Scientific Sessions: U54 and Lightning Talk Presenters

Exploring the epigenetic landscape and metastatic potential of MDA-MB21 tumor cells grown on different substrate stiffness in 2D and 3D environments. (Lighting Talk)

Nicolas Acosta , Northwestern University , (MetNet)

Recent studies have highlighted the importance of mechanical stiffness in shaping nuclear architecture and cellular behavior. This study employs multi-label single-molecule localization microscopy (SMLM) in both 2D and 3D environments to investigate how substrate stiffness influences chromatin organization in MDA-MB-231 breast cancer and HCT116 colorectal cancer cell lines. Using innovative 3D microvascular models and 2D hydrogel substrates of varying stiffness, we observed that cells grown on stiffer substrates form smaller, less dense heterochromatic clusters. We combined super-resolution imaging techniques to examine chromatin structure through EdU labeling and multi-label permutations of histone modifications (H3K9me3, H3K27ac, H3K4me3, H3K27me3) and RNA Polymerase II (RNAP II). This approach allowed us to visualize and quantify changes in chromatin organization at sub-20 nm resolution and investigate spatial distribution of other epigenetic marks in relation to these heterochromatic landmark structures. Notably, in cells cultured on softer substrates, we observed a shift towards larger, denser heterochromatic clusters. Interestingly, RNAP II localization was found closer to the interface of these clusters in soft substrate conditions, suggesting a potential mechanism for transcriptional regulation in response to mechanical cues. These findings provide new insights into how mechanical forces influence nuclear architecture and gene expression in cancer cells. Understanding these mechanisms may reveal novel therapeutic targets for modulating cell behavior and combating metastasis.

Other Authors: Nicolas Acosta 1 , Elena Cambria 1 ,Luay Almassalha 1,2,3 , Roger Kamm 4,5,6 , Vadim Backman 1,2 1. Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA. 2. Center for Physical Genomics and Engineering, Northwestern University, Evanston, IL 60208, USA 3. Department of Gastroenterology and Hepatology, Northwestern Memorial Hospital, Chicago, IL 60611, USA 4. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. ecambria@mit.edu. 5. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. rdkamm@mit.edu. 6. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. rdkamm@mit.ed

The Delta Ecology of Non-Small Cell Lung Cancer (U54 Talk)

Alexander Anderson, Moffitt Cancer Center, (CSBC)

Tumors are not simply collections of transformed cells, rather they are organized into aberrant but still recognizable spatial micro-anatomical structures, made of not only neoplastic cells but also multiple normal cell types. The abnormal spatial organization and growth of neoplastic cells leads to gradients in metabolites, cytokines, nutrients, oxygen, etc. Many of these factors, as well as space, are essential ecological resources that can limit the survival and proliferation of neoplastic cells, thereby setting the scene for the “struggle for existence”. Together with anti-tumor host responses, such as immune attack and infiltration/encapsulation by fibroblasts, limited resources create selection pressures that drive cancer evolution. Neoplastic populations not only respond to their environment but also shape it, often resulting in “niche engineering” that facilitates progression and therapy resistance. Thus, cancers must be viewed as dynamic somatic ecosystems that change throughout cancer progression and therapy, shaping clinical outcomes. Here we investigate the dynamic interplay of the tumor-host ecosystem during uninterrupted growth and under treatment perturbations. Specifically, we consider the change in both immune and stromal ecology (Delta Ecology) of Non-Small Cell Lung Cancer to targeted and immune therapies. Using multiplex imaging, temporal patient samples, preclinical and mathematical model systems we investigate how tissue ecology pre and on treatment can be used to stratify patients, direct treatment decisions and predict treatment dosing and scheduling that minimizes drug resistance an prolongs response.

Other Authors: -

Identifying regulators of intratumor heterogeneity in early-stage melanoma (U54 Talk)

Paola Angulo Salgado, NYU Langone Health, (MetNet)

Most early-stage melanoma patients can be cured with surgical resection of their primary lesion, but some will recur with metastatic disease. Although these patients might benefit from adjuvant therapy, we still lack biomarkers to identify patients who need additional treatment. Because early-stage melanomas are small and rarely available for preclinical studies, we developed a lineage-traceable melanoma mouse model that recapitulates the histopathology of human patients. Here, we defined melanoma and stromal cell types we collected at different time points of melanoma development, and we characterized them by single-cell RNA-sequencing. Our analyses of real-time and pseudo-time data suggest that multipotent melanocytic melanoma cells de-differentiate into neural crest-like and mesenchymal melanoma cell states. We identified gene regulatory networks and cell-cell communication systems that could regulate their de-differentiation and co-evolution with stromal cell types. We are validating these findings with spatial transcriptomics in primary melanoma tissues of human patients, and we are defining their functions in genetically and transcriptionally characterized short-term cultures and xenograft models. We expect these approaches will uncover how transformed melanocytes de-differentiate into various cell states and how this process affects their metastatic potential.

Other Authors: Tatsuya Ogawa, Rob Stagnitta, Pietro Berico, Katie Ventre, Milad Ibrahim, Shi Qiu, Iman Osman, Amanda W. Lund, Mayumi Ito, Eva Hernando, and Markus Schober.

Transcriptomic analysis of cell-free RNA extracted from the cerebrospinal fluid of patients with brain metastases (Lighting Talk)

Giuseppe Barisano, Stanford University , (MetNet)

Molecular studies of brain metastases (BrM) in humans are challenged by the limited availability of research samples, which represents a significant obstacle to the advancement in understanding and treatment of BrM. Cerebrospinal fluid (CSF), circulating throughout the central nervous system (CNS) and interacting with brain tumors, represents a valuable but understudied biospecimen for investigating BrM. Compared with cell-free DNA, cell-free RNA (cfRNA) is more useful in tumors with inconsistent mutations, where therapy may affect gene expression, when testing tumor-brain cell interactions, or when investigating normal brain cell toxicity. While cfRNA has been extensively investigated as a potential source of biomarkers in other biological fluids, there is no established assay for transcriptomic analysis of cfRNA in CSF. Here we present CSF-Seq, a technique that combines total RNA extraction from human CSF with whole transcriptome RNA sequencing, allowing to analyze gene expression patterns in CSF cfRNA. CSF-Seq revealed distinct expression profiles in BrM, distinguishing it from both primary brain tumors and non-cancer controls. Cancer-associated genes like CEACAM6 and MUC1 were upregulated in lung and breast BrM samples, while brain-associated genes like MBP were detected in all CSF samples. These findings support the use of this technique to study gene expression signatures related to BrM progression, offering new insights for therapeutic advancement.

