Combined JAK inhibition and PD-1 immunotherapy for non-small cell lung cancer patients.

Persistent inflammation driven by cytokines such as type-one interferon (IFN-I) can cause immunosuppression. We show that administration of the Janus kinase 1 (JAK1) inhibitor itacitinib after anti-PD-1 (programmed cell death protein 1) immunotherapy improves immune function and antitumor responses in mice and results in high response rates (67%) in a phase 2 clinical trial for metastatic non-small cell lung cancer. Patients who failed to respond to initial anti-PD-1 immunotherapy but responded after addition of itacitinib had multiple features of poor immune function to anti-PD-1 alone that improved after JAK inhibition. Itacitinib promoted CD8 T cell plasticity and therapeutic responses of exhausted and effector memory-like T cell clonotypes. Patients with persistent inflammation refractory to itacitinib showed progressive CD8 T cell terminal differentiation and progressive disease. Thus, JAK inhibition may improve the efficacy of anti-PD-1 immunotherapy by pivoting T cell differentiation dynamics.

Heat-inducible CAR-T overcomes adverse mechanical tumor microenvironment in a 3D bioprinted glioblastoma model.

Glioblastoma (GBM) presents a significant therapeutic challenge due to the limited efficacy of existing treatments. Chimeric antigen receptor (CAR) T-cell therapy offers promise, but its potential in solid tumors like GBM is undermined by the physical barrier posed by the extracellular matrix (ECM). To address the inadequacies of traditional 2D cell culture, animal models, and Matrigel-based 3D culture in mimicking the mechanical characteristics of tumor tissues, we employed biomaterials and digital light processing-based 3D bioprinting to fabricate biomimetic tumor models with finely tunable ECM stiffness independent of ECM composition. Our results demonstrated that increased material stiffness markedly impeded CAR-T cell penetration and tumor cell cytotoxicity in GBM models. The 3D bioprinted models enabled us to examine the influence of ECM stiffness on CAR-T cell therapy effectiveness, providing a clinically pertinent evaluation tool for CAR-T cell development in stiff solid tumors. Furthermore, we developed an innovative heat-inducible CAR-T cell therapy, effectively overcoming the challenges posed by the stiff tumor microenvironment.

Integration of 3D bioprinting and multi-algorithm machine learning identified glioma susceptibilities and microenvironment characteristics.

Glioma, with its heterogeneous microenvironments and genetic subtypes, presents substantial challenges for treatment prediction and development. We integrated 3D bioprinting and multi-algorithm machine learning as a novel approach to enhance the assessment and understanding of glioma treatment responses and microenvironment characteristics. The bioprinted patient-derived glioma tissues successfully recapitulated molecular properties and drug responses of native tumors. We then developed GlioML, a machine learning workflow incorporating nine distinct algorithms and a weighted ensemble model that generated robust gene expression-based predictors, each reflecting the diverse action mechanisms of various compounds and drugs. The ensemble model superseded the performance of all individual algorithms across diverse in vitro systems, including sphere cultures, complex 3D bioprinted multicellular models, and 3D patient-derived tissues. By integrating bioprinting, the evaluative scope of the treatment expanded to T cell-related therapy and anti-angiogenesis targeted therapy. We identified promising compounds and drugs for glioma treatment and revealed distinct immunosuppressive or angiogenic myeloid-infiltrated tumor microenvironments. These insights pave the way for enhanced therapeutic development for glioma and potentially for other cancers, highlighting the broad application potential of this integrative and translational approach.

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma.

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities to adult glioma, it is increasingly recognized as a molecularly distinct, yet highly heterogeneous disease. In this study, we longitudinally profiled a molecularly diverse cohort of 16 pHGG patients before and after standard therapy through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of the tumor microenvironment during progression following treatment. We found that the canonical neoplastic cell phenotypes of adult glioblastoma are insufficient to capture the range of tumor cell states in a pediatric cohort and observed differential tumor-myeloid interactions between malignant cell states. We identified key transcriptional regulators of pHGG cell states and did not observe the marked proneural to mesenchymal shift characteristic of adult glioblastoma. We showed that essential neuromodulators and the interferon response are upregulated post-therapy along with an increase in non-neoplastic oligodendrocytes. Through in vitro pharmacological perturbation, we demonstrated novel malignant cell-intrinsic targets. This multiomic atlas of longitudinal pHGG captures the key features of therapy response that support distinction from its adult counterpart and suggests therapeutic strategies which are targeted to pediatric gliomas.

