Cancer cell - Fibroblast crosstalk via HB-EGF, EGFR, and MAPK signaling promotes the expression of macrophage chemo-attractants in squamous cell carcinoma.

Interactions between cells in the tumor microenvironment (TME) shape cancer progression and patient prognosis. To gain insights into how the TME influences cancer outcomes, we derive gene expression signatures indicative of signaling between stromal fibroblasts and cancer cells, and demonstrate their prognostic significance in multiple and independent squamous cell carcinoma cohorts. By leveraging information within the signatures, we discover that the HB-EGF/EGFR/MAPK axis represents a hub of tumor-stroma crosstalk, promoting the expression of CSF2 and LIF and favoring the recruitment of macrophages. Together, these analyses demonstrate the utility of our approach for interrogating the extent and consequences of TME crosstalk.

Why do patients with cancer die?

Cancer is a major cause of global mortality, both in affluent countries and increasingly in developing nations. Many patients with cancer experience reduced life expectancy and have metastatic disease at the time of death. However, the more precise causes of mortality and patient deterioration before death remain poorly understood. This scarcity of information, particularly the lack of mechanistic insights, presents a challenge for the development of novel treatment strategies to improve the quality of, and potentially extend, life for patients with late-stage cancer. In addition, earlier deployment of existing strategies to prolong quality of life is highly desirable. In this Roadmap, we review the proximal causes of mortality in patients with cancer and discuss current knowledge about the interconnections between mechanisms that contribute to mortality, before finally proposing new and improved avenues for data collection, research and the development of treatment strategies that may improve quality of life for patients.

Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX.

The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights.

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer.

Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis. SIGNIFICANCE: This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.

Astrocyte-induced mGluR1 activates human lung cancer brain metastasis via glutamate-dependent stabilization of EGFR.

There are limited methods to stably analyze the interactions between cancer cells and glial cells in vitro, which hinders our molecular understanding. Here, we develop a simple and stable culture method of mouse glial cells, termed mixed-glial culture on/in soft substrate (MGS), which serves well as a platform to study cancer-glia interactions. Using this method, we find that human lung cancer cells become overly dependent on metabotropic glutamate receptor 1 (mGluR1) signaling in the brain microenvironment. Mechanistically, interactions with astrocytes induce mGluR1 in cancer cells through the Wnt-5a/prickle planar cell polarity protein 1 (PRICKLE1)/RE1 silencing transcription factor (REST) axis. Induced mGluR1 directly interacts with and stabilizes the epidermal growth factor receptor (EGFR) in a glutamate-dependent manner, and these cells then become responsive to mGluR1 inhibition. Our results highlight increased dependence on mGluR1 signaling as an adaptive strategy and vulnerability of human lung cancer brain metastasis.

Understanding the microenvironment and how this controls cell fate.

The microenvironment influences cell fate. In this collection of voices, researchers from the fields of cancer and regeneration highlight approaches to establish the importance of the microenvironment and discuss future directions to understand the complex interaction between cells and their surrounding environment and how this impacts on disease and regeneration.

Emergent mechanical control of vascular morphogenesis.

Vascularization is driven by morphogen signals and mechanical cues that coordinately regulate cellular force generation, migration, and shape change to sculpt the developing vascular network. However, it remains unclear whether developing vasculature actively regulates its own mechanical properties to achieve effective vascularization. We engineered tissue constructs containing endothelial cells and fibroblasts to investigate the mechanics of vascularization. Tissue stiffness increases during vascular morphogenesis resulting from emergent interactions between endothelial cells, fibroblasts, and ECM and correlates with enhanced vascular function. Contractile cellular forces are key to emergent tissue stiffening and synergize with ECM mechanical properties to modulate the mechanics of vascularization. Emergent tissue stiffening and vascular function rely on mechanotransduction signaling within fibroblasts, mediated by YAP1. Mouse embryos lacking YAP1 in fibroblasts exhibit both reduced tissue stiffness and develop lethal vascular defects. Translating our findings through biology-inspired vascular tissue engineering approaches will have substantial implications in regenerative medicine.

