Biology subjects

Marcus, A. I.

Publications and source records attributed to Marcus, A. I..

7 recordsLinked to original sources

bioRxiv2025

Clusters, Fingers, and Singles: A Mechanical Landscape of Tumor Invasion

Collective invasion is a key mechanism by which tumors disseminate and metastasize, involving coordinated migration of heterogeneous cell populations. Experimental studies have identified specialized leader and follower cells that work together during this process, but the biophysical rules governing their interaction remain unclear. We present a mechanistic, cell-based computational model using the Cellular Potts framework to investigate how heterotypic adhesion, leader motility, and follower proliferation jointly shape invasion. Leader-follower tumors were simulated across 13,310 parameter sets, and invasion was quantified by invasive and infiltrative areas, finger-like protrusions, solitary defectors, and detached clusters. From these simulations, we identified four distinct invasion phenotypes: non-invasive, bulk collective, single-cell, and multimodal. Multimodal invasion--the coexistence of cohesive strands, solitary cells, and small clusters--emerged as the most prevalent phenotype, particularly under moderate adhesion, high motility, and intermediate proliferation. Proliferation exhibited nonlinear effects: moderate division reinforced cohesive invasion, whereas excessive growth destabilized tumor architecture. Mapping outcomes across the parameter space revealed sharp transitions between invasion modes, underscoring trade-offs between adhesion and motility in shaping invasion complexity. Our results show that hybrid invasion behaviors, previously considered rare, arise robustly from simple mechanical rules and are favored in a broad region of the parameter space. This framework reconciles binary models of invasion with experimental observations of heterogeneity, providing predictive insights into how modulating adhesion, motility, or proliferation can restrict metastatic spread. Author summaryWhen cancer cells leave a primary tumor, they do not just invade as lone cells but also as cohesive fingers and small cell clusters, depending on how strongly cells stick together, how hard some cells pull, and how fast the population grows. We built a simple, physics-based computational model in which a small number of leader cells pull on the more proliferative followers. By systematically varying three key properties, cell-cell adhesion, leader motility, and follower proliferation, we generated a large simulation of invasion patterns and grouped them into four invasion modes. The resulting phase diagram shows where tumors grow as compact masses (no invasion), or invade as protruding "fingers," as single cells, or in a mixed multimodal fashion with fingers, clusters, and single cells. Surprisingly, this mixed state was the most common outcome, arising when adhesion is moderate and leader motility is strong. This map provides intuition and practical rules for thinking about how changes in adhesion or motility might reorganize invasion, such as shifting cluster-forming fronts toward more compact, less dissemination-prone configurations.

cancer biology↗

bioRxiv2024

Tenascin-C in the early lung cancer tumor microenvironment promotes progression through integrin activation and FAK

Pre-cancerous lung lesions are commonly initiated by activating mutations in the RAS pathway, but do not transition to lung adenocarcinomas (LUAD) without additional oncogenic signals. Here, we show that expression of the extracellular matrix protein Tenascin-C (TNC) is increased in and promotes the earliest stages of LUAD development in oncogenic KRAS-driven lung cancer mouse models and in human LUAD. TNC is initially expressed by fibroblasts and its expression extends to tumor cells as the tumor becomes invasive. Genetic deletion of TNC in the mouse models reduces early tumor burden and high-grade pathology and diminishes tumor cell proliferation, invasion, and focal adhesion kinase (FAK) activity. TNC stimulates cultured LUAD tumor cell proliferation and migration through engagement of v-containing integrins and subsequent FAK activation. Intringuingly, lung injury causes sustained TNC accumulation in mouse lungs, suggesting injury can induce additional TNC signaling for early tumor cell transition to invasive LUAD. Biospecimens from patients with stage I/II LUAD show TNC in regions of FAK activation and an association of TNC with tumor recurrence after primary tumor resection. These results suggest that exogenous insults that elevate TNC in the lung parenchyma interact with tumor-initiating mutations to drive early LUAD progression and local recurrence.

