Discovery Of Targets Research Articles

Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression

Immunotherapy with chimeric antigen receptor T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify cancer specific exon targets, here we analyze 1532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We find 2933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n = 148) or the alternatively spliced isoform (n = 9) level. Expression of selected alternatively spliced targets, including the EDB domain of fibronectin 1, and gene targets, such as COL11A1, are validated in pediatric patient derived xenograft tumors. We generate T cells expressing chimeric antigen receptors specific for the EDB domain or COL11A1 and demonstrate that these have antitumor activity. The full target list, explorable via an interactive web portal (https://cseminer.stjude.org/), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.

Abstract ED09-01: Emerging approaches to targeting pathways using precision medicine in breast cancer

Abstract The past few decades have yielded significant strides forward in the pursuit to extend survival for patients with breast cancer. Much of this success is directly attributed to breakthroughs in the development of targeted therapies intersecting advances in genomic medicine. Despite these achievements, challenges remain, and targeted therapeutic development is still evolving rapidly to offset them. The focus of this educational session is centered around reviewing the latest in targeted therapeutic advancements and precision medicine. Recent advances have centered on novel selective estrogen receptor degraders (SERDs) for advanced ESR1-mutated or endocrine-resistant disease. Antibody-drug conjugates (ADCs) continued to make gains, targeting HER2-positive/low advanced cancers as well as an expanded indications for TROP2-targeted ADCs. New ADCs are also on the horizon leveraging new cell surface targets. Emerging are forward-looking cell-surface methodologies that harness bispecific antibodies and T-cell engagers. Various strategies combining established targeted immunotherapies such as PD-1 and PD-L1 with additional therapies continue. Attempts to target the frequently mutated PI3K pathway have yielded some success, but clinical exploration continues using new approaches that utilize mutation specific inhibitors. Second generation PARP inhibitors have emerged recently and are being explored in a variety of indications with promising early results. Finally, understanding treatment resistance in particular with the use of longitudinal liquid biopsies is fueling further target discovery. Altogether, development in precision medicine is advancing rapidly with advanced genomics, novel targets, and cutting-edge drug modalities. Citation Format: M. Radovich. Emerging approaches to targeting pathways using precision medicine in breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr ED09-01.

Abstract PO4-05-14: Gene expression in metastatic breast cancer – patterns and prognostic potential

Abstract Introduction Metastatic breast cancer (mBC) is the leading cause of breast cancer mortality. However, mBC has a considerable variance in prognosis and course of disease, reflecting a substantial biological heterogeneity. Despite this, there is a lack of prognostic biomarkers validated for mBC. New prognostic markers and improved understanding of the molecular variants of mBC could aid in prognostication and personalizing treatments, and lead to the discovery of novel drug targets. The primary objective of this study was to explore the prognostic value of gene expression (GEX) in the distant metastasis (DM) of mBC. Secondly, we aimed to identify molecular subtypes of mBC, and describe their biological niches. Methods We used a cohort of mBC patients enrolled in a prospective trial (NCT01322893) that includes tissue from primary tumor (PT) and matched lymph node metastasis (LNM) and/or DM (1). The inclusion criteria were diagnosed mBC with a life expectancy of >2 months, ECOG score of 0-2, and an age of >18 years. RNA was extracted from formalin-fixed, paraffin-embedded tumor tissue. GEX data were acquired for n=123 PT, n=71 LNM, and n=74 DM using the NanoString Breast Cancer 360 assay, which comprises 758 genes and >30 GEX signatures. The relationships between GEX and the endpoints overall survival (OS) and progression-free survival (PFS) were assessed using cox proportional hazards regression with GEX as a continuous score. Multivariable cox regressions were adjusted for PAM50 of the DM, number of metastatic sites, visceral metastasis, ECOG, and age at mBC diagnosis. Visualization by heatmap and k-means clustering were used to identify GEX patterns. When clustering single genes, we included only the 100 genes with the highest standard deviation. Results In relation to PFS, we found prognostically unfavorable roles of DM GEX of the signatures for Treg cells (HR=1.3, p=0.02), cytotoxicity (HR=1.3, p=0.03), and p53 (HR=1.3, p=0.02). Further, our data indicate prognostically favorable value of DM GEX of ESR1 (HR=0.77, p=0.02), PGR (HR=0.65, p=0.002), FOXA1 (HR=0.76, p=0.02), and AR (HR=0.68, p=0.0006). The prognostic value of AR remained in multivariable analysis. In relation to OS the first 2 years after mBC prognosis, we found prognostically favorable value of DM GEX of B7H3 (HR=0.65, p=0.04), TGFB (HR=0.53, p=0.02) and the signatures for stroma (HR=0.7, p=0.05) and claudin-low (HR=0.61, p=0.02). Finally, our data suggests that the previously published PAM50MET panel performs well as a prognostic indicator, especially when considered on a continuous scale, for PFS (HR=1.3, p=0.0023) and OS (HR=1.3, p=0.003) (2). Based on the 100 most highly variable genes, we identified five stable tumor clusters with distinct GEX profiles, where some strongly associated with metastatic site. Using the same approach on the GEX signatures, we established four GEX profiles able to outperform PAM50 in identifying tumors with poor OS in this material. Conclusion In this study, we demonstrate prognostic value for GEX-based panels in DM samples. First, we find GEX signatures related to hormone responsiveness to be favorable, and genetic instability to be unfavorable for mBC prognosis. We also demonstrate AR to be an independent marker for better PFS. Further, we confirm the prognostic value of PAM50MET, a previously published panel with the advantage of including only PAM50 genes and clinical parameters. Finally, we identify new GEX profiles related to metastatic site and outcome. These results illuminate the biological differences between mBC in relation to outcome and metastatic site. Better understanding of the mBC GEX subtypes may open new venues for tailored treatment.