Application of digital pathology-based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response.

In recent years, the application of advanced analytics, especially artificial intelligence (AI), to digital H&E images, and other histological image types, has begun to radically change how histological images are used in the clinic. Alongside the recognition that the tumour microenvironment (TME) has a profound impact on tumour phenotype, the technical development of highly multiplexed immunofluorescence platforms has enhanced the biological complexity that can be captured in the TME with high precision. AI has an increasingly powerful role in the recognition and quantitation of image features and the association of such features with clinically important outcomes, as occurs in distinct stages in conventional machine learning. Deep-learning algorithms are able to elucidate TME patterns inherent in the input data with minimum levels of human intelligence and, hence, have the potential to achieve clinically relevant predictions and discovery of important TME features. Furthermore, the diverse repertoire of deep-learning algorithms able to interrogate TME patterns extends beyond convolutional neural networks to include attention-based models, graph neural networks, and multimodal models. To date, AI models have largely been evaluated retrospectively, outside the well-established rigour of prospective clinical trials, in part because traditional clinical trial methodology may not always be suitable for the assessment of AI technology. However, to enable digital pathology-based advanced analytics to meaningfully impact clinical care, specific measures of 'added benefit' to the current standard of care and validation in a prospective setting are important. This will need to be accompanied by adequate measures of explainability and interpretability. Despite such challenges, the combination of expanding datasets, increased computational power, and the possibility of integration of pre-clinical experimental insights into model development means there is exciting potential for the future progress of these AI applications. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Multisite assessment of reproducibility in high-content cell migration imaging data.

High-content image-based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high-quality open-access data sharing and meta-analysis. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta-analysis of results from live-cell microscopy, have not been systematically investigated. Here, using high-content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells, and time points. Significant technical variability occurred between laboratories and, to lesser extent, between persons, providing low value to direct meta-analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image-based datasets of perturbation experiments. Thus, reproducible quantitative high-content cell image analysis of perturbation effects and meta-analysis depend on standardized procedures combined with batch correction.

Interplay of adherens junctions and matrix proteolysis determines the invasive pattern and growth of squamous cell carcinoma.

Cancers, such as squamous cell carcinoma, frequently invade as multicellular units. However, these invading units can be organised in a variety of ways, ranging from thin discontinuous strands to thick 'pushing' collectives. Here we employ an integrated experimental and computational approach to identify the factors that determine the mode of collective cancer cell invasion. We find that matrix proteolysis is linked to the formation of wide strands but has little effect on the maximum extent of invasion. Cell-cell junctions also favour wide strands, but our analysis also reveals a requirement for cell-cell junctions for efficient invasion in response to uniform directional cues. Unexpectedly, the ability to generate wide invasive strands is coupled to the ability to grow effectively when surrounded by extracellular matrix in three-dimensional assays. Combinatorial perturbation of both matrix proteolysis and cell-cell adhesion demonstrates that the most aggressive cancer behaviour, both in terms of invasion and growth, is achieved at high levels of cell-cell adhesion and high levels of proteolysis. Contrary to expectation, cells with canonical mesenchymal traits - no cell-cell junctions and high proteolysis - exhibit reduced growth and lymph node metastasis. Thus, we conclude that the ability of squamous cell carcinoma cells to invade effectively is also linked to their ability to generate space for proliferation in confined contexts. These data provide an explanation for the apparent advantage of retaining cell-cell junctions in squamous cell carcinomas.

Selective advantage of epigenetically disrupted cancer cells via phenotypic inertia.

