Showing papers by "Lisa M. Coussens published in 2021"

Tumour-associated macrophages drive stromal cell-dependent collagen crosslinking and stiffening to promote breast cancer aggression.

Abstract: Stromal stiffening accompanies malignancy, compromises treatment and promotes tumour aggression. Clarifying the molecular nature and the factors that regulate stromal stiffening in tumours should identify biomarkers to stratify patients for therapy and interventions to improve outcome. We profiled lysyl hydroxylase-mediated and lysyl oxidase-mediated collagen crosslinks and quantified the greatest abundance of total and complex collagen crosslinks in aggressive human breast cancer subtypes with the stiffest stroma. These tissues harbour the highest number of tumour-associated macrophages, whose therapeutic ablation in experimental models reduced metastasis, and decreased collagen crosslinks and stromal stiffening. Epithelial-targeted expression of the crosslinking enzyme, lysyl oxidase, had no impact on collagen crosslinking in PyMT mammary tumours, whereas stromal cell targeting did. Stromal cells in microdissected human tumours expressed the highest level of collagen crosslinking enzymes. Immunohistochemical analysis of biopsies from a cohort of patients with breast cancer revealed that stromal expression of lysyl hydroxylase 2, an enzyme that induces hydroxylysine aldehyde-derived collagen crosslinks and stromal stiffening, correlated significantly with disease specific mortality. The findings link tissue inflammation, stromal cell-mediated collagen crosslinking and stiffening to tumour aggression and identify lysyl hydroxylase 2 as a stromal biomarker.

Leukocyte Heterogeneity in Pancreatic Ductal Adenocarcinoma: Phenotypic and Spatial Features Associated with Clinical Outcome

Abstract: Immunotherapies targeting aspects of T cell functionality are efficacious in many solid tumors, but pancreatic ductal adenocarcinoma (PDAC) remains refractory to these treatments. Deeper understanding of the PDAC immune ecosystem is needed to identify additional therapeutic targets and predictive biomarkers for therapeutic response and resistance monitoring. To address these needs, we quantitatively evaluated leukocyte contexture in 135 human PDACs at single-cell resolution by profiling density and spatial distribution of myeloid and lymphoid cells within histopathologically defined regions of surgical resections from treatment-naive and presurgically (neoadjuvant)-treated patients and biopsy specimens from metastatic PDAC. Resultant data establish an immune atlas of PDAC heterogeneity, identify leukocyte features correlating with clinical outcomes, and, through an in silico study, provide guidance for use of PDAC tissue microarrays to optimally measure intratumoral immune heterogeneity. Atlas data have direct applicability as a reference for evaluating immune responses to investigational neoadjuvant PDAC therapeutics where pretherapy baseline specimens are not available. SIGNIFICANCE: We provide a phenotypic and spatial immune atlas of human PDAC identifying leukocyte composition at steady state and following standard neoadjuvant therapies. These data have broad utility as a resource that can inform on leukocyte responses to emerging therapies where baseline tissues were not acquired.This article is highlighted in the In This Issue feature, p. 1861.

Neoadjuvant Selicrelumab, an Agonist CD40 Antibody, Induces Changes in the Tumor Microenvironment in Patients with Resectable Pancreatic Cancer.

Abstract: Purpose: CD40 activation is a novel clinical opportunity for cancer immunotherapy. Despite numerous active clinical trials with agonistic CD40 monoclonal antibodies (mAb), biological effects and treatment-related modulation of the tumor microenvironment (TME) remain poorly understood. Patients and Methods: Here, we performed a neoadjuvant clinical trial of agonistic CD40 mAb (selicrelumab) administered intravenously with or without chemotherapy to 16 patients with resectable pancreatic ductal adenocarcinoma (PDAC) before surgery followed by adjuvant chemotherapy and CD40 mAb. Results: The toxicity profile was acceptable, and overall survival was 23.4 months (95% confidence interval, 18.0–28.8 months). Based on a novel multiplexed immunohistochemistry platform, we report evidence that neoadjuvant selicrelumab leads to major differences in the TME compared with resection specimens from treatment-naive PDAC patients or patients given neoadjuvant chemotherapy/chemoradiotherapy only. For selicrelumab-treated tumors, 82% were T-cell enriched, compared with 37% of untreated tumors (P = 0.004) and 23% of chemotherapy/chemoradiation-treated tumors (P = 0.012). T cells in both the TME and circulation were more active and proliferative after selicrelumab. Tumor fibrosis was reduced, M2-like tumor-associated macrophages were fewer, and intratumoral dendritic cells were more mature. Inflammatory cytokines/sec CXCL10 and CCL22 increased systemically after selicrelumab. Conclusions: This unparalleled examination of CD40 mAb therapeutic mechanisms in patients provides insights for design of subsequent clinical trials targeting CD40 in cancer.

