Immune checkpoint blockade resistance in lung cancer: emerging mechanisms and therapeutic opportunities.

Immune checkpoint blockade (ICB) therapy works by inhibiting suppressive checkpoints that become upregulated after T cell activation, like PD-1/PD-L1 and CTLA-4. While the initial FDA approvals of ICB have revolutionized cancer therapies and fueled a burgeoning immuno-oncology field, more recent clinical development of new agents has been slow. Here, focusing on lung cancer, we review the latest research uncovering tumor cell intrinsic and extrinsic ICB resistance mechanisms as major hurdles to treatment efficacy and clinical progress. These include genomic and non-genomic tumor cell alterations, along with host and microenvironmental factors like the microbiome, metabolite accumulation, and hypoxia. Together, these factors can cooperate to promote immunosuppression and ICB resistance. Opportunities to prevent resistance are constantly evolving in this rapidly expanding field, with the goal of moving toward personalized immunotherapeutic regimens.

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 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 Genomic and Cellular Analysis (SaGA), for the precise imaging-based selection, isolation, and expansion of phenotypically distinct live cells. This protocol requires cells expressing a photoconvertible fluorescent protein and employs 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 subpopulations for integration with multi-omics techniques. We envision this approach providing multi-dimensional datasets exploring the relationship between live cell phenotypes and multi-omic heterogeneity within normal and diseased cellular populations.

Autotaxin suppresses cytotoxic T cells via LPAR5 to promote anti-PD-1 resistance in non-small cell lung cancer.

Non-small cell lung cancers that harbor concurrent KRAS and TP53 (KP) mutations are immunologically warm tumors with partial responsiveness to anti-PD-(L)1 blockade; however, most patients observe little or no durable clinical benefit. To identify novel tumor-driven resistance mechanisms, we developed a panel of KP murine lung cancer models with intrinsic resistance to anti-PD-1 and queried differential gene expression between these tumors and anti-PD-1-sensitive tumors. We found that the enzyme autotaxin (ATX), and the metabolite it produces, lysophosphatidic acid (LPA), were significantly upregulated in resistant tumors and that ATX directly modulated antitumor immunity, with its expression negatively correlating with total and effector tumor-infiltrating CD8+ T cells. Pharmacological inhibition of ATX, or the downstream receptor LPAR5, in combination with anti-PD-1 was sufficient to restore the antitumor immune response and efficaciously control lung tumor growth in multiple KP tumor models. Additionally, ATX was significantly correlated with inflammatory gene signatures, including a CD8+ cytolytic score in multiple lung adenocarcinoma patient data sets, suggesting that an activated tumor-immune microenvironment upregulates ATX and thus provides an opportunity for cotargeting to prevent acquired resistance to anti-PD-1 treatment. These data reveal the ATX/LPA axis as an immunosuppressive pathway that diminishes the immune checkpoint blockade response in lung cancer.

Targeting immunosuppressive Ly6C+ classical monocytes reverses anti-PD-1/CTLA-4 immunotherapy resistance.

Introduction: Despite significant clinical advancement with the use of immune checkpoint blockade (ICB) in non-small cell lung cancer (NSCLC) there are still a major subset of patients that develop adaptive/acquired resistance. Understanding resistance mechanisms to ICB is critical to developing new therapeutic strategies and improving patient survival. The dynamic nature of the tumor microenvironment and the mutational load driving tumor immunogenicity limit the efficacy to ICB. Recent studies indicate that myeloid cells are drivers of ICB resistance. In this study we sought to understand which immune cells were contributing to resistance and if we could modify them in a way to improve response to ICB therapy. Results: Our results show that combination anti-PD-1/CTLA-4 produces an initial antitumor effect with evidence of an activated immune response. Upon extended treatment with anti-PD-1/CTLA-4 acquired resistance developed with an increase of the immunosuppressive populations, including T-regulatory cells, neutrophils and monocytes. Addition of anti-Ly6C blocking antibody to anti-PD-1/CTLA-4 was capable of completely reversing treatment resistance and restoring CD8 T cell activity in multiple KP lung cancer models and in the autochthonous lung cancer KrasLSL-G12D/p53fl/fl model. We found that there were higher classical Ly6C+ monocytes in anti-PD-1/CTLA-4 combination resistant tumors. B7 blockade illustrated the importance of dendritic cells for treatment efficacy of anti-Ly6C/PD-1/CTLA-4. We further determined that classical Ly6C+ monocytes in anti-PD-1/CTLA-4 resistant tumors are trafficked into the tumor via IFN-γ and the CCL2-CCR2 axis. Mechanistically we found that classical monocytes from ICB resistant tumors were unable to differentiate into antigen presenting cells and instead differentiated into immunosuppressive M2 macrophages or myeloid-derived suppressor cells (MDSC). Classical Ly6C+ monocytes from ICB resistant tumors had a decrease in both Flt3 and PU.1 expression that prevented differentiation into dendritic cells/macrophages. Conclusions: Therapeutically we found that addition of anti-Ly6C to the combination of anti-PD-1/CTLA-4 was capable of complete tumor eradication. Classical Ly6C+ monocytes differentiate into immunosuppressive cells, while blockade of classical monocytes drives dendritic cell differentiation/maturation to reinvigorate the anti-tumor T cell response. These findings support that immunotherapy resistance is associated with infiltrating monocytes and that controlling the differentiation process of monocytes can enhance the therapeutic potential of ICB.

