A saturation mutagenesis screen uncovers resistant and sensitizing secondary KRAS mutations to clinical KRASG12C inhibitors.

Mutant-specific inhibitors of KRASG12C, such as AMG510 (sotorasib) and MRTX849 (adagrasib), offer the unprecedented opportunity to inhibit KRAS, the most frequently mutated and heretofore undruggable oncoprotein. While clinical data are still limited, on-target mutations in KRASG12C at position 12 and other sites are emerging as major drivers of clinical relapse. We identified additional mutations in KRASG12C that impact inhibitor sensitivity through a saturation mutagenesis screen in the KRASG12C NCI-H358 non­small-cell lung cancer (NSCLC) cell line. We also identified individuals in population genetic databases harboring these resistance mutations in their germline and in tumors, including a subset that co-occur with KRASG12C, indicating that these mutations may preexist in patients treated with KRASG12C inhibitors. Notably, through structural modeling, we found that one such mutation (R68L) interferes with the critical protein­drug interface, conferring resistance to both inhibitors. Finally, we uncovered a mutant (S17E) that demonstrated a strong sensitizing phenotype to both inhibitors. Functional studies suggest that S17E sensitizes KRASG12C cells to KRASG12C inhibition by impacting signaling through PI3K/AKT/mTOR but not the MAPK signaling pathway. Our studies highlight the utility of unbiased mutation profiling to understand the functional consequences of all variants of a disease-causing genetic mutant and predict acquired resistant mutations in the targeted therapeutics.

Neuroconductor: an R platform for medical imaging analysis.

Neuroconductor (https://neuroconductor.org) is an open-source platform for rapid testing and dissemination of reproducible computational imaging software. The goals of the project are to: (i) provide a centralized repository of R software dedicated to image analysis, (ii) disseminate software updates quickly, (iii) train a large, diverse community of scientists using detailed tutorials and short courses, (iv) increase software quality via automatic and manual quality controls, and (v) promote reproducibility of image data analysis. Based on the programming language R (https://www.r-project.org/), Neuroconductor starts with 51 inter-operable packages that cover multiple areas of imaging including visualization, data processing and storage, and statistical inference. Neuroconductor accepts new R package submissions, which are subject to a formal review and continuous automated testing. We provide a description of the purpose of Neuroconductor and the user and developer experience.

Harmonization of cortical thickness measurements across scanners and sites.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as "scanner effects", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.

Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi.

Summary: The minfi package is widely used for analyzing Illumina DNA methylation array data. Here we describe modifications to the minfi package required to support the HumanMethylationEPIC ('EPIC') array from Illumina. We discuss methods for the joint analysis and normalization of data from the HumanMethylation450 ('450k') and EPIC platforms. We introduce the single-sample Noob ( ssNoob ) method, a normalization procedure suitable for incremental preprocessing of individual methylation arrays and conclude that this method should be used when integrating data from multiple generations of Infinium methylation arrays. We show how to use reference 450k datasets to estimate cell type composition of samples on EPIC arrays. The cumulative effect of these updates is to ensure that minfi provides the tools to best integrate existing and forthcoming Illumina methylation array data. Availability and Implementation: The minfi package version 1.19.12 or higher is available for all platforms from the Bioconductor project. Contact: khansen@jhsph.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Harmonization of multi-site diffusion tensor imaging data.

Diffusion tensor imaging (DTI) is a well-established magnetic resonance imaging (MRI) technique used for studying microstructural changes in the white matter. As with many other imaging modalities, DTI images suffer from technical between-scanner variation that hinders comparisons of images across imaging sites, scanners and over time. Using fractional anisotropy (FA) and mean diffusivity (MD) maps of 205 healthy participants acquired on two different scanners, we show that the DTI measurements are highly site-specific, highlighting the need of correcting for site effects before performing downstream statistical analyses. We first show evidence that combining DTI data from multiple sites, without harmonization, may be counter-productive and negatively impacts the inference. Then, we propose and compare several harmonization approaches for DTI data, and show that ComBat, a popular batch-effect correction tool used in genomics, performs best at modeling and removing the unwanted inter-site variability in FA and MD maps. Using age as a biological phenotype of interest, we show that ComBat both preserves biological variability and removes the unwanted variation introduced by site. Finally, we assess the different harmonization methods in the presence of different levels of confounding between site and age, in addition to test robustness to small sample size studies.

funtooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types.