Other Authors: Giuseppe Barisano, Maxine Umeh-Garcia, Rukayat Taiwo, Elias Spiliotopoulos,

Daniel Herrick, Charlotte Weixel, Pablo Nunez, Bryanna Godfrey, Sophia Chernikova, Thy Trinh, Seunghyun Lee, Thuy Ngo, Melanie Hayden-Gephart

Dissecting subpopulation responses to therapy in triple negative breast cancer models (Lighting Talk)

Amy Brock, University of Texas at Austin , (CSBC)

Mechanisms of chemoresistance in TNBC patients remain poorly understood, in part due to a lack of available methods and models to measure intratumor heterogeneity and monitor changes in heterogeneous tumor compositions over time. We are using the ClonMapper platform to track individual cells and clones as they respond to different chemotherapeutic agents and to improve modeling of therapeutic response. We measure individual cell gene expression changes in response to treatment and then assemble these measurements into cell subpopulation trajectories, taking advantage of cell barcoding technology developed in the Brock lab to quantify clonally-resolved single cell transcriptomes. Using cell lines and patient-specific models, we are building a compendium of gene expression, cell growth and survival data that describes how each of the heterogeneous cells in personalized models of subtypes of triple negative breast cancer respond to therapeutic agents. The new ability to layer clonal identifier information on single cell gene expression data reveals the detailed trajectories of individual cells that escape therapy. It also distinguishes subpopulations with pre-existing treatment resistance from those in which a resistant state is induced. By integrating these new data types into a cohesive framework, we aim to describe how sensitive and resistant subpopulations in TNBC grow, die, and undergo transitions in response to treatment.

Other Authors: Thomas Yankeelov

The Cancer Systems Therapeutics Center (CaST) at Columbia University (U54 Talk)

Andrea Califano , Columbia University , (CSBC)

This talk will present a general overview of the integrative approaches that leverage structural and systems biology to identify and pharmacologically target key dependencies of cancer cells and of the tumor microenvironment. The talk will summarize some of the key accomplishments by the CaST center over the last year and provide pointers to some of the additional presentations, including talks and posters, by center members.

Other Authors: -

Plasma exosomes from individuals with type 2 diabetes drive breast cancer progression in patient-derived organoids (Lighting Talk)

Christina Ennis, Boston University , (CSBC)

Over 68 million American women with obesity-driven (Type 2) diabetes (T2D) and prediabetes are predisposed to more aggressive breast cancers. Despite this significant risk factor, metabolic status does not currently inform clinical management of breast cancer. We have previously identified circulating exosomes as crucial components of intercellular communication and potent modulators of pro-oncogenic processes. To accurately model this signaling within the human breast tumor microenvironment (TME), we developed a method to generate patient-derived organoids (PDOs) from breast tumor resection samples. Novel techniques and time limited development permit native primary immune cells to be included and profiled. Here, we explored the impact of exosomal signaling on these PDOs via single-cell RNA sequencing. Intratumoral heterogeneity of the PDOs underwent notable shifts during a 3-day exosome treatment, highlighting the impact of metabolic dysregulation on the cellular architecture and transcriptional networks of breast tumors. We discovered significant upregulation of pathways associated with epithelial-to-mesenchymal transition, invasiveness, cancer stemness, and immune exhaustion in PDOs treated with T2D-derived exosomes compared to non-diabetic exosome controls, indicating enhanced tumor aggressiveness and metastatic potential. Further, analysis of ligand-receptor interactions highlighted a significant downregulation of T cell signaling pathways, leading to immune exhaustion. This immune suppression likely permits the survival of micrometastases and could undermine the efficacy of immune checkpoint therapies, such as atezolizumab, approved for triple-negative breast cancer. Together, these findings enhance our understanding of dynamic interactions within the TME and offer new insights into the significance of novel exosomal communication on tumor biology.

Other Authors: Christina S. Ennis (*presenter), Michael Seen, Heejoo Kang, Andrew Chen, Adrian Ilinski, Kiana Mahdaviani, Naomi Ko, Stefano Monti, Christina Ennis

Active transcription and epigenetic reactions synergistically regulate meso-scale genomic organization in cancer cells

Monika Dhankhar, University of Pennsylvania, (MetNet)

In interphase nuclei, chromatin forms dense domains of characteristic sizes, but the influence of transcription and histone modifications on domain size is not understood. We present a theoretical model exploring this relationship, considering chromatin-chromatin interactions, histone modifications, and chromatin extrusion. We predict that the size of heterochromatic domains is governed by a balance among the diffusive flux of methylated histones sustaining them and the acetylation reactions in the domains and the process of loop extrusion via supercoiling by RNAPII at their periphery, which contributes to size reduction. Super-resolution and nano-imaging of five distinct cell lines confirm the predictions indicating that the absence of transcription leads to larger heterochromatin domains. Furthermore, the model accurately reproduces the findings regarding how transcription-mediated supercoiling loss can mitigate the impacts of excessive cohesin loading. Our findings shed light on the role of transcription in genome organization, offering insights into chromatin dynamics and potential therapeutic targets.

Other Authors: Aaysuh Kant, Vivek Shenoy

Suppression of epithelial proliferation and tumorigenesis by immunoglobulin A (Lighting Talk)

Gregory Donaldson, Rockefeller University ,( MetNet)

Immunoglobulin A (IgA) is the most abundant antibody isotype produced across mammals and plays a specialized role in mucosal homeostasis. Constantly secreted into the lumen of the intestine, IgA binds commensal microbiota to regulate their colonization and function, with unclear implications for health. IgA deficiency is common in humans but is difficult to study due to its complex etiology and comorbidities. Using genetically and environmentally controlled mice, here we show that IgA-deficient animals have a baseline alteration in the colon epithelium that increases susceptibility to multiple models of colorectal cancer. Transcriptome, imaging, and flow cytometry-based analyses revealed that, in the absence of IgA, colonic epithelial cells induce antibacterial factors and accelerate cell cycling in response to the microbiota. Oral treatment with IgA was sufficient to suppress aberrant epithelial proliferation independently of bacterial binding, suggesting that IgA provides a feedback signal to epithelial cells in parallel with its known roles in microbiome shaping. In a primary colonic organoid culture system, IgA directly suppresses epithelial growth. Conversely, the susceptibility of IgA-deficient mice to colorectal cancer was reversed by Notch inhibition to suppress the absorptive colonocyte developmental program, or by inhibition of the cytokine MIF, the receptor for which was upregulated in stem cells of IgA-deficient animals. These studies demonstrate a homeostatic function for IgA in tempering physiological epithelial responses to microbiota to maintain mucosal health.