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.

Targeting CDK4 overcomes EMT-mediated tumor heterogeneity and therapeutic resistance in KRAS-mutant lung cancer.

Lack of sustained response to therapeutic agents in patients with KRAS-mutant lung cancer poses a major challenge and arises partly due to intratumor heterogeneity that defines phenotypically distinct tumor subpopulations. To attain better therapeutic outcomes, it is important to understand the differential therapeutic sensitivities of tumor cell subsets. Epithelial-mesenchymal transition is a biological phenomenon that can alter the state of cells along a phenotypic spectrum and cause transcriptional rewiring to produce distinct tumor cell subpopulations. We utilized functional shRNA screens, in in vitro and in vivo models, to identify and validate an increased dependence of mesenchymal tumor cells on cyclin-dependent kinase 4 (CDK4) for survival, as well as a mechanism of resistance to MEK inhibitors. High zinc finger E-box binding homeobox 1 levels in mesenchymal tumor cells repressed p21, leading to perturbed CDK4 pathway activity. Increased dependence on CDK4 rendered mesenchymal cancer cells particularly vulnerable to selective CDK4 inhibitors. Coadministration of CDK4 and MEK inhibitors in heterogeneous tumors effectively targeted different tumor subpopulations, subverting the resistance to either single-agent treatment.

Th17 cells contribute to combination MEK inhibitor and anti-PD-L1 therapy resistance in KRAS/p53 mutant lung cancers.

Understanding resistance mechanisms to targeted therapies and immune checkpoint blockade in mutant KRAS lung cancers is critical to developing novel combination therapies and improving patient survival. Here, we show that MEK inhibition enhanced PD-L1 expression while PD-L1 blockade upregulated MAPK signaling in mutant KRAS lung tumors. Combined MEK inhibition with anti-PD-L1 synergistically reduced lung tumor growth and metastasis, but tumors eventually developed resistance to sustained combinatorial therapy. Multi-platform profiling revealed that resistant lung tumors have increased infiltration of Th17 cells, which secrete IL-17 and IL-22 cytokines to promote lung cancer cell invasiveness and MEK inhibitor resistance. Antibody depletion of IL-17A in combination with MEK inhibition and PD-L1 blockade markedly reduced therapy-resistance in vivo. Clinically, increased expression of Th17-associated genes in patients treated with PD-1 blockade predicted poorer overall survival and response in melanoma and predicated poorer response to anti-PD1 in NSCLC patients. Here we show a triple combinatorial therapeutic strategy to overcome resistance to combined MEK inhibitor and PD-L1 blockade.

Dual Inhibition of MEK and AXL Targets Tumor Cell Heterogeneity and Prevents Resistant Outgrowth Mediated by the Epithelial-to-Mesenchymal Transition in NSCLC.

The epithelial-to-mesenchymal transition (EMT) is a dynamic epigenetic reprogramming event that occurs in a subset of tumor cells and is an initiating step toward invasion and distant metastasis. The process is reversible and gives plasticity to cancer cells to survive under variable conditions, with the acquisition of cancer stem cell-like characteristics and features such as drug resistance. Therefore, understanding survival dependencies of cells along the phenotypic spectrum of EMT will provide better strategies to target the spatial and temporal heterogeneity of tumors and prevent their ability to bypass single-inhibitor treatment strategies. To address this, we integrated the data from a selective drug screen in epithelial and mesenchymal KRAS/p53 (KP)-mutant lung tumor cells with separate datasets including reverse-phase protein array and an in vivo shRNA dropout screen. These orthogonal approaches identified AXL and MEK as potential mesenchymal and epithelial cell survival dependencies, respectively. To capture the dynamicity of EMT, incorporation of a dual fluorescence EMT sensor system into murine KP lung cancer models enabled real-time analysis of the epigenetic state of tumor cells and assessment of the efficacy of single agent or combination treatment with AXL and MEK inhibitors. Both two- and three-dimensional culture systems and in vivo models revealed that this combination treatment strategy of MEK plus AXL inhibition synergistically killed lung cancer cells by specifically targeting each phenotypic subpopulation. In conclusion, these results indicate that cotargeting the specific vulnerabilities of EMT subpopulations can prevent EMT-mediated drug resistance, effectively controlling tumor cell growth and metastasis. SIGNIFICANCE: This study shows that a novel combination of MEK and AXL inhibitors effectively bypasses EMT-mediated drug resistance in KRAS/p53-mutant non-small cell lung cancer by targeting EMT subpopulations, thereby preventing tumor cell survival.