MOTIVATION: DNA methylation patterns are well known to vary substantially across cell types or tissues. Hence, existing normalization methods may not be optimal if they do not take this into account. We therefore present a new R package for normalization of data from the Illumina Infinium Human Methylation450 BeadChip (Illumina 450 K) built on the concepts in the recently published funNorm method, and introducing cell-type or tissue-type flexibility. RESULTS: funtooNorm is relevant for data sets containing samples from two or more cell or tissue types. A visual display of cross-validated errors informs the choice of the optimal number of components in the normalization. Benefits of cell (tissue)-specific normalization are demonstrated in three data sets. Improvement can be substantial; it is strikingly better on chromosome X, where methylation patterns have unique inter-tissue variability. AVAILABILITY AND IMPLEMENTATION: An R package is available at https://github.com/GreenwoodLab/funtooNorm, and has been submitted to Bioconductor at http://bioconductor.org.

Removing inter-subject technical variability in magnetic resonance imaging studies.

Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect, and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, 2008, Gagnon-Bartsch and Speed, 2012], two batch effect correction tools largely used in genomics, we decompose the voxel intensities of images registered to a template into a biological component and an unwanted variation component. The unwanted variation component is estimated from a control region obtained from the cerebrospinal fluid (CSF), where intensities are known to be unassociated with disease status and other clinical covariates. We perform a singular value decomposition (SVD) of the control voxels to estimate factors of unwanted variation. We then estimate the unwanted factors using linear regression for every voxel of the brain and take the residuals as the RAVEL-corrected intensities. We assess the performance of RAVEL using T1-weighted (T1-w) images from more than 900 subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI), as well as healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compare RAVEL to two intensity-normalization-only methods: histogram matching and White Stripe. We show that RAVEL performs best at improving the replicability of the brain regions that are empirically found to be most associated with AD, and that these regions are significantly more present in structures impacted by AD (hippocampus, amygdala, parahippocampal gyrus, enthorinal area, and fornix stria terminals). In addition, we show that the RAVEL-corrected intensities have the best performance in distinguishing between MCI subjects and healthy subjects using the mean hippocampal intensity (AUC=67%), a marked improvement compared to results from intensity normalization alone (AUC=63% and 59% for histogram matching and White Stripe, respectively). RAVEL is promising for many other imaging modalities.

A potentiator of orthosteric ligand activity at GLP-1R acts via covalent modification.

We report that 4-(3-(benzyloxy)phenyl)-2-ethylsulfinyl-6-(trifluoromethyl)pyrimidine (BETP), which behaves as a positive allosteric modulator at the glucagon-like peptide-1 receptor (GLP-1R), covalently modifies cysteines 347 and 438 in GLP-1R. C347, located in intracellular loop 3 of GLP-1R, is critical to the activity of BETP and a structurally distinct GLP-1R ago-allosteric modulator, N-(tert-butyl)-6,7-dichloro-3-(methylsulfonyl)quinoxalin-2-amine. We further show that substitution of cysteine for phenylalanine 345 in the glucagon receptor is sufficient to confer sensitivity to BETP.

Cell-tethered ligands modulate bone remodeling by osteoblasts and osteoclasts.

The goals of the present study are to establish an in vitro co-culture model of osteoblast and osteoclast function and to quantify the resulting bone remodeling. The bone is tissue engineered using well-defined silk protein biomaterials in 2D and 3D formats in combination with human cells expressing tethered agonists for selected G protein-coupled receptors (GPCRs). The tethered constructs are introduced with the objective of triggering sustained and localized GPCR signaling. The cell-modified biomaterial surfaces are reconstructed from SEM images into 3D models using image processing for quantitative measurement of surface characteristics. Parathyroid hormone (PTH) and glucose-dependent insulinotropic peptide (GIP) are selected because of their roles in bone remodeling for expression in tethered format on bone marrow derived human mesenchymal stem cells (hMSCs). Increased calcium deposition and increased surface roughness are found in 3D digital surface models constructed from SEM images of silk protein films remodeled by the co-cultures containing the tethered PTH, and decreased surface roughness is found for the films remodeled by the tethered GIP co-cultures. Increased surface roughness is not found in monocultures of hMSCs expressing tethered PTH, suggesting that osteoclast-osteoblast interactions in the presence of PTH signaling are responsible for the increased mineralization. These data point towards the design of in vitro bone models in which osteoblast-osteoclast interactions are mimicked for a better understanding of bone remodeling.

