Post-transplant complications reduce allograft and recipient survival. Current approaches for detecting allograft injury non-invasively are limited and do not differentiate between cellular mechanisms. Here, we monitor cellular damages after liver transplants from cell-free DNA (cfDNA) fragments released from dying cells into the circulation. We analyzed 130 blood samples collected from 44 patients at different time points after transplant. Sequence-based methylation of cfDNA fragments were mapped to an atlas of cell-type-specific DNA methylation patterns derived from 476 methylomes of purified cells. For liver cell types, DNA methylation patterns and multi-omic data integration show distinct enrichment in open chromatin and functionally important regulatory regions. We find that multi-tissue cellular damages post-transplant recover in patients without allograft injury during the first post-operative week. However, sustained elevation of hepatocyte and biliary epithelial cfDNA within the first month indicates early-onset allograft injury. Further, cfDNA composition differentiates amongst causes of allograft injury indicating the potential for non-invasive monitoring and intervention.

Abstract Background: Decoding the origins of cell-free DNA (cfDNA) released from dying cells in a liquid biopsy sample offers the potential to provide insight into the dynamic, organism-wide changes reflective of health and disease, making cfDNA an ideal target for serial, minimally invasive monitoring of disease-related changes. To this end, cell-type specific DNA methylation patterns offer a promising target to facilitate tissue of origin analysis, yet limited methods exist to identify differentially methylated regions that distinguish cell-types. Methods: We develop a robust differentially methylated marker region identification pipeline, DiMMER, that leverages cfDNA fragment level information of neighboring, co-regulated CpG sites on methylome-wide sequencing reads. Compared to prior methods that utilize simple heuristics in one-vs-all average methylation rate comparisons, we implement an individual pairwise statistical test procedure across all cell-types or groups under consideration. We assess the cell-specific nature of identified differentially methylated marker regions by generating in-silico mixtures from known cell-type of origin at each region, and calculating the area under the receiver operating characteristic curve (AUROC). We utilize our differentially methylated marker finding pipeline to identify melanocyte specific methylation marker regions and assess their functional role through annotations. We show these cell-specific regions are conserved in melanoma cell-lines and are distinct from the aberrant changes in a cancer context. Results: We identified the most cell-type specific differentially methylated marker regions across 24 distinct cell-type groups using our pipeline. Compared to a simpler one-vs-all heuristic, we demonstrate improved cell-type specificity evidenced by a higher AUROC on average. Using our pipeline we identified melanocyte-specific marker regions, which were commonly found in intronic and promoter regions of genes related to melanocyte development and differentiation. When comparing methylation patterns between melanocytes and melanoma cell-lines, we demonstrate melanocyte specific methylation marks are conserved through the transformation to malignant melanoma. Conclusion: As methylome-wide sequencing methods continue to rapidly develop and more cell-specific methylation data is generated, there is unmet need for more statistically robust differentially methylated marker finding tools. Here we present one such tool, DiMMER, and demonstrate the potential utility of identifying such regions to be used to assess organ-specific load as a measure of residual disease, as opposed to traditional circulating tumor DNA quanitification. Citation Format: Arthur P McDeed, Sidharth S Jain, Megan E McNamara, Amber Alley, Anton Wellstein, Jaeil Ahn. DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B063.

Cellular senescence accumulates with age and has been shown to impact numerous physiological and pathological processes, including immune function. The role of cellular senescence in cancer is multifaceted, but the impact on immune checkpoint inhibitor response and toxicity has not been fully evaluated. In this review, we evaluate the impact of cellular senescence in various biological compartments, including the tumor, the tumor microenvironment, and the immune system on immune checkpoint inhibitor efficacy and toxicity. We provide an overview of the impact of cellular senescence in normal and pathological contexts and examine recent studies that have connected aging and cellular senescence to immune checkpoint inhibitor treatment in both the pre-clinical and clinical contexts. Overall, senescence plays a multi-faceted, context-specific role, and has been shown to modulate immune-related adverse event incidence as well as immune checkpoint inhibitor response.