Other Authors: Gabriella Reis, Marwa Saad, Izabela Mamede, Guo Chen, Nicole DelGaudio, Dayu Zhang, Begüm Aydin, Caroline Harrer, Tiago Castro, Sergei Grivennikov, Bernardo Reis, Beth Stadtmueller, Gabriel Victora, Daniel Mucida

Modeling Genetic Subclones and Transcriptional Programs in IPMN Progression to High-Grade Dysplasia (Lighting Talk)

Rachel Karchin, Johns Hopkins University , (CSBC)

Pancreatic ductal adenocarcinoma (PDAC) is highly lethal, with a low five-year survival rate. A significant subset arises from intraductal papillary mucinous neoplasms (IPMN), cystic precursor lesions detectable via imaging, allowing early intervention through pancreatic resection. Understanding the genetic and transcriptional changes driving IPMN progression from low-grade to high-grade dysplasia is essential for targeted interventions.

We are conducting multi-region whole exome and transcriptome sequencing on IPMN samples harboring low-grade dysplasia (LGD) and high-grade dysplasia (HGD). Our goal is to uncover the mechanisms behind this progression by identifying transcriptional programs contributing to the expansion of specific clones. To achieve this, we combine two computational approaches: CoGAPS, a Bayesian method that deconvolves transcriptome data into latent transcriptional patterns, and PICTograph, which models the genetic subclonal architecture of neoplasms.

As proof of concept, we analyzed public bulk DNA and RNA sequencing data from 11 patients. Initial findings showed minimal transcriptional heterogeneity across the cohort, but mapping patterns onto individual subclones revealed intra-patient heterogeneity. To further explore these differences, we are applying Visium HD technology to IPMN tissue sections, allowing spatial localization of subclones and transcriptional patterns. This enables us to examine spatial relationships between subclones, transcriptional programs, and their interactions with the tumor microenvironment.

Other Authors: Jiaying Lai, Kathleen Noller, Prathima Nagendra, Robert Scharpf, Luciane Kagohara, Laura Wood, Elana Fertig, Rachel Karchin

Institute for Computational Medicine

Department of Biomedical Engineering

Department of Oncology

Department of Pathology

Johns Hopkins University and Medicine

Identifying and exploiting mechano-chemical vulnerabilities during metastatic organ colonization (U54 Talk)

Peter Friedl, Radboud University Medical Centre, (MetNet)

Cancer cells experience a variety of stressors during metastasis, each of which represents a low probability event and a major barrier to survival. Using tumor cell analysis in vascularized 3D models of extravasation, in vivo analysis of metastasis in mouse models, and computational modeling, we here investigate how cancer cell subpopulations cope with intravascular and extravasation stressors. We explore targeted perturbations to limit metastasis and analyze the corresponding changes in phenotype. Our recent integrated analyses identified the Rho/ROCK pathway, preconditioning by stiff substrate, and the production of reactive oxygen species and changes of chromatin organization as important responses and modulators of tumor cell ability to extravasate and survive in the secondary organ. We identified tumor cell fragmentation as a previously unappreciated process presenting a major impediment to tumor cell survival and organ colonization. Both tumor cell deformation and fragmentation are enhanced by pharmacological inhibition of ROCK. Both the tumor cell mechanical deformation and fragmentation and its dependence on ROCK inhibition were captured in a computational model. The adaptive programs underlying tumor cell survival during extravasation and early organ colonization were further analyzed using single-cell transcriptomics, identifying cytoskeletal programs and cell detoxification as significantly regulated pathways. Molecular interventions against identified regulated pathways will enable the identification of molecular mechanisms of mechano-adaptation and adaptation to environmental stress and, using suitable antagonization, limit de-novo organ colonization and metastasis by circulating tumor cells.

Other Authors: U54 MetNet Center at MIT, UPENN, Northwestern, RadboudUMC

Systems analysis of mechanisms driving response to immunotherapy in clear cell cancers (Lighting Talk)

Andrew Gentles , Stanford University, (CSBC)

Clear cell ovarian cancer (ccOC) is a rare and lethal cancer with few treatment options. Based on molecular analysis ccOC has an immunosuppressive tumor microenvironment, similar to other ovarian cancer types. However, ccOC is very distinct from high grade serous ovarian carcinoma. Strikingly, it is similar in gene expression profiles to more frequent clear cell renal cell carcinomas (ccRCC), suggesting that clear cell cancers share intrinsic mechanistic or microenvironment properties, not just morphological appearance. Around 25% of ccRCC respond well to immune checkpoint inhibitors (ICIs), but markers for predicting response are lacking. We are taking systems biology approaches to (i) elucidate and compare the cell types and their transcriptional states present in ccOC and ccRCC; (ii) characterize the spatial architecture of these cells within tumors using the CODEX (CODetection by indEXing) single cell proteomic imaging platform; and (iii) model and validate cell-cell interactions in the spatial tumor microenvironment that drive clear cell cancer response to immunotherapy. Based on archival FFPE samples from both cancers we are using scRNA-seq, snRNA-seq, bulk RNA-seq, TCR-seq, exome sequencing, as well as spatial transcriptomics and proteomics to identify common features and mechanisms between these clear cell cancers. Our approach aims to open new avenues for treatment, particularly in rare cancer types.

Other Authors: -

The ST-Analytics U54 program: Towards Understanding the Benefits of Sequencing Cancer Immunotherapy with Targeted Inhibitors for Tumor Eradication (U54 Talk)

James Heath, Institute for Systems Biology, (CSBC)

The ST-Analytics U54 program within the CSBC network is a collaborative effort between the Institute for Systems Biology, Yale University, and the UCLA School of Medicine. The primary goal of our program is to quantitatively understand how the sequencing of cancer immunotherapies with targeted inhibitors can lead to durable therapy responses for certain tumors, even in cases where those same therapies, used either individually or in combination, are ineffective. To achieve this goal, we have assembled a collaborative group with expertise in clinical oncology and syngenetic murine models of cancer, expertise in spatial multiomics profiling of tissues, and expertise in the development of computational pipelines for guiding both data collection and analysis. A particular technology focus of our program has been to apply spatial epigenetic profiling of tumor sections as a tool that can provide insights into both the differentiation states and spatial distributions of both immune cells and tumor cells within the tumor microenvironment. To aid in the interpretation of this data, we have combined spatial-ATAC-seq with other imaging modalities, including AI-interpreted H&E stained tissues, and multiplex IHC imaging through CODEX or multicolor fluorescence microscopy. I will briefly discuss recent results from our program, as well as emerging computational pipelines for spatial data analysis and integration.

