Predicting overall survival from tumor dynamics metrics using parametric statistical and machine learning models: application to patients with RET-altered solid tumors.

In oncology drug development, tumor dynamics modeling is widely applied to predict patients' overall survival (OS) via parametric models. However, the current modeling paradigm, which assumes a disease-specific link between tumor dynamics and survival, has its limitations. This is particularly evident in drug development scenarios where the clinical trial under consideration contains patients with tumor types for which there is little to no prior institutional data. In this work, we propose the use of a pan-indication solid tumor machine learning (ML) approach whereby all three tumor metrics (tumor shrinkage rate, tumor regrowth rate and time to tumor growth) are simultaneously used to predict patients' OS in a tumor type independent manner. We demonstrate the utility of this approach in a clinical trial of cancer patients treated with the tyrosine kinase inhibitor, pralsetinib. We compared the parametric and ML models and the results showed that the proposed ML approach is able to adequately predict patient OS across RET-altered solid tumors, including non-small cell lung cancer, medullary thyroid cancer as well as other solid tumors. While the findings of this study are promising, further research is needed for evaluating the generalizability of the ML model to other solid tumor types.

NSD2 is a requisite subunit of the AR/FOXA1 neo-enhanceosome in promoting prostate tumorigenesis.

The androgen receptor (AR) is a ligand-responsive transcription factor that binds at enhancers to drive terminal differentiation of the prostatic luminal epithelia. By contrast, in tumors originating from these cells, AR chromatin occupancy is extensively reprogrammed to drive hyper-proliferative, metastatic, or therapy-resistant phenotypes, the molecular mechanisms of which remain poorly understood. Here, we show that the tumor-specific enhancer circuitry of AR is critically reliant on the activity of Nuclear Receptor Binding SET Domain Protein 2 (NSD2), a histone 3 lysine 36 di-methyltransferase. NSD2 expression is abnormally gained in prostate cancer cells and its functional inhibition impairs AR trans-activation potential through partial off-loading from over 40,000 genomic sites, which is greater than 65% of the AR tumor cistrome. The NSD2-dependent AR sites distinctly harbor a chimeric AR-half motif juxtaposed to a FOXA1 element. Similar chimeric motifs of AR are absent at the NSD2-independent AR enhancers and instead contain the canonical palindromic motifs. Meta-analyses of AR cistromes from patient tumors uncovered chimeric AR motifs to exclusively participate in tumor-specific enhancer circuitries, with a minimal role in the physiological activity of AR. Accordingly, NSD2 inactivation attenuated hallmark cancer phenotypes that were fully reinstated upon exogenous NSD2 re-expression. Inactivation of NSD2 also engendered increased dependency on its paralog NSD1, which independently maintained AR and MYC hyper-transcriptional programs in cancer cells. Concordantly, a dual NSD1/2 PROTAC degrader, called LLC0150, was preferentially cytotoxic in AR-dependent prostate cancer as well as NSD2-altered hematologic malignancies. Altogether, we identify NSD2 as a novel subunit of the AR neo-enhanceosome that wires prostate cancer gene expression programs, positioning NSD1/2 as viable paralog co-targets in advanced prostate cancer.

gPKPDviz: A flexible R shiny tool for pharmacokinetic/pharmacodynamic simulations using mrgsolve.

GPKPDviz is a Shiny application (app) dedicated to real-time simulation, visualization, and assessment of the pharmacokinetic/pharmacodynamic (PK/PD) models. Within the app, gPKPDviz is capable of generating virtual populations and complex dosing and sampling scenarios, which, together with the streamlined workflow, is designed to efficiently assess the impact of covariates and dosing regimens on PK/PD end points. The actual population data from clinical trials can be loaded into the app for simulation if desired. The app-generated dosing regimens include single or multiple dosing, and more complex regimens, such as loading doses or intermittent dosing. When necessary, the dosing regimens can be defined externally and loaded to the app for simulation. Using mrgsolve as the simulation engine, gPKPDviz is typically used for population simulation, however, with a slight modification of the mrgsolve model, gPKPDviz is capable of performing individual simulations with individual post hoc parameters, individual dosing logs, and individual sampling timepoints through an external dataset. A built-in text editor has a debugging feature for the mrgsolve model, providing the same error messages as model compilation in R. GPKPDviz has had stringent validation by comparing simulation results between the app and using mrgsolve in R. GPKPDviz is a member of the suite of Modeling and Simulation Shiny apps developed at Genentech to facilitate the typical modeling work in Clinical Pharmacology. For broader access to the Pharmacometric community, gPKPDviz has been published as an open-source application in GitHub under the terms of GNU General Public License.

Loss of LCMT1 and biased protein phosphatase 2A heterotrimerization drive prostate cancer progression and therapy resistance.

