Microenvironmental Context Research Articles

Single-cell stimulus-response gene expression trajectories reveal the stimulus specificities of dynamic responses by single macrophages.

Macrophages induce the expression of hundreds of genes in response to immune threats. However, current technology limits our ability to capture single-cell inducible gene expression dynamics. Here, we generated high-resolution time series single-cell RNA sequencing (scRNA-seq) data from mouse macrophages responding to six stimuli, and imputed ensembles of real-time single-cell gene expression trajectories (scGETs). We found that dynamic information contained in scGETs substantially contributes to macrophage stimulus-response specificity (SRS). Dynamic information also identified correlations between immune response genes, indicating biological coordination. Furthermore, we showed that the microenvironmental context of polarizing cytokines profoundly affects scGETs, such that measuring response dynamics offered clearer discrimination of the polarization state of individual macrophage cells than single time-point measurements. Our findings highlight the important contribution of dynamic information contained in the single-cell expression responses of immune genes in characterizing the SRS and functional states of macrophages.

Family-Wide Photoproximity Profiling of Integrin Protein Social Networks in Cancer.

Integrin family transmembrane receptors mediate dynamic interactions between cells and their extracellular microenvironment. The heterogeneous interaction partners of integrins directly regulate cell adhesion, motility, proliferation, and intracellular signaling. Despite the recognized importance of protein-protein interactions and the formation of signaling hubs around integrins, the ability to detect and quantify these dynamic binding partners with high spatial and temporal resolution remains challenging. Here, we developed an integrin-family-directed quantitative photoproximity protein interaction (PhotoPPI) profiling method to detect and quantify native integrin-centered protein social networks on live cells and tissues without the need for genetic manipulation, antibodies, or non-physiologic cell culture conditions. We drafted quantitative maps of integrin-centered protein social networks, highlighting conserved and unique binding partners between different cell types and cellular microenvironments. Comparison of integrin social networks in cancer cell lines of diverse tissue of origin and disease state identified specific AND-gate binding partners involved cell migration, microenvironmental interactions and proliferation that serve as markers of tumor cell metastatic state. Finally, we identified unique combinations - or barcodes - of integrin-proximal proteins on the surface of pre- and post-metastatic triple negative breast cancer (TNBC) cells whose expression strongly correlate with both positive and negative disease progression and outcomes in TNBC patients. Taken together, these data provide the first family-wide high-resolution maps of native protein interactors on live cells and identify dynamic integrin-centered social networks as potential AND-gate markers of cell identity, microenvironmental context and disease state.

Comprehensive analysis of the editing window of C-to-T TALE base editors

One of the most recent advances in the genome editing field has been the addition of “TALE Base Editors”, an innovative platform for cell therapy that relies on the deamination of cytidines within double strand DNA, leading to the formation of an uracil (U) intermediate. These molecular tools are fusions of transcription activator-like effector domains (TALE) for specific DNA sequence binding, split-DddA deaminase halves that will, upon catalytic domain reconstitution, initiate the conversion of a cytosine (C) to a thymine (T), and an uracil glycosylase inhibitor (UGI). We developed a high throughput screening strategy capable to probe key editing parameters in a precisely defined genomic context in cellulo, excluding or minimizing biases arising from different microenvironmental and/or epigenetic contexts. Here we aimed to further explore how target composition and TALEB architecture will impact the editing outcomes. We demonstrated how the nature of the linker between TALE array and split DddAtox head allows us to fine tune the editing window, also controlling possible bystander activity. Furthermore, we showed that both the TALEB architecture and spacer length separating the two TALE DNA binding regions impact the target TC editing dependence by the surrounding bases, leading to more restrictive or permissive editing profiles.

Stimulus-response signaling dynamics characterize macrophage polarization states

The functional state of cells is dependent on their microenvironmental context. Prior studies described how polarizing cytokines alter macrophage transcriptomes and epigenomes. Here, we characterized the functional responses of 6 differentially polarized macrophage populations by measuring the dynamics of transcription factor nuclear factor κB (NF-κB) in response to 8 stimuli. The resulting dataset of single-cell NF-κB trajectories was analyzed by three approaches: (1) machine learning on time-series data revealed losses of stimulus distinguishability with polarization, reflecting canalized effector functions. (2) Informative trajectory features driving stimulus distinguishability ("signaling codons") were identified and used for mapping a cell state landscape that could then locate macrophages conditioned by an unrelated condition. (3) Kinetic parameters, inferred using a mechanistic NF-κB network model, provided an alternative mapping of cell states and correctly predicted biochemical findings. Together, this work demonstrates that a single analyte's dynamic trajectories may distinguish the functional states of single cells and molecular network states underlying them. A record of this paper's transparent peer review process is included in the supplemental information.

Engineering Cell Instructive Microenvironments for In Vitro Replication of Functional Barrier Organs.