Accelerated drug-resistant variant discovery with an enhanced, scalable mutagenic base editor platform.

Personalized cancer therapeutics bring directed treatment options to patients based on their tumor's genetic signature. Unfortunately, tumor genomes are remarkably adaptable, and acquired resistance through gene mutation frequently occurs. Identifying mutations that promote resistance within drug-treated patient populations can be cost, resource, and time intensive. Accordingly, base editing, enabled by Cas9-deaminase domain fusions, has emerged as a promising approach for rapid, large-scale gene variant screening in situ. Here, we adapt and optimize a conditional activation-induced cytidine deaminase (AID)-dead Cas9 (dCas9) system, which demonstrates greater heterogeneity of edits with an expanded footprint compared to the most commonly utilized cytosine base editor, BE4. In combination with a custom single guide RNA (sgRNA) library, we identify individual and compound variants in epidermal growth factor receptor (EGFR) and v-raf murine sarcoma viral oncogene homolog B1 (BRAF) that confer resistance to established EGFR inhibitors. This system and analytical pipeline provide a simple, highly scalable platform for cis or trans drug-modifying variant discovery and for uncovering valuable insights into protein structure-function relationships.

CRISPR activation screens identify the SWI/SNF ATPases as suppressors of ferroptosis.

Ferroptosis is an iron-dependent cell death mechanism characterized by the accumulation of toxic lipid peroxides and cell membrane rupture. GPX4 (glutathione peroxidase 4) prevents ferroptosis by reducing these lipid peroxides into lipid alcohols. Ferroptosis induction by GPX4 inhibition has emerged as a vulnerability of cancer cells, highlighting the need to identify ferroptosis regulators that may be exploited therapeutically. Through genome-wide CRISPR activation screens, we identify the SWI/SNF (switch/sucrose non-fermentable) ATPases BRM (SMARCA2) and BRG1 (SMARCA4) as ferroptosis suppressors. Mechanistically, they bind to and increase chromatin accessibility at NRF2 target loci, thus boosting NRF2 transcriptional output to counter lipid peroxidation and confer resistance to GPX4 inhibition. We further demonstrate that the BRM/BRG1 ferroptosis connection can be leveraged to enhance the paralog dependency of BRG1 mutant cancer cells on BRM. Our data reveal ferroptosis induction as a potential avenue for broadening the efficacy of BRM degraders/inhibitors and define a specific genetic context for exploiting GPX4 dependency.

Membrane tethered bursicon constructs as heterodimeric modulators of the Drosophila G protein-coupled receptor rickets.

The study of complex heterodimeric peptide ligands has been hampered by a paucity of pharmacological tools. To facilitate such investigations, we have explored the utility of membrane tethered ligands (MTLs). Feasibility of this recombinant approach was explored with a focus on Drosophila bursicon, a heterodimeric cystine-knot protein that activates the G protein-coupled receptor rickets (rk). Rk/bursicon signaling is an evolutionarily conserved pathway in insects required for wing expansion, cuticle hardening, and melanization during development. We initially engineered two distinct MTL constructs, each composed of a type II transmembrane domain, a peptide linker, and a C terminal extracellular ligand that corresponded to either the α or ß bursicon subunit. Coexpression of the two complementary bursicon MTLs triggered rk-mediated signaling in vitro. We were then able to generate functionally active bursicon MTLs in which the two subunits were fused into a single heterodimeric peptide, oriented as either α-ß or ß-α. Carboxy-terminal deletion of 32 amino acids in the ß-α MTL construct resulted in loss of agonist activity. Coexpression of this construct with rk inhibited receptor-mediated signaling by soluble bursicon. We have thus generated membrane-anchored bursicon constructs that can activate or inhibit rk signaling. These probes can be used in future studies to explore the tissue and/or developmental stage-dependent effects of bursicon in the genetically tractable Drosophila model organism. In addition, our success in generating functionally diverse bursicon MTLs offers promise that such technology can be broadly applied to other complex ligands, including the family of mammalian cystine-knot proteins.