The evolution of established cancers is driven by selection of cells with enhanced fitness. Subclonal mutations in numerous epigenetic regulator genes are common across cancer types, yet their functional impact has been unclear. Here, we show that disruption of the epigenetic regulatory network increases the tolerance of cancer cells to unfavorable environments experienced within growing tumors by promoting the emergence of stress-resistant subpopulations. Disruption of epigenetic control does not promote selection of genetically defined subclones or favor a phenotypic switch in response to environmental changes. Instead, it prevents cells from mounting an efficient stress response via modulation of global transcriptional activity. This "transcriptional numbness" lowers the probability of cell death at early stages, increasing the chance of long-term adaptation at the population level. Our findings provide a mechanistic explanation for the widespread selection of subclonal epigenetic-related mutations in cancer and uncover phenotypic inertia as a cellular trait that drives subclone expansion.

Loss of secreted gelsolin enhances response to anticancer therapies.

Type 1 conventional dendritic cells (cDC1) play a critical role in priming anticancer cytotoxic CD8+ T cells. DNGR-1 (a.k.a. CLEC9A) is a cDC1 receptor that binds to F-actin exposed on necrotic cancer and normal cells. DNGR-1 signaling enhances cross-presentation of dead-cell associated antigens, including tumor antigens. We have recently shown that secreted gelsolin (sGSN), a plasma protein, competes with DNGR-1 for binding to dead cell-exposed F-actin and dampens anticancer immunity. Here, we investigated the effects of loss of sGSN on various anticancer therapies that are thought to induce cell death and provoke an immune response to cancer. We compared WT (wildtype) with Rag1-/- , Batf3-/- , Clec9agfp/gfp , sGsn-/- or sGsn-/- Clec9agfp/gfp mice implanted with transplantable tumor cell lines, including MCA-205 fibrosarcoma, 5555 BrafV600E melanoma and B16-F10 LifeAct (LA)-ovalbumin (OVA)-mCherry melanoma. Tumor-bearing mice were treated with (1) doxorubicin (intratumoral) chemotherapy for MCA-205, (2) BRAF-inhibitor PLX4720 (oral gavage) targeted therapy for 5555 BrafV600E, and (3) X-ray radiotherapy for B16 LA-OVA-mCherry. We confirmed that efficient tumor control following each therapy requires an immunocompetent host as efficacy was markedly reduced in Rag1-/- compared with WT mice. Notably, across all the therapeutic modalities, loss of sGSN significantly enhanced tumor control compared with treated WT controls. This was an on-target effect as mice deficient in both sGSN and DNGR-1 behaved no differently from WT mice following therapy. In sum, we find that mice deficient in sGsn display enhanced DNGR-1-dependent responsiveness to chemotherapy, targeted therapy and radiotherapy. Our findings are consistent with the notion some cancer therapies induce immunogenic cell death (ICD), which mobilizes anticancer T cells. Our results point to cDC1 and DNGR-1 as decoders of ICD and to sGSN as a negative regulator of such decoding, highlighting sGSN as a possible target in cancer treatment. Further prospective studies are warranted to identify patients who may benefit most from inhibition of sGSN function.

Adhesion-independent topography-based leukocyte migration.

Cells need to couple intracellular actin flows with the substrate to generate forward movement. This has traditionally been studied in the context of specific transmembrane receptors, particularly integrin adhesion receptors, which link extracellular adhesive molecules to the actin cytoskeleton. However, leukocytes and other cells can also migrate using integrin-independent strategies both in vivo and in vitro, though the cellular and environmental requirements for this mode are not fully understood. In seminal recent work, Reversat et al.1 develop a range of innovative 2D and 3D engineered microdevices and probe the biophysical mechanisms underlying T lymphocytes and dendritic cells in conditions of limited substrate adhesion. They identify a physical principle of mechano-coupling between retrograde actin flow and irregular extracellular confinement, which allows the cell to generate mechanical resistance and move in the absence of receptor-mediated adhesion. Through the combined use of experiments and theoretical modeling, this work resolves a long-standing question in cell biology and establishes mechanical interaction with an irregular-shaped 3D environment which may be relevant to cell migration in a range of tissue contexts.