cancer biology↗

bioRxiv2023

Live-cell invasive phenotyping uncovers the ALK2/BMP6 iron homeostasis pathway as a therapeutic vulnerability in LKB1-mutant lung cancer

The acquisition of invasive properties is a prerequisite for tumor progression and metastasis. Molecular subtypes of KRAS-driven lung cancer exhibit distinct modes of invasion that likely contribute to unique growth properties and therapeutic susceptibilities. Despite this, pre-clinical discovery strategies designed to exploit invasive phenotypes are lacking. To address this, we designed an experimental system to screen for targetable signaling pathways linked to active early invasion phenotypes in the two most prominent molecular subtypes, TP53 and LKB1, of KRAS-driven lung adenocarcinoma (LUAD). By combining live-cell imaging of human bronchial epithelial cells in a 3D invasion matrix with RNA transcriptome profiling, we identified the LKB1-specific upregulation of bone morphogenetic protein 6 (BMP6). Examination of early-stage lung cancer patients confirmed upregulation of BMP6 in LKB1-mutant lung tumors. At the molecular level, we find that the canonical iron regulatory hormone Hepcidin is induced via BMP6 signaling upon LKB1 loss, where intact LKB1 kinase activity is necessary to maintain signaling homeostasis. Furthermore, pre-clinical studies in a novel Kras/Lkb1-mutant syngeneic mouse model show that potent growth suppression was achieved by inhibiting the ALK2/BMP6 signaling axis with single agents that are currently in clinical trials. We show that alterations in the iron homeostasis pathway are accompanied by simultaneous upregulation of ferroptosis protection proteins. Thus, LKB1 is sufficient to regulate both the gas and breaks to finely tune iron-regulated tumor progression.

cancer biology↗

bioRxiv2023

A live-cell platform to isolate phenotypically defined subpopulations for spatial multi-omic profiling

Numerous techniques have been employed to deconstruct the heterogeneity observed in normal and diseased cellular populations, including single cell RNA sequencing, in situ hybridization, and flow cytometry. While these approaches have revolutionized our understanding of heterogeneity, in isolation they cannot correlate phenotypic information within a physiologically relevant live-cell state, with molecular profiles. This inability to integrate a historical live-cell phenotype, such as invasiveness, cell:cell interactions, and changes in spatial positioning, with multi-omic data, creates a gap in understanding cellular heterogeneity. We sought to address this gap by employing lab technologies to design a detailed protocol, termed Spatiotemporal Genomics and Cellular Analysis (SaGA), for the precise imaging-based selection, isolation, and expansion of phenotypically distinct live-cells. We begin with cells stably expressing a photoconvertible fluorescent protein and employ live cell confocal microscopy to photoconvert a user-defined single cell or set of cells displaying a phenotype of interest. The total population is then extracted from its microenvironment, and the optically highlighted cells are isolated using fluorescence activated cell sorting. SaGA-isolated cells can then be subjected to multi-omics analysis or cellular propagation for in vitro or in vivo studies. This protocol can be applied to a variety of conditions, creating protocol flexibility for user-specific research interests. The SaGA technique can be accomplished in one workday by non-specialists and results in a phenotypically defined cellular subpopulation for integration with multi-omics techniques. We envision this approach providing multi-dimensional datasets exploring the relationship between live-cell phenotype and multi-omic heterogeneity within normal and diseased cellular populations.

cell biology↗

bioRxiv2023

Loss of the endocytic tumor suppressor HD-PTP phenocopies LKB1 and promotes RAS-driven oncogenesis.