Abstract Breast cancer is the most common type of cancer in females and recurrence increases over time, unlike many other cancers. Treatment for recurrent cancer is often the same as the primary with no additional biopsies taken. Current research suggests that subtype switching and tumor character changes frequently occur between primary and recurrent breast cancers. Therefore, it may be beneficial to patients to switch treatment based on these changes. Since physical biopsies are cumbersome and not always feasible, liquid biopsies open a way to monitor tumor changes less invasively and more comprehensively. It has been previously established that cell free DNA (cfDNA) shed into the bloodstream from dying cells can reflect cell type of origin via methylation pattern and rate of death via concentration of cfDNA. In this pilot study, we seek to look at the cfDNA of fifteen late stage pre-/ post-surgical breast cancer patients who also received radiation treatment. We will perform cfDNA extraction on the serum of these patients and both whole genome bisulfite sequencing (WGBS), which chemically converts unmethylated cytosine to uracil/thymine in the DNA and is the current gold-standard of methylation sequencing, and a newer method, enzymatic methylation sequencing (EM-seq), which enzymatically converts (TET2/APOBEC) unmethylated cytosine to uracil/thymine and potentially preserves more of the cfDNA. To validate any signatures found in the cfDNA of the breast cancer patients, we have begun the genomic DNA (gDNA) extraction and WGBS/ EM-seq protocols on a variety of breast cancer cell lines including: MCF10A, MCFDCIS, MCF7, T47D, BT474 MDA MB453, MDA MB436 and MDA MB231 (including in-lab brain, bone, and lung metastatic clones). Bioanalyzer traces are produced from the extracted cfDNA/gDNA and also for the final sequencing libraries. The success of the methylation conversion is evaluated after sequencing data is returned and conversion rates of the cytosine to uracil/thymine are compared to unmethylated DNA control (lambda) and methylated DNA control (pUC19). Once this sequencing data is obtained, we use an in-lab deconvolution algorithm to detect cell types of origin and intend to make the algorithm more robust for cancer cell types as well. We have currently produced breast cancer cell line methylation sequencing libraries and are in the process of producing the libraries for the patient samples. Our current data suggests that there are changes in the cfDNA general fragmentation patterns and cfDNA concentrations between pre-/post- surgery samples. Once our sequencing data is obtained for the patient samples, we will run our deconvolution algorithm. The potential of characterizing breast cancer subtype and progression signatures in cfDNA of late stage pre-/ post-surgical breast cancer patients can have significant impact on patient treatment options. Identifying these breast cancer signatures less invasively and, therefore, more frequently may allow for early and more targeted intervention to improve breast cancer patient outcomes. Citation Format: Amber Alley, Megan McNamara, Sidharth Jain, Anton Wellstein. Investigating distinct methylation signatures characteristic of breast cancer subtypes in residual disease via cell free DNA methylation [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B005.

Abstract Background: The DREAMseq trial (EA6134, NCT02224781) was a national multi-center randomized phase III trial coordinated by ECOG-ACRIN that found that immune checkpoint inhibitor (IO) treatment achieves improved survival outcomes compared to targeted therapy (TT) in patients with BRAF V600-mutant metastatic melanoma. Still, approximately 40% of patients do not respond to IO, and existing biomarkers fail to distinguish this subset of patients who do not benefit from IO therapy. Additionally, as many as 80% of patients may experience immune- related adverse events (irAEs), which range from mild dermatological symptoms to life- threatening myocarditis. Here, we explore the use of the methylation status of cell-free DNA (cfDNA) in serially collected blood samples to measure response and toxicity in the context of IO- and TT-treated metastatic melanoma. Methods: Serial serum samples were collected from patients with BRAF V600-mutant metastatic melanoma treated with ipilimumab/nivolumab (IO) or dabrafenib/trametinib (TT). Circulating cfDNA was isolated from serially collected serum samples, enriched for regions of interest by hybridization capture and sequenced using enzymatic methyl-seq. Cell-type deconvolution was performed to determine the abundance of cell type- specific methylation patterns of cfDNA molecules in patient serum at different time points of treatment. The BRAF V600 mutation abundance in total cfDNA was also assessed. Results: We identified melanocyte lineage-specific DNA methylation regions and demonstrate that the methylation status of these regions remains conserved in malignant melanoma. We characterized the changes in abundance of the melanocyte-lineage cfDNA over the course of treatment and show that these changes distinguish responders from non-responders to either IO or TT. Furthermore, we track the abundance of cell type-specific DNA from normal tissues to identify markers indicative of adverse effects or disease progression. Conclusions: We established melanocyte-lineage methylation markers and evaluated the use of cell-type specific DNA methylation to monitor treatment effects of immune checkpoint or BRAF/MEK inhibitors in metastatic melanoma using serially collected blood samples. Citation Format: Sidharth S Jain, A. Patrick IV McDeed, Megan E McNamara, Amber R Alley, Dori S Rosenstrauch, Harry Sun, Natalie Thompson, John M Kirkwood, Geoffrey T Gibney, Michael B Atkins, Anton Wellstein. Monitoring treatment response and toxicity in BRAF V600-mutant metastatic melanoma with circulating cell-free DNA [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B047.