Identification and targeting of treatment resistant progenitor populations in T-cell Acute Lymphoblastic Leukemia.

Refractoriness to initial chemotherapy and relapse after remission are the main obstacles to cure in T-cell Acute Lymphoblastic Leukemia (T-ALL). Biomarker guided risk stratification and targeted therapy have the potential to improve outcomes in high-risk T-ALL; however, cellular and genetic factors contributing to treatment resistance remain unknown. Previous bulk genomic studies in T-ALL have implicated tumor heterogeneity as an unexplored mechanism for treatment failure. To link tumor subpopulations with clinical outcome, we created an atlas of healthy pediatric hematopoiesis and applied single-cell multiomic (CITE-seq/snATAC-seq) analysis to a cohort of 40 cases of T-ALL treated on the Children's Oncology Group AALL0434 clinical trial. The cohort was carefully selected to capture the immunophenotypic diversity of T-ALL, with early T-cell precursor (ETP) and Near/Non-ETP subtypes represented, as well as enriched with both relapsed and treatment refractory cases. Integrated analyses of T-ALL blasts and normal T-cell precursors identified a bone-marrow progenitor-like (BMP-like) leukemia sub-population associated with treatment failure and poor overall survival. The single-cell-derived molecular signature of BMP-like blasts predicted poor outcome across multiple subtypes of T-ALL within two independent patient cohorts using bulk RNA-sequencing data from over 1300 patients. We defined the mutational landscape of BMP-like T-ALL, finding that NOTCH1 mutations additively drive T-ALL blasts away from the BMP-like state. We transcriptionally matched BMP-like blasts to early thymic seeding progenitors that have low NR3C1 expression and high stem cell gene expression, corresponding to a corticosteroid and conventional cytotoxic resistant phenotype we observed in ex vivo drug screening. To identify novel targets for BMP-like blasts, we performed in silico and in vitro drug screening against the BMP-like signature and prioritized BMP-like overexpressed cell-surface (CD44, ITGA4, LGALS1) and intracellular proteins (BCL-2, MCL-1, BTK, NF-κB) as candidates for precision targeted therapy. We established patient derived xenograft models of BMP-high and BMP-low leukemias, which revealed vulnerability of BMP-like blasts to apoptosis-inducing agents, TEC-kinase inhibitors, and proteasome inhibitors. Our study establishes the first multi-omic signatures for rapid risk-stratification and targeted treatment of high-risk T-ALL.

Organization of the human intestine at single-cell resolution.

The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall health1. The intesting has a length of over nine metres, along which there are differences in structure and function2. The localization of individual cell types, cell type development trajectories and detailed cell transcriptional programs probably drive these differences in function. Here, to better understand these differences, we evaluated the organization of single cells using multiplexed imaging and single-nucleus RNA and open chromatin assays across eight different intestinal sites from nine donors. Through systematic analyses, we find cell compositions that differ substantially across regions of the intestine and demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighbourhoods and communities, highlighting distinct immunological niches that are present in the intestine. We also map gene regulatory differences in these cells that are suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation and organization for this organ, and serve as an important reference map for understanding human biology and disease.

Geographical disparities in hepatitis b virus related hepatocellular carcinoma mortality rates worldwide from 1990 to 2019.

