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Hodgkin lymphoma is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of noncancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding cross-talk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 Hodgkin lymphoma tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the Hodgkin lymphoma–specific immune microenvironment at single-cell resolution. Single-cell expression profiling identified a novel Hodgkin lymphoma–associated subset of T cells with prominent expression of the inhibitory receptor LAG3, and functional analyses established this LAG3+ T-cell population as a mediator of immunosuppression. Multiplexed spatial assessment of immune cells in the microenvironment also revealed increased LAG3+ T cells in the direct vicinity of MHC class II–deficient tumor cells. Our findings provide novel insights into TME biology and suggest new approaches to immune-checkpoint targeting in Hodgkin lymphoma.Significance:We provide detailed functional and spatial characteristics of immune cells in classic Hodgkin lymphoma at single-cell resolution. Specifically, we identified a regulatory T-cell–like immunosuppressive subset of LAG3+ T cells contributing to the immune-escape phenotype. Our insights aid in the development of novel biomarkers and combination treatment strategies targeting immune checkpoints.See related commentary by Fisher and Oh, p. 342.This article is highlighted in the In This Issue feature, p. 327

Supplementary Methods, Supplementary Figures 1-19, Supplementary References

Pixel-level detection of expansion joints on complex pavements is significant for traffic safety and the structural integrity of highway bridges. This paper proposed an improved HRNet-OCR, named as expansion joints segmentation network (EJSNet), for automated pixel-level detection of the expansion joints on asphalt pavement. Different from the high-resolution network (HRNet), the proposed EJSNet modifies the residual structure of the first stage by conducting a Conv. + BN + ReLU (convolution + batch normalization + rectified linear unit) operation for each shortcut connection, which can avoid the network degradation. The feature selection module (FSM) and receptive field block (RFB) module are incorporated into the proposed EJSNet model to learn and extract the contexts at different resolution levels for enhanced latent representations. The convolutional block attention module (CBAM) is introduced to enhance the adaptive feature refinement of the network. Moreover, the shared multilayer perceptron (MLP) architecture of the channel attention module (CAM) is also modified in this paper. Experimental results demonstrate that the F-measure and intersection-over-union (IOU) attained by the proposed EJSNet model on 500 testing image sets are 95.14% and 0.9036, respectively. Compared with four state-of-the-art models for semantic segmentation (i.e., SegNet, DeepLabv3+, dual attention network (DANet), and HRNet-OCR), the proposed EJSNet model can yield higher detection accuracy on both private and public datasets.

Background Accurately predicting outcomes for cancer patients with COVID-19 has been clinically challenging. Numerous clinical variables have been retrospectively associated with disease severity, but the predictive value of these variables, and how multiple variables interact to increase risk, remains unclear. Methods We used machine learning algorithms to predict COVID-19 severity in 348 cancer patients at Memorial Sloan Kettering Cancer Center in New York City. Using only clinical variables collected on or before a patient’s COVID-19 positive date (time zero), we sought to classify patients into one of three possible future outcomes: Severe-early (the patient required high levels of oxygen support within 3 days of being tested positive for COVID-19), Severe-late (the patient required high levels of oxygen after 3 days), and Non-severe (the patient never required oxygen support). Results Our algorithm classified patients into these classes with an area under the receiver operating characteristic curve (AUROC) ranging from 70 to 85%, significantly outperforming prior methods and univariate analyses. Critically, classification accuracy is highest when using a potpourri of clinical variables — including basic patient information, pre-existing diagnoses, laboratory and radiological work, and underlying cancer type — suggesting that COVID-19 in cancer patients comes with numerous, combinatorial risk factors. Conclusions Overall, we provide a computational tool that can identify high-risk patients early in their disease progression, which could aid in clinical decision-making and selecting treatment options.

BACKGROUND Lumbar puncture (LP) is a frequently performed diagnostic and therapeutic procedure in oncology patients. Transfusing to a minimum preprocedural platelet threshold of 50 × 109 /L is widely upheld without good quality evidence. The objective was to compare the outcomes of LPs performed with platelets above and below this threshold. An increased risk of adverse events in patients with lower platelet counts was not expected. As a corollary, transfusion reaction rates incurred by transfusing to this recommended threshold are also reported. METHODS A total of 2259 LPs performed on 1137 oncology patients (adult, n = 871, and pediatric, n = 266) were retrospectively analyzed between February 2011 and December 2017. The incidence of LP-related complications for groups above and below the minimum platelet threshold was compared. Traumatic tap was defined as 500 or more red blood cells per high-power field in the cerebral spinal fluid. Groups were compared using the 2-Proportion Z-test and Fisher exact test. RESULTS At time of LP, the total number of events with platelets less than 50 × 109 /L and 50 × 109 /L or greater were 110 and 2149, respectively. There were no significant differences in LP-associated complications between patients with platelet counts above or below 50 × 109 /L (P = .29). Patients with a pre-LP platelet count of less than 50 × 109 /L had a higher proportion of traumatic taps (P

At the present time, increasing attention is being paid to the detection of road facilities, such as manhole covers— an important type of road facility which can have tangible impacts on driving safety and comfort. This paper proposes a robust method based on a modification of the Faster Region Convolutional Neural Network (Faster R-CNN) to automatically detect pavement manhole covers. We establish a manually annotated image library that consists of 1,245 manhole cover images collected by 1 mm laser imaging system, and implement the modified Faster R-CNN architecture to locate manhole covers exclusively under realistic and complex environments. Compared with the original Faster R-CNN, the proposed modification is to replace the feature extractor used in the original Faster R-CNN with a more-efficient backbone ResNet50, and implement a Feature Pyramid Network (FPN) to fuse multi-scale features. The experimental results demonstrate that the modified Faster R-CNN outperforms the original Faster R-CNN and other state-of-the-art models, including YOLOv4, EfficientDet, and YOLOX. The F1-score and Overall-IOU achieved by the modified Faster R-CNN on 250 test images are 98.15 per cent and 92.07 per cent respectively. To further verify the robustness of the proposed method, the modified Faster R-CNN is applied to process manhole cover images which are taken randomly by a smartphone and thus very different to the manhole cover images acquired by the laser imaging system. It is found that the modified Faster R-CNN can also yield similar detection efficiency even for images representing highly dissimilar viewing angles and unforeseen scenarios, implying the benefits of deep-learning-based object detection algorithms to intelligent investigation of pavement manhole covers.