Epigenetically heterogeneous tumor cells direct collective invasion through filopodia-driven fibronectin micropatterning.

Tumor heterogeneity drives disease progression, treatment resistance, and patient relapse, yet remains largely underexplored in invasion and metastasis. Here, we investigated heterogeneity within collective cancer invasion by integrating DNA methylation and gene expression analysis in rare purified lung cancer leader and follower cells. Our results showed global DNA methylation rewiring in leader cells and revealed the filopodial motor MYO10 as a critical gene at the intersection of epigenetic heterogeneity and three-dimensional (3D) collective invasion. We further identified JAG1 signaling as a previously unknown upstream activator of MYO10 expression in leader cells. Using live-cell imaging, we found that MYO10 drives filopodial persistence necessary for micropatterning extracellular fibronectin into linear tracks at the edge of 3D collective invasion exclusively in leaders. Our data fit a model where epigenetic heterogeneity and JAG1 signaling jointly drive collective cancer invasion through MYO10 up-regulation in epigenetically permissive leader cells, which induces filopodia dynamics necessary for linearized fibronectin micropatterning.

Prognostic significance of an invasive leader cell-derived mutation cluster on chromosome 16q.

BACKGROUND: Intratumoral heterogeneity is defined by subpopulations with varying genotypes and phenotypes. Specialized, highly invasive leader cells and less invasive follower cells are phenotypically distinct subpopulations that cooperate during collective cancer invasion. Because leader cells are a rare subpopulation that would be missed by bulk sequencing, a novel image-guided genomics platform was used to precisely select this subpopulation. This study identified a novel leader cell mutation signature and tested its ability to predict prognosis in non-small cell lung cancer (NSCLC) patient cohorts. METHODS: Spatiotemporal genomic and cellular analysis was used to isolate and perform RNA sequencing on leader and follower populations from the H1299 NSCLC cell line, and it revealed a leader-specific mutation cluster on chromosome 16q. Genomic data from patients with lung squamous cell carcinoma (LUSC; n = 475) and lung adenocarcinoma (LUAD; n = 501) from The Cancer Genome Atlas were stratified by 16q mutation cluster (16qMC) status (16qMC+ vs 16qMC-) and compared for overall survival (OS), progression-free survival (PFS), and gene set enrichment analysis (GSEA). RESULTS: Poorer OS, poorer PFS, or both were found across all stages and among early-stage patients with 16qMC+ tumors within the LUSC and LUAD cohorts. GSEA revealed 16qMC+ tumors to be enriched for the expression of metastasis- and survival-associated gene sets. CONCLUSIONS: This represents the first leader cell mutation signature identified in patients and has the potential to better stratify high-risk NSCLC and ultimately improve patient outcomes.

The Good, the Bad and the Unknown of CD38 in the Metabolic Microenvironment and Immune Cell Functionality of Solid Tumors.

The regulation of the immune microenvironment within solid tumors has received increasing attention with the development and clinical success of immune checkpoint blockade therapies, such as those that target the PD-1/PD-L1 axis. The metabolic microenvironment within solid tumors has proven to be an important regulator of both the natural suppression of immune cell functionality and the de novo or acquired resistance to immunotherapy. Enzymatic proteins that generate immunosuppressive metabolites like adenosine are thus attractive targets to couple with immunotherapies to improve clinical efficacy. CD38 is one such enzyme. While the role of CD38 in hematological malignancies has been extensively studied, the impact of CD38 expression within solid tumors is largely unknown, though most current data indicate an immunosuppressive role for CD38. However, CD38 is far from a simple enzyme, and there are several remaining questions that require further study. To effectively treat solid tumors, we must learn as much about this multifaceted protein as possible-i.e., which infiltrating immune cell types express CD38 for functional activities, the most effective CD38 inhibitor(s) to employ, and the influence of other similarly functioning enzymes that may also contribute towards an immunosuppressive microenvironment. Gathering knowledge such as this will allow for intelligent targeting of CD38, the reinvigoration of immune functionality and, ultimately, tumor elimination.

