RNA-protein Interactions Research Articles

Structure of HIV-1 RRE stem-loop II identifies two conformational states of the high-affinity Rev binding site

During HIV infection, specific RNA-protein interaction between the Rev response element (RRE) and viral Rev protein is required for nuclear export of intron-containing viral mRNA transcripts. Rev initially binds the high-affinity site in stem-loop II, which promotes oligomerization of additional Rev proteins on RRE. Here, we present the crystal structure of RRE stem-loop II in distinct closed and open conformations. The high-affinity Rev-binding site is located within the three-way junction rather than the predicted stem IIB. The closed and open conformers differ in their non-canonical interactions within the three-way junction, and only the open conformation has the widened major groove conducive to initial Rev interaction. Rev binding assays show that RRE stem-loop II has high- and low-affinity binding sites, each of which binds a Rev dimer. We propose a binding model, wherein Rev-binding sites on RRE are sequentially created through structural rearrangements induced by Rev-RRE interactions.

Dynamics of Protein-RNA Interfaces Using All-Atom Molecular Dynamics Simulations.

Facing the current challenges posed by human health diseases requires the understanding of cell machinery at a molecular level. The interplay between proteins and RNA is key for any physiological phenomenon, as well protein-RNA interactions. To understand these interactions, many experimental techniques have been developed, spanning a very wide range of spatial and temporal resolutions. In particular, the knowledge of tridimensional structures of protein-RNA complexes provides structural, mechanical, and dynamical pieces of information essential to understand their functions. To get insights into the dynamics of protein-RNA complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on nine different protein-RNA complexes with different functions and interface size by taking into account the bound and unbound forms. First, we characterized structural changes upon binding and, for the RNA part, the change in the puckering. Second, we extensively analyzed the interfaces, their dynamics and structural properties, and the structural waters involved in the binding, as well as the contacts mediated by them. Based on our analysis, the interfaces rearranged during the simulation time showing alternative and stable residue-residue contacts with respect to the experimental structure.

Massively parallel dissection of RNA in RNA-protein interactions in vivo.

Many of the biological functions performed by RNA are mediated by RNA-binding proteins (RBPs), and understanding the molecular basis of these interactions is fundamental to biology. Here, we present massively parallel RNA assay combined with immunoprecipitation (MPRNA-IP) for in vivo high-throughput dissection of RNA-protein interactions and describe statistical models for identifying RNA domains and parsing the structural contributions of RNA. By using custom pools of tens of thousands of RNA sequences containing systematically designed truncations and mutations, MPRNA-IP is able to identify RNA domains, sequences, and secondary structures necessary and sufficient for protein binding in a single experiment. We show that this approach is successful for multiple RNAs of interest, including the long noncoding RNA NORAD, bacteriophage MS2 RNA, and human telomerase RNA, and we use it to interrogate the hitherto unknown sequence or structural RNA-binding preferences of the DNA-looping factor CTCF. By integrating systematic mutation analysis with crosslinking immunoprecipitation, MPRNA-IP provides a novel high-throughput way to elucidate RNA-based mechanisms behind RNA-protein interactions in vivo.

The role of RNA in the maintenance of chromatin domains as revealed by antibody-mediated proximity labelling coupled to mass spectrometry.

Eukaryotic chromatin is organized into functional domains, that are characterized by distinct proteomic compositions and specific nuclear positions. In contrast to cellular organelles surrounded by lipid membranes, the composition of distinct chromatin domains is rather ill described and highly dynamic. To gain molecular insight into these domains and explore their composition, we developed an antibody-based proximity biotinylation method targeting the RNA and proteins constituents. The method that we termed antibody-mediated proximity labelling coupled to mass spectrometry (AMPL-MS) does not require the expression of fusion proteins and therefore constitutes a versatile and very sensitive method to characterize the composition of chromatin domains based on specific signature proteins or histone modifications. To demonstrate the utility of our approach we used AMPL-MS to characterize the molecular features of the chromocenter as well as the chromosome territory containing the hyperactive X chromosome in Drosophila. This analysis identified a number of known RNA-binding proteins in proximity of the hyperactive X and the centromere, supporting the accuracy of our method. In addition, it enabled us to characterize the role of RNA in the formation of these nuclear bodies. Furthermore, our method identified a new set of RNA molecules associated with the Drosophila centromere. Characterization of these novel molecules suggested the formation of R-loops in centromeres, which we validated using a novel probe for R-loops in Drosophila. Taken together, AMPL-MS improves the selectivity and specificity of proximity ligation allowing for novel discoveries of weak protein-RNA interactions in biologically diverse domains.

RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders.

RNA-protein interactions (RPIs) play an important role in several fundamental cellular physiological processes, including cell motility, chromosome replication, transcription and translation, and signaling. Predicting RPI can guide the exploration of cellular biological functions, intervening in diseases, and designing drugs. Given this, this study proposes the RPI-gated graph convolutional network (RPI-GGCN) method for predicting RPI based on the gated graph convolutional neural network (GGCN) and co-regularized variational autoencoder (Co-VAE). First, different types of feature information were extracted from RNA and protein sequences by nine feature extraction methods. Second, Co-VAEs are used to eliminate the redundancy of fused features and generate optimal features. Finally, this study introduces gated cyclic units into graph convolutional networks (GCNs) to construct a model for RPI prediction, which efficiently extracts topological information and improves the model's interpretable feature learning and expression capabilities. In the fivefold cross-validation test, the RPI-GGCN method achieved prediction accuracies of 97.27%, 97.32%, 96.54%, 95.76%, and 94.98% on the RPI369, RPI488, RPI1446, RPI1807, and RPI2241 datasets. To test the generalization performance of the model, we used the model trained on RPI369 to predict the independent NPInter v3.0 dataset and achieved excellent performance in all six independent validation sets. By visualizing the RPI network graph based on the prediction results, we aim to provide a new perspective and reference for studying RPI mechanisms and exploring new RPIs. Extensive experimental results demonstrate that RPI-GGCN can provide an efficient, accurate, and stable RPI prediction method.

Annotation of nuclear lncRNAs based on chromatin interactions.

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

TFAIP6 facilitates hepatocellular carcinoma cell glycolysis through upregulating c-myc/PKM2 axis

BackgroundHepatocellular carcinoma (HCC) is the most prevalent liver cancer. Despite of the improvement of therapies, the durable response rate and survival benefit are still limited for HCC patients. It's urgent to clarify the molecular mechanisms and find therapeutic strategies to improve the clinical outcome. TNFα-stimulated gene-6 (TNFAIP6) plays a critical role in the prognosis of various tumors, but its roles in HCC are still unclear. MethodsQuantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) analysis were employed to evaluate the clinical relevance of TNFAIP6 expressions in HCC patients. Cell counting kit-8 (CCK-8), Edu assay, and transwell assay were performed to evaluate the malignancy of HCC cells. Glucose uptake, lactate production, ATP production, extracellular acidification rate (ECAR) by Seahorse XF analyzer were employed to evaluate the role of TNFAIP6 in the regulation of aerobic glycolysis. The expressions of key proteins involved in glycolysis were examined by Western blot. Co-immunoprecipitation (Co-IP) and chromatin immunoprecipitation (ChIP) were used for protein-protein interactions or protein-RNA interactions respectively. Knockdown and overexpression of TNFAIP6 in HCC cells were employed for analyzing the functions of TNFAIP6 in HCC. ResultsTNFAIP6 was significantly upregulated in HCC and predicted a poor clinical prognosis. Knockdown of TNFAIP6 inhibited in vitro cell proliferation, invasion, migration, as well as glycolysis in HCC cells. Mechanistically, we clarified that TNFAIP6 interacted with heterogeneous nuclear ribonucleoprotein C (HNRNPC), stabilized c-Myc mRNA and upregulated pyruvate kinase M2 (PKM2) to promote glycolysis. ConclusionsOur study reveals a molecular mechanism by which TNFAIP6 promotes aerobic glycolysis, which is beneficial for malignance of HCC and provides a potential clinical therapy for disease management.

Mapping RNA-protein interactions with subcellular resolution using colocalization CLIP.