Multicellular organisms exhibit synergistic effects among their components, giving rise to emergent properties crucial for their genesis and overall functionality and survival. Morphogenesis involves and relies upon intricate and biunivocal interactions among cells and their environment, that is, the extracellular matrix (ECM). Cells secrete their own ECM, which in turn, regulates their morphogenetic program by controlling time and space presentation of matricellular signals. The ECM, once considered passive, is now recognized as an informative space where both biochemical and biophysical signals are tightly orchestrated. Replicating this sophisticated and highly interconnected informative media in a synthetic scaffold for tissue engineering is unattainable with current technology and this limits the capability to engineer functional human organs in vitro and in vivo. This review explores current limitations to in vitro organ morphogenesis, emphasizing the interplay of gene regulatory networks, mechanical factors, and tissue microenvironment cues. In vitro efforts to replicate biological processes for barrier organs such as the lung and intestine, are examined. The importance of maintaining cells within their native microenvironmental context is highlighted to accurately replicate organ-specific properties. The review underscores the necessity for microphysiological systems that faithfully reproduce cell-native interactions, for advancing the understanding of developmental disorders and disease progression.

Abstract B001: Glioblastoma evolution and resistance is mediated by a shift in cell state and tumor microenvironmental interactions

Abstract Glioblastoma (GBM) is a lethal disease characterized by inevitable recurrence. Recently, single cell sequencing studies of primary GBM have defined various tumor cell states, specifically the neural progenitor-like (NPC-like), oligodendrocyte progenitor (OPC-like), astrocyte-like(AC-like), and mesenchymal(MES-like) states. Yet, the role these cell states play in treatment resistance and recurrence is not well defined. Furthermore, the spatial tumor microenvironmental (TME) context of tumor cells clearly plays a role in treatment response. Here we utilize in vivo recurrence models, and single cell and spatial transcriptomic (ST) analyses of primary and recurrent GBM to determine the pathways and spatial TME interactions mediating recurrence. Experimental Design: To define the evolution of the tumor landscape from primary to recurrence, we performed single cell RNA sequencing from stereotactically resected primary GBM (178K cells from 26 patients) and at recurrence (170K cells from 12 patients). ST analyses were also completed, as well as in vitro and in vivo mechanistic studies. Results: We identified a notable shift in the proportion of cell states in response to treatment from primary to recurrence with a significant decrease in AC-like cells (72% vs 55%, p<2e-16) and increase in MES-like cells (15% vs 34%, p<2e-16). This suggests that AC-like cells may be more treatment sensitive compared to other cell states, especially MES-like cells. We then worked to define potential TME interactions of these cell states to define drivers of recurrence. ST analyses revealed NPC-like cells in the infiltrative edge, AC-like cells in the tumor core, and MES-like cells in the hypoxic zones. We performed pseudotime trajectory analysis which identified that NPC-like cells divided into 2 daughter lineages: 1) AC-like cells which form the bulk of primary tumors and 2) MES-like cells that make up a large proportion of the recurrence. We then found that THY1, a cell surface receptor, was highly expressed in NPC-like cells in the primary tumors. While at recurrence, there was a remarkable increase in THY1 expression coincident with a switch to a predominantly MES-like state. Furthermore, ST analyses revealed upregulation of stem-like pathways in THY1 regions, as well as co-localization of MES-like THY1 cells with monocytes in hypoxic zones(p<0.001), suggesting an important role for TME interactions in mediating recurrence. To assess the biological implications of THY1, subsequent in vitro and in vivo studies revealed that THY1 knockout significantly decreased cell proliferation and tumor volume, and improved treatment response suggesting an important role for THY1 in driving treatment resistance and inevitable recurrence. Conclusions: Utilizing mechanistic and bioinformatic analyses, we show that a small population of NPC and MES-like THY1+ cells in primary GBM is likely to survive chemoradiation and mediate recurrence. Defining the interactions of these cell states in their TME and the mechanistic underpinnings of THY1 interactions may be critical to identifying new treatments. Citation Format: Sunita Shankar, Visweswaran Ravikumar, Arushi Tripathy, Sunjong Ji, Jackson Loper, Zainab Hassan, Ziad Fehmi, Yacoub Haydin, Dah-Luen Huang, Sagnik Bhadury, Reva Kulkarni, Jeffrey Regier, Daniel Wahl, Arvind Rao, Alnawaz Rehemtulla, Wajd N. Al-Holou. Glioblastoma evolution and resistance is mediated by a shift in cell state and tumor microenvironmental interactions [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr B001.

Tumor-immune metaphenotypes orchestrate an evolutionary bottleneck that promotes metabolic transformation.