Other Authors: Jim Heath 1 (presenter), Roger Lo 2 , Gastien Moriceau 2 , Zhentao Yang 2 , Rong Fan 3 , Chong Xia 3 , Wei Wei 1 , Chong Xia 3 , Shuho Wang 3 , Juho Kim 3 , Sarah Li 3 , Vesteinn Thorsson 3 , Yin Tang 3 , David Gibbs 3 , and Raphael Levine 2

1 Institute for Systems Biology, 401 Terry Ave. N, Seattle, WA

2 UCLA Geffen School of Medicine

3 Yale University Dept. of Bioengineering/p>

Assessment of E-cadherin dynamics and metastatic trajectories in a mouse model of luminal breast cancer (Lighting Talk)

Ryan Huizar, Johns Hopkins Medical School , (MetNet)

E-cadherin, a key cell adhesion protein, exhibits a complex and context-dependent role in metastasis, though its precise function remains unclear. Using a combination of imaging and transcriptional analysis in a luminal breast cancer mouse model (MMTV-PyMT), we investigate the heterogeneity and dynamic regulation of E-cadherin. We identify two distinct cellular states within primary tumors, termed mEcad-Lo and mEcad-Hi, based on differential subcellular localization of E-cadherin. The mEcad-Lo state is characterized by increased invasiveness and an epithelial-mesenchymal transition (EMT) transcriptional profile, while the mEcad-Hi state correlates with enhanced proliferation. Notably, cells are capable of transitioning between these states in response to environmental cues. Bulk RNA-sequencing of the mEcad-Lo and mEcad-Hi populations reveals distinct transcriptional signatures linked to invasion and spatial organization within primary tumors. mEcad-Lo populations show enriched expression of EMT and angiogenesis-related transcripts. Inhibition of angiogenic pathways reduces cancer cell invasion, underscoring the importance of these pathways in the invasive behavior of cancer cells in isolation of the endothelium. Moreover, we identify upregulation of notch-delta family members in mEcad-Lo populations, specifically in perivascular epithelial cells. Knockdown of these pathways enhances EMT heterogeneity ex vivo, inducing a strongly mesenchymal phenotype, suggesting that notch-delta signaling maintains a hybrid epithelial/mesenchymal (E/M) state in this model of luminal breast cancer. Collectively, these findings underscore the multifaceted role of E-cadherin in metastasis and provide insights into the epithelial state transitions that cells undergo during the metastatic cascade.

Other Authors: James McCann, Andrew Ewald

Tumor hybrid cells in metastasis (Lighting Talk)

Chia-Nung Hung , UT Health San Antonio , (MetNet)

Inappropriate cell fusions during tumorigenesis can lead to the formation of hybrid cells that may be more malignant than their parental counterparts. Our recent study showed that low CD47-expressing cancer cells permit phagocytosis; however, reverse signaling can delay this process, resulting in incomplete digestion and tumor hybrid cells (THCs) formation. Viable THCs upregulate genes related to M1- and M2-like macrophage polarization via acquiring c-Myc from parent cancer cells. This dual macrophage mimicry allows THCs to evade immunosurveillance, providing a survival advantage. Notably, THCs have been identified in metastatic lesions. Our preliminary results using a bone metastatic xenograft mouse model showed mono- or di-nucleated osteoclast-like THCs (OTHCs) around trabecular and cortical bones expressing both osteoclast and cancer markers. These observations were confirmed in vitro through co-culturing osteoclast precursors and cancer cells. We hypothesize that cancer cells can influence osteoclast differentiation via paracrine signaling and may enhance osteoclast function through fusion, shifting functions from paracrine to autocrine and increasing bone resorption. Additionally, multi-omics analyses have been conducted to investigate further gene expression and functionality of OTHCs in mouse models and human samples, aiming to elucidate their role in bone metastasis.

Other Authors: -

Molecular Networks and Intelligent Systems for Precision Oncology (CCMI) (U54 Talk)

The mission of the Cancer Cell Map Initiative (CCMI) is to enable a new era of cancer discovery and treatment through the generation of multi-scale cancer cell maps and advancements to our DrugCell interpretable deep learning system for cancer precision medicine. Focusing on key cancer driver genes in lung cancer as well as the PIK3CA and TP53 pathways, CCMI projects and cores at UCSF, UCSD and Stanford University have developed an integrated multimodal platform leveraging comprehensive protein interaction network mapping, protein immunofluorescent imaging, cryo- electron microscopy and systematic genetic screening experiments. Our recent advances include systematic physical mapping of protein-protein interactions (PPIs) of key oncogenic drivers, and the application of AlphaFold-Multimer (AF) predictions to prioritize direct PPIs and variants for in-depth interrogations. We further integrated proteomic technologies with high-throughput multimodal imaging to generate deep spatial proteomic maps of thousands of proteins in breast cancer cells, acquired high-resolution structures of multi-protein PIK3CA complexes bound to lipid nanodiscs, and used CRISPRi synthetic lethal screens and peptile assays to identify cancer driver networks. Using our multiscale maps of tumor cell architecture (MuSIC), we modeled static structures of ordered protein complexes and developed deep learning models to predict immunotherapy responses using cancer mutations and tumor mutation burden. These systematic approaches mapping the molecular cancer networks will serve as key resources for precision medicine.

Other Authors: Nevan J. Krogan, University of California San Francisco

Agent-based Modeling of Dysregulated Cell Signaling and the Tumor-Immune Landscape Predicts New Possibilities for Combination Therapy (Lighting Talk)

Trachette Jackson , University of Michigan , (CSBC)

Mathematical models, specifically agent-based models (ABMs), have shown recent successes in uncovering the multiscale dynamics that shape the trajectory of cancer. They have enabled the optimization of treatment methods and the identification of novel therapeutic strategies. To assess the combined effects of anti-PD-1 and anti-FGFR3 small molecule inhibitors (SMI) on tumor growth and the immune response, this talk presents an ABM that captures key facets of tumor heterogeneity and CD8+ T cell phenotypes, their spatial interactions, and their response to therapeutic pressures. The model quantifies how tumor antigenicity and FGFR3 activating mutations impact disease trajectory and response to anti-PD-1 antibodies and anti-FGFR3 SMI. ABM simulations show that even a small population of weakly antigenic tumor cells bearing an FGFR3 mutation can render the tumor resistant to combination therapy. However, highly antigenic tumors can overcome therapeutic resistance mediated by FGFR3 mutation. The optimal treatment depends on the strength of the FGFR3 signaling pathway. Under certain conditions, ICI alone is optimal; in others, ICI followed by anti-FGFR3 therapy is best. These results indicate the need to quantify FGFR3 signaling strength and the fitness advantages conferred to cancer cells harboring this mutation. This ABM approach may enable rationally designed treatment plans to improve clinical outcomes, providing practical insights for cancer treatment strategies.