Composition, Spatial Characteristics, and Prognostic Significance of Myeloid Cell Infiltration in Pancreatic Cancer.

Abstract: Purpose: While abundant myeloid cell populations in the pancreatic ductal adenocarcinoma (PDAC) microenvironment have been postulated to suppress anti-tumor immunity, the composition of these populations, their spatial locations, and how they relate to patient outcomes are poorly understood. Experimental Design: To generate spatially-resolved tumor and immune cell data at single cell resolution, we developed two quantitative multiplex immunofluorescence assays to interrogate myeloid cells (CD15, CD14, ARG1, CD33, HLA-DR) and macrophages [CD68, CD163, CD86, interferon regulatory factor 5 (IRF5), MRC1 (CD206)] in the PDAC tumor microenvironment. Spatial point pattern analyses were conducted to assess the degree of co-localization between tumor cells and immune cells. Multivariable-adjusted Cox proportional hazards regression was used to assess associations with patient outcomes. Results: In a multi-institutional cohort of 305 primary PDAC resection specimens, myeloid cells were abundant, enriched within stromal regions, highly heterogeneous across tumors, and differed by somatic genotype. High densities of CD15+ARG1+ immunosuppressive granulocytic cells and M2-polarized macrophages were associated with worse patient survival. Moreover, beyond cell density, closer proximity of M2-polarized macrophages to tumor cells was strongly associated with disease-free survival, revealing the clinical significance and biologic importance of immune cell localization within tumor areas. Conclusions: A diverse set of myeloid cells are present within the PDAC tumor microenvironment and are distributed heterogeneously across patient tumors. Not only the densities but also the spatial locations of myeloid immune cells are associated with patient outcomes, highlighting the potential role of spatially-resolved myeloid cell subtypes as quantitative biomarkers for PDAC prognosis and therapy.

MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging

Abstract: Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data. We demonstrate the use of MCMICRO on tissue and tumor images acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software. MCMICRO is a modular and open-source computational pipeline for transforming highly multiplexed whole-slide images of tissues into single-cell data. MCMICRO is versatile and can be used with CODEX, mxIF, CyCIF, mIHC and H&E staining data.

MCMICRO: A scalable, modular image-processing pipeline for multiplexed tissue imaging

Abstract: Highly multiplexed tissue imaging makes molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of the underlying data poses a substantial computational challenge. Here we describe a modular and open-source computational pipeline (MCMICRO) for performing the sequential steps needed to transform large, multi-channel whole slide images into single-cell data. We demonstrate use of MCMICRO on images of different tissues and tumors acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.

High IRF8 expression correlates with CD8 T cell infiltration and is a predictive biomarker of therapy response in ER-negative breast cancer.