Metabolism plays a complex role in the evolution of cancerous tumors, including inducing a multifaceted effect on the immune system to aid immune escape. Immune escape is, by definition, a collective phenomenon by requiring the presence of two cell types interacting in close proximity: tumor and immune. The microenvironmental context of these interactions is influenced by the dynamic process of blood vessel growth and remodelling, creating heterogeneous patches of well-vascularized tumor or acidic niches. Here, we present a multiscale mathematical model that captures the phenotypic, vascular, microenvironmental, and spatial heterogeneity which shapes acid-mediated invasion and immune escape over a biologically-realistic time scale. The model explores several immune escape mechanisms such as i) acid inactivation of immune cells, ii) competition for glucose, and iii) inhibitory immune checkpoint receptor expression (PD-L1). We also explore the efficacy of anti-PD-L1 and sodium bicarbonate buffer agents for treatment. To aid in understanding immune escape as a collective cellular phenomenon, we define immune escape in the context of six collective phenotypes (termed "meta-phenotypes"): Self-Acidify, Mooch Acid, PD-L1 Attack, Mooch PD-L1, Proliferate Fast, and Starve Glucose. Fomenting a stronger immune response leads to initial benefits (additional cytotoxicity), but this advantage is offset by increased cell turnover that leads to accelerated evolution and the emergence of aggressive phenotypes. This creates a bimodal therapy landscape: either the immune system should be maximized for complete cure, or kept in check to avoid rapid evolution of invasive cells. These constraints are dependent on heterogeneity in vascular context, microenvironmental acidification, and the strength of immune response. This model helps to untangle the key constraints on evolutionary costs and benefits of three key phenotypic axes on tumor invasion and treatment: acid-resistance, glycolysis, and PD-L1 expression. The benefits of concomitant anti-PD-L1 and buffer treatments is a promising treatment strategy to limit the adverse effects of immune escape.

Abstract A107: MAPK signaling is a conserved mechanism explaining phenotypic heterogeneity across diverse drivers of epithelial-mesenchymal transition in pancreas cancer

Abstract Epithelial-mesenchymal transition (EMT) is a developmental process that is aberrantly activated in cancers such as pancreatic ductal adenocarcinoma (PDAC) to promote disease progression and chemoresistance. EMT occurs heterogeneously among PDAC ductal cells, which frustrates efforts to identify the underlying signaling regulatory mechanisms. We hypothesize that cell-to-cell variation in the activities of specific signaling pathways explains EMT heterogeneity. To test this, we developed a workflow integrating: 1) iterative indirect immunofluorescence imaging (4i) to quantify the activities of up to seven purported EMT-regulating pathways with single-cell resolution and 2) a multivariate mutual information computational model to predict the pathways that are most informative of the EMT phenotype. In cultured PDAC cells, EMT was induced by treating cells with growth factors present in the tumor microenvironment (hepatocyte growth factor, epidermal growth factor, transforming growth factor β1, or two combinations) or with chemotherapeutics (gemcitabine or 5-fluorouracil). EMT phenotypic markers and signaling pathway proxies were assessed daily for up to 96 hr. A mutual information analysis of the aggregated data identified ERK as the most important signaling node explaining EMT heterogeneity across the diverse set of agonists investigated. Kinase inhibition and siRNA studies confirmed the implied role of ERK but also revealed a compensatory, EMT-driving JNK activation in the context of MEK inhibition that explains a cooperative effect of simultaneous MEK and JNK inhibition on EMT antagonism. Importantly, a model based on cell population-level measurements nominated JNK as more informative than ERK for determining EMT state in response to growth factors. We are implementing this approach in vivo using pancreas cancer tissue sections to determine generalizability of these findings in different microenvironmental contexts. Overall, our results demonstrate the pervasive importance of ERK for diverse drivers of EMT and the need to account for the effects of heterogeneous signaling pathway activation in the determination of EMT. Citation Format: Michelle C. Barbeau, Matthew J. Lazzara. MAPK signaling is a conserved mechanism explaining phenotypic heterogeneity across diverse drivers of epithelial-mesenchymal transition in pancreas cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A107.

Pharmacological reactivation of p53 in the era of precision anticancer medicine.

p53, which is encoded by the most frequently mutated gene in cancer, TP53, is an attractive target for novel cancer therapies. Despite major challenges associated with this approach, several compounds that either augment the activity of wild-type p53 or restore all, or some, of the wild-type functions to p53 mutants are currently being explored. In wild-type TP53 cancer cells, p53 function is often abrogated by overexpression of the negative regulator MDM2, and agents that disrupt p53-MDM2 binding can trigger a robust p53 response, albeit potentially with induction of p53 activity in non-malignant cells. In TP53-mutant cancer cells, compounds that promote the refolding of missense mutant p53 or the translational readthrough of nonsense mutant TP53 might elicit potent cell death. Some of these compounds have been, or are being, tested in clinical trials involving patients with various types of cancer. Nonetheless, no p53-targeting drug has so far been approved for clinical use. Advances in our understanding of p53 biology provide some clues as to the underlying reasons for the variable clinical activity of p53-restoring therapies seen thus far. In this Review, we discuss the intricate interactions between p53 and its cellular and microenvironmental contexts and factors that can influence p53's activity. We also propose several strategies for improving the clinical efficacy of these agents through the complex perspective of p53 functionality.