Loss of the tumor suppressive activity of the protein phosphatase 2A (PP2A) is associated with cancer, but the underlying molecular mechanisms are unclear. PP2A holoenzyme comprises a heterodimeric core, a scaffolding A subunit and a catalytic C subunit, and one of over 20 distinct substrate-directing regulatory B subunits. Methylation of the C subunit regulates PP2A heterotrimerization, affecting B subunit binding and substrate specificity. Here, we report that the leucine carboxy methyltransferase (LCMT1), which methylates the L309 residue of the C subunit, acts as a suppressor of androgen receptor (AR) addicted prostate cancer (PCa). Decreased methyl-PP2A-C levels in prostate tumors is associated with biochemical recurrence and metastasis. Silencing LCMT1 increases AR activity and promotes castration-resistant prostate cancer growth. LCMT1-dependent methyl-sensitive AB56αCme heterotrimers target AR and its critical coactivator MED1 for dephosphorylation, resulting in the eviction of the AR-MED1 complex from chromatin and loss of target gene expression. Mechanistically, LCMT1 is regulated by S6K1-mediated phosphorylation-induced degradation requiring the ß-TRCP, leading to acquired resistance to anti-androgens. Finally, feedforward stabilization of LCMT1 by small molecule activator of phosphatase (SMAP) results in attenuation of AR-signaling and tumor growth inhibition in anti-androgen refractory PCa. These findings highlight methyl-PP2A-C as a prognostic marker and that the loss of LCMT1 is a major determinant in AR-addicted PCa, suggesting therapeutic potential for AR degraders or PP2A modulators in prostate cancer treatment.

Oncofusion-driven de novo enhancer assembly promotes malignancy in Ewing sarcoma via aberrant expression of the stereociliary protein LOXHD1.

Ewing sarcoma (EwS) is a highly aggressive tumor of bone and soft tissues that mostly affects children and adolescents. The pathognomonic oncofusion EWSR1::FLI1 transcription factor drives EwS by orchestrating an oncogenic transcription program through de novo enhancers. By integrative analysis of thousands of transcriptomes representing pan-cancer cell lines, primary cancers, metastasis, and normal tissues, we identify a 32-gene signature (ESS32 [Ewing Sarcoma Specific 32]) that stratifies EwS from pan-cancer. Among the ESS32, LOXHD1, encoding a stereociliary protein, is the most highly expressed gene through an alternative transcription start site. Deletion or silencing of EWSR1::FLI1 bound upstream de novo enhancer results in loss of the LOXHD1 short isoform, altering EWSR1::FLI1 and HIF1α pathway genes and resulting in decreased proliferation/invasion of EwS cells. These observations implicate LOXHD1 as a biomarker and a determinant of EwS metastasis and suggest new avenues for developing LOXHD1-targeted drugs or cellular therapies for this deadly disease.

CANVS: an easy-to-use application for the analysis and visualization of mass spectrometry-based protein-protein interaction/association data.

The elucidation of a protein's interaction/association network is important for defining its biological function. Mass spectrometry-based proteomic approaches have emerged as powerful tools for identifying protein-protein interactions (PPIs) and protein-protein associations (PPAs). However, interactome/association experiments are difficult to interpret, considering the complexity and abundance of data that are generated. Although tools have been developed to identify protein interactions/associations quantitatively, there is still a pressing need for easy-to-use tools that allow users to contextualize their results. To address this, we developed CANVS, a computational pipeline that cleans, analyzes, and visualizes mass spectrometry-based interactome/association data. CANVS is wrapped as an interactive Shiny dashboard with simple requirements, allowing users to interface easily with the pipeline, analyze complex experimental data, and create PPI/A networks. The application integrates systems biology databases such as BioGRID and CORUM to contextualize the results. Furthermore, CANVS features a Gene Ontology tool that allows users to identify relevant GO terms in their results and create visual networks with proteins associated with relevant GO terms. Overall, CANVS is an easy-to-use application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying interactome/association data.

Mapping Proximity Associations of Core Spindle Assembly Checkpoint Proteins.

The spindle assembly checkpoint (SAC) is critical for sensing defective microtubule-kinetochore attachments and tension across the kinetochore and functions to arrest cells in prometaphase to allow time to repair any errors before proceeding into anaphase. Dysregulation of the SAC leads to chromosome segregation errors that have been linked to human diseases like cancer. Although much has been learned about the composition of the SAC and the factors that regulate its activity, the proximity associations of core SAC components have not been explored in a systematic manner. Here, we have taken a BioID2-proximity-labeling proteomic approach to define the proximity protein environment for each of the five core SAC proteins BUB1, BUB3, BUBR1, MAD1L1, and MAD2L1 in mitotic-enriched populations of cells where the SAC is active. These five protein association maps were integrated to generate a SAC proximity protein network that contains multiple layers of information related to core SAC protein complexes, protein-protein interactions, and proximity associations. Our analysis validated many known SAC complexes and protein-protein interactions. Additionally, it uncovered new protein associations, including the ELYS-MAD1L1 interaction that we have validated, which lend insight into the functioning of core SAC proteins and highlight future areas of investigation to better understand the SAC.