Hepatocellular carcinoma (HCC) has been an approved indication for the administration of immunotherapy since 2017, but biomarkers that predict therapeutic response have remained limited. Understanding and characterizing the tumor immune microenvironment enables better classification of these tumors and may reveal biomarkers that predict immunotherapeutic efficacy. In this paper, we applied a cell-type deconvolution algorithm using DNA methylation array data to investigate the composition of the tumor microenvironment in HCC. Using publicly available and in-house datasets with a total cohort size of 57 patients, each with tumor and matched normal tissue samples, we identified key differences in immune cell composition. We found that NK cell abundance was significantly decreased in HCC tumors compared to adjacent normal tissue. We also applied DNA methylation "clocks" which estimate phenotypic aging and compared these findings to expression-based determinations of cellular senescence. Senescence and epigenetic aging were significantly increased in HCC tumors, and the degree of age acceleration and senescence was strongly associated with decreased NK cell abundance. In summary, we found that NK cell infiltration in the tumor microenvironment is significantly diminished, and that this loss of NK abundance is strongly associated with increased senescence and age-related phenotype. These findings point to key interactions between NK cells and the senescent tumor microenvironment and offer insights into the pathogenesis of HCC as well as potential biomarkers of therapeutic efficacy.

Oncogenesis, a complex and multifaceted process, is profoundly modulated by miRNA’s regulatory role in gene expression. Over the years, a substantial body of knowledge concerning miRNA and mRNA has been accumulated, drawing from both rigorous biological experiments and intricate statistical analyses. In the realm of statistical modeling, the integration of such information as "prior knowledge" often amplifies the model’s ability to pinpoint molecular targets of significance. This study seeks to leverage prior knowledge of miRNA-mRNA regulatory interactions to map the dynamic landscape of interactions in the specific context of hepatocellular carcinoma (HCC).To address this, we introduce an evolved iteration of a Bayesian two-step integrative method previously established in the literature. This augmented approach includes improved computing efficiency when dealing with high dimensional data and a novel mechanistic submodel, which operates autonomously, devoid of prior knowledge. Employing this method, we identified two discrete gene lists: one informed by prior knowledge and the other independently inferred. This bifurcated strategy provides a comprehensive perspective on gene interactions.Our methodological advancement allows for a nuanced analysis of gene networks, distinguishing between direct and indirect gene relationships and considering miRNA influences with two available sub-mechanistic submodels. We introduce an approach to validate our findings using a biological interaction network, emphasizing the quality and relevance of identified gene-gene relationships. Metrics like the Matthews Correlation Coefficient (MCC) and the true discovery rate (TDR) further attest to the robustness of our findings.In summation, aside from improving the existing sub-mechanistic model that requires prior knowledge, this paper presents an innovative prior knowledge-free sub-mechanistic model as an alternative. It champions the use of biological networks for validation, underscoring the significance of methodological advancements in genomics research.

Radiation therapy is an effective cancer treatment, although damage to healthy tissues is common. Here we analyzed cell-free, methylated DNA released from dying cells into the circulation to evaluate radiation-induced cellular damage in different tissues. To map the circulating DNA fragments to human and mouse tissues, we established sequencing-based, cell-type-specific reference DNA methylation atlases. We found that cell-type-specific DNA blocks were mostly hypomethylated and located within signature genes of cellular identity. Cell-free DNA fragments were captured from serum samples by hybridization to CpG-rich DNA panels and mapped to the DNA methylation atlases. In a mouse model, thoracic radiation-induced tissue damage was reflected by dose-dependent increases in lung endothelial and cardiomyocyte methylated DNA in serum. The analysis of serum samples from patients with breast cancer undergoing radiation treatment revealed distinct dose-dependent and tissue-specific epithelial and endothelial responses to radiation across multiple organs. Strikingly, patients treated for right-sided breast cancers also showed increased hepatocyte and liver endothelial DNA in the circulation, indicating the impact on liver tissues. Thus, changes in cell-free methylated DNA can uncover cell-type-specific effects of radiation and provide a readout of the biologically effective radiation dose received by healthy tissues.