RNA-binding proteins (RBPs) are essential for RNA metabolism and profoundly impact health and disease. The subcellular organization of RBP interaction networks with target RNAs remains largely unexplored. Here, we develop colocalization CLIP (coCLIP), a method that combines cross-linking and immunoprecipitation (CLIP) with proximity labeling, to explore in-depth the subcellular RNA interactions of the RBP human antigen R (HuR). Using this method, we uncover HuR's dynamic and location-specific interactions with RNA, revealing alterations in sequence preferences and interactions in the nucleus, cytosol, or stress granule (SG) compartments. We uncover HuR's unique binding preferences within SGs during arsenite stress, illuminating intricate interactions that conventional methodologies cannot capture. Overall, coCLIP provides a powerful method for revealing RBP-RNA interactions based on localization and lays the foundation for an advanced understanding of RBP models that incorporate subcellular location as a critical determinant of their functions.

The overlooked evolutionary dynamics of 16S rRNA revises its role as the “gold standard” for bacterial species identification

The role of 16S rRNA has been and largely remains crucial for the identification of microbial organisms. Although 16S rRNA could certainly be described as one of the most studied sequences ever, the current view of it remains somewhat ambiguous. While some consider 16S rRNA to be a variable marker with resolution power down to the strain level, others consider them to be living fossils that carry information about the origin of domains of cellular life. We show that 16S rRNA is clearly an evolutionarily very rigid sequence, making it a largely unique and irreplaceable marker, but its applicability beyond the genus level is highly limited. Interestingly, it seems that the evolutionary rigidity is not driven by functional constraints of the sequence (RNA–protein interactions), but rather results from the characteristics of the host organism. Our results suggest that, at least in some lineages, Horizontal Gene Transfer (HGT) within genera plays an important role for the evolutionary non-dynamics (stasis) of 16S rRNA. Such genera exhibit an apparent lack of diversification at the 16S rRNA level in comparison to the rest of a genome. However, why it is limited specifically and solely to 16S rRNA remains enigmatic.

ECRUIS captures RNA-protein interaction in vitro and in vivo

As an information bridge between DNA and protein, RNA regulates cellular processes and gene expression in various ways. From its synthesis to degradation, RNA is associated with a range of RNA-binding proteins. Therefore, it is necessary to develop innovative methods to study the interaction between RNA and proteins. Previously, we developed an RNA-centric method, called CRISPR-based RNA-United Interacting System (CRUIS), to capture RNA-protein interaction in cells. On this basis, here we develop an enhanced CRUIS (eCRUIS) by combining the power of dCas13d and the engineered promiscuous ligase TurboID. The current version allows us to rapidly label RNA-binding proteins on the target RNA within 30 minutes, potentially for in vivo use. By introducing bait-assay with exogenous RNA, we confirm that eCRUIS can effectively label RNA-binding proteins on bait RNA in a short time. eCRUIS provides a broader range of in vitro and in vivo applications for studying RNA-protein interactions.

Decoding the neurotoxic effects of propofol: insights into the RARα-Snhg1-Bdnf regulatory cascade.

The potential neurotoxic effects of propofol, an extensively utilized anesthetic, underline the urgency to comprehend its influence on neuronal health. Insights into the role of the retinoic acid receptor-α, small nucleolar RNA host gene 1, and brain-derived neurotrophic factor (RARα-Snhg1-Bdnf) network can offer significant advancements in minimizing these effects. The study targets the exploration of the RARα and Snhg1 regulatory network's influence on Bdnf expression in the realm of propofol-induced neurotoxicity. Harnessing the Gene Expression Omnibus (GEO) database and utilizing JASPAR and RNA-Protein Interaction Prediction (RPISeq) database for projections, the study embarks on an in-depth analysis employing both in vitro and in vivo models. The findings draw a clear link between propofol-induced neurotoxicity and the amplification of RAR signaling pathways, impacting hippocampal development and apoptosis and leading to increased RARα and Snhg1 and decreased Bdnf. Propofol is inferred to accentuate neurotoxicity by heightening RARα and Snhg1 interactions, culminating in Bdnf suppression.NEW & NOTEWORTHY This study aimed to decode propofol's neurotoxic effects on the regulatory cascade, provide insights into the RARα-Snhg1-Bdnf interaction, apply extensive validation techniques, provide a detailed analysis and exploration of propofol's neurotoxicity, and offer a comprehensive approach to understanding molecular interactions.

