Dissecting the treatment-naive ecosystem of human melanoma brain metastasis.

Melanoma brain metastasis (MBM) frequently occurs in patients with advanced melanoma; yet, our understanding of the underlying salient biology is rudimentary. Here, we performed single-cell/nucleus RNA-seq in 22 treatment-naive MBMs and 10 extracranial melanoma metastases (ECMs) and matched spatial single-cell transcriptomics and T cell receptor (TCR)-seq. Cancer cells from MBM were more chromosomally unstable, adopted a neuronal-like cell state, and enriched for spatially variably expressed metabolic pathways. Key observations were validated in independent patient cohorts, patient-derived MBM/ECM xenograft models, RNA/ATAC-seq, proteomics, and multiplexed imaging. Integrated spatial analyses revealed distinct geography of putative cancer immune evasion and evidence for more abundant intra-tumoral B to plasma cell differentiation in lymphoid aggregates in MBM. MBM harbored larger fractions of monocyte-derived macrophages and dysfunctional TOX+CD8+ T cells with distinct expression of immune checkpoints. This work provides comprehensive insights into MBM biology and serves as a foundational resource for further discovery and therapeutic exploration.

A Cancer Cell Program Promotes T Cell Exclusion and Resistance to Checkpoint Blockade.

Immune checkpoint inhibitors (ICIs) produce durable responses in some melanoma patients, but many patients derive no clinical benefit, and the molecular underpinnings of such resistance remain elusive. Here, we leveraged single-cell RNA sequencing (scRNA-seq) from 33 melanoma tumors and computational analyses to interrogate malignant cell states that promote immune evasion. We identified a resistance program expressed by malignant cells that is associated with T cell exclusion and immune evasion. The program is expressed prior to immunotherapy, characterizes cold niches in situ, and predicts clinical responses to anti-PD-1 therapy in an independent cohort of 112 melanoma patients. CDK4/6-inhibition represses this program in individual malignant cells, induces senescence, and reduces melanoma tumor outgrowth in mouse models in vivo when given in combination with immunotherapy. Our study provides a high-resolution landscape of ICI-resistant cell states, identifies clinically predictive signatures, and suggests new therapeutic strategies to overcome immunotherapy resistance.

A molecular single-cell lung atlas of lethal COVID-19.

Respiratory failure is the leading cause of death in patients with severe SARS-CoV-2 infection1,2, but the host response at the lung tissue level is poorly understood. Here we performed single-nucleus RNA sequencing of about 116,000 nuclei from the lungs of nineteen individuals who died of COVID-19 and underwent rapid autopsy and seven control individuals. Integrated analyses identified substantial alterations in cellular composition, transcriptional cell states, and cell-to-cell interactions, thereby providing insight into the biology of lethal COVID-19. The lungs from individuals with COVID-19 were highly inflamed, with dense infiltration of aberrantly activated monocyte-derived macrophages and alveolar macrophages, but had impaired T cell responses. Monocyte/macrophage-derived interleukin-1ß and epithelial cell-derived interleukin-6 were unique features of SARS-CoV-2 infection compared to other viral and bacterial causes of pneumonia. Alveolar type 2 cells adopted an inflammation-associated transient progenitor cell state and failed to undergo full transition into alveolar type 1 cells, resulting in impaired lung regeneration. Furthermore, we identified expansion of recently described CTHRC1+ pathological fibroblasts3 contributing to rapidly ensuing pulmonary fibrosis in COVID-19. Inference of protein activity and ligand-receptor interactions identified putative drug targets to disrupt deleterious circuits. This atlas enables the dissection of lethal COVID-19, may inform our understanding of long-term complications of COVID-19 survivors, and provides an important resource for therapeutic development.

COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets.

COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure1-4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63+ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments.

From patient tissue correlates to molecular mechanisms of cancer immune evasion: the emerging role of CD58 and PD-L1 co-regulation via CMTM6.

Immune evasion is a hallmark of cancer, yet the underlying mechanisms are often unknown in many patients. Using single-cell transcriptomics analysis, we previously identified the co-stimulator CD58 as part of a cancer cell-intrinsic immune checkpoint resistance signature in patient melanoma tissue. We subsequently validated CD58 loss as a driver of immune evasion using a patient-derived co-culture model of cancer and cytotoxic tumor-infiltrating lymphocytes in a pooled single-cell perturbation experiment, where we additionally observed concurrent upregulation of PD-L1 protein expression in melanoma cells with CD58 loss. In our most recent study, we uncovered the mechanisms of immune evasion mediated by CD58 loss, including impaired T cell activation and infiltration within tumors, as well as inhibitory signaling by PD-L1 via a shared regulator, CMTM6. Thus, cancer cell-intrinsic reduction of CD58 represents a multi-faceted determinant of immune evasion. Furthermore, its reciprocal interaction with PD-L1 via CMTM6 provides critical insights into how co-inhibitory and co-stimulatory immune cues are regulated.