Abstract 5723: An in vivo pharmacogenomics platform replicates and extends biomarkers of therapy response identified via causal inference analysis of clinical data

Abstract Recent development of therapies targeting oncogenes have dramatically improved cancer care for subsets of patients and generated a wave of interest in cancer precision medicine. However, effective targeted therapies are scarce as we have a limited understanding of how drug responses are modulated by tumor genotype. Here, we utilize both human data and in vivo models to identify genetic drivers of therapy response in KRAS-driven non-small cell lung cancer patients treated with chemotherapy. We first present an integrative causal inference analysis of three clinical data resources: (1) the recently released Genomics Evidence Neoplasia Information Exchange, Biopharma Collaboration dataset (GENIE-BPC; n=197), (2) a selected set of patients from the Tempus Clinico-genomic Database (n=330), and (3) an additional cohort from Memorial Sloan Kettering Cancer Center (n=218). Each dataset was first analyzed separately using a causal inference pipeline. Doubly robust estimators for each variant were inferred within a counting process survival analysis model accounting for time-varying treatments and immortal time bias. Meta-analysis of the results from all three cohorts identified three commonly mutated and highly replicable genes with a significant effect on overall survival: KEAP1, SMARCA4, and CDKN2A. As further validation, we used our murine in vivo pharmacogenomics (PGx) platform that can quantify the effects of therapies across thousands of tumors of diverse genotypes. These tumors are initiated de novo in the native microenvironmental context in mice with an intact adaptive immune system. We tested a chemotherapy combination of carboplatin and pemetrexed in mice with KrasG12D-driven lung tumors and inactivation of each of 60 putative tumor suppressors. Treatment led to >75% reduction in tumor sizes relative to tumor suppressor inactivated (matched) vehicle-treated controls. These models identified causal effects for two out of the three candidates above: KEAP1 (resistance) and CDKN2A (sensitive). Moreover, our PGx platform identified additional candidate genes beyond those found using the clinical data, which had insufficient sample size for these rarely mutated genes. Together, we demonstrate how leveraging our PGx platform together with human data within a causal inference framework may improve the stratification of patients by their clinical outcomes, profoundly advancing the promise of precision medicine. Citation Format: David Amar, Erick Scott, Ian P. Winters, Gregory D. Wall, Dmitri A. Petrov, Monte M. Winslow, Joseph Juan, Ian K. Lai, Lafia Sebastian, Edwin A. Apilado, Gabriel Grenot, Vy B. Tran, Charles Rudin, Michael J. Rosen. An in vivo pharmacogenomics platform replicates and extends biomarkers of therapy response identified via causal inference analysis of clinical data. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5723.

Chaotic fractals: Why chaos is the dynamic of carcinogenesis

We can see the fractals in our environment every day (trees, snowflakes, broccoli, etc.). Even the shapes of the DNA helix and anatomical structures are fractal, for example, the branching of blood vessels, bronchi, and cell membranes [1]. Unlike euclidean geometry, fractal geometry reveals how an object with irregularities in many dimensions can be identified by examining how the number of features in one dimension relates to the number of similarly shaped features in other dimensions [2]. Mandelbrot used fractal geometry to describe such irregular shapes and demonstrated that this geometry was an appropriate mathematical language for describing chaotic systems [1]. In fractal geometry, the fractal dimension (FD) is a statistical quantity that gives an indication of how completely a fractal appears to fill space, as one zooms down to finer and finer scales. The FD provides a measure of the complexity of a structure. Increased FD is an indicator of chaos [3]. A complex adaptive system (CAS) is a type of system that is composed of many interacting components, called agents, which can adapt and change their behavior based on their interactions with the environment and with other agents. CAS are characterized by their ability to self-organize and evolve over time, often resulting in emergent properties and behaviors that cannot be predicted from the properties of the individual agents alone. Examples of CAS include ecosystems, economies, social networks, and the human brain. It is also worth noting that a CAS can have both chaotic and regular behavior depending on the circumstances and the complexity of the system. Stem cells can also be considered CAS because they possess many of the characteristics that define CAS. Stem cells have the ability to self-renew, differentiate into multiple cell types, and respond to signals from their environment [4]. Some studies suggest an important role of the feedback loop between cancer cells and the microenvironment. Also, putting cells into an “inappropriate” microenvironmental context can otherwise trigger pathological issues, and even neoplastic transformation [5]. Cancer has previously been demonstrated to be a chaotic behavior of the stem cell [6]. The FD of chromatin has been demonstrated to increase during carcinogenesis and tumor growth in diffuse large B-cell lymphoma, chronic lymphocytic leukemia, oropharyngeal carcinoma, and hepatocarcinoma compared to equivalent normal tissue. A research study of over 3000 cancer specimens revealed the prevalence of fractal chromatin structure in neoplasias, as well as the importance of this arrangement in the creation of chromosomal abnormalities [7]. Fractal analysis of the cell surface is a rather sensitive method that has been recently introduced to characterize cell progression toward cancer. Analysis of FD of cell surface imaged with atomic force microscopy (AFM) showed strong segregation between normal and malignant human cervical epithelial cells [8]. There is a growing literature that shows FD to be a useful measure of the pathologies of the tumoral vascular architecture, and tumor/parenchymal border [3, 9]. Entropy-based fractal image modeling has been used to increase the diagnostic accuracy of mammographic detection of breast tumors. Mammographic density correlates with the FD of breast cancer and eventually with a higher growth rate. Breast masses with higher FD show increased aggressiveness and poor prognosis [5]. The FD of the lung tumor on contrast-enhanced computed tomography (CT) images demonstrated that the use of FD as a predictive indicator of therapeutic response or progression is warranted [10]. Similarly, the FD of liver mass in contrast-enhanced CT is a useful prognostic biomarker for hepatocellular carcinoma patients treated with sunitinib [11]. The FD analysis of thyroid ultrasound images is used for the prediction and early detection of thyroid malignancy [12]. Moreover, fractal geometry is applied in many radiographic analyses. At least, the application of chaos theory opens up the opportunity for novel dynamic access to carcinogenesis. Of course, the application of chaos theory cannot solve all problems, but such an interdisciplinary approach may increase the understanding of carcinogenesis. Mesut Tez: Writing—review and editing (equal). None. The author declares no conflict of interest. Not applicable. Not applicable. If no data are available, there is no data for this review.