The PI3K/Akt/mTOR pathway as a preventive target in melanoma brain metastasis.

BACKGROUND: Brain metastases (BM) are a frequent complication of malignant melanoma (MM), with limited treatment options and poor survival. Prevention of BM could be more effective and better tolerated than treating established BM in various conditions. METHODS: To investigate the temporospatial dynamics of PI3K/Akt/mTOR (PAM) pathway activation during BM formation and the preventive potential of its inhibition, in vivo molecular imaging with an Akt biosensor was performed, and long-term intravital multiphoton microscopy through a chronic cranial window in mice. RESULTS: In vivo molecular imaging revealed invariable PAM pathway activation during the earliest steps of brain colonization. In order to perform a long-term intravascular arrest and to extravasate, circulating MM cells needed to activate their PAM pathway during this process. However, the PAM pathway was quite heterogeneously activated in established human brain metastases, and its inhibition with the brain-penetrant PAM inhibitor GNE-317 resulted in only modest therapeutic effects in mice. In contrast, giving GNE-317 in preventive schedules that included very low doses effectively reduced the growth rate and number of BM in two MM mouse models over time, and led to an overall survival benefit. Longitudinal intravital multiphoton microscopy found that the first, rate-limiting steps of BM formation-permanent intravascular arrest, extravasation, and initial perivascular growth-are most vulnerable to dual PI3K/mTOR inhibition. CONCLUSION: These findings establish a key role of PAM pathway activation for critical steps of early metastatic brain colonization and reveal its pharmacological inhibition as a potent avenue to prevent the formation of clinically relevant BM.

Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study.

Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal diversification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal diversification, enabling interpretation of clonal diversity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and microdiversity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal diversification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution.

Recruitment of dendritic cell progenitors to foci of influenza A virus infection sustains immunity.

Protection from infection with respiratory viruses such as influenza A virus (IAV) requires T cell­mediated immune responses initiated by conventional dendritic cells (cDCs) that reside in the respiratory tract. Here, we show that effective induction of T cell responses against IAV in mice requires reinforcement of the resident lung cDC network by cDC progenitors. We found that CCR2-binding chemokines produced during IAV infection recruit pre-cDCs from blood and direct them to foci of infection, increasing the number of progeny cDCs next to sites of viral replication. Ablation of CCR2 in the cDC lineage prevented this increase and resulted in a deficit in IAV-specific T cell responses and diminished resistance to reinfection. These data suggest that the homeostatic network of cDCs in tissues is insufficient for immunity and reveal a chemokine-driven mechanism of expansion of lung cDC numbers that amplifies T cell responses against respiratory viruses.

Parameter estimation in fluorescence recovery after photobleaching: quantitative analysis of protein binding reactions and diffusion.

Fluorescence recovery after photobleaching (FRAP) is a common experimental method for investigating rates of molecular redistribution in biological systems. Many mathematical models of FRAP have been developed, the purpose of which is usually the estimation of certain biological parameters such as the diffusivity and chemical reaction rates of a protein, this being accomplished by fitting the model to experimental data. In this article, we consider a two species reaction-diffusion FRAP model. Using asymptotic analysis, we derive new FRAP recovery curve approximation formulae, and formally re-derive existing ones. On the basis of these formulae, invoking the concept of Fisher information, we predict, in terms of biological and experimental parameters, sufficient conditions to ensure that the values all model parameters can be estimated from data. We verify our predictions with extensive computational simulations. We also use computational methods to investigate cases in which some or all biological parameters are theoretically inestimable. In these cases, we propose methods which can be used to extract the maximum possible amount of information from the FRAP data.

An optogenetic method for interrogating YAP1 and TAZ nuclear-cytoplasmic shuttling.