HACD3 Prevents PB1 from Autophagic Degradation to Facilitate the Replication of Influenza A Virus

Influenza A virus (IAV) continues to pose serious threats to the global animal industry and public health security. Identification of critical host factors engaged in the life cycle of IAV and elucidation of the underlying mechanisms of their action are particularly important for the discovery of potential new targets for the development of anti-influenza drugs. Herein, we identified Hydroxyacyl-CoA Dehydratase 3 (HACD3) as a new host factor that supports the replication of IAV. Downregulating the expression of HACD3 reduced the level of viral PB1 protein in IAV-infected cells and in cells that were transiently transfected to express PB1. Silencing HACD3 expression had no effect on the level of PB1 mRNA but could promote the lysosome-mediated autophagic degradation of PB1 protein. Further investigation revealed that HACD3 interacted with PB1 and selective autophagic receptor SQSTM1/p62, and HACD3 competed with SQSTM1/p62 for the interaction with PB1, which prevented PB1 from SQSTM1/p62-mediated autophagic degradation. Collectively, these findings establish that HACD3 plays a positive regulatory role in IAV replication by stabilizing the viral PB1 protein.

Circular RNA PRKCI (hsa_circ_0067934): a potential target in the pathogenesis of human malignancies

Circular RNAs (circRNAs) are a new type of endogenous non-coding RNA formed by a covalent closed loop. CircRNAs are characterized by specificity, universality, conservation, and stability. They are abundant in eukaryotic cells and have biological regulatory roles at various transcriptional and post-transcriptional levels. The upregulation of circPRKCI has been observed in a variety of tumors and is directly related to the clinicopathological characteristics of tumors and prognosis. More importantly, circPRKCI can participate in the tumorigenesis, progression, recurrence, and metastasis of various tumors through many functional mechanisms, including the activation of signaling pathways, such as the phosphatidylinositol-3-kinase (PI3K)/AKT pathway, and sponging of many microRNAs (miRNAs). This review summarizes the progress achieved in understanding the biological functions of circRNA PRKCI in various tumors. The goal is to inform the discovery of more functional mechanisms and new anticancer molecular targets.