Genetic heterogeneity within collective invasion packs drives leader and follower cell phenotypes.

Collective invasion, the coordinated movement of cohesive packs of cells, has become recognized as a major mode of metastasis for solid tumors. These packs are phenotypically heterogeneous and include specialized cells that lead the invasive pack and others that follow behind. To better understand how these unique cell types cooperate to facilitate collective invasion, we analyzed transcriptomic sequence variation between leader and follower populations isolated from the H1299 non-small cell lung cancer cell line using an image-guided selection technique. We now identify 14 expressed mutations that are selectively enriched in leader or follower cells, suggesting a novel link between genomic and phenotypic heterogeneity within a collectively invading tumor cell population. Functional characterization of two phenotype-specific candidate mutations showed that ARP3 enhances collective invasion by promoting the leader cell phenotype and that wild-type KDM5B suppresses chain-like cooperative behavior. These results demonstrate an important role for distinct genetic variants in establishing leader and follower phenotypes and highlight the necessity of maintaining a capacity for phenotypic plasticity during collective cancer invasion.

Targeting the Interplay between Epithelial-to-Mesenchymal-Transition and the Immune System for Effective Immunotherapy.

Over the last decade, both early diagnosis and targeted therapy have improved the survival rates of many cancer patients. Most recently, immunotherapy has revolutionized the treatment options for cancers such as melanoma. Unfortunately, a significant portion of cancers (including lung and breast cancers) do not respond to immunotherapy, and many of them develop resistance to chemotherapy. Molecular characterization of non-responsive cancers suggest that an embryonic program known as epithelial-mesenchymal transition (EMT), which is mostly latent in adults, can be activated under selective pressures, rendering these cancers resistant to chemo- and immunotherapies. EMT can also drive tumor metastases, which in turn also suppress the cancer-fighting activity of cytotoxic T cells that traffic into the tumor, causing immunotherapy to fail. In this review, we compare and contrast immunotherapy treatment options of non-small cell lung cancer (NSCLC) and triple negative breast cancer (TNBC). We discuss why, despite breakthrough progress in immunotherapy, attaining predictable outcomes in the clinic is mostly an unsolved problem for these tumors. Although these two cancer types appear different based upon their tissues of origin and molecular classification, gene expression indicate that they possess many similarities. Patient tumors exhibit activation of EMT, and resulting stem cell properties in both these cancer types associate with metastasis and resistance to existing cancer therapies. In addition, the EMT transition in both these cancers plays a crucial role in immunosuppression, which exacerbates treatment resistance. To improve cancer-related survival we need to understand and circumvent, the mechanisms through which these tumors become therapy resistant. In this review, we discuss new information and complementary perspectives to inform combination treatment strategies to expand and improve the anti-tumor responses of currently available clinical immune checkpoint inhibitors.

Ntrk1 Promotes Resistance to PD-1 Checkpoint Blockade in Mesenchymal Kras/p53 Mutant Lung Cancer.

The implementation of cancer immunotherapeutics for solid tumors including lung cancers has improved clinical outcomes in a small percentage of patients. However, the majority of patients show little to no response or acquire resistance during treatment with checkpoint inhibitors delivered as a monotherapy. Therefore, identifying resistance mechanisms and novel combination therapy approaches is imperative to improve responses to immune checkpoint inhibitors. To address this, we performed an in vivo shRNA dropout screen that focused on genes encoding for FDA-approved drug targets (FDAome). We implanted epithelial and mesenchymal Kras/p53 (KP) mutant murine lung cancer cells expressing the FDAome shRNA library into syngeneic mice treated with an anti-PD-1 antibody. Sequencing for the barcoded shRNAs revealed Ntrk1 was significantly depleted from mesenchymal tumors challenged with PD-1 blockade, suggesting it provides a survival advantage to tumor cells when under immune system pressure. Our data confirmed Ntrk1 transcript levels are upregulated in tumors treated with PD-1 inhibitors. Additionally, analysis of tumor-infiltrating T cell populations revealed that Ntrk1 can promote CD8+ T cell exhaustion. Lastly, we found that Ntrk1 regulates Jak/Stat signaling to promote expression of PD-L1 on tumor cells. Together, these data suggest that Ntrk1 activates Jak/Stat signaling to regulate expression of immunosuppressive molecules including PD-L1, promoting exhaustion within the tumor microenvironment.

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 2-dimensional 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.