Demonstration of the innate electrophilicity of 4-(3-(benzyloxy)phenyl)-2-(ethylsulfinyl)-6-(trifluoromethyl)pyrimidine (BETP), a small-molecule positive allosteric modulator of the glucagon-like peptide-1 receptor.

4-(3-(Benzyloxy)phenyl)-2-(ethylsulfinyl)-6-(trifluoromethyl)pyrimidine (BETP) represents a novel small-molecule activator of the glucagon-like peptide-1 receptor (GLP-1R), and exhibits glucose-dependent insulin secretion in rats following i.v. (but not oral) administration. To explore the quantitative pharmacology associated with GLP-1R agonism in preclinical species, the in vivo pharmacokinetics of BETP were examined in rats after i.v. and oral dosing. Failure to detect BETP in circulation after oral administration of a 10-mg/kg dose in rats was consistent with the lack of an insulinotropic effect of orally administered BETP in this species. Likewise, systemic concentrations of BETP in the rat upon i.v. administration (1 mg/kg) were minimal (and sporadic). In vitro incubations in bovine serum albumin, plasma, and liver microsomes from rodents and humans indicated a facile degradation of BETP. Failure to detect metabolites in plasma and liver microsomal incubations in the absence of NADP was suggestive of a covalent interaction between BETP and a protein amino acid residue(s) in these matrices. Incubations of BETP with glutathione (GSH) in buffer revealed a rapid nucleophilic displacement of the ethylsulfoxide functionality by GSH to yield adduct M1, which indicated that BETP was intrinsically electrophilic. The structure of M1 was unambiguously identified by comparison of its chromatographic and mass spectral properties with an authentic standard. The GSH conjugate of BETP was also characterized in NADPH- and GSH-supplemented liver microsomes and in plasma samples from the pharmacokinetic studies. Unlike BETP, M1 was inactive as an allosteric modulator of the GLP-1R.

Chronic UCN2 treatment desensitizes CRHR2 and improves insulin sensitivity.

Urocortin 2 (UCN2) acts as a ligand for the G protein-coupled receptor corticotropin-releasing hormone receptor 2 (CRHR2). UCN2 has been reported to improve or worsen insulin sensitivity and glucose tolerance in vivo. Here we show that acute dosing of UCN2 induces systemic insulin resistance in male mice and skeletal muscle. Inversely, chronic elevation of UCN2 by injection with adenovirus encoding UCN2 resolves metabolic complications, improving glucose tolerance. CRHR2 recruits Gs in response to low concentrations of UCN2, as well as Gi and ß-Arrestin at high concentrations of UCN2. Pre-treating cells and skeletal muscle ex vivo with UCN2 leads to internalization of CRHR2, dampened ligand-dependent increases in cAMP, and blunted reductions in insulin signaling. These results provide mechanistic insights into how UCN2 regulates insulin sensitivity and glucose metabolism in skeletal muscle and in vivo. Importantly, a working model was derived from these results that unifies the contradictory metabolic effects of UCN2.

An inverse agonist of orphan receptor GPR61 acts by a G protein-competitive allosteric mechanism.

GPR61 is an orphan GPCR related to biogenic amine receptors. Its association with phenotypes relating to appetite makes it of interest as a druggable target to treat disorders of metabolism and body weight, such as obesity and cachexia. To date, the lack of structural information or a known biological ligand or tool compound has hindered comprehensive efforts to study GPR61 structure and function. Here, we report a structural characterization of GPR61, in both its active-like complex with heterotrimeric G protein and in its inactive state. Moreover, we report the discovery of a potent and selective small-molecule inverse agonist against GPR61 and structural elucidation of its allosteric binding site and mode of action. These findings offer mechanistic insights into an orphan GPCR while providing both a structural framework and tool compound to support further studies of GPR61 function and modulation.

Discovery of the Potent and Selective MC4R Antagonist PF-07258669 for the Potential Treatment of Appetite Loss.