Histone acetylation of bile acid transporter genes plays a critical role in cirrhosis.

BACKGROUND & AIMS: Owing to the lack of genetic animal models that adequately recreate key clinical characteristics of cirrhosis, the molecular pathogenesis of cirrhosis has been poorly characterized, and treatments remain limited. Hence, we aimed to better elucidate the pathological mechanisms of cirrhosis using a novel murine model. METHODS: We report on the first murine genetic model mimicking human cirrhosis induced by hepatocyte-specific elimination of microspherule protein 1 (MCRS1), a member of non-specific lethal (NSL) and INO80 chromatin-modifier complexes. Using this genetic tool with other mouse models, cell culture and human samples, combined with quantitative proteomics, single nuclei/cell RNA sequencing and chromatin immunoprecipitation assays, we investigated mechanisms of cirrhosis. RESULTS: MCRS1 loss in mouse hepatocytes modulates the expression of bile acid (BA) transporters - with a pronounced downregulation of Na+-taurocholate cotransporting polypeptide (NTCP) - concentrating BAs in sinusoids and thereby activating hepatic stellate cells (HSCs) via the farnesoid X receptor (FXR), which is predominantly expressed in human and mouse HSCs. Consistently, re-expression of NTCP in mice reduces cirrhosis, and genetic ablation of FXR in HSCs suppresses fibrotic marks in mice and in vitro cell culture. Mechanistically, deletion of a putative SANT domain from MCRS1 evicts histone deacetylase 1 from its histone H3 anchoring sites, increasing histone acetylation of BA transporter genes, modulating their expression and perturbing BA flow. Accordingly, human cirrhosis displays decreased nuclear MCRS1 and NTCP expression. CONCLUSIONS: Our data reveal a previously unrecognized function of MCRS1 as a critical histone acetylation regulator, maintaining gene expression and liver homeostasis. MCRS1 loss induces acetylation of BA transporter genes, perturbation of BA flow, and consequently, FXR activation in HSCs. This axis represents a central and universal signaling event in cirrhosis, which has significant implications for cirrhosis treatment. LAY SUMMARY: By genetic ablation of MCRS1 in mouse hepatocytes, we generate the first genetic mouse model of cirrhosis that recapitulates human features. Herein, we demonstrate that the activation of the bile acid/FXR axis in liver fibroblasts is key in cirrhosis development.

micronuclAI: Automated quantification of micronuclei for assessment of chromosomal instability.

Chromosomal instability (CIN) is a hallmark of cancer that drives metastasis, immune evasion and treatment resistance. CIN results from chromosome mis-segregation events during anaphase, as excessive chromatin is packaged in micronuclei (MN), that can be enumerated to quantify CIN. Despite recent advancements in automation through computer vision and machine learning, the assessment of CIN remains a predominantly manual and time-consuming task, thus hampering important work in the field. Here, we present micronuclAI , a novel pipeline for automated and reliable quantification of MN of varying size, morphology and location from DNA-only stained images. In micronucleAI , single-cell crops are extracted from high-resolution microscopy images with the help of segmentation masks, which are then used to train a convolutional neural network (CNN) to output the number of MN associated with each cell. The pipeline was evaluated against manual single-cell level counts by experts and against routinely used MN ratio within the complete image. The classifier was able to achieve a weighted F1 score of 0.937 on the test dataset and the complete pipeline can achieve close to human-level performance on various datasets derived from multiple human and murine cancer cell lines. The pipeline achieved a root-mean-square deviation (RMSE) value of 0.0041, an R 2 of 0.87 and a Pearson's correlation of 0.938 on images obtained at 10X magnification. We tested the approach in otherwise isogenic cell lines in which we genetically dialed up or down CIN rates, and also on a publicly available image data set (obtained at 100X) and achieved an RMSE value of 0.0159, an R 2 of 0.90, and a Pearson's correlation of 0.951. Given the increasing interest in developing therapies for CIN-driven cancers, this method provides an important, scalable, and rapid approach to quantifying CIN on routinely obtained images. We release a GUI-implementation for easy access and utilization of the pipeline.

Single-Cell Profiling of Sarcomas from Archival Tissue Reveals Programs Associated with Resistance to Immune Checkpoint Blockade.