Hepatocellular carcinoma (HCC) has been an approved indication for the administration of immunotherapy since 2017, but biomarkers that predict therapeutic response have remained limited. Understanding and characterizing the tumor immune microenvironment enables better classification of these tumors and may reveal biomarkers that predict immunotherapeutic efficacy. In this paper, we applied a cell-type deconvolution algorithm using DNA methylation array data to investigate the composition of the tumor microenvironment in HCC. Using two publicly available datasets with a total cohort size of 57 patients, each with tumor and matched normal tissue samples, we identified key differences in immune cell composition. We found that NK cell abundance was significantly decreased in HCC tumors compared to adjacent normal tissue. We also applied DNA methylation "clocks" which estimate phenotypic aging and compared these findings to expression-based determinations of cellular senescence. Senescence and epigenetic aging was significantly increased in HCC tumors, and the degree of age acceleration and senescence was strongly associated with decreased NK cell abundance. In summary, we found that NK cell infiltration in the tumor microenvironment is significantly diminished, and that this loss of NK abundance is strongly associated with increased senescence and age-related phenotype. These findings point to key interactions between NK cells and the senescent tumor microenvironment and offer insights into the pathogenesis of HCC as well as potential biomarkers of therapeutic efficacy.

In this study, we found gene expression changes in key genes involved in activating immune pathways and genes targeted by SARS-CoV-2 to interfere with normal host cell functioning. Notably, critical changes have been observed in Eukaryotic Translation Initiation Factor 2 Alpha Kinase 2 (EIF2AK2), which plays an important role in activating the interferon response and interfering with host cell translational machinery in SARS-CoV-2 infection, 1,2,3 pre-senting a prospective therapeutic target. We demonstrated the therapeutic antiviral effect of the EIF2AK2 with its inhibitor compound C16, which showed strong antiviral potency in multiple antiviral assays. We genomics Our gene analysis several target genes and pathways well described in Our interaction analysis

Given the rapid spread of SARS-CoV-2 and rising death toll of COVID-19 in the currentabsence of effective treatments, it is imperative that therapeutics are developed and madeavailable to patients as quickly as possible. Publicly available COVID-19 patient data can be usedto identify host therapeutic targets, tailoring treatments to the disease signatures observed inpatients. In this study, we identify potential host therapeutic targets based on gene expressionalterations observed in COVID-19 patients. We analyzed RNAseq data from airway samples ofCOVID-19 patients and healthy controls to detect significantly differentially expressed genes andpathways that present potential therapeutic targets. Our analysis revealed expression changes inkey genes involved in activation of immune pathways, as well as genes targeted by SARS-CoV2 to interfere with normal host cell functioning. Critical changes were observed in a number ofgenes, including EIF2AK2, which was shown to play important roles in activating the interferonresponse and interfering with host cell translational machinery in SARS-CoV-2 infection,presenting a prospective therapeutic target. We also identified drugs with potential to modulatemultiple therapeutic targets within the most significant pathways. Our results both validate keygenes, pathways, and drug candidates that have been reported by other studies and suggestothers that have not been well-characterized and warrant further investigation by future studies.Further investigation of these therapeutic targets and their drug interactions may lead to effectivetherapeutic strategies to combat the current COVID-19 pandemic and protect against futureoutbreaks.

Angiotensin II can cause oxidative stress and increased blood pressure that result in long term cardiovascular pathologies. Here we evaluated the contribution of cellular senescence to the effect of chronic exposure to low dose angiotensin II in a model that mimics long term tissue damage. We utilized the INK-ATTAC (p16 Ink4a –Apoptosis Through Targeted Activation of Caspase 8) transgenic mouse model that allows for conditional elimination of p16 Ink4a -dependent senescent cells by administration of AP20187. Angiotensin II treatment for 3 weeks induced ATTAC transgene expression in kidneys but not in lung, spleen and brain tissues. In the kidneys increased expression of ATM, p15 and p21 matched with angiotensin II induction of senescence-associated secretory phenotype genes MMP3, FGF2, IGFBP2, and tPA. Senescent cells in the kidneys were identified as endothelial cells by detection of GFP expressed from the ATTAC transgene and increased expression of angiopoietin 2 and von Willebrand Factor, indicative of endothelial cell damage. Furthermore, angiotensin II induced expression of the inflammation-related glycoprotein versican and immune cell recruitment to the kidneys. AP20187-mediated elimination of p16-dependent senescent cells prevented physiologic, cellular and molecular responses to angiotensin II and provides mechanistic evidence of cellular senescence as a driver of angiotensin II effects.