Abstract P3-08-06: Monitoring Lymphovascular Invasion and Tumor Growth of Inflammatory Breast Cancer in a Murine Lymphatic Reporter Window Chamber Model

Abstract Background: Lymphovascular invasion (LVI) is a major route of metastatic dissemination and recent studies indicate its value as an independent prognostic indicator for advanced breast, colorectal, squamous cell, prostate, brain cancers. LVI is a clinicopathological hallmark of inflammatory breast cancer (IBC), an understudied and most lethal breast cancer. IBC is often misdiagnosed due to an absence of a solid mass and its unique presentation of diffuse tumor cell clusters/emboli in the dermal lymphatics. Widely used mammary tumor implantation models coupled with bioluminescence or fluorescence imaging to monitor tumor growth kinetics are ineffective for evaluating spatial and temporal changes in growth and migration patterns of individual tumor cells and clusters within their microenvironmental context. The goal of this study was to develop a murine model to simulate the unique clinicopathological features of IBC patients and to assess both qualitatively and quantitatively local tumor growth, motility, and LVI. Methods: To specifically facilitate visualization of lymphatic and endothelial vessels along with tumor-vessel interactions, we generated a transgenic nude mice model (ProxTom RFP Nu/Nu) wherein, the mice exhibit red, fluorescent lymphatics [tdTomato fluorophore under control of a Prox1 promoter, which encodes a transcription factor (prospero-related homeobox 1) necessary for the formation and maintenance of lymphatic vessels]. Next, we employed a surgical technique, wherein a window chamber is placed on the dorsal skinfold of mice, which allows for microscopic examination of implanted tumor cells and ability to track dynamic changes of the tumor in its local microenvironment from the time of implantation up to 10 days. Patient-derived IBC or PDX stably transfected to express green, red fluorescent and/or dual tagged with luciferase reporters were transplanted in mice bearing window chambers. Intravital fluorescence microscopy and IVIS imaging were used to serially quantify local tumor growth, motility, length density of lymph and blood vessels, and degree of tumor cell lymphatic invasion over 0-140h. Results: Multichannel optical imaging of the window chamber in the ProxTom RFP Nu/Nu mice demonstrated co-localization of IBC tumor cells and lymphatics. Diffuse tumor cells were observed along regions of lymphatic vessels both proximal and distal to the primary tumor site. However, measurement of blood and lymph vessel density showed no significant change over time. Next, these datasets were used for quantitative analysis by setting the tumor cell channel (GFP) at a threshold to count any clusters greater than 50 pixels2 (~0.0013mm2) and with greater than the mean + 2 standard deviations of the background signal while avoiding noise/artifacts from very small regions (<~0.001mm2). This allowed for computation of the total tumor area including average area of each cluster. In addition, the area moment, which describes the basic directional growth pattern of the tumor cells, was quantified by multiplying a cluster distance from the center of mass by its area. Conclusions: A key novel finding from structured illumination imaging data was the observation of LVI occurring early, similar with the clinical presentation in IBC patients. This model was able to effectively track tumor cluster migration. This approach of short-term longitudinal imaging time frame in studying transient or dynamic events of diffuse, collectively migrating tumor cells in the local environment and quantitative analysis of the tumor area, motility and vessel characteristics is an innovation that can be used to investigate other cancer cell types exhibiting LVI. Funding in part by DoD W81XWH-17-1-0297; W81XWH201053 (GRD); ACS Mission Boost grant MBG-20-141-01 (GRD) and NIH grant P30-CA014236 (Imaging Core/GMP) Citation Format: Gayathri R Devi, Dorababu Sannareddy, Alexandra Bennion, Ashlyn Rickard, Douglas C Rouse, Mark W Dewhirst, Gregory M Palmer. Monitoring Lymphovascular Invasion and Tumor Growth of Inflammatory Breast Cancer in a Murine Lymphatic Reporter Window Chamber Model [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-08-06.