This study aims to evaluate global trends in hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) related mortality over the past 30 years. Despite improvements in the treatment of both HBV and HCC, disparities in access to care and treatment persist, and these disparities may have affected HBV-HCC outcomes across certain global regions disproportionately. Using data from the Global Burden of Diseases, Injury, and Risk Factors Study (GBD) from 1990 to 2019, we evaluated overall mortality rates related to HBV-HCC. From 1990 to 2019, overall global HBV-HCC mortality rate decreased by 30.3%. While most world regions experienced declines in HBV-HCC mortality, several regions also experienced significant increases in mortality, including Australasia, Central Asia, and Eastern Europe. When stratified by age, all age groups demonstrated declines in HBV-HCC mortality from 1990 to 2019. Similar trends were observed for both men and women. When stratified by world regions, HBV-HCC mortality in 2019 was highest in East Asia, which was significantly higher than the region with the next highest HBV-HCC mortality, Southeast Asia. Significant disparities in HBV-HCC mortality are observed among global regions. We observed higher HBV-HCC mortality rates with older age, higher mortality in males, and highest mortality in East Asia. The clinical significance of these findings are to highlight those regions that need more targeted resources to improve HBV testing and treatment to reduce the long term consequences of untreated HBV, such as HCC.

Single cell and spatial alternative splicing analysis with long read sequencing.

Long-read sequencing has become a powerful tool for alternative splicing analysis. However, technical and computational challenges have limited our ability to explore alternative splicing at single cell and spatial resolution. The higher sequencing error of long reads, especially high indel rates, have limited the accuracy of cell barcode and unique molecular identifier (UMI) recovery. Read truncation and mapping errors, the latter exacerbated by the higher sequencing error rates, can cause the false detection of spurious new isoforms. Downstream, there is yet no rigorous statistical framework to quantify splicing variation within and between cells/spots. In light of these challenges, we developed Longcell, a statistical framework and computational pipeline for accurate isoform quantification for single cell and spatial spot barcoded long read sequencing data. Longcell performs computationally efficient cell/spot barcode extraction, UMI recovery, and UMI-based truncation- and mapping-error correction. Through a statistical model that accounts for varying read coverage across cells/spots, Longcell rigorously quantifies the level of inter-cell/spot versus intra-cell/ spot diversity in exon-usage and detects changes in splicing distributions between cell populations. Applying Longcell to single cell long-read data from multiple contexts, we found that intra-cell splicing heterogeneity, where multiple isoforms co-exist within the same cell, is ubiquitous for highly expressed genes. On matched single cell and Visium long read sequencing for a tissue of colorectal cancer metastasis to the liver, Longcell found concordant signals between the two data modalities. Finally, on a perturbation experiment for 9 splicing factors, Longcell identified regulatory targets that are validated by targeted sequencing.

Clonal cell states link Barrett's esophagus and esophageal adenocarcinoma.

Barrett's esophagus is a common type of metaplasia and a precursor of esophageal adenocarcinoma. However, the cell states and lineage connections underlying the origin, maintenance, and progression of Barrett's esophagus have not been resolved in humans. To address this, we performed single-cell lineage tracing and transcriptional profiling of patient cells isolated from metaplastic and healthy tissue. Our analysis revealed discrete lineages in Barrett's esophagus, normal esophagus, and gastric cardia. Transitional basal progenitor cells of the gastroesophageal junction were unexpectedly related to both esophagus and gastric cardia cells. Barrett's esophagus was polyclonal, with lineages that contained all progenitor and differentiated cell types. In contrast, precancerous dysplastic foci were initiated by the expansion of a single molecularly aberrant Barrett's esophagus clone. Together, these findings provide a comprehensive view of the cell dynamics of Barrett's esophagus, linking cell states along the full disease trajectory, from its origin to cancer.

Model-based meta-analysis of non-small cell lung cancer with standard of care PD-1 inhibitors and chemotherapy for early development decision making.