Abstract/SummaryOncogenic RAS mutations drive aggressive cancers that are difficult to treat in the clinic, and while direct inhibition of the most common KRAS variant in lung adenocarcinoma (G12C) is undergoing clinical evaluation, a wide spectrum of oncogenic RAS variants together make up a large percentage of untargetable lung and GI cancers. Here we report that loss-of-function alterations (mutations and deep deletions) in the gene that encodes HD-PTP (PTPN23) occur in up to 14% of lung cancers in the ORIEN Avatar lung cancer cohort, associate with adenosquamous histology, and occur alongside an altered spectrum of KRAS alleles. Furthermore, we show that in publicly available early-stage NSCLC studies loss of HD-PTP is mutually exclusive with loss of LKB1, which suggests they restrict a common oncogenic pathway in early lung tumorigenesis. In support of this, knockdown of HD-PTP in RAS-transformed lung cancer cells is sufficient to promote FAK-dependent invasion. Lastly, knockdown of the Drosophila homolog of HD-PTP (dHD-PTP/Myopic) synergizes to promote RAS-dependent neoplastic progression. Our findings highlight a novel tumor suppressor that can restrict RAS-driven lung cancer oncogenesis and identify a targetable pathway for personalized therapeutic approaches for adenosquamous lung cancer.

cancer biology↗

bioRxiv2017

The Complex Ecosystem in Non Small Cell Lung Cancer Invasion

Many tumors are characterized by genetic instability, producing an assortment of genetic variants of tumor cells called subclones. These tumors and their surrounding environments form complex multi-cellular ecosystems, where subclones compete for resources and cooperate to perform multiple tasks, including cancer invasion. Our recent empirical studies revealed existence of such distinct phenotypes of cancer cells, leaders and followers, in lung cancer. These two cellular subclones exchange a complex array of extracellular signals demonstrating a symbiotic relationship at the cellular level. Here, we develop a computational model of the microenvironment of the lung cancer ecosystem to explore how the interactions between subclones can advance or inhibit invasion. We found that, due to the complexity of the ecosystem, invasion may have very different dynamics characterized by the different levels of aggressiveness. By altering the signaling environment, we could alter the ecological relationship between the cell types and the overall ecosystem development. Competition between leader and follower cell populations (defined by the limited amount of resources), positive feedback within the leader cell population (controlled by the focal adhesion kinase and fibronectin signaling), and impact of the follower cells to the leaders (represented by yet undetermined proliferation signal) all had major effects on the outcome of the collective dynamics. Specifically, our analysis revealed a class of tumors (defined by the strengths of fibronectin signaling and competition) that are particularly sensitive to manipulations of the signaling environment. This class can undergo irreversible changes to the tumor ecosystem that outlast these manipulations of feedbacks and have a profound impact on invasive potential. Our study predicts a complex division of labor between cancer cell subclones and suggests new treatment strategies targeting signaling within the tumor ecosystem.\n\nAuthor SummaryCancer is an elusive disease due to the wide variety of cancer types and adaptability to treatment. How is this adaptability accomplished? Loss of genetic stability, a hallmark of cancer, leads to the emergence of many different types of cancer cells within a tumor. This creates a complex ecosystem where cancer cell types can cooperate, compete, and exploit each other. We have previously used an image-guided technology to isolatedistinct cancer subclones and identify how they interact. Here, we have employed mathematical modeling to understand how the dynamic feedbacks between different cancer cell types can impact the success of invasion in lung cancer. We found that successful invasion required for feedbacks to support the less viable but more invasive cell types. These predictions may have implications for novel clinical treatment options and emphasize the need to visualize and probe cancer as a tumor ecosystem.

cancer biology↗

bioRxiv2017

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics

Spheroid cultures derived from explanted cancer specimens are an increasingly utilized resource for studying complex biological processes like tumor cell invasion and metastasis, representing an important bridge between the simplicity and practicality of 2D monolayer cultures and the complexity and realism of in vivo animal models. Temporal imaging of spheroids can capture the dynamics of cell behaviors and microenvironments, and when combined with quantitative image analysis methods, enables deep interrogation of biological mechanisms. This paper presents a comprehensive open-source software framework for Temporal Analysis of Spheroid Imaging (TASI) that allows investigators to objectively characterize spheroid growth and invasion dynamics. TASI performs spatiotemporal segmentation of spheroid cultures, extraction of features describing spheroid morpho-phenotypes, mathematical modeling of spheroid dynamics, and statistical comparisons of experimental conditions. We demonstrate the utility of this tool in an analysis of non-small cell lung cancer spheroids that exhibit variability in metastatic and proliferative behaviors.

bioinformatics↗