An RNA-dependent and phase-separated active subnuclear compartment safeguards repressive chromatin domains

The nucleus is composed of functionally distinct membraneless compartments that undergo phase separation (PS). However, whether different subnuclear compartments are connected remains elusive. We identified a type of nuclear body with PS features composed of BAZ2A that associates with active chromatin. BAZ2A bodies depend on RNA transcription and BAZ2A non-disordered RNA-binding TAM domain. Although BAZ2A and H3K27me3 occupancies anticorrelate in the linear genome, in the nuclear space, BAZ2A bodies contact H3K27me3 bodies. BAZ2A-body disruption promotes BAZ2A invasion into H3K27me3 domains, causing H3K27me3-body loss and gene upregulation. Weak BAZ2A-RNA interactions, such as with nascent transcripts, promote BAZ2A bodies, whereas the strong binder long non-coding RNA (lncRNA) Malat1 impairs them while mediating BAZ2A association to chromatin at nuclear speckles. In addition to unraveling a direct connection between nuclear active and repressive compartments through PS mechanisms, the results also showed that the strength of RNA-protein interactions regulates this process, contributing to nuclear organization and the regulation of chromatin and gene expression.

Phosphorylation of the compartmentalized PKA substrate TAF15 regulates RNA-protein interactions.

Spatiotemporal-controlled second messengers alter molecular interactions of central signaling nodes for ensuring physiological signal transmission. One prototypical second messenger molecule which modulates kinase signal transmission is the cyclic-adenosine monophosphate (cAMP). The main proteinogenic cellular effectors of cAMP are compartmentalized protein kinase A (PKA) complexes. Their cell-type specific compositions precisely coordinate substrate phosphorylation and proper signal propagation which is indispensable for numerous cell-type specific functions. Here we present evidence that TAF15, which is implicated in the etiology of amyotrophic lateral sclerosis, represents a novel nuclear PKA substrate. In cross-linking and immunoprecipitation experiments (iCLIP) we showed that TAF15 phosphorylation alters the binding to target transcripts related to mRNA maturation, splicing and protein-binding related functions. TAF15 appears to be one of multiple PKA substrates that undergo RNA-binding dynamics upon phosphorylation. We observed that the activation of the cAMP-PKA signalingaxis caused a change in the composition of a collection of RNA species that interact with TAF15. This observation appears to be a broader principle in the regulation of molecular interactions, as we identified a significant enrichment of RNA-binding proteins within endogenous PKA complexes. We assume that phosphorylation of RNA-binding domains adds another layer of regulation to binary protein-RNAs interactions with consequences to RNA features including binding specificities, localization, abundance and composition.

Nonspecific Interactions in Transcription Regulation and Organization of Transcriptional Condensates.

Eukaryotic cells are characterized by a high degree of compartmentalization of their internal contents, which ensures precise and controlled regulation of intracellular processes. During many processes, including different stages of transcription, dynamic membraneless compartments termed biomolecular condensates are formed. Transcription condensates contain various transcription factors and RNA polymerase and are formed by high- and low-specificity interactions between the proteins, DNA, and nearby RNA. This review discusses recent data demonstrating important role of nonspecific multivalent protein-protein and RNA-protein interactions in organization and regulation of transcription.

Intensity and retention time prediction improves the rescoring of protein-nucleic acid cross-links.

In protein-RNA cross-linking mass spectrometry, UV or chemical cross-linking introduces stable bonds between amino acids and nucleic acids in protein-RNA complexes that are then analyzed and detected in mass spectra. This analytical tool delivers valuable information about RNA-protein interactions and RNA docking sites in proteins, both in vitro and in vivo. The identification of cross-linked peptides with oligonucleotides of different length leads to a combinatorial increase in search space. We demonstrate that the peptide retention time prediction tasks can be transferred to the task of cross-linked peptide retention time prediction using a simple amino acid composition encoding, yielding improved identification rates when the prediction error is included in rescoring. For the more challenging task of including fragment intensity prediction of cross-linked peptides in the rescoring, we obtain, on average, a similar improvement. Further improvement in the encoding and fine-tuning of retention time and intensity prediction models might lead to further gains, and merit further research.