Other Authors: Daniel Bergman, Yixuan Wang, Erica Trujillo, Anthony Fernald, Lie Li, Alexander Pearson and Randy Sweis

Systems modeling of a mitotic organelle in triple-negative breast cancer (U54 Talk)

Kevin Janes , University of Virginia , (CSBC)

Chromosome missegregation causes whole-chromosome aberrations and aneuploidy characterizing most solid tumors and virtually all breast cancers of the triple-negative subtype. The origins of chromosome instability are poorly understood because genes involved in the mitotic spindle checkpoint are almost never mutated in cancer, although abundances are highly variable. An important sensor of improper microtubule attachments during metaphase is the chromosomal passenger complex (CPC). The CPC is activated by upstream protein kinases and histone modifications that recruit it to chromatin within minutes after prophase. Positive feedback in the network culminates in a CPC biomolecular condensate at the inner centromere. Before progression to anaphase, this condensate must dissolve or avoid forming when chromosomes are properly attached. To link abundance variability with CPC regulation, we have built a reaction-diffusion model of the signaling events surrounding the CPC on a prototypical metaphase chromosome. The model is constrained by biochemical parameters from the literature and protein concentrations measured in metaphase-arrested triple-negative breast cancer cells and controls. The model predicts an organism-dependent synergy between CPC kinase activity and a phospho-histone adaptor that we are testing in human and mouse chromosomes. In parallel, we have modeled CPC condensates with advanced numerical approaches to the Cahn-Hilliard equation for two-phase systems. The equation captures CPC droplet patterns on prometaphase chromosomes and identifies parameter regimes where inner centromere condensates coalesce or dissolve. The long-term goal is to merge the reaction-diffusion and Cahn-Hilliard models and predict chromosome instability patterns in individual breast tumors that arise from differences in mitotic initial conditions.

Other Authors: A. Catalina Alvarez-Yela, Sarah M. Groves, Monserrat Gerardo-Ramírez, Joseph Guillen, P. Todd Stukenberg

Decoding the cellular and spatial complexity of lung cancer development (Lighting Talk)

Humam Kadara, University of Texas MD Anderson Cancer Center, (CSBC)

This talk will describe progress under our CSBC U01 project that focuses on developing models that inform of the development of lung adenocarcinoma (LUAD). We will discuss role alveolar intermediate cells and how these transitional subsets in the lung can act as progenitors of LUAD. We will discuss how interplay and proximity with immune and stromal subsets can impinge on oncogenesis of these "normal" alveolar cells. The lighting talk will also discuss our efforts in understanding tumor-immune interactions that underlie LUAD pathogenesis by spatial omics analysis of the pathologic continuum of normal-appearing lung tissue (NAT), adenomatous premalignant lesion (aPML) and LUAD.

Other Authors: Fuduan Peng, Ansam Sinjab, Yibo Dai, Linghua Wang

Organ-specific macrophages may lead to suppressive tumor microenvironment in metastatic pancreatic cancer (Lighting Talk)

Yu-Lan Kao , Washington University in St. Louis, (MetNet)

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a five-year survival rate of just 13%. The disease is frequently diagnosed at the metastatic stage, with the liver being the most common site of metastasis, accounting for approximately 80% of cases, followed by the lung at 20%. Macrophages play a crucial role in the development of tumor resistance mechanisms, particularly by promoting immunosuppression. Previous studies have demonstrated that liver macrophages can induce systemic immunosuppression by driving T cell apoptosis in a mouse model of melanoma liver metastasis. In this study, we employed single-nuclei RNA sequencing and multiplex immunohistochemistry staining to characterize immune cells in different organs from human samples, including primary pancreatic tumors, metastatic livers, and lungs. Our findings reveal that macrophages in liver metastases exhibit upregulation of the hypoxia pathways and downregulation of interferon signaling and antigen presentation pathways compared to the primary PDAC. Moreover, we observed a reduced density of T cells in liver metastases compared to both primary tumors and lung metastases, which is consistent with the poorer prognosis associated with liver metastasis. In contrast, lung metastases are linked to better patient outcomes, as supported by existing literature. These results suggest that the liver exhibits a less immunologically active environment compared to the lung. Further research needs to be conducted to elucidate the mechanisms by which macrophages and other cells within the tumor microenvironment contribute to immune suppression. Understanding these mechanisms may identify specific macrophage populations in the liver as potential therapeutic targets.

Other Authors: Varun Shenoy1, Blake E. Sells1, Alyssa Weinstein1, Liang-I Kang1,6,7, Brett L Knolhoff1, Paul M. Grandgenett2, Michael A. Hollingsworth3,4, Ryan C. Fields5,7, Li Ding1,7,8,9, David G. DeNardo1,6,8* Affiliations: 1Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA 2Eppley Institute for Research in Cancer and Allied Diseases, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198 USA 3Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, NE 68198 USA 4Fred & Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE, 68198 USA 5 Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA 6 Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA 7 Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110, USA 8McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63110, USA 9 Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA

Mechanistic maps of adaptive responses to therapeutic stress to optimize combination therapies (Lighting Talk)

Anil Korkut , UT MDACC, (CSBC)

In triple-negative breast cancer and high-grade serous ovarian cancer, the emergence of resistance to therapy is virtually inevitable and contributes to dismal long-term patient outcomes. We are developing computational, systems biology and translational approaches to discover combination therapies that will interdict the emergence of resistance. Our efforts to develop combination therapies are based on the rationale that tumor ecosystems rapidly adapt to stress engendered by therapies, leading to the emergence of resistance. As a corollary, blocking adaptive responses in tumor cells and the immune microenvironment with drug combinations can overcome the resistance. We are combining computational approaches such as network modeling, image analysis and machine learning methods with state-of-the-art omics technologies including bulk and spatially resolved single-cell proteomics. We benefit from a large repository of cell lines, PDXs and syngeneic animal models, and clinically-annotated patient samples. Our key innovation for combination therapy discovery is the iterative computational systems biology approach from the patient to the bench, and back to the patient. Our studies have led to the discovery of combination therapies targeting the DNA repair, growth, apoptosis, epigenetic regulation, and immune mechanisms. Our preclinical findings resulted in clinical trials aiming to improve response depth and duration to therapy in breast and ovarian cancer patients.

Other Authors: Gordon Mills, Han Liang

Multiomic and spatial dissection of the tumor immune microenvironment (U54 Talk)

Christina Leslie, memorial sloan kettering cancer center , (CSBC)

We will present novel computational methods and biological findings from the Center for Tumor-Immune Systems Biology at MSK.