Systems Biology for Drug Target Discovery in Acute Myeloid Leukemia

Combining new therapeutics with all-trans-retinoic acid (ATRA) could improve the efficiency of acute myeloid leukemia (AML) treatment. Modeling the process of ATRA-induced differentiation based on the transcriptomic profile of leukemic cells resulted in the identification of key targets that can be used to increase the therapeutic effect of ATRA. The genome-scale transcriptome analysis revealed the early molecular response to the ATRA treatment of HL-60 cells. In this study, we performed the transcriptomic profiling of HL-60, NB4, and K562 cells exposed to ATRA for 3–72 h. After treatment with ATRA for 3, 12, 24, and 72 h, we found 222, 391, 359, and 1032 differentially expressed genes (DEGs) in HL-60 cells, as well as 641, 1037, 1011, and 1499 DEGs in NB4 cells. We also found 538 and 119 DEGs in K562 cells treated with ATRA for 24 h and 72 h, respectively. Based on experimental transcriptomic data, we performed hierarchical modeling and determined cyclin-dependent kinase 6 (CDK6), tumor necrosis factor alpha (TNF-alpha), and transcriptional repressor CUX1 as the key regulators of the molecular response to the ATRA treatment in HL-60, NB4, and K562 cell lines, respectively. Mapping the data of TMT-based mass-spectrometric profiling on the modeling schemes, we determined CDK6 expression at the proteome level and its down-regulation at the transcriptome and proteome levels in cells treated with ATRA for 72 h. The combination of therapy with a CDK6 inhibitor (palbociclib) and ATRA (tretinoin) could be an alternative approach for the treatment of acute myeloid leukemia (AML).

Metabolomics-driven discovery of therapeutic targets for cancer cachexia.

Cancer cachexia (CC) is a devastating metabolic syndrome characterized by skeletal muscle wasting and body weight loss, posing a significant burden on the health and survival of cancer patients. Despite ongoing efforts, effective treatments for CC are still lacking. Metabolomics, an advanced omics technique, offers a comprehensive analysis of small-molecule metabolites involved in cellular metabolism. In CC research, metabolomics has emerged as a valuable tool for identifying diagnostic biomarkers, unravelling molecular mechanisms and discovering potential therapeutic targets. A comprehensive search strategy was implemented to retrieve relevant articles from primary databases, including Web of Science, Google Scholar, Scopus and PubMed, for CC and metabolomics. Recent advancements in metabolomics have deepened our understanding of CC by uncovering key metabolic signatures and elucidating underlying mechanisms. By targeting crucial metabolic pathways including glucose metabolism, amino acid metabolism, fatty acid metabolism, bile acid metabolism, ketone body metabolism, steroid metabolism and mitochondrial energy metabolism, it becomes possible to restore metabolic balance and alleviate CC symptoms. This review provides a comprehensive summary of metabolomics studies in CC, focusing on the discovery of potential therapeutic targets and the evaluation of modulating specific metabolic pathways for CC treatment. By harnessing the insights derived from metabolomics, novel interventions for CC can be developed, leading to improved patient outcomes and enhanced quality of life.

Single-Nucleus Transcriptome Profiling from the Hippocampus of a PTSD Mouse Model and CBD-Treated Cohorts.

Post-traumatic stress disorder (PTSD) is the most common psychiatric disorder after a catastrophic event; however, the efficacious treatment options remain insufficient. Increasing evidence suggests that cannabidiol (CBD) exhibits optimal therapeutic effects for treating PTSD. To elucidate the cell-type-specific transcriptomic pathology of PTSD and the mechanisms of CBD against this disease, we conducted single-nucleus RNA sequencing (snRNA-seq) in the hippocampus of PTSD-modeled mice and CBD-treated cohorts. We constructed a mouse model by adding electric foot shocks following exposure to single prolonged stress (SPS+S) and tested the freezing time, anxiety-like behavior, and cognitive behavior. CBD was administrated before every behavioral test. The PTSD-modeled mice displayed behaviors resembling those of PTSD in all behavioral tests, and CBD treatment alleviated all of these PTSD-like behaviors (n = 8/group). Three mice with representative behavioral phenotypes were selected from each group for snRNA-seq 15 days after the SPS+S. We primarily focused on the excitatory neurons (ExNs) and inhibitory neurons (InNs), which accounted for 68.4% of the total cell annotations. A total of 88 differentially upregulated genes and 305 differentially downregulated genes were found in the PTSD mice, which were found to exhibit significant alterations in pathways and biological processes associated with fear response, synaptic communication, protein synthesis, oxidative phosphorylation, and oxidative stress response. A total of 63 overlapping genes in InNs were identified as key genes for CBD in the treatment of PTSD. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the anti-PTSD effect of CBD was related to the regulation of protein synthesis, oxidative phosphorylation, oxidative stress response, and fear response. Furthermore, gene set enrichment analysis (GSEA) revealed that CBD also enhanced retrograde endocannabinoid signaling in ExNs, which was found to be suppressed in the PTSD group. Our research may provide a potential explanation for the pathogenesis of PTSD and facilitate the discovery of novel therapeutic targets for drug development. Moreover, it may shed light on the therapeutic mechanisms of CBD.