Single-arm cohorts/trials are often used in early phase oncology programs to support preliminary clinical activity assessments for investigational products, administered alone or in combination with standard of care (SOC) agents. Benchmarking clinical activity of those combinations against other treatments, including SOC, requires indirect comparisons against external trials, which presents challenges including cross-study differences in trial populations/other factors. To facilitate such nonrandomized comparisons, we developed a comprehensive model-based meta-analysis (MBMA) framework to quantitatively adjust for factors related to efficacy in metastatic non-small cell lung cancer (mNSCLC). Data were derived from 15 published studies assessing key programmed cell death protein-1 (PD-1) inhibitors pembrolizumab (n = 8) and nivolumab (n = 7), representing current SOC in mNSCLC. In the first stage, a mixed-effects logistic regression model for overall response rate (ORR) was developed accounting for effects of various population covariates on ORR. The ORR model results indicated an odds ratio (OR) of 1.02 for squamous versus non-squamous histology and OR of 1.20 for PD-ligand 1 tumor proportion score (TPS) per every 10% increase of TPS level. Next, a nonparametric mixed-effects model for overall survival (OS) was developed with ORR/other clinical covariates as input. Subsequently, MBMA simulations of relevant hypothetical scenarios involving single-arm trial design predicted OS hazard ratios as a function of ORR with matched patient characteristics. Findings from this MBMA and derived parameter estimates can be generally applied by the reader as a framework for interpreting efficacy data from early phase trials to support ORR-based go/no-go decisions and futility rules, illustrated through examples in this report.

Colorectal Cancer Metastases in the Liver Establish Immunosuppressive Spatial Networking between Tumor-Associated SPP1+ Macrophages and Fibroblasts.

PURPOSE: The liver is the most frequent metastatic site for colorectal cancer. Its microenvironment is modified to provide a niche that is conducive for colorectal cancer cell growth. This study focused on characterizing the cellular changes in the metastatic colorectal cancer (mCRC) liver tumor microenvironment (TME). EXPERIMENTAL DESIGN: We analyzed a series of microsatellite stable (MSS) mCRCs to the liver, paired normal liver tissue, and peripheral blood mononuclear cells using single-cell RNA sequencing (scRNA-seq). We validated our findings using multiplexed spatial imaging and bulk gene expression with cell deconvolution. RESULTS: We identified TME-specific SPP1-expressing macrophages with altered metabolism features, foam cell characteristics, and increased activity in extracellular matrix (ECM) organization. SPP1+ macrophages and fibroblasts expressed complementary ligand-receptor pairs with the potential to mutually influence their gene-expression programs. TME lacked dysfunctional CD8 T cells and contained regulatory T cells, indicative of immunosuppression. Spatial imaging validated these cell states in the TME. Moreover, TME macrophages and fibroblasts had close spatial proximity, which is a requirement for intercellular communication and networking. In an independent cohort of mCRCs in the liver, we confirmed the presence of SPP1+ macrophages and fibroblasts using gene-expression data. An increased proportion of TME fibroblasts was associated with the worst prognosis in these patients. CONCLUSIONS: We demonstrated that mCRC in the liver is characterized by transcriptional alterations of macrophages in the TME. Intercellular networking between macrophages and fibroblasts supports colorectal cancer growth in the immunosuppressed metastatic niche in the liver. These features can be used to target immune-checkpoint-resistant MSS tumors.

The interferon-stimulated gene RIPK1 regulates cancer cell intrinsic and extrinsic resistance to immune checkpoint blockade.

Interferon-gamma (IFN-γ) has pleiotropic effects on cancer immune checkpoint blockade (ICB), including roles in ICB resistance. We analyzed gene expression in ICB-sensitive versus ICB-resistant tumor cells and identified a strong association between interferon-mediated resistance and expression of Ripk1, a regulator of tumor necrosis factor (TNF) superfamily receptors. Genetic interaction screening revealed that in cancer cells, RIPK1 diverted TNF signaling through NF-κB and away from its role in cell death. This promoted an immunosuppressive chemokine program by cancer cells, enhanced cancer cell survival, and decreased infiltration of T and NK cells expressing TNF superfamily ligands. Deletion of RIPK1 in cancer cells compromised chemokine secretion, decreased ARG1+ suppressive myeloid cells linked to ICB failure in mice and humans, and improved ICB response driven by CASP8-killing and dependent on T and NK cells. RIPK1-mediated resistance required its ubiquitin scaffolding but not kinase function. Thus, cancer cells co-opt RIPK1 to promote cell-intrinsic and cell-extrinsic resistance to immunotherapy.

Human pluripotent stem cell-derived myogenic progenitors undergo maturation to quiescent satellite cells upon engraftment.