Loss-of-function mutation in PRMT9 causes abnormal synapse development by dysregulation of RNA alternative splicing

Protein arginine methyltransferase 9 (PRMT9) is a recently identified member of the PRMT family, yet its biological function remains largely unknown. Here, by characterizing an intellectual disability associated PRMT9 mutation (G189R) and establishing a Prmt9 conditional knockout (cKO) mouse model, we uncover an important function of PRMT9 in neuronal development. The G189R mutation abolishes PRMT9 methyltransferase activity and reduces its protein stability. Knockout of Prmt9 in hippocampal neurons causes alternative splicing of ~1900 genes, which likely accounts for the aberrant synapse development and impaired learning and memory in the Prmt9 cKO mice. Mechanistically, we discover a methylation-sensitive protein–RNA interaction between the arginine 508 (R508) of the splicing factor 3B subunit 2 (SF3B2), the site that is exclusively methylated by PRMT9, and the pre-mRNA anchoring site, a cis-regulatory element that is critical for RNA splicing. Additionally, using human and mouse cell lines, as well as an SF3B2 arginine methylation-deficient mouse model, we provide strong evidence that SF3B2 is the primary methylation substrate of PRMT9, thus highlighting the conserved function of the PRMT9/SF3B2 axis in regulating pre-mRNA splicing.

Interrogation of RNA-protein interaction dynamics in bacterial growth

Characterising RNA–protein interaction dynamics is fundamental to understand how bacteria respond to their environment. In this study, we have analysed the dynamics of 91% of the Escherichia coli expressed proteome and the RNA-interaction properties of 271 RNA-binding proteins (RBPs) at different growth phases. We find that 68% of RBPs differentially bind RNA across growth phases and characterise 17 previously unannotated proteins as bacterial RBPs including YfiF, a ncRNA-binding protein. While these new RBPs are mostly present in Proteobacteria, two of them are orthologs of human mitochondrial proteins associated with rare metabolic disorders. Moreover, we reveal novel RBP functions for proteins such as the chaperone HtpG, a new stationary phase tRNA-binding protein. For the first time, the dynamics of the bacterial RBPome have been interrogated, showcasing how this approach can reveal the function of uncharacterised proteins and identify critical RNA–protein interactions for cell growth which could inform new antimicrobial therapies.

Lipopolysaccharide Regulates the Macrophage RNA-Binding Proteome.

RNA-protein interactions within cellular signaling pathways have significant modulatory effects on RNA binding proteins' (RBPs') effector functions. During the innate immune response, specific RNA-protein interactions have been reported as a regulatory layer of post-transcriptional control. We investigated changes in the RNA-bound proteome of immortalized mouse macrophages (IMM) following treatment with lipopolysaccharide (LPS). Stable isotope labeling by amino acids in cell culture (SILAC) of cells followed by unbiased purification of RNP complexes at two time points after LPS stimulation and bottom-up proteomic analysis by LC-MS/MS resulted in a set of significantly affected RBPs. Global RNA sequencing and LFQ proteomics were used to characterize the correlation of transcript and protein abundance changes in response to LPS at different time points with changes in protein-RNA binding. Il1α, MARCKS, and ACOD1 were noted as RBP candidates involved in innate immune signaling. The binding sites of the RBP and RNA conjugates at amino acid resolution were investigated by digesting the cross-linked oligonucleotide from peptides remaining after elution using Nuclease P1. The combined data sets provide directions for further studies of innate immune signaling regulation by RBP interactions with different classes of RNA.

Regulating Protein-RNA Interactions: Advances in Targeting the LIN28/Let-7 Pathway.