Refining the impact of genetic evidence on clinical success.

The cost of drug discovery and development is driven primarily by failure1, with only about 10% of clinical programmes eventually receiving approval2-4. We previously estimated that human genetic evidence doubles the success rate from clinical development to approval5. In this study we leverage the growth in genetic evidence over the past decade to better understand the characteristics that distinguish clinical success and failure. We estimate the probability of success for drug mechanisms with genetic support is 2.6 times greater than those without. This relative success varies among therapy areas and development phases, and improves with increasing confidence in the causal gene, but is largely unaffected by genetic effect size, minor allele frequency or year of discovery. These results indicate we are far from reaching peak genetic insights to aid the discovery of targets for more effective drugs.

Application and difficulties of deep learning in drug target discovery

Application and difficulties of deep learning in drug target discovery

Abstract P29: GSTT2 AND THE RESPONSE TO BCG IMMUNOTHERAPY

Abstract Whilst M. bovis Bacillus Calmette-Guérin (BCG) therapy remains the gold-standard for treatment of high-risk non-muscle invasive bladder cancer (BC), 30-40% of patients fail therapy, resulting in disease recurrence and progression. A better understanding of the underlying mechanisms of BCG therapy can aid in revealing key response pathways, which may lead to the discovery of new targets, and in turn new approaches to treat BC. The glutathione-S-transferase theta 2 (GSTT2) gene is a member of the GST family. Loss of GSTT2 expression has been associated with modulation of intracellular ROS and BCG survival in BC cell lines. Retrospective analysis of BC patients revealed that patients with the GSTT2B deletion responded better to fewer instillations of BCG. To understand these responses, wild-type (WT) and GSTT2-knockout (KO) mice were implanted with MB49-PSA BC cells, in subcutaneous and orthotopic settings. Once tumors were established, the mice were treated with four weekly BCG instillations, after which the subcutaneous tumors and bladders were harvested for downstream analysis. Single-cell RNA sequencing of whole-bladders was used to identify specific cell clusters within the bladder, and to analyze differential gene expression. Hmga2, Ahnak and Peak1 were found to be differentially expressed in bladders from WT and GSTT2-KO mice. These genes are known to be involved in pro- and anti-tumorigenic pathways such as epithelial-mesenchymal transition and inflammation. Additionally, quantitative real-time PCR analysis in the subcutaneous and orthotopic tumors revealed differences in the expression of immune-related genes, especially markers of immune exhaustion such as PD-L1 and CTLA-4. Flow cytometry analysis of subcutaneous tumors also revealed differences in T-cell infiltration. Thus, loss of GSTT2 may influence the response to BCG therapy, through modulating downstream signaling pathways and immune responses. Elucidating such pathways can lead to a better understanding of the mechanism of BCG and its role as a therapy for BC. Citation Format: Mugdha Patwardhan, Kane Toh, Edmund Chiong, Ratha Mahendran. GSTT2 AND THE RESPONSE TO BCG IMMUNOTHERAPY [abstract]. In: Proceedings of Frontiers in Cancer Science; 2023 Nov 6-8; Singapore. Philadelphia (PA): AACR; Cancer Res 2024;84(8_Suppl):Abstract nr P29.

Integrating Multi-omics Data for Alzheimer's Disease to Explore Its Biomarkers Via the Hypergraph-Regularized Joint Deep Semi-Non-Negative Matrix Factorization Algorithm.

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disorder. Its etiology may be associated with genetic, environmental, and lifestyle factors. With the advancement of technology, the integration of genomics, transcriptomics, and imaging data related to AD allows simultaneous exploration of molecular information at different levels and their interaction within the organism. This paper proposes a hypergraph-regularized joint deep semi-non-negative matrix factorization (HR-JDSNMF) algorithm to integrate positron emission tomography (PET), single-nucleotide polymorphism (SNP), and gene expression data for AD. The method employs matrix factorization techniques to nonlinearly decompose the original data at multiple layers, extracting deep features from different omics data, and utilizes hypergraph mining to uncover high-order correlations among the three types of data. Experimental results demonstrate that this approach outperforms several matrix factorization-based algorithms and effectively identifies multi-omics biomarkers for AD. Additionally, single-cell RNA sequencing (scRNA-seq) data for AD were collected, and genes within significant modules were used to categorize different types of cell clusters into high and low-risk cell groups. Finally, the study extensively explores the differences in differentiation and communication between these two cell types. The multi-omics biomarkers unearthed in this study can serve as valuable references for the clinical diagnosis and drug target discovery for AD. The realization of the algorithm in this paper code is available at https://github.com/ShubingKong/HR-JDSNMF .