Human pluripotent stem cell (hPSC)-derived myogenic progenitor cell (MPC) transplantation is a promising therapeutic approach for a variety of degenerative muscle disorders. Here, using an MPC-specific fluorescent reporter system (PAX7::GFP), we demonstrate that hPSC-derived MPCs can contribute to the regeneration of myofibers in mice following local injury and in mice deficient of dystrophin (mdx). We also demonstrate that a subset of PAX7::GFP MPCs engraft within the basal lamina of regenerated myofibers, adopt a quiescent state, and contribute to regeneration upon reinjury and in mdx mouse models. This subset of PAX7::GFP MPCs undergo a maturation process and remodel their molecular characteristics to resemble those of late-stage fetal MPCs/adult satellite cells following in vivo engraftment. These in-vivo-matured PAX7::GFP MPCs retain a cell-autonomous ability to regenerate and can repopulate in the niche of secondary recipient mice, providing a proof of principle for future hPSC-based cell therapy for muscle disorders.

Single cell biology-a Keystone Symposia report.

Single cell biology has the potential to elucidate many critical biological processes and diseases, from development and regeneration to cancer. Single cell analyses are uncovering the molecular diversity of cells, revealing a clearer picture of the variation among and between different cell types. New techniques are beginning to unravel how differences in cell state-transcriptional, epigenetic, and other characteristics-can lead to different cell fates among genetically identical cells, which underlies complex processes such as embryonic development, drug resistance, response to injury, and cellular reprogramming. Single cell technologies also pose significant challenges relating to processing and analyzing vast amounts of data collected. To realize the potential of single cell technologies, new computational approaches are needed. On March 17-19, 2021, experts in single cell biology met virtually for the Keystone eSymposium "Single Cell Biology" to discuss advances both in single cell applications and technologies.

Development and Performance of a CD8 Gene Signature for Characterizing Inflammation in the Tumor Microenvironment across Multiple Tumor Types.

Across multiple tumor types, immune checkpoint inhibitors (ICIs) have demonstrated clinical benefit to patients with cancer, yet there is a need to identify predictive biomarkers of response to these therapies. A multiparameter gene expression profiling-based tumor inflammation assay may offer robust characterization of the tumor microenvironment, thereby extending the utility of single-gene analysis or immunohistochemistry (IHC) in predicting response to ICIs. The authors interrogated 1778 commercially procured, formalin-fixed, paraffin-embedded samples using gene expression profiling and pathology-assisted digital CD8 IHC. A machine-learning approach was used to develop gene expression signatures that predicted CD8+ immune cell abundance as surrogates for tumor inflammation in melanoma and squamous cell carcinoma of the head and neck samples. An assay for a 16-gene CD8 signature was developed and analytically validated across 12 tumor types. CD8 signature scores correlated with CD8 IHC in a platform-independent manner, and inflammation prevalence was similar between assay methods for all tumor types except prostate cancer and small cell lung cancer. In retrospective analyses, CD8 signature scores were associated with progression-free survival and overall survival with nivolumab in patients with urothelial carcinoma from CheckMate 275. This study demonstrated that the CD8 signature assay can be used to accurately quantify CD8+ immune cell abundance in the tumor microenvironment and has potential clinical utility for determining patients with cancer likely to respond to ICIs.

Integrative single-cell analysis of allele-specific copy number alterations and chromatin accessibility in cancer.

Cancer progression is driven by both somatic copy number aberrations (CNAs) and chromatin remodeling, yet little is known about the interplay between these two classes of events in shaping the clonal diversity of cancers. We present Alleloscope, a method for allele-specific copy number estimation that can be applied to single-cell DNA- and/or transposase-accessible chromatin-sequencing (scDNA-seq, ATAC-seq) data, enabling combined analysis of allele-specific copy number and chromatin accessibility. On scDNA-seq data from gastric, colorectal and breast cancer samples, with validation using matched linked-read sequencing, Alleloscope finds pervasive occurrence of highly complex, multiallelic CNAs, in which cells that carry varying allelic configurations adding to the same total copy number coevolve within a tumor. On scATAC-seq from two basal cell carcinoma samples and a gastric cancer cell line, Alleloscope detected multiallelic copy number events and copy-neutral loss-of-heterozygosity, enabling dissection of the contributions of chromosomal instability and chromatin remodeling to tumor evolution.