Although single-gene perturbation screens have revealed a number of new targets, vulnerabilities specific to frequently altered drivers have not been uncovered. An important question is whether the compensatory relationship between functionally redundant genes masks potential therapeutic targets in single-gene perturbation studies. To identify digenic dependencies, we developed a CRISPR paralog targeting library to investigate the viability effects of disrupting 3,284 genes, 5,065 paralog pairs and 815 paralog families. We identified that dual inactivation of DUSP4 and DUSP6 selectively impairs growth in NRAS and BRAF mutant cells through the hyperactivation of MAPK signaling. Furthermore, cells resistant to MAPK pathway therapeutics become cross-sensitized to DUSP4 and DUSP6 perturbations such that the mechanisms of resistance to the inhibitors reinforce this mechanism of vulnerability. Together, multigene perturbation technologies unveil previously unrecognized digenic vulnerabilities that may be leveraged as new therapeutic targets in cancer.

The spread of SARS-CoV-2 and the increasing mortality rates of COVID-19 create an urgent need for treatments, which are currently lacking. Although vaccines have been approved by the FDA for emergency use in the U.S., patients will continue to require pharmacologic intervention to reduce morbidity and mortality as vaccine availability remains limited. The rise of new variants makes the development of therapeutic strategies even more crucial to combat the current pandemic and future outbreaks. Evidence from several studies suggests the host immune response to SARS-CoV-2 infection plays a critical role in disease pathogenesis. Consequently, host immune factors are becoming more recognized as potential biomarkers and therapeutic targets for COVID-19. To develop therapeutic strategies to combat current and future coronavirus outbreaks, understanding how the coronavirus hijacks the host immune system during and after the infection is crucial. In this study, we investigated immunological patterns or characteristics of the host immune response to SARS-CoV-2 infection that may contribute to the disease severity of COVID-19 patients. We analyzed large bulk RNASeq and single cell RNAseq data from COVID-19 patient samples to immunoprofile differentially expressed gene sets and analyzed pathways to identify human host protein targets. We observed an immunological profile of severe COVID-19 patients characterized by upregulated cytokines, interferon-induced proteins, and pronounced T cell lymphopenia, supporting findings by previous studies. We identified a number of host immune targets including PERK, PKR, TNF, NF-kB, and other key genes that modulate the significant pathways and genes identified in COVID-19 patients. Finally, we identified genes modulated by COVID-19 infection that are implicated in oncogenesis, including E2F7 and RB1, suggesting a mechanism by which cancer may arise in patients infected with SARS-CoV2. Further clinical investigation of these targets may lead to bonafide therapeutic strategies to treat the current COVID-19 pandemic and protect against future outbreaks and viral escape variants.

The spread of SARS-CoV-2 and the increasing mortality rates of COVID-19 create an urgent need for treatments, which are currently lacking. Although vaccines have been approved by the FDA for emergency use in the U.S., patients will continue to require pharmacologic intervention to reduce morbidity and mortality as vaccine availability remains limited. The rise of new variants makes the development of therapeutic strategies even more crucial to combat the current pandemic and future outbreaks. Evidence from several studies suggests the host immune response to SARS-CoV-2 infection plays a critical role in disease pathogenesis. Consequently, host immune factors are becoming more recognized as potential biomarkers and therapeutic targets for COVID-19. To develop therapeutic strategies to combat current and future coronavirus outbreaks, understanding how the coronavirus hijacks the host immune system during and after the infection is crucial. In this study, we investigated immunological patterns or characteristics of the host immune response to SARS-CoV-2 infection that may contribute to the disease severity of COVID-19 patients. We analyzed large bulk RNASeq and single cell RNAseq data from COVID-19 patient samples to immunoprofile differentially expressed gene sets and analyzed pathways to identify human host protein targets. We observed an immunological profile of severe COVID-19 patients characterized by upregulated cytokines, interferon-induced proteins, and pronounced T cell lymphopenia, supporting findings by previous studies. We identified a number of host immune targets including PERK, PKR, TNF, NF-kB, and other key genes that modulate the significant pathways and genes identified in COVID-19 patients. Finally, we identified genes modulated by COVID-19 infection that are implicated in oncogenesis, including E2F transcription factors and RB1, suggesting a mechanism by which SARS-CoV-2 infection may contribute to oncogenesis. Further clinical investigation of these targets may lead to bonafide therapeutic strategies to treat the current COVID-19 pandemic and protect against future outbreaks and viral escape variants.