Deciphering Ferroptosis: From Molecular Pathways to Machine Learning-Guided Therapeutic Innovation.

Ferroptosis is a unique form of cell death reliant on iron and lipid peroxidation. It disrupts redox balance, causing cell death by damaging the plasma membrane, with inducers acting through enzymatic pathways or transport systems. In cancer treatment, suppressing ferroptosis or circumventing it holds significant promise. Beyond cancer, ferroptosis affects aging, organs, metabolism, and nervous system. Understanding ferroptosis mechanisms holds promise for uncovering novel therapeutic strategies across a spectrum of diseases. However, detection and regulation of this regulated cell death are still mired with challenges. The dearth of cell, tissue, or organ-specific biomarkers muted the pharmacological use of ferroptosis. This review covers recent studies on ferroptosis, detailing its properties, key genes, metabolic pathways, and regulatory networks, emphasizing the interaction between cellular signaling and ferroptotic cell death. It also summarizes recent findings on ferroptosis inducers, inhibitors, and regulators, highlighting their potential therapeutic applications across diseases. The review addresses challenges in utilizing ferroptosis therapeutically and explores the use of machine learning to uncover complex patterns in ferroptosis-related data, aiding in the discovery of biomarkers, predictive models, and therapeutic targets. Finally, it discusses emerging research areas and the importance of continued investigation to harness the full therapeutic potential of targeting ferroptosis.

Effect of coffee, tea and alcohol intake on circulating inflammatory cytokines: a two sample-Mendelian randomization study.

Despite the abundance of research examining the effects of coffee, tea, and alcohol on inflammatory diseases, there is a notable absence of conclusive evidence regarding their direct causal influence on circulating inflammatory cytokines. Previous studies have primarily concentrated on established cytokines, neglecting the potential impact of beverage consumption on lesser-studied but equally important cytokines. Information regarding the consumption of coffee, tea, and alcohol was collected from the UK Biobank, with sample sizes of 428,860, 447,485, and 462,346 individuals, respectively. Data on 41 inflammatory cytokines were obtained from summary statistics of 8293 healthy participants from Finnish cohorts. The consumption of coffee was found to be potentially associated with decreased levels of Macrophage colony-stimulating factor (β = -0.57, 95% CI -1.06 ~ -0.08; p = 0.022) and Stem cell growth factor beta (β = -0.64, 95% CI -1.16 ~ -0.12; p = 0.016), as well as an increase in TNF-related apoptosis-inducing ligand (β = 0.43, 95% CI 0.06 ~ 0.8; p = 0.023) levels. Conversely, tea intake was potentially correlated with a reduction in Interleukin-8 (β = -0.45, 95% CI -0.9 ~ 0; p = 0.045) levels. Moreover, our results indicated an association between alcohol consumption and decreased levels of Regulated on Activation, Normal T Cell Expressed and Secreted (β = -0.24, 95% CI -0.48 ~ 0; p = 0.047), as well as an increase in Stem cell factor (β = 0.17, 95% CI 0.02 ~ 0.31; p = 0.023) and Stromal cell-derived factor-1 alpha (β = 0.20, 95% CI 0.04 ~ 0.36; p = 0.013). Revealing the interactions between beverage consumption and various inflammatory cytokines may lead to the discovery of novel therapeutic targets, thereby facilitating dietary interventions to complement clinical disease treatments.