Applying Strategic Management approaches to a nursery school in the United Arab Emirates

Strategic management is the evaluation, planning, and implementation process to maintain or improve competitive advantage. The examination consists of appraising the macro and the microenvironmental contexts. The strategic implementation looks forward to effective leadership in practice to establish the suitable structure of the firm, foster organizational culture and evaluate the strategic processes through the relevant control systems and tools. The organizational results demonstrate the success of the strategic measures undertaken like revenues, market shares, profitability and the return on investment. We chose a nursery located in the UAE where one of the authors was associated and explored the application of the salient strategic management concepts and business strategies. Permission was taken from the management to conform to the ethical guidelines. The brief case study can light the future research implications on the management and overcoming the obstacles encountered in the process.

Engineered matrix microenvironments reveal the heterogeneity of liver sinusoidal endothelial cell phenotypic responses.

Fibrosis is one of the hallmarks of chronic liver disease and is associated with aberrant wound healing. Changes in the composition of the liver microenvironment during fibrosis result in a complex crosstalk of extracellular cues that promote altered behaviors in the cell types that comprise the liver sinusoid, particularly liver sinusoidal endothelial cells (LSECs). Recently, it has been observed that LSECs may sustain injury before other fibrogenesis-associated cells of the sinusoid, implicating LSECs as key actors in the fibrotic cascade. A high-throughput cellular microarray platform was used to deconstruct the collective influences of defined combinations of extracellular matrix (ECM) proteins, substrate stiffness, and soluble factors on primary human LSEC phenotype in vitro. We observed remarkable heterogeneity in LSEC phenotype as a function of stiffness, ECM, and soluble factor context. LYVE-1 and CD-31 expressions were highest on 1 kPa substrates, and the VE-cadherin junction localization was highest on 25 kPa substrates. Also, LSECs formed distinct spatial patterns of LYVE-1 expression, with LYVE-1+ cells observed in the center of multicellular domains, and pattern size regulated by microenvironmental context. ECM composition also influenced a substantial dynamic range of expression levels for all markers, and the collagen type IV was observed to promote elevated expressions of LYVE-1, VE-cadherin, and CD-31. These studies highlight key microenvironmental regulators of LSEC phenotype and reveal unique spatial patterning of the sinusoidal marker LYVE-1. Furthermore, these data provide insight into understanding more precisely how LSECs respond to fibrotic microenvironments, which will aid drug development and identification of targets to treat liver fibrosis.

Applying Strategic Management approaches to a nursery school in the United Arab Emirates

Strategic management is the evaluation, planning, and implementation process to maintain or improve competitive advantage. The examination consists of appraising the macro and the microenvironmental contexts. The strategic implementation looks forward to effective leadership in practice to establish the suitable structure of the firm, foster organizational culture and evaluate the strategic processes through the relevant control systems and tools. The organizational results demonstrate the success of the strategic measures undertaken like revenues, market shares, profitability and the return on investment. We chose a nursery located in the UAE where one of the authors was associated and explored the application of the salient strategic management concepts and business strategies. Permission was taken from the management to conform to the ethical guidelines. The brief case study can light the future research implications on the management and overcoming the obstacles encountered in the process.

P1414: MARROW ADIPOCYTE-ENRICHED NICHE HOSTS AND INFLUENCES A FRACTION OF HEMATOPOIETIC PROGENITORS IN ADULT HIP BONE

Background: The hematopoietic process is tightly regulated by the bone marrow (BM) microenvironment. Emerging studies recognized a regulatory role of mouse BM adipose tissue (BMAT) on self-renewal and differentiation of hematopoietic stem cells (HSC) and progenitors, while results on human BMAT are still scarce. Aims: Although hip arthroplasty-derived BM serves as an available resource for non-malignant hematopoietic cell research, the BMAT component of this BM and its’ impact on hematopoietic progenitors is not yet revealed. Therefore, our aims were to explore the contribution of human BMAT to the maintenance of hematopoietic progenitors. Methods: BM samples of acetabular bones were obtained from patients undergoing hip arthroplasty (n=13, 65.7±12.5 years, Ethical approval 187/18). Centrifugation was applied to separate the fatty layer containing BMAT from the BM cell suspension. The BM fraction was used for isolation of BM mononuclear (BMC) and expansion of BM mesenchymal stromal cells (BM-MSC). Digestion of BMAT was applied to separate the non-adipocytic cells of BMAT from mature adipocytes, expand them, and to investigate their functions and transcriptional activity by RNA sequencing. Multiparametric flow cytometry was applied to explore surface marker expression. Hematopoietic activity was investigated by short-term colony assays of cells ex vivo and in vitro upon co-culture with BM-MSC or sub-cultured BMAT adipocytes. Results are presented as mean ±SD and statistical significance was estimated by paired tests. Results: We found that the total colony forming cell number in BMC (0.147±0.068) was significantly higher than in BMAT-associated cells (0.0684±0.062%, p=0.0002, n=11). The strongest reduction within BMAT was observed in colony forming unit (CFU)-macrophages and CFU-granulocyte-erythroid-macrophage/monocyte-megakaryocytes. The content of CD45+CD34+ cells was higher in BMC (0.901±1.009%) than in BMAT (0.357±0.505%), while interestingly no differences were found in CD33+ cell frequencies. Both, expanded BMAT and sub-cultured BMAT adipocytes showed stronger adipogenic potential than BM-MSC. When compared to BM-MSC, sub-cultured BMAT adipocytes showed weaker potential to support growth of committed hematopoietic progenitors within BMC ex vivo, favorizing the growth of early and late erythroid progenitors at the expense of other hematopoietic cells. Transcriptomic analyses showed that HSC niche factors (Angptl4, Wnt5b, Il7, Dkk3), but also LepR were upregulated in BM-MSC compared to expanded BMAT cells. Summary/Conclusion: Our findings indicate a yet unrevealed participation of the BMAT niche in compartmentalization of adult hip bone hematopoietic progenitors by hosting a set of hematopoietic cells and potentially, BMAT progenitors in the close proximity of BM adipocytes. Since a behavior of BM populations is dependent on local microenvironmental context and bone region, obtained results might reflect pathologic settings in arthroplasty patients. Further studies have to address the potential coupling of marrow adipogenesis and hematopoietic progenitor maintenance during aging and diseases.