PURPOSE: Sarcoma encompasses a diverse group of cancers that are typically resistant to current therapies, including immune checkpoint blockade (ICB), and underlying mechanisms are poorly understood. The contexture of sarcomas limits generation of high-quality data using cutting-edge molecular profiling methods, such as single-cell RNA-sequencing, thus hampering progress in understanding these understudied cancers. EXPERIMENTAL DESIGN: Here, we demonstrate feasibility of producing multimodal single-cell genomics and whole-genome sequencing data from frozen tissues, profiling 75,716 cell transcriptomes of five undifferentiated pleomorphic sarcoma and three intimal sarcoma samples, including paired specimens from two patients treated with ICB. RESULTS: We find that genomic diversity decreases in patients with response to ICB, and, in unbiased analyses, identify cancer cell programs associated with therapy resistance. Although interactions of tumor-infiltrating T lymphocytes within the tumor ecosystem increase in ICB responders, clonal expansion of CD8+ T cells alone was insufficient to predict drug responses. CONCLUSIONS: This study provides a framework for studying rare tumors and identifies salient and treatment-associated cancer cell intrinsic and tumor microenvironmental features in sarcomas.

Mapping variant effects on anti-tumor hallmarks of primary human T cells with base-editing screens.

Single-nucleotide variants (SNVs) in key T cell genes can drive clinical pathologies and could be repurposed to improve cellular cancer immunotherapies. Here, we perform massively parallel base-editing screens to generate thousands of variants at gene loci annotated with known or potential clinical relevance. We discover a broad landscape of putative gain-of-function (GOF) and loss-of-function (LOF) mutations, including in PIK3CD and the gene encoding its regulatory subunit, PIK3R1, LCK, SOS1, AKT1 and RHOA. Base editing of PIK3CD and PIK3R1 variants in T cells with an engineered T cell receptor specific to a melanoma epitope or in different generations of CD19 chimeric antigen receptor (CAR) T cells demonstrates that discovered GOF variants, but not LOF or silent mutation controls, enhanced signaling, cytokine production and lysis of cognate melanoma and leukemia cell models, respectively. Additionally, we show that generations of CD19 CAR T cells engineered with PIK3CD GOF mutations demonstrate enhanced antigen-specific signaling, cytokine production and leukemia cell killing, including when benchmarked against other recent strategies.

Loss of Pip4k2c confers liver-metastatic organotropism through insulin-dependent PI3K-AKT pathway activation.

Liver metastasis (LM) confers poor survival and therapy resistance across cancer types, but the mechanisms of liver-metastatic organotropism remain unknown. Here, through in vivo CRISPR-Cas9 screens, we found that Pip4k2c loss conferred LM but had no impact on lung metastasis or primary tumor growth. Pip4k2c-deficient cells were hypersensitized to insulin-mediated PI3K/AKT signaling and exploited the insulin-rich liver milieu for organ-specific metastasis. We observed concordant changes in PIP4K2C expression and distinct metabolic changes in 3,511 patient melanomas, including primary tumors, LMs and lung metastases. We found that systemic PI3K inhibition exacerbated LM burden in mice injected with Pip4k2c-deficient cancer cells through host-mediated increase in hepatic insulin levels; however, this circuit could be broken by concurrent administration of an SGLT2 inhibitor or feeding of a ketogenic diet. Thus, this work demonstrates a rare example of metastatic organotropism through co-optation of physiological metabolic cues and proposes therapeutic avenues to counteract these mechanisms.

KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response.

Current methods for biomarker discovery and target identification in immuno-oncology rely on static snapshots of tumor immunity. To thoroughly characterize the temporal nature of antitumor immune responses, we developed a 34-parameter spectral flow cytometry panel and performed high-throughput analyses in critical contexts. We leveraged two distinct preclinical models that recapitulate cancer immunoediting (NPK-C1) and immune checkpoint blockade (ICB) response (MC38), respectively, and profiled multiple relevant tissues at and around key inflection points of immune surveillance and escape and/or ICB response. Machine learning-driven data analysis revealed a pattern of KLRG1 expression that uniquely identified intratumoral effector CD4 T cell populations that constitutively associate with tumor burden across tumor models, and are lost in tumors undergoing regression in response to ICB. Similarly, a Helios - KLRG1 + subset of tumor-infiltrating regulatory T cells (Tregs) was associated with tumor progression from immune equilibrium to escape, and were also lost in tumors responding to ICB. Validation studies confirmed KLRG1 signatures in human tumorinfiltrating CD4 T cells associate with disease progression in renal cancer. These findings nominate KLRG1 + CD4 T cell populations as subsets for further investigation in cancer immunity and demonstrate the utility of longitudinal spectral flow profiling as an engine of dynamic biomarker and/or target discovery.

KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response.

Current methods for biomarker discovery and target identification in immuno-oncology rely on static snapshots of tumor immunity. To thoroughly characterize the temporal nature of antitumor immune responses, we developed a 34-parameter spectral flow cytometry panel and performed high-throughput analyses in critical contexts. We leveraged two distinct preclinical models that recapitulate cancer immunoediting (NPK-C1) and immune checkpoint blockade (ICB) response (MC38), respectively, and profiled multiple relevant tissues at and around key inflection points of immune surveillance and escape and/or ICB response. Machine learning-driven data analysis revealed a pattern of KLRG1 expression that uniquely identified intratumoral effector CD4 T cell populations that constitutively associate with tumor burden across tumor models, and are lost in tumors undergoing regression in response to ICB. Similarly, a Helios-KLRG1+ subset of tumor-infiltrating regulatory T cells was associated with tumor progression from immune equilibrium to escape and was also lost in tumors responding to ICB. Validation studies confirmed KLRG1 signatures in human tumor-infiltrating CD4 T cells associate with disease progression in renal cancer. These findings nominate KLRG1+ CD4 T cell populations as subsets for further investigation in cancer immunity and demonstrate the utility of longitudinal spectral flow profiling as an engine of dynamic biomarker discovery.

Mapping human natural killer cell development in pediatric tonsil by imaging mass cytometry and high-resolution microscopy.

Natural killer (NK) cells develop from CD34+ progenitors in a stage-specific manner defined by changes in cell surface receptor expression and function. Secondary lymphoid tissues, including tonsil, are sites of human NK cell development. Here we present new insights into human NK cell development in pediatric tonsil using cyclic immunofluorescence and imaging mass cytometry. We show that NK cell subset localization and interactions are dependent on NK cell developmental stage and tissue residency. NK cell progenitors are found in the interfollicular domain in proximity to cytokine-expressing stromal cells that promote proliferation and maturation. Mature NK cells are primarily found in the T-cell rich parafollicular domain engaging in cell-cell interactions that differ depending on their stage and tissue residency. The presence of local inflammation results in changes in NK cell interactions, abundance, and localization. This study provides the first comprehensive atlas of human NK cell development in secondary lymphoid tissue.

Massively parallel base editing screens to map variant effects on anti-tumor hallmarks of primary human T cells.

Base editing enables generation of single nucleotide variants, but large-scale screening in primary human T cells is limited due to low editing efficiency, among other challenges 1 . Here, we developed a high-throughput approach for high-efficiency and massively parallel adenine and cytosine base-editor screening in primary human T cells. We performed multiple large-scale screens editing 102 genes with central functions in T cells and full-length tiling mutagenesis of selected genes, and read out variant effects on hallmarks of T cell anti-tumor immunity, including activation, proliferation, and cytokine production. We discovered a broad landscape of gain- and loss-of-function mutations, including in PIK3CD and its regulatory subunit encoded by PIK3R1, LCK , AKT1, CTLA-4 and JAK1 . We identified variants that affected several (e.g., PIK3CD C416R) or only selected (e.g. LCK Y505C) hallmarks of T cell activity, and functionally validated several hits by probing downstream signaling nodes and testing their impact on T cell polyfunctionality and proliferation. Using primary human T cells in which we engineered a T cell receptor (TCR) specific to a commonly presented tumor testis antigen as a model for cellular immunotherapy, we demonstrate that base edits identified in our screens can tune specific or broad T cell functions and ultimately improve tumor elimination while exerting minimal off-target activity. In summary, we present the first large-scale base editing screen in primary human T cells and provide a framework for scalable and targeted base editing at high efficiency. Coupled with multi-modal phenotypic mapping, we accurately nominate variants that produce a desirable T cell state and leverage these synthetic proteins to improve models of cellular cancer immunotherapies.

Multimodal single-cell and whole-genome sequencing of small, frozen clinical specimens.

Single-cell genomics enables dissection of tumor heterogeneity and molecular underpinnings of drug response at an unprecedented resolution1-11. However, broad clinical application of these methods remains challenging, due to several practical and preanalytical challenges that are incompatible with typical clinical care workflows, namely the need for relatively large, fresh tissue inputs. In the present study, we show that multimodal, single-nucleus (sn)RNA/T cell receptor (TCR) sequencing, spatial transcriptomics and whole-genome sequencing (WGS) are feasible from small, frozen tissues that approximate routinely collected clinical specimens (for example, core needle biopsies). Compared with data from sample-matched fresh tissue, we find a similar quality in the biological outputs of snRNA/TCR-seq data, while reducing artifactual signals and compositional biases introduced by fresh tissue processing. Profiling sequentially collected melanoma samples from a patient treated in the KEYNOTE-001 trial12, we resolved cellular, genomic, spatial and clonotype dynamics that represent molecular patterns of heterogeneous intralesional evolution during anti-programmed cell death protein 1 therapy. To demonstrate applicability to banked biospecimens of rare diseases13, we generated a single-cell atlas of uveal melanoma liver metastasis with matched WGS data. These results show that single-cell genomics from archival, clinical specimens is feasible and provides a framework for translating these methods more broadly to the clinical arena.

