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Moran, A. E.

Publications and source records attributed to Moran, A. E..

6 recordsLinked to original sources

IGF1 modulates lesional skin inflammation in checkpoint inhibitor-induced lichen planus

Immune checkpoint inhibitor-induced lichen planus (ICI-LP) is a cutaneous immune related adverse event (irAE) that shares key clinicopathologic features with spontaneous lichen planus (LP) but differs histologically and in the sex distribution of its incidence, and may therefore reflect a distinct tissue inflammatory state. To define the cellular programs that distinguish ICI-LP from LP, we profiled lesional skin by single cell and spatial transcriptomic approaches. We found few differences in the T cell and keratinocyte compartments between ICI-LP and LP, which shared similar inflammatory signatures. Rather, the dominant transcriptional features differentiating these two eruptions occurred within the fibroblast and myeloid cell compartments. Fibroblasts in ICI-LP were enriched for IGF1, FGF7, and androgen-response-associated programs, whereas myeloid cells exhibited amplified JAK-STAT and interferon-responsive states spanning both type I and type II interferon signatures. The potential role of androgen response in shaping lichenoid inflammation was supported by a striking loss of androgen receptor expression in lesional keratinocytes by immunohistochemistry. Furthermore, using spatial RNA and transcriptomic approaches, we identified anatomically segregated IFNG, IL17A, and IL13 niches within lesional skin, suggesting that regional immune compartmentalization with differences in local immunoregulation may explain the mixed inflammatory features reported in both ICI-LP and LP. Collectively, these data indicate that ICI-LP is not simply a more inflamed form of LP, but a distinct form of the disease with more prominent inflammatory perturbations within stromal and innate immune cell populations.

immunology↗

Deciphering single-cell heterogeneity and cellular ecosystem dynamics during prostate cancer progression

Prostate cancer (PC) progresses from benign epithelium through pre-malignant lesions, localized tumors, metastatic dissemination, and castration-resistant stages, with some cases exhibiting phenotype plasticity under therapeutic pressure. However, high-resolution insights into how cell phenotypes evolve across successive stages of PC remain limited. Here, we present the Prostate Cancer Cell Atlas (PCCAT) by integrating [~]710,000 single cells from 197 human samples covering a spectrum of tumor stages. This comprehensive analysis dissects the cellular landscape and characterizes key cell types and molecular features that associate with PC progression and prognosis. In malignant cells, we highlight a distinctive profile denoted by high Major Histocompatibility Complex (MHC) expression, low Androgen Receptor (AR) activity, and enhanced stemness programs associated with enzalutamide resistance. Moreover, we reveal several cell states strongly correlated with PC progression and adverse prognosis, including lineage plasticity-like malignant cells (LPCs), neuroendocrine tumor cells, pericytes, and matrix cancer-associated fibroblasts (mCAFs). Furthermore, we uncover shared cell states that underpin the immune suppressive tumor microenvironment in advanced PC, including activated regulatory T cells, exhausted CD8+ T cells, and SPP1-expressing macrophages. Lastly, we pinpoint a spatial niche composed of mCAFs and SPP1-expressing macrophages localized near the tumor boundary in aggressive PC, which correlates with poor prognosis. Overall, our work provides a valuable resource and offers deeper insights into the diverse cell states, dynamics, and functional characteristics involved in PC progression at single-cell resolution.

cancer biology↗

Androgen receptor activity inversely correlates with immune cell infiltration and immunotherapy response across multiple cancer lineages

There is now increasing recognition of the important role of androgen receptor (AR) in modulating immune function. To gain a comprehensive understanding of the effects of AR activity on cancer immunity, we employed a computational approach to profile AR activity in 33 human tumor types using RNA-Seq datasets from The Cancer Genome Atlas. Our pan-cancer analysis revealed that the genes most negatively correlated with AR activity across cancers are involved in active immune system processes. Importantly, we observed a significant negative correlation between AR activity and IFN{gamma} pathway activity at the pan-cancer level. Indeed, using a matched biopsy dataset from subjects with prostate cancer before and after AR-targeted treatment, we verified that inhibiting AR enriches immune cell abundances and is associated with higher IFN{gamma} pathway activity. Furthermore, by analyzing immunotherapy datasets in multiple cancers, our results demonstrate that low AR activity was significantly associated with a favorable response to immunotherapy. Together, our data provide a comprehensive assessment of the relationship between AR signaling and tumor immunity.