Multiple Mechanisms of NOTCH1 Activation in Chronic Lymphocytic Leukemia: NOTCH1 Mutations and Beyond.

Simple SummaryMutations of the NOTCH1 gene are a validated prognostic marker in chronic lymphocytic leukemia and a potential predictive marker for anti-CD20-based therapies. At present, the most frequent pathological alteration of the NOTCH1 gene is due to somatic genetic mutations, which have a multifaceted functional impact. However, beside NOTCH1 mutations, other factors may lead to activation of the NOTCH1 pathway, and these include mutations of FBXW7, MED12, SPEN, SF3B1 as well as other B-cell pathways. Understanding the preferential strategies though which CLL cells hijack NOTCH1 signaling may present important clues for designing targeted treatment strategies for the management of CLL.The Notch signaling pathway plays a fundamental role for the terminal differentiation of multiple cell types, including B and T lymphocytes. The Notch receptors are transmembrane proteins that, upon ligand engagement, undergo multiple processing steps that ultimately release their intracytoplasmic portion. The activated protein ultimately operates as a nuclear transcriptional co-factor, whose stability is finely regulated. The Notch pathway has gained growing attention in chronic lymphocytic leukemia (CLL) because of the high rate of somatic mutations of the NOTCH1 gene. In CLL, NOTCH1 mutations represent a validated prognostic marker and a potential predictive marker for anti-CD20-based therapies, as pathological alterations of the Notch pathway can provide significant growth and survival advantage to neoplastic clone. However, beside NOTCH1 mutation, other events have been demonstrated to perturb the Notch pathway, namely somatic mutations of upstream, or even apparently unrelated, proteins such as FBXW7, MED12, SPEN, SF3B1, as well as physiological signals from other pathways such as the B-cell receptor. Here we review these mechanisms of activation of the NOTCH1 pathway in the context of CLL; the resulting picture highlights how multiple different mechanisms, that might occur under specific genomic, phenotypic and microenvironmental contexts, ultimately result in the same search for proliferative and survival advantages (through activation of MYC), as well as immune escape and therapy evasion (from anti-CD20 biological therapies). Understanding the preferential strategies through which CLL cells hijack NOTCH1 signaling may present important clues for designing targeted treatment strategies for the management of CLL.

Abstract 2146: A quantitative in vivo pharmacogenomics platform uncovers biomarkers of therapy response