Neoadjuvant durvalumab plus radiation versus durvalumab alone in stages I-III non-small cell lung cancer: survival outcomes and molecular correlates of a randomized phase II trial.

We previously reported the results of a randomized phase II trial (NCT02904954) in patients with early-stage non-small cell lung cancer (NSCLC) who were treated with either two preoperative cycles of the anti-PD-L1 antibody durvalumab alone or combined with immunomodulatory doses of stereotactic radiation (DRT). The trial met its primary endpoint of major pathological response, which was significantly higher following DRT with no new safety signals. Here, we report on the prespecified secondary endpoint of disease-free survival (DFS) regardless of treatment assignment and the prespecified exploratory analysis of DFS in each arm of the trial. DFS at 2 and 3 years across patients in both arms of the trial were 73% (95% CI: 62.1-84.5) and 65% (95% CI: 52.5-76.9) respectively. For the exploratory endpoint of DFS in each arm of the trial, three-year DFS was 63% (95% CI: 46.0-80.4) in the durvalumab monotherapy arm compared to 67% (95% CI: 49.6-83.4) in the dual therapy arm. In addition, we report post hoc exploratory analysis of progression-free survival as well as molecular correlates of response and recurrence through high-plex immunophenotyping of sequentially collected peripheral blood and gene expression profiles from resected tumors in both treatment arms. Together, our results contribute to the evolving landscape of neoadjuvant treatment regimens for NSCLC and identify easily measurable potential biomarkers of response and recurrence.

The CD58-CD2 axis is co-regulated with PD-L1 via CMTM6 and shapes anti-tumor immunity.

The cell-autonomous balance of immune-inhibitory and -stimulatory signals is a critical process in cancer immune evasion. Using patient-derived co-cultures, humanized mouse models, and single-cell RNA-sequencing of patient melanomas biopsied before and on immune checkpoint blockade, we find that intact cancer cell-intrinsic expression of CD58 and ligation to CD2 is required for anti-tumor immunity and is predictive of treatment response. Defects in this axis promote immune evasion through diminished T cell activation, impaired intratumoral T cell infiltration and proliferation, and concurrently increased PD-L1 protein stabilization. Through CRISPR-Cas9 and proteomics screens, we identify and validate CMTM6 as critical for CD58 stability and upregulation of PD-L1 upon CD58 loss. Competition between CD58 and PD-L1 for CMTM6 binding determines their rate of endosomal recycling over lysosomal degradation. Overall, we describe an underappreciated yet critical axis of cancer immunity and provide a molecular basis for how cancer cells balance immune inhibitory and stimulatory cues.

Contribution of Trp63CreERT2-labeled cells to alveolar regeneration is independent of tuft cells.

Viral infection often causes severe damage to the lungs, leading to the appearance of ectopic basal cells (EBCs) and tuft cells in the lung parenchyma. Thus far, the roles of these ectopic epithelial cells in alveolar regeneration remain controversial. Here, we confirm that the ectopic tuft cells are originated from EBCs in mouse models and COVID-19 lungs. The differentiation of tuft cells from EBCs is promoted by Wnt inhibition while suppressed by Notch inhibition. Although progenitor functions have been suggested in other organs, pulmonary tuft cells don't proliferate or give rise to other cell lineages. Consistent with previous reports, Trp63CreERT2 and KRT5-CreERT2-labeled ectopic EBCs do not exhibit alveolar regeneration potential. Intriguingly, when tamoxifen was administrated post-viral infection, Trp63CreERT2 but not KRT5-CreERT2 labels islands of alveolar epithelial cells that are negative for EBC biomarkers. Furthermore, germline deletion of Trpm5 significantly increases the contribution of Trp63CreERT2-labeled cells to the alveolar epithelium. Although Trpm5 is known to regulate tuft cell development, complete ablation of tuft cell production fails to improve alveolar regeneration in Pou2f3-/- mice, implying that Trpm5 promotes alveolar epithelial regeneration through a mechanism independent of tuft cells.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients.

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.