DUSP7 regulates the activity of ERK2 to promote proper chromosome alignment during cell division.

Human cell division is a highly regulated process that relies on the accurate capture and movement of chromosomes to the metaphase plate. Errors in the fidelity of chromosome congression and alignment can lead to improper chromosome segregation, which is correlated with aneuploidy and tumorigenesis. These processes are known to be regulated by extracellular signal-regulated kinase 2 (ERK2) in other species, but the role of ERK2 in mitosis in mammals remains unclear. Here, we have identified the dual-specificity phosphatase 7 (DUSP7), known to display selectivity for ERK2, as important in regulating chromosome alignment. During mitosis, DUSP7 bound to ERK2 and regulated the abundance of active phospho-ERK2 through its phosphatase activity. Overexpression of DUSP7, but not catalytically inactive mutants, led to a decrease in the levels of phospho-ERK2 and mitotic chromosome misalignment, while knockdown of DUSP7 also led to defective chromosome congression that resulted in a prolonged mitosis. Consistently, knockdown or chemical inhibition of ERK2 or chemical inhibition of the MEK kinase that phosphorylates ERK2 led to chromosome alignment defects. Our results support a model wherein MEK-mediated phosphorylation and DUSP7-mediated dephosphorylation regulate the levels of active phospho-ERK2 to promote proper cell division.

The myosin regulatory light chain Myl5 localizes to mitotic spindle poles and is required for proper cell division.

Myosins are ATP-dependent actin-based molecular motors critical for diverse cellular processes like intracellular trafficking, cell motility, and cell invasion. During cell division, myosin MYO10 is important for proper mitotic spindle assembly, the anchoring of the spindle to the cortex, and positioning of the spindle to the cell mid-plane. However, myosins are regulated by myosin regulatory light chains (RLCs), and whether RLCs are important for cell division has remained unexplored. Here, we have determined that the previously uncharacterized myosin RLC Myl5 associates with the mitotic spindle and is required for cell division. We show that Myl5 localizes to the leading edge and filopodia during interphase and to mitotic spindle poles and spindle microtubules during early mitosis. Importantly, depletion of Myl5 led to defects in mitotic spindle assembly, chromosome congression, and chromosome segregation and to a slower transition through mitosis. Furthermore, Myl5 bound to MYO10 in vitro and co-localized with MYO10 at the spindle poles. These results suggest that Myl5 is important for cell division and that it may be performing its function through MYO10.

Regulation of Iron Homeostasis through Parkin-Mediated Lactoferrin Ubiquitylation.

Somatic mutations that perturb Parkin ubiquitin ligase activity and the misregulation of iron homeostasis have both been linked to Parkinson's disease. Lactotransferrin (LTF) is a member of the family of transferrin iron binding proteins that regulate iron homeostasis, and increased levels of LTF and its receptor have been observed in neurodegenerative disorders like Parkinson's disease. Here, we report that Parkin binds to LTF and ubiquitylates LTF to influence iron homeostasis. Parkin-dependent ubiquitylation of LTF occurred most often on lysines (K) 182 and 649. Substitution of K182 or K649 with alanine (K182A or K649A, respectively) led to a decrease in the level of LTF ubiquitylation, and substitution at both sites led to a major decrease in the level of LTF ubiquitylation. Importantly, Parkin-mediated ubiquitylation of LTF was critical for regulating intracellular iron levels as overexpression of LTF ubiquitylation site point mutants (K649A or K182A/K649A) led to an increase in intracellular iron levels measured by ICP-MS/MS. Consistently, RNAi-mediated depletion of Parkin led to an increase in intracellular iron levels in contrast to overexpression of Parkin that led to a decrease in intracellular iron levels. Together, these results indicate that Parkin binds to and ubiquitylates LTF to regulate intracellular iron levels. These results expand our understanding of the cellular processes that are perturbed when Parkin activity is disrupted and more broadly the mechanisms that contribute to Parkinson's disease.

Counter Regulation of Spic by NF-κB and STAT Signaling Controls Inflammation and Iron Metabolism in Macrophages.