CDK4/6 inhibition sensitizes MEK inhibition by inhibiting cell cycle and proliferation in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is not sensitive to most chemotherapy drugs, leading to poor chemotherapy efficacy. Recently, Trametinib and Palbociclib have promising prospects in the treatment of pancreatic cancer. This article aims to explore the effects of Trametinib on pancreatic cancer and address the underlying mechanism of resistance as well as its reversal strategies. The GDSC (Genomics of Drug Sensitivity in Cancer) and CTD2 (Cancer Target Discovery and Development) were utilized to screen the potential drug candidate in PDAC cell lines. The dose-increase method combined with the high-dose shock method was applied to induce the Trametinib-resistant PANC-1 and MIA PaCa-2 cell lines. The CCK8 proliferation assay, colony formation assay, flow cytometry, and western blot were conducted to verify the inhibitory effect of Trametinib and Palbociclib. RNA-seq was performed in resistant PDAC cell lines to find the differential expression genes related to drug resistance and predict pathways leading to the reversal of Trametinib resistance. The GDSC and CTD2 database screening revealed that Trametinib demonstrates a significant inhibitory effect on PDAC. We found that Trametinib has a lower IC50 than Gemcitabine in PDAC cell lines. Both Trametinib and Gemcitabine can decrease the proliferation capacity of pancreatic cells, induce cell cycle arrest, and increase apoptosis. Simultaneously, the phosphorylation of the AKT and ERK pathways were inhibited by the treatment of Trametinib. In addition, the RNA-seq of Trametinib-induced resistance PDAC cell lines reveals that the cyclin-dependent kinase (CDK)-RB-E2F regulatory axis and G2/M DNA damage checkpoint might lead the drug resistance. Besides, the combination of Trametinib with Palbociclib could inhibit the proliferation and cell cycle of both resistant cells lines and also restore the sensitivity of drug-resistant cells to Trametinib. Last but not least, the interferon-α and interferon-γ expression were upregulated in resistance cell lines, which might lead to the reversal of drug resistance. The study shows Trametinib has a critical inhibitory effect on PDAC. Besides, the combination of Trametinib with Palbociclib can inhibit the proliferation of PDAC-resistant cells.

Spinal Meningiomas: A Comprehensive Review and Update on Advancements in Molecular Characterization, Diagnostics, Surgical Approach and Technology, and Alternative Therapies.

Spinal meningiomas are the most common intradural, extramedullary tumor in adults, yet the least common entity when accounting for all meningiomas spanning the neuraxis. While traditionally considered a benign recapitulation of their intracranial counterpart, a paucity of knowledge exists regarding the differences between meningiomas arising from these two anatomic compartments in terms of histopathologic subtypes, molecular tumor biology, surgical principles, long-term functional outcomes, and recurrence rates. To date, advancements at the bench have largely been made for intracranial meningiomas, including the discovery of novel gene targets, DNA methylation profiles, integrated diagnoses, and alternative systemic therapies, with few exceptions reserved for spinal pathology. Likewise, evolving clinical research offers significant updates to our understanding of guiding surgical principles, intraoperative technology, and perioperative patient management for intracranial meningiomas. Nonetheless, spinal meningiomas are predominantly relegated to studies considering non-specific intradural extramedullary spinal tumors of all histopathologic types. The aim of this review is to comprehensively report updates in both basic science and clinical research regarding intraspinal meningiomas and to provide illustrative case examples thereof, thereby lending a better understanding of this heterogenous class of central nervous system tumors.

Abstract LB331: Integrating multiple spatial transcriptomic and proteomic technologies to generate a cancer atlas to understand the tumor microenvironment

Abstract Deep single-cell genomics has provided a monumental leap in our understanding and categorical analysis of cancer cells and their unique molecular properties. With spatial platforms that preserve the tissue architecture, an emerging understanding of complex cell interactions and local environment influences is providing new perspectives for targeted therapies. Here we describe a comprehensive approach at profiling the tumor immune microenvironment across multiple solid malignancies to provide an atlas of tumor biology. To generate this atlas, we created a MERFISH panel of 500 genes representing over 40 cell phenotyping pathways and dozens of signaling pathways including chemokines, cytokines, interferon, and ligand-receptor interactions. This panel was used across 15 patients representing multiple solid malignancies. We also utilized the Immuno-Oncology focused Xenium panel to profile 16 different patients across the same indications. With the Xenium data we simultaneously assessed proteomic expression using a 16 plex panel focused on immuno-oncology targets and subsequently did H&E staining, allowing multiple -omic data collections within a single slide. After initial filtering and quality control this projects produced a total dataset with over 15 million cells and billions of transcripts. The 500 gene MERFISH panel revealed complex relationships between diverse cell types within the tumor microenvironment that was dependent on cellular location and surrounding area. While the presence of major immune cell types was observed in all cancer tissues, the ratio and spatial relationship to cancer cells differed between each tumor. Accordingly, we observed that differences in cellular composition of the microenvironment corresponded with associated changes in cellular signaling. Similarly, with Xenium we identified new spatial relationships between cancer and immune cells with their environment while confirming part of these relationships with subsequent immunofluorescence data. The H&E data provided an opportunity to overlay this data with standard pathological annotation. We further investigated how each cellular microneighborhood varied throughout the tumor and varied from patient. This comprehensive map of the tumor immune microenvironment is a deep cellular dive into cellular architecture. As this Cancer Atlas evolves this will drive the discovery of several new potential biological targets and cell types of interest. This will also be critical for the assessment of current cellular and drug therapies in preclinical and clinical models. This effort will continue with more patient samples across a greater number of disease indications and will include more technologies. We will also expand the development and implementation of analytical tools to maximum the knowledge and insights gained from this Atlas. Together, this will be a critical tool in the continuing fight against cancer. Citation Format: Colles Price, Kazuho Nishimura, Som Bandyopadhyay, Darrell Borger, Russell Weiner. Integrating multiple spatial transcriptomic and proteomic technologies to generate a cancer atlas to understand the tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB331.