The melanocortin-4 receptor (MC4R) is a centrally expressed, class A GPCR that plays a key role in the regulation of appetite and food intake. Deficiencies in MC4R signaling result in hyperphagia and increased body mass in humans. Antagonism of MC4R signaling has the potential to mitigate decreased appetite and body weight loss in the setting of anorexia or cachexia due to underlying disease. Herein, we report on the identification of a series of orally bioavailable, small-molecule MC4R antagonists using a focused hit identification effort and the optimization of these antagonists to provide clinical candidate 23. Introduction of a spirocyclic conformational constraint allowed for simultaneous optimization of MC4R potency and ADME attributes while avoiding the production of hERG active metabolites observed in early series leads. Compound 23 is a potent and selective MC4R antagonist with robust efficacy in an aged rat model of cachexia and has progressed into clinical trials.

Membrane-tethered ligands are effective probes for exploring class B1 G protein-coupled receptor function.

Class B1 (secretin family) G protein-coupled receptors (GPCRs) modulate a wide range of physiological functions, including glucose homeostasis, feeding behavior, fat deposition, bone remodeling, and vascular contractility. Endogenous peptide ligands for these GPCRs are of intermediate length (27-44 aa) and include receptor affinity (C-terminal) as well as receptor activation (N-terminal) domains. We have developed a technology in which a peptide ligand tethered to the cell membrane selectively modulates corresponding class B1 GPCR-mediated signaling. The engineered cDNA constructs encode a single protein composed of (i) a transmembrane domain (TMD) with an intracellular C terminus, (ii) a poly(asparagine-glycine) linker extending from the TMD into the extracellular space, and (iii) a class B1 receptor ligand positioned at the N terminus. We demonstrate that membrane-tethered peptides, like corresponding soluble ligands, trigger dose-dependent receptor activation. The broad applicability of this approach is illustrated by experiments using tethered versions of 7 mammalian endogenous class B1 GPCR agonists. In parallel, we carried out mutational studies focused primarily on incretin ligands of the glucagon-like peptide-1 receptor. These experiments suggest that tethered ligand activity is conferred in large part by the N-terminal domain of the peptide hormone. Follow-up studies revealed that interconversion of tethered agonists and antagonists can be achieved with the introduction of selected point mutations. Such complementary receptor modulators provide important new tools for probing receptor structure-function relationships as well as for future studies aimed at dissecting the tissue-specific biological role of a GPCR in vivo (e.g., in the brain vs. in the periphery).

A comprehensive Bioconductor ecosystem for the design of CRISPR guide RNAs across nucleases and technologies.

The success of CRISPR-mediated gene perturbation studies is highly dependent on the quality of gRNAs, and several tools have been developed to enable optimal gRNA design. However, these tools are not all adaptable to the latest CRISPR modalities or nucleases, nor do they offer comprehensive annotation methods for advanced CRISPR applications. Here, we present a new ecosystem of R packages, called crisprVerse, that enables efficient gRNA design and annotation for a multitude of CRISPR technologies. This includes CRISPR knockout (CRISPRko), CRISPR activation (CRISPRa), CRISPR interference (CRISPRi), CRISPR base editing (CRISPRbe) and CRISPR knockdown (CRISPRkd). The core package, crisprDesign, offers a user-friendly and unified interface to add off-target annotations, rich gene and SNP annotations, and on- and off-target activity scores. These functionalities are enabled for any RNA- or DNA-targeting nucleases, including Cas9, Cas12, and Cas13. The crisprVerse ecosystem is open-source and deployed through the Bioconductor project ( https://github.com/crisprVerse ).

Effector membrane translocation biosensors reveal G protein and ßarrestin coupling profiles of 100 therapeutically relevant GPCRs.

The recognition that individual GPCRs can activate multiple signaling pathways has raised the possibility of developing drugs selectively targeting therapeutically relevant ones. This requires tools to determine which G proteins and ßarrestins are activated by a given receptor. Here, we present a set of BRET sensors monitoring the activation of the 12 G protein subtypes based on the translocation of their effectors to the plasma membrane (EMTA). Unlike most of the existing detection systems, EMTA does not require modification of receptors or G proteins (except for Gs). EMTA was found to be suitable for the detection of constitutive activity, inverse agonism, biased signaling and polypharmacology. Profiling of 100 therapeutically relevant human GPCRs resulted in 1500 pathway-specific concentration-response curves and revealed a great diversity of coupling profiles ranging from exquisite selectivity to broad promiscuity. Overall, this work describes unique resources for studying the complexities underlying GPCR signaling and pharmacology.