Activated macrophages must carefully calibrate their inflammatory responses to balance efficient pathogen control with inflammation-mediated tissue damage, but the molecular underpinnings of this "balancing act" remain unclear. Using genetically engineered mouse models and primary macrophage cultures, we show that Toll-like receptor (TLR) signaling induces the expression of the transcription factor Spic selectively in patrolling monocytes and tissue macrophages by a nuclear factor κB (NF-κB)-dependent mechanism. Functionally, Spic downregulates pro-inflammatory cytokines and promotes iron efflux by regulating ferroportin expression in activated macrophages. Notably, interferon-gamma blocks Spic expression in a STAT1-dependent manner. High levels of interferon-gamma are indicative of ongoing infection, and in its absence, activated macrophages appear to engage a "default" Spic-dependent anti-inflammatory pathway. We also provide evidence for the engagement of this pathway in sterile inflammation. Taken together, our findings uncover a pathway wherein counter-regulation of Spic by NF-κB and STATs attune inflammatory responses and iron metabolism in macrophages.

Development of a Cysteine-Conjugatable Disulfide FRET Probe: Influence of Charge on Linker Cleavage and Payload Trafficking for an Anti-HER2 Antibody Conjugate.

Disulfide-linked bioconjugates allow the delivery of pharmacologically active or other cargo to specific tissues in a redox-sensitive fashion. However, an understanding of the kinetics, subcellular distribution, and mechanism of disulfide cleavage in such bioconjugates is generally lacking. Here, we report a modular disulfide-linked TAMRA-BODIPY based FRET probe that can be readily synthesized, modified, and conjugated to a cysteine-containing biomolecule to enable real-time monitoring of disulfide cleavage during receptor-mediated endocytosis in cells. We demonstrate the utility of this probe to study disulfide reduction during HER2 receptor-mediated uptake of a Cys-engineered anti-HER2 THIOMAB antibody. We found that introduction of positive, but not negative, charges in the probe improved retention of the BODIPY catabolite. This permitted the observation of significant disulfide cleavage in endosomes or lysosomes on par with proteolytic cleavage of a similarly charged valine-citrulline peptide-based probe. In general, the FRET probe we describe should enable real-time cellular monitoring of disulfide cleavage in other targeted delivery systems for mechanistic or diagnostic applications. Furthermore, modifications to the released BODIPY moiety permit evaluation of physicochemical properties that govern lysosomal egress or retention, which may have implications for the development of next-generation antibody-drug conjugates.

CDK7 Inhibition Suppresses Castration-Resistant Prostate Cancer through MED1 Inactivation.

Metastatic castration-resistant prostate cancer (CRPC) is a fatal disease, primarily resulting from the transcriptional addiction driven by androgen receptor (AR). First-line CRPC treatments typically target AR signaling, but are rapidly bypassed, resulting in only a modest survival benefit with antiandrogens. Therapeutic approaches that more effectively block the AR-transcriptional axis are urgently needed. Here, we investigated the molecular mechanism underlying the association between the transcriptional coactivator MED1 and AR as a vulnerability in AR-driven CRPC. MED1 undergoes CDK7-dependent phosphorylation at T1457 and physically engages AR at superenhancer sites, and is essential for AR-mediated transcription. In addition, a CDK7-specific inhibitor, THZ1, blunts AR-dependent neoplastic growth by blocking AR/MED1 corecruitment genome-wide, as well as reverses the hyperphosphorylated MED1-associated enzalutamide-resistant phenotype. In vivo, THZ1 induces tumor regression of AR-amplified human CRPC in a xenograft mouse model. Together, we demonstrate that CDK7 inhibition selectively targets MED1-mediated, AR-dependent oncogenic transcriptional amplification, thus representing a potential new approach for the treatment of CRPC. SIGNIFICANCE: Potent inhibition of AR signaling is critical to treat CRPC. This study uncovers a driver role for CDK7 in regulating AR-mediated transcription through phosphorylation of MED1, thus revealing a therapeutically targetable potential vulnerability in AR-addicted CRPC.See related commentary by Russo et al., p. 1490.This article is highlighted in the In This Issue feature, p. 1469.

Leukemia Cell Cycle Chemical Profiling Identifies the G2-Phase Leukemia Specific Inhibitor Leusin-1.

Targeting the leukemia proliferation cycle has been a successful approach to developing antileukemic therapies. However, drug screening efforts to identify novel antileukemic agents have been hampered by the lack of a suitable high-throughput screening platform for suspension cells that does not rely on flow-cytometry analyses. We report the development of a novel leukemia cell-based high-throughput chemical screening platform for the discovery of cell cycle phase specific inhibitors that utilizes chemical cell cycle profiling. We have used this approach to analyze the cell cycle response of acute lymphoblastic leukemia CCRF-CEM cells to each of 181420 druglike compounds. This approach yielded cell cycle phase specific inhibitors of leukemia cell proliferation. Further analyses of the top G2-phase and M-phase inhibitors identified the leukemia specific inhibitor 1 (Leusin-1). Leusin-1 arrests cells in G2 phase and triggers an apoptotic cell death. Most importantly, Leusin-1 was more active in acute lymphoblastic leukemia cells than other types of leukemias, non-blood cancers, or normal cells and represents a lead molecule for developing antileukemic drugs.