Abstract LB211: Genetic complexity in OSCC metastasis: From transcription factors to novel therapeutic targets

Abstract Background: The survival of patients with oral cavity squamous cell carcinoma (OSCC) is largely influenced by the extent of locoregional recurrence. Recurrence after standard therapy occurs in about 30% of patients with late-stage OSCC, highlighting the challenge in managing this aggressive form of cancer. The transition of cells from an epithelial to mesenchymal phenotype is a critical event in OSCC invasion and metastasis and is governed by a complex interplay of genes and signaling pathways, with transcription factors such as ZEB1/2 and SNAI1/2 being pivotal players in this process. However, these transcription factors have proven challenging to target therapeutically, and it is likely that additional genes play crucial roles in OSCC pathology. Furthermore, the biology of locoregionally aggressive OSCC cancer cells is poorly understood, and this gap in knowledge is critical to predicting patient outcomes and improving treatment. This lack of understanding underscores the need for further research into identifying the specific molecular mechanisms and genetic factors that drive the locoregional aggressiveness of OSCC. Objective: To evaluate the impact of individual genes on OSCC cell migration, perform a comprehensive analysis of gene-specific effects on cell migration, and develop a valuable platform for the discovery of potential therapeutic targets. Methods: Our lab has created an in vitro model system of “mesenchymal-like” OSCC which exhibits increased migration and chemotherapeutic resistance. Using this model, we generated several cell lines expressing either Cas9 or an activating dCas9. We next transfected genome wide sgRNA libraries. Using a transwell assay platform we are working to identify several key genes necessary for successful cell migration and genes that amplify OSCC cell migratory potential. Results: Our results indicate that OSCC invasion and regional metastasis is a multifaceted process influenced by a network of genes beyond the well-known transcription factors. By subdividing gene expression changes based on E-cadherin protein expression, we are working to therapeutically isolate genes that may be critical during the fleeting transition from an epithelial to mesenchymal phenotype necessary for aggressive OSCC biology. Conclusions: We have identified several genes whose knockout or activation resulted in a significant impact on cell migration, shedding light on potential candidates for therapeutic intervention. The findings from this study will open new avenues for the development of targeted therapies to improve the prognosis of OSCC patients by focusing on previously unexplored genes involved in the invasion and metastatic cascade. Citation Format: Guillermo Flores, Slyn Uaroon, Marisa Buchakjian. Genetic complexity in OSCC metastasis: From transcription factors to novel therapeutic targets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB211.