Other Authors: Gordon Mills, Han Liang

RIG-I-dependent type I interferon mediates tumor-intrinsic inflammation in breast cancer 3D culture (Lighting Talk)

Katherine Liu , Stanford University, (MetNet)

The type I interferon pathway, initially recognized as a crucial element in the antiviral immune response, has been extensively studied in the context of cancer. In breast cancers, activation of the type I IFN signaling pathway has been shown to induce apoptosis, but can also contribute to the evolution of drug resistance and metastasis. The dual role of type I IFN in breast cancers remains incompletely understood. Recent studies suggest that the impact of type I IFN on cancer therapy response is highly variable, contingent upon the strength, duration, and source of IFN signaling stimuli. We sought to leverage our scalable 3D spheroid cell model to investigate the role of tumor-intrinsic type I IFN in breast cancers. Through CRISPR-interference screening, we discover that perturbation of the type I IFN pathway increases growth in 3D breast cancer spheroids relative to 2D monolayers. RNA-seq analysis further demonstrates an inflammatory profile in 3D spheroids, indicative of tumor-intrinsic type I IFN. Spatial transcriptomic analysis of breast cancer patient samples reveals an enrichment of the same tumor-intrinsic IFN inflammatory signature in immune-desert tumor cell niches. To dissect the mechanism driving this response, we assessed several potential innate immune sensors and identified retinoic acid-inducible gene-I (RIG-I) as the necessary upstream effector. RIG-I is a nucleic acid sensor that triggers innate immune response by inducing type I IFN transcription. RIG-I agonists have been shown to induce cancer cell death and are currently undergoing evaluation in multiple clinical trials. These insights shed light on the potential to harness innate immune signaling to effectively target and eliminate tumors.

Other Authors: Katherine Liu, Lise Mangiante, Kaitlyn Spees, Michael Bassik, Christina Curtis

Complex rearrangements fuel the progression of High-risk ER-positive and HER2-positive breast tumors (U54 Talk)

Lise Mangiante, Stanford University, (MetNet)

Clinically, breast tumors are stratified based on the expression of three receptors - estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2). Breast cancer is a highly heterogeneous disease as we established a genome-driven breast cancer classification scheme that defines 11 integrative subgroups of disease with distinct copy number aberrations, transcriptional profiles, and clinical outcomes. Specifically, we identify four ER+ subgroups (IC1, IC2, IC6, IC9) with a persistent risk of lethal distant relapse up to two decades after diagnosis, each with focal copy number drivers (Curtis et al. Nature 2012; Rueda et al. Nature 2019). These findings nominate new therapeutic strategies, however, it is not known how mutational processes and genomic architecture differ across subtypes to sculpt the evolution of disease, nor how their microenvironments differ. To interrogate the genomic and immune landscape of breast cancer throughout the disease continuum, we established a meta- cohort of 2,877 breast tumors spanning pre-invasive, primary, and metastatic breast cancer with whole-genome and whole-transcriptome sequencing. We identified highly concordant mutational signatures and higher order genomic features in high-risk ER+ and HER2+ tumors, including distinct patterns of structural variation. In contrast, triple-negative tumors were characterized by global genomic instability, whilst a third group is largely genomically stable. These distinct genomic architectures were associated with specific tumor microenvironments with immune depletion in the high-risk ER+ and HER2+ tumors. Taken together, our data demonstrate that complex structural alterations established early in breast cancer, and persist throughout the life history of the tumor through metastasis.

Other Authors: Lise Mangiante 1 (presenter), Kathleen E. Houlahan 1 , Cristina Sotomayor-Vivas 1 , Alvina

Adimoelja 2 , Seongyeol Park 1 , Aziz Khan 1 , Sophia J. Pribus 1 , Zhicheng Ma 1 , Jennifer Caswell- Jin 3 , Christina Curtis 1,2,3,4,5

1 Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

2 Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

3 Department of Medicine (Oncology), Stanford University School of Medicine, Stanford, CA, USA

4 Department of Biomedical Data Science, Stanford University

Overcoming Intrinsic Mechanisms of Cell Cycle Inhibitor Resistance in Estrogen Receptor-Positive (ER+) Breast Cancer (Lighting Talk)

Aritro Nath , City of Hope , (CSBC)

Estrogen receptor-positive (ER+) breast cancer accounts for about 75% of all breast cancers and is a leading cause of cancer-related deaths worldwide. Endocrine therapy is the primary treatment for ER+ breast cancer. While combination therapy with CDK4/6 inhibitors has shown promise in advanced cases, results for early-stage disease are mixed. To investigate resistance to CDK4/6 inhibitors, we analyzed pre- and post- treatment samples from patients on endocrine therapy alone or combined with ribociclib using single-cell RNA sequencing. Our findings indicate that tumors resistant to ribociclib often rely more on ERBB signaling, suggesting an alternate growth pathway. We developed an in vitro 3D model to study ER+ breast cancer cells that are either sensitive or resistant to ribociclib, reflecting patient treatment progression. This model revealed that afatinib, a pan-ERBB inhibitor, combined with ribociclib, effectively inhibits proliferation in resistant cells. Dynamical analysis of temporal RNA-seq data showed that this combination synergistically promotes early cell cycle arrest and later apoptosis. By simultaneously blocking the cyclin E/CDK2 complex and the cyclin B/CDK1 complex, this dual inhibition strategy not only controls cancer cell proliferation but also induces cell death. Thus, the ribociclib-afatinib combination effectively overcomes resistance mechanisms in ER+ breast cancer.

Other Authors: -

From Nerves to Nodules: How sensory neurons fuel breast cancer metastasis (U54 Talk)

Veena Padmanaban, Rockefeller University, (MetNet)

Tumour innervation is associated with worse patient outcomes in multiple cancers1,2, which suggests that it may regulate metastasis. Here we observed that highly metastatic mouse mammary tumours acquired more innervation than did less-metastatic tumours. This enhanced innervation was driven by expression of the axon-guidance molecule SLIT2 in tumour vasculature. Breast cancer cells induced spontaneous calcium activity in sensory neurons and elicited release of the neuropeptide substance P (SP). Using three-dimensional co-cultures and in vivo models, we found that neuronal SP promoted breast tumour growth, invasion and metastasis. Moreover, patient tumours with elevated SP exhibited enhanced lymph node metastatic spread. SP acted on tumoral tachykinin receptors (TACR1) to drive death of a small population of TACR1high cancer cells. Single-stranded RNAs (ssRNAs) released from dying cells acted on neighbouring tumoural Toll-like receptor 7 (TLR7) to non-canonically activate a prometastatic gene expression program. This SP- and ssRNA-induced Tlr7 gene expression signature was associated with reduced breast cancer survival outcomes. Therapeutic targeting of this neuro–cancer axis with the TACR1 antagonist aprepitant, an approved anti-nausea drug, suppressed breast cancer growth and metastasis in multiple models. Our findings reveal that tumour-induced hyperactivation of sensory neurons regulates multiple aspects of metastatic progression in breast cancer through a therapeutically targetable neuropeptide/extracellular ssRNA sensing axis.