The shuttling of transcription factors and transcriptional regulators into and out of the nucleus is central to the regulation of many biological processes. Here we describe a new method for studying the rates of nuclear entry and exit of transcriptional regulators. A photo-responsive LOV (light-oxygen-voltage) domain from Avena sativa is used to sequester fluorescently labelled transcriptional regulators YAP1 and TAZ (also known as WWTR1) on the surface of mitochondria and to reversibly release them upon blue light illumination. After dissociation, fluorescent signals from the mitochondria, cytoplasm and nucleus are extracted by a bespoke app and used to generate rates of nuclear entry and exit. Using this method, we demonstrate that phosphorylation of YAP1 on canonical sites enhances its rate of nuclear export. Moreover, we provide evidence that, despite high intercellular variability, YAP1 import and export rates correlate within the same cell. By simultaneously releasing YAP1 and TAZ from sequestration, we show that their rates of entry and exit are correlated. Furthermore, combining the optogenetic release of YAP1 with lattice light-sheet microscopy reveals high heterogeneity of YAP1 dynamics within different cytoplasmic regions, demonstrating the utility and versatility of our tool to study protein dynamics. This article has an associated First Person interview with Anna M. Dowbaj, joint first author of the paper.

Selection of metastasis competent subclones in the tumour interior.

The genetic evolutionary features of solid tumour growth are becoming increasingly well described, but the spatial and physical nature of subclonal growth remains unclear. Here, we utilize 102 macroscopic whole-tumour images from clear cell renal cell carcinoma patients, with matched genetic and phenotypic data from 756 biopsies. Utilizing a digital image processing pipeline, a renal pathologist marked the boundaries between tumour and normal tissue and extracted positions of boundary line and biopsy regions to X and Y coordinates. We then integrated coordinates with genomic data to map exact spatial subclone locations, revealing how genetically distinct subclones grow and evolve spatially. We observed a phenotype of advanced and more aggressive subclonal growth in the tumour centre, characterized by an elevated burden of somatic copy number alterations and higher necrosis, proliferation rate and Fuhrman grade. Moreover, we found that metastasizing subclones preferentially originate from the tumour centre. Collectively, these observations suggest a model of accelerated evolution in the tumour interior, with harsh hypoxic environmental conditions leading to a greater opportunity for driver somatic copy number alterations to arise and expand due to selective advantage. Tumour subclone growth is predominantly spatially contiguous in nature. We found only two cases of subclone dispersal, one of which was associated with metastasis. The largest subclones spatially were dominated by driver somatic copy number alterations, suggesting that a large selective advantage can be conferred to subclones upon acquisition of these alterations. In conclusion, spatial dynamics is strongly associated with genomic alterations and plays an important role in tumour evolution.

EphB6 Regulates TFEB-Lysosomal Pathway and Survival of Disseminated Indolent Breast Cancer Cells.

Late relapse of disseminated cancer cells is a common feature of breast and prostate tumors. Several intrinsic and extrinsic factors have been shown to affect quiescence and reawakening of disseminated dormant cancer cells (DDCCs); however, the signals and processes sustaining the survival of DDCCs in a foreign environment are still poorly understood. We have recently shown that crosstalk with lung epithelial cells promotes survival of DDCCs of estrogen receptor-positive (ER+) breast tumors. By using a lung organotypic system and in vivo dissemination assays, here we show that the TFEB-lysosomal axis is activated in DDCCs and that it is modulated by the pro-survival ephrin receptor EphB6. TFEB lysosomal direct targets are enriched in DDCCs in vivo and correlate with relapse in ER+ breast cancer patients. Direct coculture of DDCCs with alveolar type I-like lung epithelial cells and dissemination in the lung drive lysosomal accumulation and EphB6 induction. EphB6 contributes to survival, TFEB transcriptional activity, and lysosome formation in DDCCs in vitro and in vivo. Furthermore, signaling from EphB6 promotes the proliferation of surrounding lung parenchymal cells in vivo. Our data provide evidence that EphB6 is a key factor in the crosstalk between disseminated dormant cancer cells and the lung parenchyma and that the TFEB-lysosomal pathway plays an important role in the persistence of DDCCs.