Abstract LB289: Single-cell CRISPR screens at scale to understand T cell biology

Abstract CRISPR screens have become the primary discovery engine in modern biology and are widely used to uncover novel targets in immuno-oncology. However, these genetic screens are usually coupled to rather simplistic read-outs such as cell fitness. In contrast, CROP-Seq (or “CRISPR Droplet” Sequencing) screens combine CRISPR perturbation with single-cell transcriptomics, enabling high-content phenotyping at single-cell resolution. Briefly, cells are perturbed with a pooled sgRNA library and transcriptomic profiles of each cell are recorded using conventional single-cell RNA sequencing platforms. Currently, the scale of these screens is limited to the perturbation of a couple of hundred genes, possibly up to 1.000 genes, because of increased costs for single-cell library preparation and next generation sequencing (NGS). At Myllia, we have built a platform allowing high-content CROP-Seq screens in both CRISPR-ready cancer cell lines as well as primary immune cells, e.g., human T cells. Using CRISPR KO, CRISPR interference or CRISPR activation workflows, we can help accelerate the identification of target genes and regulatory networks involved in immuno-oncology. Primary T cells are of great interest in the immunotherapy community as they are key players in autoimmune and inflammatory disease. Engineered T-lymphocytes such as CAR-T cells are currently developed as novel cellular medicines, yet many T cell-intrinsic features involved in CAR-T potency remain elusive. To enable the discovery of novel targets, we have performed multiple customized CROP-Seq CRISPR KO screens in primary human T cells investigating T cell stemness and effector phenotypes as well as CD4+ T helper cell differentiation towards Th1, Th2, or Th17 subsets. Here, we present screens for regulators of functional T cell plasticity and Th2 commitment in which we aimed to identify genes determining critical T cell fate decisions, potentially linking gene (dys)function to either autoimmune/inflammatory disease or functional persistence of cytotoxic T cells for cancer immunotherapy. Overall, the advanced CROP-Seq platform combining large-scale perturbations and targeted sequencing (TA) read-outs will catalyse a paradigm shift for CROP-Seq enabling high-throughput functional genomic screens that support the validation of drug targets in autoimmunity, inflammation and immuno-oncology. Citation Format: Nicole Untermoser, Johanna Irnstorfer, Anatoly Vasilyev, Nikola Vinko, Sumit Pawar, Anke Loregger, Adam Krejci, Henrik Schmidt, Tilmann Bürckstümmer. Single-cell CRISPR screens at scale to understand T cell biology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB289.

Abstract LB432: Identification of novel drug targets using the ADAPT biotargeting system on FFPE tissue from patients with glioblastoma multiforme

Abstract Glioblastoma Multiforme (GBM) is one of the most aggressive and lethal brain tumor types with a five-year survival rate of 6.9%. In 2023, more than 14,490 Americans were expected to receive a diagnosis. Although great progress has been achieved in protein target identification and treatment over the last few years, current treatment options are limited, and tumor recurrence occurs at a high rate due to treatment resistance. Aptamers, short single-stranded oligonucleotide ligands with high-affinity binding to molecular targets, are well suited tools for exploring novel targets in highly heterogeneous tumors with complex etiologies like GBM, where clinically relevant biomarkers are limited. In this study, aptamer-based cancer-specific drug target identification was performed by Adaptive Dynamic Artificial Polyligand Targeting (ADAPT) Biotargeting System. In short, a GBM-specific library was enriched through a Systematic Evolution of Ligands by EXponential enrichment (SELEX) process using micro dissected Formalin-Fixed Paraffin-Embedded (FFPE) tissues from GBM patients, along with whole body normal tissue for counterselection. Microdissection of tissue allows the partitioning of different types of cells to focus on specific cells of interest. The enriched libraries have been evaluated on clinical GBM and normal brain control samples through aptamer mediated tissue staining, resulting in preferential binding of enriched libraries compared to controls in the vast majority of GBM patients with little binding to normal brain samples. The final library was subsequently applied in an in-house developed library-based affinity pull-down assay using lysates from FFPE tissue of the same group of GBM patients and normal brain samples, followed by unbiased Mass Spectrometry for protein target identification. Combining the results from this proteomics analysis and data from the internal Whole Transcriptome Sequencing (WTS) database, we were able to identify several targets that are highly expressed in GBM and other cancer lineages. Antibody staining provided further validation of the expression levels and the cellular localization. The targets identified in this study include not only potential novel therapeutic targets, but also well-studied biomarkers and targets with available drugs already in clinical trials, demonstrating the platform has great potential for identifying high affinity binding and selectivity compared to traditional proteomics and other methods in drug target discovery. Citation Format: Xixi Wei, Myunggi An, Radhika Santhanam, Barbara Richardson, Lucas Vu, Justin Saul, Anna Walton, Michael Gee, Daniel Martin, Amanda Hubbard, Alexis Rodin, Matthew Rosenow, Tassilo Hornung. Identification of novel drug targets using the ADAPT biotargeting system on FFPE tissue from patients with glioblastoma multiforme [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB432.