Pathologic alterations in epigenetic regulation have long been considered a hallmark of many cancers, including hepatocellular carcinoma (HCC). In a healthy individual, the relationship between DNA methylation and microRNA (miRNA) expression maintains a fine balance; however, disruptions in this harmony can aid in the genesis of cancer or the propagation of existing cancers. The balance between DNA methylation and microRNA expression and its potential disturbance in HCC can vary by race. There is emerging evidence linking epigenetic events including DNA methylation and miRNA expression to cancer disparities. In this paper, we evaluate the epigenetic mechanisms of racial heterogenity in HCC through an integrated analysis of DNA methylation, miRNA, and combined regulation of gene expression. Specifically, we generated DNA methylation, mRNA-seq, and miRNA-seq data through the analysis of tumor and adjacent non-tumor liver tissues from African Americans (AA) and European Americans (EA) with HCC. Using mixed ANOVA, we identified cytosine-phosphate-guanine (CpG) sites, mRNAs, and miRNAs that are significantly altered in HCC vs. adjacent non-tumor tissue in a race-specific manner. We observed that the methylome was drastically changed in EA with a significantly larger number of differentially methylated and differentially expressed genes than in AA. On the other hand, the miRNA expression was altered to a larger extent in AA than in EA. Pathway analysis functionally linked epigenetic regulation in EA to processes involved in immune cell maturation, inflammation, and vascular remodeling. In contrast, cellular proliferation, metabolism, and growth pathways are found to predominate in AA as a result of this epigenetic analysis. Furthermore, through integrative analysis, we identified significantly differentially expressed genes in HCC with disparate epigenetic regulation, associated with changes in miRNA expression for AA and DNA methylation for EA.

PRMT5 is an essential arginine methyltransferase and a therapeutic target in MTAP-null cancers. PRMT5 uses adaptor proteins for substrate recruitment through a previously undefined mechanism. Here, we identify an evolutionarily conserved peptide sequence shared among the three known substrate adaptors (CLNS1A, RIOK1, and COPR5) and show that it is necessary and sufficient for interaction with PRMT5. We demonstrate that PRMT5 uses modular adaptor proteins containing a common binding motif for substrate recruitment, comparable with other enzyme classes such as kinases and E3 ligases. We structurally resolve the interface with PRMT5 and show via genetic perturbation that it is required for methylation of adaptor-recruited substrates including the spliceosome, histones, and ribosomal complexes. Furthermore, disruption of this site affects Sm spliceosome activity, leading to intron retention. Genetic disruption of the PRMT5-substrate adaptor interface impairs growth of MTAP-null tumor cells and is thus a site for development of therapeutic inhibitors of PRMT5.

PRMT5 is an arginine methyltransferase and a therapeutic target in MTAP null cancers. PRMT5 utilizes adaptor proteins for substrate recruitment through a previously undefined mechanism. Here, we identify an evolutionarily conserved peptide sequence shared among the three known substrate adaptors (pICln/CLNS1A, RIOK1 and COPR5) and show it is necessary and sufficient for interaction with PRMT5. We structurally resolve the interface with PRMT5 and show via genetic perturbation that it is required for methylation of adaptor-recruited substrates including the spliceosome, histones, and ribosome assembly complexes. Genetic disruption of the PRMT5-substrate adaptor interface leads to a hypomorphic decrease in growth of MTAP null tumor cells and is thus a novel site for development of therapeutic inhibitors of PRMT5.

Systems for CRISPR-based combinatorial perturbation of two or more genes are emerging as powerful tools for uncovering genetic interactions. However, systematic identification of these relationships is complicated by sample, reagent, and biological variability. We develop a variational Bayes approach (GEMINI) that jointly analyzes all samples and reagents to identify genetic interactions in pairwise knockout screens. The improved accuracy and scalability of GEMINI enables the systematic analysis of combinatorial CRISPR knockout screens, regardless of design and dimension. GEMINI is available as an open source R package on GitHub at https://github.com/sellerslab/gemini.