Originally discovered in C. elegans, LIN28 is an evolutionarily conserved zinc finger RNA-binding protein (RBP) that post-transcriptionally regulates genes involved in developmental timing, stem cell programming, and oncogenesis. LIN28 acts via two distinct mechanisms. It blocks the biogenesis of the lethal-7 (let-7) microRNA (miRNA) family, and also directly binds messenger RNA (mRNA) targets, such as IGF-2 mRNA, and alters downstream splicing and translation events. This review focuses on the molecular mechanism of LIN28 repression of let-7 and current strategies to overcome this blockade for the purpose of cancer therapy. We highlight the value of the LIN28/let-7 pathway as a drug target, as multiple oncogenic proteins that the pathway regulates are considered undruggable due to their inaccessible cellular location and lack of cavities for small molecule binding.

Abstract 463: The small nucleolar RNA SNORD46 and SNORD72 have tumor suppressor activity in diffuse large B cell lymphoma

Abstract Background. Following the identification of an 11q24.3 gain upregulating the ETS factors ETS1 and FLI1 in diffuse large B cell lymphoma (DLBCL) (Bonetti et al. Blood 2013), we observed the anti-lymphoma activity of blocking the protein-protein interaction of ETS factors with RNA helicases, using YK-4-279 and its clinical derivative TK-216 (Spriano, Chung et al. CCR 2019). DLBCL cells exposed to the two small molecule inhibitors presented a significant upregulation of small nucleolar RNAs (snoRNAs). Besides their primary functions in rRNA processing, snoRNAs are often deregulated in cancers, with microRNA-like actions and direct interaction with proteins. Here, we characterized SNORD46 and SNORD72, the two snoRNAs most upregulated cells after YK-4-279 and TK-216 and mapped to the 1p34.1 locus recurrently lost in DLBCL. Methods. Real-time PCR, immunoblotting, and shRNA silencing were conducted based on established protocols. RNA-Protein Interaction Prediction (RPISeq) was used to calculate the interaction probabilities of snoRNAs with proteins of interest. The prediction was made using both the Random Forest (RF) and the Support Vector Machine (SVM) classifiers, using a stringent threshold of >0.6. Results. The time-dependent changes of SNORD46 and 74 were validated with real-time PCR in the U2932 activated B cell-like (ABC) DLBCL cell line exposed to YK- 4-279 for 4 or 8 h. Upregulation of SNORD46 and 74 were significantly upregulated compared to their host genes upon YK-4-279 treatment, suggesting these snoRNAs have different functions from the genes in which they are encoded. Across 48 lymphoma cell lines, SNORD74 was more expressed in ABC DLBCL than in the remaining cell lines (P 0.03) or GCB DLBCL (P 0.05), while SNORD46 did not differ. Stable lentiviral-based overexpression of SNORD46 and 74, U2932 ABC DLBCL demonstrated that both SNORD46 and SNORD74 overexpression impaired growth while SNORD92, the control did not SNORD74 overexpression inhibited pAKT-Ser473, suggesting it could exert its anti-tumor effect by negatively impacting BCR signaling. Since constitutive BCR is the main driver for the pathogenesis in ABC DLBCL, we studied the impact of BCR signaling on SNORD46 and 74 expressions. IgM stimulation downregulated the snoRNAs in U2932 and TMD8 ABC DLBCL cell lines at 1 and 2.5 h poststimulation, with a more substantial effect for SNORD74. Furthermore, the snoRNAs were upregulated in four ABCs and four GCB DLBCLs cell lines exposed to the PI3K/mTOR inhibitor bimiralisib. Bioinformatic analysis indicated the possible binding of SNORD46 and especially of SNORD74 to BCR signaling molecules (SYK, LYN, BTK, PI3Kδ, IRAK4, IRAK1, CARD11), RNA helicases (RHA, DDX21, DDX5) and essential DLBCL proteins (BCL6, IRF4). Conclusions. SNORD46 and SNORD74 exert tumor suppressor activity in DLBCL cells, possibly as negative regulators of the BCR signaling. Citation Format: Elaine YL Chung, Filippo Spriano, Sara Napoli, Giulio Sartori, Luciano Cascione, Francesco Bertoni. The small nucleolar RNA SNORD46 and SNORD72 have tumor suppressor activity in diffuse large B cell lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 463.