cancer biology↗

Androgen blockade primes NLRP3 in macrophages to induce tumor phagocytosis

Immune-based therapies induce durable remissions in subsets of patients across multiple malignancies. However, there is limited efficacy of immunotherapy in metastatic castrate-resistant prostate cancer (mCRPC), manifested by an enrichment of immunosuppressive (M2) tumor- associated macrophages (TAM) in the tumor immune microenvironment (TME). Therefore, therapeutic strategies to overcome TAM-mediated immunosuppression are critically needed in mCRPC. Here we discovered that NLR family pyrin domain containing 3 (NLRP3), an innate immune sensing protein, is highly expressed in TAM from metastatic PC patients treated with standard-of-care androgen deprivation therapy (ADT). Importantly, ex vivo studies revealed that androgen receptor (AR) blockade in TAM upregulates NLRP3 expression, but not inflammasome activity, and concurrent AR blockade/NLRP3 agonist (NLRP3a) treatment promotes cancer cell phagocytosis by immunosuppressive M2 TAM. In contrast, NLRP3a monotherapy was sufficient to enhance phagocytosis of cancer cells in anti-tumor (M1) TAM, which exhibit high de novo NLRP3 expression. Critically, combinatorial treatment with ADT/NLRP3a in a murine model of advanced PC resulted in significant tumor control, with tumor clearance in 55% of mice via TAM phagocytosis. Collectively, our results demonstrate NLRP3 as an AR-regulated "macrophage phagocytic checkpoint", inducibly expressed in TAM by ADT and activated by NLRP3a treatment, the combination resulting in TAM-mediated phagocytosis and tumor control.

cancer biology↗

Phenotype-guided subpopulation identification from single-cell sequencing data

Single-cell sequencing yields novel discoveries by distinguishing cell types, states and lineages within the context of heterogeneous tissues. However, interpreting complex single-cell data from highly heterogeneous cell populations remains challenging. Currently, most existing single-cell data analyses focus on cell type clusters defined by unsupervised clustering methods, which cannot directly link cell clusters with specific biological and clinical phenotypes. Here we present Scissor, a novel approach that utilizes disease phenotypes to identify cell subpopulations from single-cell data that most highly correlate with a given phenotype. This "phenotype-to-cell within a single step" strategy enables the utilization of a large amount of clinical information that has been collected for bulk assays to identify the most highly phenotype-associated cell subpopulations. When applied to a lung cancer single-cell RNA-seq (scRNA-seq) dataset, Scissor identified a subset of cells exhibiting high hypoxia activities, which predicted worse survival outcomes in lung cancer patients. Furthermore, in a melanoma scRNA-seq dataset, Scissor discerned a T cell subpopulation with low PDCD1/CTLA4 and high TCF7 expressions, which is associated with a favorable immunotherapy response. Thus, Scissor provides a novel framework to identify the biologically and clinically relevant cell subpopulations from single-cell assays by leveraging the wealth of phenotypes and bulk-omics datasets.

bioinformatics↗

PD-1 Specific 'Blocking' Antibodies That Deplete PD-1+ T Cells Present An Inconvenient Variable In Pre-clinical Immunotherapy Experiments

Therapeutic antibodies blocking PD-1-/PD-L1 interaction have achieved remarkable clinical success in cancer. In addition to blocking a target molecule, some isotypes of antibodies can activate complement, NK cells or phagocytes, resulting in death of the cell expressing the antibodys target. Human anti-PD-1 therapeutics use antibody isotypes designed to minimize such antibody-dependent lysis. In contrast, anti-PD-1 reagents used in mice are derived from multiple species, with different isotypes, and are not engineered to reduce target cell death: few studies analyze or discuss how antibody species and isotype may impact data interpretation. We demonstrate here that anti-PD-1 therapy to promote activation and proliferation of PD-1-expressing CD8 T cells sometimes led instead to a loss of antigen specific cells. This phenomenon was seen in two tumor models and a model of virus infection, and was varied with the clone of anti-PD-1 antibody. Additionally, we compared competition among anti-PD-1 clones to find a combination that allows detection of PD-1-expressing cells despite the presence of blocking anti-PD1 antibodies in vivo. These data bring attention to the possibility of unintended target cell depletion with some commonly used anti-mouse PD-1 clones, and should provide a valuable resource for the design and interpretation of anti-PD-1 studies in mice. (200)

immunology↗