Abstract: Characterization of breast cancer (BC) through the determination of conventional markers such as ER, PR, HER2, and Ki67 has been useful as a predictive and therapeutic tool. Also, assessment of tumor-infiltrating lymphocytes has been proposed as an important prognostic aspect to be considered in certain BC subtypes. However, there is still a need to identify additional biomarkers that could add precision in distinguishing therapeutic response of individual patients. To this end, we focused in the expression of interferon regulatory factor 8 (IRF8) in BC cells. IRF8 is a transcription factor which plays a well-determined role in myeloid cells and that seems to have multiple antitumoral roles: it has tumor suppressor functions; it acts downstream IFN/STAT1, required for the success of some therapeutic regimes, and its expression in neoplastic cells seems to depend on a cross talk between the immune contexture and the tumor cells. The goal of the present study was to examine the relationship between IRF8 with the therapeutic response and the immune contexture in BC, since its clinical significance in this type of cancer has not been thoroughly addressed. We identified the relationship between IRF8 expression and the clinical outcome of BC patients and validated IRF8 as predictive biomarker by using public databases and then performed in silico analysis. To correlate the expression of IRF8 with the immune infiltrate in BC samples, we performed quantitative multiplex immunohistochemistry. IRF8 expression can precisely predict the complete pathological response to monoclonal antibody therapy or to select combinations of chemotherapy such as FAC (fluorouracil, adriamycin, and cytoxan) in ER-negative BC subtypes. Analysis of immune cell infiltration indicates there is a strong correlation between activated and effector CD8+ T cell infiltration and tumoral IRF8 expression. We propose IRF8 expression as a potent biomarker not only for prognosis, but also for predicting therapy response in ER-negative BC phenotypes. Its expression in neoplastic cells also correlates with CD8+ T cell activation and infiltration. Therefore, our results justify new efforts towards understanding mechanisms regulating IRF8 expression and how they can be therapeutically manipulated.

Multiomics analysis of serial PARP inhibitor treated metastatic TNBC inform on rational combination therapies.

Abstract: In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). In a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor destruction was accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor rapid progressor, likely due to indifference to the effects of PARP inhibition. Together, identification of PARPi-induced emergent changes could be used to select patient specific combination therapies, based on tumor and immune state changes.

Spatial Profiles of Intratumoral PD-1+ Helper T Cells Predict Prognosis in Head and Neck Squamous Cell Carcinoma.

Abstract: Background Functional interactions between immune cells and neoplastic cells in the tumor immune microenvironment have been actively pursued for both biomarker discovery for patient stratification, as well as therapeutic anti-cancer targets to improve clinical outcomes. Although accumulating evidence indicates that intratumoral infiltration of immune cells has prognostic significance, limited information is available on the spatial infiltration patterns of immune cells within intratumoral regions. This study aimed to understand the intratumoral heterogeneity and spatial distribution of immune cell infiltrates associated with cell phenotypes and prognosis in head and neck squamous cell carcinoma (HNSCC). Methods A total of 88 specimens of oropharyngeal squamous cell carcinoma, categorized into discovery (n = 38) and validation cohorts (n = 51), were analyzed for immune contexture by multiplexed immunohistochemistry (IHC) and image cytometry-based quantification. Tissue segmentation was performed according to a mathematical morphological approach using neoplastic cell IHC images to dissect intratumoral regions into tumor cell nests versus intratumoral stroma. Results Tissue segmentation revealed heterogeneity in intratumoral T cells, varying from tumor cell nest-polarized to intratumoral stroma-polarized distributions. Leukocyte composition analysis revealed higher ratios of TH1/TH2 in tumor cell nests with higher percentages of helper T cells, B cells, and CD66b+ granulocytes within intratumoral stroma. A discovery and validation approach revealed a high density of programmed death receptor-1 (PD-1)+ helper T cells in tumor cell nests as a negative prognostic factor for short overall survival. CD163+ tumor-associated macrophages (TAM) provided the strongest correlation with PD-1+ helper T cells, and cases with a high density of PD-1+ helper T cells and CD163+ TAM had a significantly shorter overall survival than other cases. Conclusion This study reveals the significance of analyzing intratumoral cell nests and reports that an immune microenvironment with a high density of PD-1+ helper T cells in tumoral cell nests is a poor prognostic factor for HNSCC.

