwent nonsurgical menopause before age 40 years. Risk of premature menopause increased more than 20-fold after ovarian radiotherapy, alkylating chemotherapy other than dacarbazine, or BEAM (bis-chloroethylnitrosourea [BCNU], etoposide, cytarabine, melphalan) chemotherapy for stem cell transplantation, but was not statistically significantly raised after adriamycin, bleomycin, vinblastine, dacarbazine (ABVD). Menopause generally occurred sooner after ovarian radiotherapy (62.5% within five years of ≥5 Gy treatment) and BEAM (50.9% within five years) than after alkylating chemotherapy (24.2% within five years of ≥6 cycles), and after treatment at older than at younger ages. Cumulative risk of menopause by age 40 years was 81.3% after greater than or equal to 5Gy ovarian radiotherapy, 75.3% after BEAM, 49.1% after greater than or equal to 6 cycles alkylating chemotherapy, 1.4% after ABVD, and 3.0% after solely supradiaphragmatic radiotherapy. Tables of individualized risk information for patients by future period, treatment type, dose and age are provided. CONCLUSIONS: Patients treated with HL need to plan intended pregnancies using personalized information on their risk of menopause by different future time points.