Abstract Cancer is characterized by heterogeneous genetic alterations that drive changes in cell state that often impact responses to therapy. Recent successes in the development of therapies targeting oncogenes has dramatically improved cancer care for subsets of patients and generated a wave of interest in precision cancer medicines. However, efforts to broadly discover effective targeted therapies have been stymied by a limited understanding of how response to drugs is modulated by tumor genotype. Here, we describe an in vivo functional cancer pharmacogenomics (PGx) platform optimized for the discovery of genetic drivers of response to therapies. By ​​coupling somatic genome editing, DNA barcoding, next generation sequencing, and robust statistical methods with genetically engineered mouse models of human lung cancer, the effects of different candidate therapies can be precisely quantified across thousands of tumors of diverse tumor suppressor genotypes. These tumors are initiated de novo in the native microenvironmental context in mice with an intact adaptive immune system. To illustrate the translational value of our platform, we tested a standard-of-care chemotherapy combination of carboplatin and pemetrexed (carbo/pem) in mice with oncogenic KrasG12D-driven lung tumors with inactivation of 22 putative tumor suppressors. Treatment after 12 weeks of tumor growth for 3 weeks led to greater than 75% reduction in tumor sizes relative to vehicle controls. Surprisingly, although chemotherapy affects cell proliferation pathways rather than a defined genetic component, we identified a diverse spectrum of genotype-specific sensitivity and resistance to carbo/pem treatment in our model. We next determined the extent to which our empirical PGx data could predict human clinical outcomes by analyzing clinicogenomic data from >200 patients with KRAS mutant lung cancer who received combination chemotherapy treatment. Training a multivariate Cox proportional hazards (PH) model on overall survival from treatment initiation using our 22 cancer-associated genes as binary features in combination with baseline clinical data revealed a remarkable agreement between the Cox-PH coefficients and our empirical PGx data. Further analysis of the human survival data using multiple machine learning (ML) methods identified Random Survival Forests (RSF) as the top performing model. Importantly, using mouse empirical PGx data to rank genes for feature selection significantly improved the predictive power of the ML model. Together, these results demonstrate how leveraging our PGx platform together with human data within a machine learning framework may improve the prediction of patient clinical outcomes, and thus profoundly impact our ability to realize the promise of precision medicine. Citation Format: Michael Rosen, David Amar, Ian Winters, Hira Rizvi, Wensheng Nie, Gregory Wall, Dmitri Petrov, Monte Winslow, Charles Rudin, Joseph Juan. A quantitative in vivo pharmacogenomics platform uncovers biomarkers of therapy response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2146.

High throughput interrogation of human liver stellate cells reveals microenvironmental regulation of phenotype

Liver fibrosis is a common feature of progressive liver disease and is manifested as a dynamic series of alterations in both the biochemical and biophysical properties of the liver. Hepatic stellate cells (HSCs) reside within the perisinusoidal space of the liver sinusoid and are one of the main drivers of liver fibrosis, yet it remains unclear how changes to the sinusoidal microenvironment impact HSC phenotype in the context of liver fibrosis. Cellular microarrays were used to examine and deconstruct the impacts of bio-chemo-mechanical changes on activated HSCs in vitro. Extracellular matrix (ECM) composition and stiffness were found to act individually and in combination to regulate HSC fibrogenic phenotype and proliferation. Hyaluronic acid and collagen III promoted elevated collagen I expression while collagen IV mediated a decrease. Previously activated HSCs exhibited reduced lysyl oxidase (Lox) expression as array substrate stiffness increased, with less dependence on ECM composition. Collagens III and IV increased HSC proliferation, whereas hyaluronic acid had the opposite effect. Meta-analysis performed on these data revealed distinct phenotypic clusters (e.g. low fibrogenesis/high proliferation) as a direct function of their microenvironmental composition. Notably, soft microenvironments mimicking healthy tissue (1 kPa), promoted higher levels of intracellular collagen I and Lox expression in activated HSCs, compared to stiff microenvironments mimicking fibrotic tissue (25 kPa). Collectively, these data suggest potential HSC functional adaptations in response to specific bio-chemo-mechanical changes relevant towards the development of therapeutic interventions. These findings also underscore the importance of the microenvironment when interrogating HSC behavior in healthy, disease, and treatment settings. Statement of significanceIn this work we utilized high-throughput cellular microarray technology to systematically interrogate the complex interactions between HSCs and their microenvironment in the context of liver fibrosis. We observed that HSC phenotype is regulated by ECM composition and stiffness, and that these phenotypes can be classified into distinct clusters based on their microenvironmental context. Moreover, the range of these phenotypic responses to microenvironmental stimuli is substantial and a direct consequence of the combinatorial pairing of ECM protein and stiffness signals. We also observed a novel role for microenvironmental context in affecting HSC responses to potential fibrosis therapeutics.

SOX9 has distinct roles in the formation and progression of different non-small cell lung cancer histotypes.

The transcription factor SOX9 is a key regulator of multiple developmental processes and is frequently re-expressed in non-small cell lung cancer (NSCLC). Its precise role in the progression of NSCLC histotypes has, however, remained elusive. We show that SOX9 expression relates to poor overall survival and invasive histopathology in human non-mucinous adenocarcinoma and is absent in murine early minimally invasive and low in human in situ adenocarcinoma. Interestingly, despite wide SOX9 expression across advanced NSCLC histotypes, its genetic deletion in the murine KrasG12D ;Lkb1fl/fl model selectively disrupted only the growth of papillary NSCLC, without affecting the initiation of precursor lesions or growth of mucinous or squamous tissue. Spatial tissue phenotyping indicated a requirement of SOX9 expression for the progression of surfactant protein C-expressing progenitor cells, which gave rise to papillary tumours. Intriguingly, while SOX9 expression was dispensable for squamous tissue formation, its loss in fact led to enhanced squamous tumour metastasis, which was associated with altered collagen IV deposition in the basement membrane. Our work therefore demonstrates histopathology-selective roles for SOX9 in NSCLC progression, namely as a promoter for papillary adenocarcinoma progression, but an opposing metastasis-suppressing role in squamous histotype tissue. This attests to a pleiotropic SOX9 function, linked to the cell of origin and microenvironmental tissue contexts. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.