Single-Cell Spatial Proteomics Analyses of Head and Neck Squamous Cell Carcinoma Reveal Tumor Heterogeneity and Immune Architectures Associated with Clinical Outcome

Abstract: There is increasing evidence that the spatial organization of cells within the tumor-immune microenvironment (TiME) of solid tumors influences survival and response to therapy in numerous cancer types. Here, we report results and demonstrate the applicability of quantitative single-cell spatial proteomics analyses in the TiME of primary and recurrent human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) tumors. Single-cell compositions of a nine patient, primary and recurrent (n=18), HNSCC cohort is presented, followed by deeper investigation into the spatial architecture of the TiME and its relationship with clinical variables and progression free survival (PFS). Multiple spatial algorithms were used to quantify the spatial landscapes of immune cells within TiMEs and demonstrate that neoplastic tumor-immune cell spatial compartmentalization, rather than mixing, is associated with longer PFS. Mesenchymal (αSMA+) cellular neighborhoods describe distinct immune landscapes associated with neoplastic tumor-immune compartmentalization and improved patient outcomes. Results from this investigation are concordant with studies in other tumor types, suggesting that trends in TiME cellular heterogeneity and spatial organization may be shared across cancers and may provide prognostic value in multiple cancer types.

Tumor-Infiltrating Leukocyte Phenotypes Distinguish Outcomes in Related Patients With Pancreatic Adenocarcinoma

Abstract: Pancreatic ductal adenocarcinoma (PDAC) carries one of the highest mortality risks of all cancers.Most patients present with either metastatic PDAC (50%-60%) or locally advanced tumors (30%-40%), for which the median survival is 5-9 months after diagnosis. Outcomes are still suboptimal for the small subset (10%20%) of patients who present with resectable tumors confined to the pancreas; , 50% of these patients survive 5 years after surgery despite modern adjuvant chemotherapy. Moreover, at autopsy, the disease is metastatic for 88% of recurrences, and . 80% have more than 10 distinct metastatic lesions that are genetically related to the primary tumor and other metastases. These observations indicate that the majority of patients with PDAC harbor nonradiographically evident, micrometastatic disease after resection and that remnant tumor cells evade—or acquire resistance to—adjuvant chemotherapy. Although tropism to specific organs during metastatic spread is still poorly understood, patients with recurrence in the liver or peritoneum survive significantly shorter than patients with recurrent lung metastases.

An Omic and Multidimensional Spatial Atlas from Serial Biopsies of an Evolving Metastatic Breast Cancer

Abstract: Summary Mechanisms of therapeutic resistance manifest in metastatic cancers as tumor cell intrinsic alterations and extrinsic microenvironmental influences that can change during treatment. To support the development of methods for the identification of these mechanisms in individual patients, we present here an Omic and Multidimensional Spatial (OMS) Atlas generated from four serial biopsies of a metastatic breast cancer patient during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata including treatment times and doses, anatomic imaging, and blood-based response measurements to exploratory analytics including comprehensive DNA, RNA, and protein profiles, images of multiplexed immunostaining, and 2- and 3-dimensional scanning electron micrographs. These data reveal aspects of therapy-associated heterogeneity and evolution of the cancer’s genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples showing how integrative analyses of these data provide insights into potential mechanisms of response and resistance, and suggest novel therapeutic vulnerabilities.

Multiplex spatial systems analysis of local nanodose drug responses predicts effective treatment combinations of immunotherapies and targeted agents in mammary carcinoma

Abstract: SUMMARY Better methods are needed to identify effective combinations of immunotherapies with chemotherapies and targeted anti-cancer agents. Here we present a Multiplex Implantable Microdevice Assay (MIMA) system for rapid in vivo assessment of the effects of multiple, spatially separate anticancer drugs directly in the complex tumor microenvironment. In prototypic experiments, olaparib, lenvatinib, palbociclib, venetoclax, panobinostat, doxorubicin, and paclitaxel and combinations thereof were administered simultaneously to murine mammary tumor models. Quantitative multiplex immunohistochemistry and spatial systems analyses of each local drug response defined cellular relations of fibroblasts, endothelial cells, immune lineages, immunogenic cell death, tumor proliferation and/or cancer stem cells that were used to predict effective drug combinations. A predicted combination of panobinostat, venetoclax and anti-CD40 showed long-term anti-tumor efficacy in multiple mouse models with no observable toxicity when administered systemically. Future MIMA use promises to design effective drug combinations for tumor cell control and immune activation on a personalized basis.