Other Authors: Sohail Tavazoie

Mapping the Medulloblastoma Landscape and a Path to Better Therapies (Lighting Talk)

Veronika Pister, MIT, (CSBC)

Medulloblastoma is one of the most common malignant pediatric brain tumors and demands identification of targeted therapies for improved patient outcome. It is a heterogeneous disease with 4 distinct molecule subgroups, recognized by the World Health Organization for their shared clinical outcomes. Traditional treatments are available; however, they are untargeted, and lead to an increased rate of secondary cancer and neurological disorders in pediatric patients. A more targeted treatment plan could enhance patient prognosis, but requires a better understanding of the different tumor microenvironments in each medulloblastoma subgroup. Here, we investigate potential therapeutic avenues for patients belonging to two of the medulloblastoma subgroups, SHH and group 3. SHH medulloblastomas are driven by an overactive sonic hedgehog pathway. In SHH subgroup tumors, we mapped malignant cell states to canonical stages of granule neuron development. Using this mapping, we identified distinct histological and metabolic profiles for highly differentiated tumors which can elucidate future avenues for targeted therapeutics. Group 3 is the most aggressive subtype of medulloblastoma and is characterized by overexpression of MYC. We established a mouse model for group 3 that is characterized by the overexpression of c-Myc and a dominant negative form of p53. Although brain tumors are generally thought to have minimal immune effector cell infiltration, our findings show that CD4 and CD8 T cells both play crucial roles in regulating tumor progression in this model.

Other Authors: Tanja Eisemann, Alexander Wenzel, Koei Chin, Ernest Fraenkel, Scott Pomeroy, Jill Mesirov, Rob Wechsler-Reya

Stanford Center for Cancer System Biology: Systems Biology of Tumor Immune Stromal Interactions in Metastatic Progression? (U54 Talk)

Sylvia Plevritis, Stanford University , (CSBC)

The major three goals of our Stanford Center are to maintain a research team with multidisciplinary systems biology approaches to further dissect the multistep process of metastasis, conduct highly integrative multi-species, multi-modality, multi-cancer research to identify the role of lymph node metastasis in enabling distant metastasis and to engage the community of cancer systems biology researchers in contributing to the overarching goals of the CSBC consortium. We are currently composed of a multidisciplinary team whose members have established expertise in areas that include cancer systems biology, pathology, immunology, data science/AI, particularly in the study of lung cancer and head and neck cancer. In our arching goal to study the role of lymph nodes as active players in metastasis that create organism-wide tumor-immune tolerance, the Stanford CCSB Research Center interweaves mouse models and primary human data in head and neck cancer and lung cancer. We analyze highly multiplexed, multi-scale datasets with novel bio-computational methods to reconstruct intracellular and intercellular crosstalk between cell types in the microenvironment of primary tumors, lymph nodes, and distant metastases. This research is organized around two projects and one shared core that are closely integrated, and we will discuss them in more detail in our talk.

Other Authors: Sylvia K. Plevritis, PhD, Professor and Chair of Biomedical Data Science; Edgar Engleman, MD, Professor, Pathology and Medicine

Investigating disseminated cancer cell clonal cooperation and immune control in dormancy and metastasis (Lighting Talk)

Carolina Rodriguez Tirado, Albert Einstein College of Medicine , (MetNet)

Despite advancements in early breast cancer detection, many patients still develop metastatic disease post-surgery. Understanding metastasis mechanisms is crucial for preventing recurrence. Disseminated cancer cells (DCCs), the source of metastasis, accumulate as heterogeneous populations in secondary organs like the lungs. Early DCCs (eDCCs) originate from early lesions, while late DCCs (L-DCCs) derive from overt primary tumors (PT). DCCs can remain dormant in organs for years before reactivation. As the PT progresses, we hypothesize that more evolved L-DCCs disseminate, potentially collaborating with existing eDCCs to drive metastasis. Our published research, using genetic lineage tracing and single-cell RNA sequencing, demonstrated that 79% of breast cancer metastases originate from eDCCs. Furthermore, we reasoned that the continuous influx of genetically diverse DCCs to the lungs may alter the immune microenvironment, facilitating evasion mechanisms that explain the inefficient clearance of eDCCs. The UO1 project aims to elucidate how eDCC and L-DCC cooperation drives immune evasion and metastasis, and to identify potential therapeutic targets. Key findings include: 1. MMTV-HER2 eDCCs in the lungs exit dormancy more efficiently in the presence of L-DCCs and become the dominant population. 2. Metastases exhibit clonal distributions that do not reflect their primary lesion. 3. The collaboration between eDCCs and L-DCCs triggers a transcriptional switch, suppressing NR2F1 (a dormancy-related transcription factor) in eDCCs and their precursors. 4. RNA sequencing data from eDCC, L-DCC, and co-founded e+L-DCC lesions identified Thrombospondin1-Syndecan1 as a potential ligand-receptor pair mediating eDCC-L-DCC crosstalk.

Other Authors: Lornella Seeneevasen, Uliana Berseneva, Luisiana Pia, Luis Valencia-Salazar, Brian Brown, Julio Aguirre-Ghiso and Maria Soledad Sosa

Spatial niche reprogramming and genomic instability in colorectal cancer brain metastasis (U54 Talk)

Anuja Sathe , Stanford University , (MetNet)

Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA 2 Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA 3 Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA 4 Department of Pathology, Stanford University, Stanford, CA, USA Brain metastasis in colorectal cancer (mCRC) poses significant clinical challenges with poor outcomes. Our study, the largest spatial analysis to date, aimed to uncover cellular and genomic features facilitating metastatic lesion development. Employing spatial transcriptomics on 53 patients' surgical resections, validated by single-cell RNA sequencing (scRNA-seq), whole-genome sequencing (WGS), and ex vivo tumor slice cultures, we characterized gene expression in metastatic tumor cells, the tumor microenvironment (TME), and brain parenchymal lineages. Metastatic cells exhibited spatially heterogeneous upregulation of PI3K, MAPK, EGFR, p53, and TGFβ signaling, with high chromosomal instability (CIN), including recurrent amplifications in chromosomes 6, 7, 17, and 20. WGS from independent cohorts showed significantly higher CIN in mCRC brain metastases compared to primary CRC or other metastases. Spatial neighborhood analysis revealed an immune desert phenotype, characterized by the exclusion of lymphocytes and a significant association between tumor and endothelial cells, suggesting a role in tumor seeding and growth. Macrophages expressed pro-fibrogenic genes, with SPP1 ligand interaction between macrophages and spatially proximal fibroblasts, indicating key niche reorganization promoting metastatic growth. We explored the ex vivo effects of perturbing the metastatic niche. scRNA-seq confirmed that tumor slice cultures derived from an mCRC brain resection maintained the metastatic niche composition. Metastatic tumor cells were resistant to regorafenib, a multi-receptor tyrosine kinase inhibitor. However, pirfenidone, an anti-fibrotic and anti-inflammatory small molecule, effectively reduced extracellular matrix gene expression in fibroblasts within the TME. Our analysis identified chromosomal instability, lymphocyte evasion, and macrophage-fibroblast interactions as potential therapeutic targets in mCRC brain.

Other Authors: Anuja Sathe 1 , Aparajita Khan 2 , Ji In Kang 1 , Rithika Meka 1 , Susan M. Grimes 1 , Andrew S. Luksik 3 , Michael Lim 2 , Claudia Petrisch 2 , Christopher M. Jackson 3 , Hannes Vogel 4 , Melanie Gephart 2 , Summer Han 2 , Hanlee P. Ji 1

Mathematical Oncology Systems Analysis of Imaging Center (U54 Talk)

Kristin Swanson, Mayo Clinic , (CSBC)

We will introduce the MOSAIC centet and share preliminary results connecting MRI to cancer complex systems leveraging image-localized biopsies and experimental methods.

Other Authors: Peter Canoll

Spatiotemporal mapping of melanoma-draining lymph nodes reveals a protective innate alarm system ahead of metastasis (Lighting Talk)

Katherine Ventre , NYU , (MetNet)

Despite increasing data that lymph node (LN) metastasis is immunosuppressive, local LN tumor-immune interactions remain poorly understood. Here, we map the immunological impact of metastasis on human and mouse LN. We performed high-dimensional (40-plex) immunofluorescence and Visium 10X spatial transcriptomics (ST) on adjacent sections from sentinel LNs of 12 patients with stage III cutaneous melanoma. Imaging captured lesions from single cells to macrometastases. We hypothesized these represent independent metastatic events, supported by InferCNV analysis; we therefore used lesion size and clonal projections to model a metastatic trajectory. Individual melanoma cells localized to the subcapsular sinus (SCS) and clustered with macrophages, IL-33-producing lymphatic endothelial cells (LECs), and mast cells. Larger lesions did not associate with this network. Multimodal integration analysis of paired real-time longitudinal scRNAseq and ST of tumor-draining LN from an inducible mouse melanoma model (TyrCreERT2;BrafV600E;Pten-/-) indicated that the innate leukocyte composition of the SCS shifts before metastasis. Mast cell quantity and LEC Il33 expression both peaked in the pre-metastatic niche. NicheNet analysis on predicted SCS populations revealed significant Tnf signaling in the pre-metastatic niche but not after macrometastasis. Mast cells are the primary producer of Tnf in our data, and their Tnf expression peaks pre-metastasis. We therefore propose a model by which lymphatic drainage from the primary tumor induces SCS LEC IL-33 production before metastasis. IL-33 induces mast cell TNF production, coordinating a type I inflammatory response that attempts to protect against metastasis. Reinforcement of this network may minimize metastasis and preserve the anti-tumor immune function of the LN.

Other Authors: KatherinRob Stagnatti, Itai Yanai, Iman Osman, Markus Schober, Amanda W Lund

MIT/DFCI Center for Glioblastoma Systems Biology (U54 Talk)

Forest White , MIT, (CSBC)

The primary focus of the MIT/DFCI Center for Systems Biology of Glioblastoma is to understand the intersections between neurons, immune cells, and tumor cells. The lack of response to immunotherapy strategies despite prominent infiltrates of immune cells in many GBM highlights the immunosuppressive nature of the GBM microenvironment and the importance of understanding the dynamic interactions at the tumor/immune interface. Similarly, interactions between tumor cells and neural cells in the tumor microenvironment have emerged as driving forces in tumor progression and invasion. The central hypothesis of this proposal is that developing a systems-level understanding of the dynamic interactions between tumor cells, neurons and immune cells will provide unprecedented insights into glioma tumor biology and foster development of novel therapeutic strategies to abrogate tumor invasion, enhance the efficacy of cytotoxic therapies, and increase clearance of tumor burden by the innate and adaptive immune system. The planned analyses will enable building an integrated computational model of tumor-neural-immune interactions for GBM tumors. The model will be based on a foundation of in vitro, in vivo, and ex vivo model systems, and then validated in dozens of human patients. Image-registered biopsies from different tumor regions within each patient will be analyzed to test predictions of this model against the ‘ground truth’ of human tumors. The ultimate goal of the MIT/DFCI Center for Systems Biology of Glioblastoma is to improve patient care by using systems biology and computational modeling to identify therapeutic strategies to specifically disrupt critical tumor cell – microenvironment interactions.

Other Authors: Franziska Michor

Spotiphy enables single-cell spatial whole transcriptomics across the entire section (Lighting Talk)

Jiyang Yu, St. Jude Children's Research Hospital, (CSBC)

Spatial transcriptomics (ST) has advanced our understanding of tissue regionalization by enabling the visualization of gene expression within whole tissue sections, but the approach remains dogged by the challenge of achieving single-cell resolution without sacrificing whole genome coverage. Here we present Spotiphy (Spot imager with pseudo single-cell resolution histology), a novel computational toolkit that transforms sequencing-based ST data into single-cell-resolved whole-transcriptome images. In evaluations with Alzheimer’s disease (AD) and normal mouse brains, Spotiphy delivers the most precise cellular compositions. For the first time, Spotiphy reveals novel astrocyte regional specification in mouse brains. It distinguishes sub-populations of DAM (Disease-Associated Microglia) located in different AD mouse brain regions. Spotiphy also identifies multiple spatial domains as well as changes in the patterns of tumor-tumor microenvironment interactions using human breast ST data. Spotiphy enables visualization of cell localization and gene expression in tissue sections, offering key insights into the function of complex biological systems.

Other Authors: Spotiphy enables single-cell spatial whole transcriptomics across the entire section