Delayed diagnoses of Acanthamoeba keratitis at a tertiary care medical centre.

PURPOSE: To determine the prevalence and reasons for delays in diagnosis in patients with Acanthamoeba keratitis (AK) presenting to Wilmer Eye Institute, Baltimore, Maryland. METHODS: This retrospective study analysed all patients with culture-positive AK seen between 2012 and 2019 at a tertiary referral centre. Patient demographic information, clinical history, risk factors, symptom duration, referral patterns, slit lamp examination findings, visual acuity and need for surgery were collected. RESULTS: The study included 45 eyes of 43 patients. On average, patients were symptomatic for 52.6 days before culture collection. Thirty-one percent of patients were diagnosed within 28 days of symptom onset while 69% were diagnosed after 28 days. Before presentation to a tertiary care centre, 69% of patients were evaluated by an ophthalmologist outside of this institution and 27% were evaluated by a provider other than an ophthalmologist. AK was most commonly misdiagnosed as herpetic keratitis, occurring in 38% of patients. The strongest risk factor for AK was contact lens use. Only 11% of patients presented with the classic ring infiltrate and 82% had pain. Patients with an early versus late diagnosis had a mean Snellen visual acuity (VA) of 20/224 versus 20/296 at presentation (p = 0.33) and a mean Snellen VA of 20/91 versus 20/240 at final visit (p = 0.07). 11% of patients required a therapeutic penetrating keratoplasty. CONCLUSION: Delayed diagnosis of AK in our cohort occurred due to a misdiagnosis as herpetic keratitis, non-specific clinical signs including the lack of pain in a number of patients, and a delay in referral to a tertiary care centre. Any contact lens wearer with an atypical keratitis should be referred promptly for Acanthamoeba cultures.

DENDRO: genetic heterogeneity profiling and subclone detection by single-cell RNA sequencing.

Although scRNA-seq is now ubiquitously adopted in studies of intratumor heterogeneity, detection of somatic mutations and inference of clonal membership from scRNA-seq is currently unreliable. We propose DENDRO, an analysis method for scRNA-seq data that clusters single cells into genetically distinct subclones and reconstructs the phylogenetic tree relating the subclones. DENDRO utilizes transcribed point mutations and accounts for technical noise and expression stochasticity. We benchmark DENDRO and demonstrate its application on simulation data and real data from three cancer types. In particular, on a mouse melanoma model in response to immunotherapy, DENDRO delineates the role of neoantigens in treatment response.

Data denoising with transfer learning in single-cell transcriptomics.

Single-cell RNA sequencing (scRNA-seq) data are noisy and sparse. Here, we show that transfer learning across datasets remarkably improves data quality. By coupling a deep autoencoder with a Bayesian model, SAVER-X extracts transferable gene-gene relationships across data from different labs, varying conditions and divergent species, to denoise new target datasets.

Opposing Functions of Interferon Coordinate Adaptive and Innate Immune Responses to Cancer Immune Checkpoint Blockade.

Interferon-gamma (IFNG) augments immune function yet promotes T cell exhaustion through PDL1. How these opposing effects are integrated to impact immune checkpoint blockade (ICB) is unclear. We show that while inhibiting tumor IFNG signaling decreases interferon-stimulated genes (ISGs) in cancer cells, it increases ISGs in immune cells by enhancing IFNG produced by exhausted T cells (TEX). In tumors with favorable antigenicity, these TEX mediate rejection. In tumors with neoantigen or MHC-I loss, TEX instead utilize IFNG to drive maturation of innate immune cells, including a PD1+TRAIL+ ILC1 population. By disabling an inhibitory circuit impacting PD1 and TRAIL, blocking tumor IFNG signaling promotes innate immune killing. Thus, interferon signaling in cancer cells and immune cells oppose each other to establish a regulatory relationship that limits both adaptive and innate immune killing. In melanoma and lung cancer patients, perturbation of this relationship is associated with ICB response independent of tumor mutational burden.