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. These tumors can undergo irreversible changes to the tumor ecosystem that outlast the 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.

Vimentin Is Required for Lung Adenocarcinoma Metastasis via Heterotypic Tumor Cell-Cancer-Associated Fibroblast Interactions during Collective Invasion.

Purpose: Vimentin is an epithelial-to-mesenchymal transition (EMT) biomarker and intermediate filament protein that functions during cell migration to maintain structure and motility. Despite the abundance of clinical data linking vimentin to poor patient outcome, it is unclear if vimentin is required for metastasis or is a correlative biomarker. We developed a novel genetically engineered mouse model (GEMM) to probe vimentin in lung adenocarcinoma metastasis.Experimental Design: We used the LSL-KrasG12D/Lkb1fl/fl/Vim-/- model (KLV-/-), which incorporates a whole-body knockout of vimentin and is derived from the Cre-dependent LSL-KrasG12D/Lkb1fl/fl model (KLV+/+). We compared the metastatic phenotypes of the GEMMs and analyzed primary tumors from the KLV models and lung adenocarcinoma patients to assess vimentin expression and function.Results: Characterization of KLV+/+ and KLV-/- mice shows that although vimentin is not required for primary lung tumor growth, vimentin is required for metastasis, and vimentin loss generates lower grade primary tumors. Interestingly, in the KLV+/+ mice, vimentin was not expressed in tumor cells but in cancer-associated fibroblasts (CAFs) surrounding collective invasion packs (CIPs) of epithelial tumor cells, with significantly less CIPs in KLV-/- mice. CIPs correlate with tumor grade and are vimentin-negative and E-cadherin-positive, indicating a lack of cancer cell EMT. A similar heterotypic staining pattern was observed in human lung adenocarcinoma samples. In vitro studies show that vimentin is required for CAF motility to lead tumor cell invasion, supporting a vimentin-dependent model of collective invasion.Conclusions: These data show that vimentin is required for lung adenocarcinoma metastasis by maintaining heterotypic tumor cell-CAF interactions during collective invasion. Clin Cancer Res; 24(2); 420-32. ©2017 AACR.

Targeting adhesion signaling in KRAS, LKB1 mutant lung adenocarcinoma.

Loss of LKB1 activity is prevalent in KRAS mutant lung adenocarcinoma and promotes aggressive and treatment-resistant tumors. Previous studies have shown that LKB1 is a negative regulator of the focal adhesion kinase (FAK), but in vivo studies testing the efficacy of FAK inhibition in LKB1 mutant cancers are lacking. Here, we took a pharmacologic approach to show that FAK inhibition is an effective early-treatment strategy for this high-risk molecular subtype. We established a lenti-Cre-induced Kras and Lkb1 mutant genetically engineered mouse model (KLLenti) that develops 100% lung adenocarcinoma and showed that high spatiotemporal FAK activation occurs in collective invasive cells that are surrounded by high levels of collagen. Modeling invasion in 3D, loss of Lkb1, but not p53, was sufficient to drive collective invasion and collagen alignment that was highly sensitive to FAK inhibition. Treatment of early, stage-matched KLLenti tumors with FAK inhibitor monotherapy resulted in a striking effect on tumor progression, invasion, and tumor-associated collagen. Chronic treatment extended survival and impeded local lymph node spread. Lastly, we identified focally upregulated FAK and collagen-associated collective invasion in KRAS and LKB1 comutated human lung adenocarcinoma patients. Our results suggest that patients with LKB1 mutant tumors should be stratified for early treatment with FAK inhibitors.

Local alignment vectors reveal cancer cell-induced ECM fiber remodeling dynamics.

Invasive cancer cells interact with the surrounding extracellular matrix (ECM), remodeling ECM fiber network structure by condensing, degrading, and aligning these fibers. We developed a novel local alignment vector analysis method to quantitatively measure collagen fiber alignment as a vector field using Circular Statistics. This method was applied to human non-small cell lung carcinoma (NSCLC) cell lines, embedded as spheroids in a collagen gel. Collagen remodeling was monitored using second harmonic generation imaging under normal conditions and when the LKB1-MARK1 pathway was disrupted through RNAi-based approaches. The results showed that inhibiting LKB1 or MARK1 in NSCLC increases the collagen fiber alignment and captures outward alignment vectors from the tumor spheroid, corresponding to high invasiveness of LKB1 mutant cancer cells. With time-lapse imaging of ECM micro-fiber morphology, the local alignment vector can measure the dynamic signature of invasive cancer cell activity and cell-migration-induced ECM and collagen remodeling and realigning dynamics.