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability1–4 patterned by distinct mutational processes5,6, tumour heterogeneity7–9 and intraperitoneal spread7,8,10. Immunotherapies have had limited efficacy in HGSOC11–13, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC. Homologous recombination-deficient HRD-Dup (BRCA1 mutant-like) and HRD-Del (BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8+ T cells. By contrast, foldback-inversion-bearing tumours exhibited elevated immunosuppressive TGFβ signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research.

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability patterned by distinct mutational processes, intratumoral heterogeneity and intraperitoneal spread. We investigated determinants of immune recognition and evasion in HGSOC to elucidate co- evolutionary processes underlying malignant progression and tumor immunity. Mutational processes and anatomic sites of tumor foci were key determinants of tumor microenvironment cellular phenotypes, inferred from whole genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumor sites from 42 treatment-naive HGSOC patients. Homologous recombination-deficient (HRD)-Dup (BRCA1 mutant-like) and HRD- Del (BRCA2 mutant-like) tumors harbored increased neoantigen burden, inflammatory signaling and ongoing immunoediting, reflected in loss of HLA diversity and tumor infiltration with highly- differentiated dysfunctional CD8+ T cells. Foldback inversion (FBI, non-HRD) tumors exhibited elevated TGFβ signaling and immune exclusion, with predominantly naive/stem-like and memory T cells. Our findings implicate distinct immune resistance mechanisms across HGSOC subtypes which can inform future immunotherapeutic strategies.HIGHLIGHTSMulti-region, multi-modal profiling of malignant and immune cell phenotypes in ovarian cancerAnatomic site specificity is a determinant of cancer cell and intratumoral immune phenotypesTumor mutational processes impact mechanisms of immune control and immune evasionSpatial topology of HR-deficient tumors is defined by immune interactions absent from immune inert HR-proficient subtypes

How cell-to-cell copy number alterations that underpin genomic instability

Background Neutropenia is commonly encountered in cancer patients. Recombinant human granulocyte colony-stimulating factor (G-CSF, filgrastim), a cytokine that initiates proliferation and differentiation of mature granulocytes, is widely given to oncology patients to counteract neutropenia, reducing susceptibility to infection. However, the clinical impact of neutropenia and G-CSF use in cancer patients with coronavirus disease 2019 (COVID-19) remains unknown. Methods An observational cohort of 379 actively treated cancer patients with COVID-19 was assembled to investigate links between concurrent neutropenia and G-CSF administration on COVID-19-associated respiratory failure and death. These factors were encoded as time-dependent predictors in an extended Cox model, controlling for age and underlying cancer diagnosis. To determine whether the degree of granulocyte response to G-CSF affected outcomes, the degree of response to G-CSF, based on rise in absolute neutrophil count (ANC) 24 hours after growth factor administration, was also incorporated into a similar Cox model. Results In the setting of active COVID-19 infection, outpatient receipt of G-CSF led to an increased number of hospitalizations (hazard ratio [HR]: 3.54, 95% confidence interval [CI]: 1.25–10.0, P value: .017). Furthermore, among inpatients, G-CSF administration was associated with increased need for high levels of oxygen supplementation and death (HR: 3.56, 95% CI: 1.19–10.2, P value: .024). This effect was predominantly seen in patients that exhibited a high response to G-CSF based on their ANC increase post-G-CSF administration (HR: 7.78, 95% CI: 2.05–27.9, P value: .004). Conclusions The potential risks versus benefits of G-CSF administration should be considered in neutropenic cancer patients with COVID-19, because G-CSF administration may lead to worsening clinical and respiratory status.

Tumour fitness landscapes underpin selection in cancer, impacting etiology, evolution and response to treatment. Progress in defining fitness landscapes has been impeded by a lack of timeseries perturbation experiments over realistic intervals at single cell resolution. We studied the nature of clonal dynamics induced by genetic and pharmacologic perturbation with a quantitative fitness model developed to ascribe quantitative selective coefficients to individual cancer clones, enable prediction of clone-specific growth potential, and forecast competitive clonal dynamics over time. We applied the model to serial single cell genome (>60,000 cells) and transcriptome (>58,000 cells) experiments ranging from 10 months to 2.5 years in duration. We found that genetic perturbation ofTP53in epithelial cell lines induces multiple forms of copy number alteration that confer increased fitness to clonal populations with measurable consequences on gene expression. In patient derived xenografts, predicted selective coefficients accurately forecasted clonal competition dynamics, that were validated with timeseries sampling of experimentally engineered mixtures of low and high fitness clones. In cisplatin-treated patient derived xenografts, the fitness landscape was inverted in a time-dependent manner, whereby a drug resistant clone emerged from a phylogenetic lineage of low fitness clones, and high fitness clones were eradicated. Moreover, clonal selection mediated reversible drug response early in the selection process, whereas late dynamics in genomically fixed clones were associated with transcriptional plasticity on a fixed clonal genotype. Together, our findings outline causal mechanisms with implication for interpreting how mutations and multi-faceted drug resistance mechanisms shape the etiology and cellular fitness of human cancers.

Single-cell technologies have revolutionized biomedical research by enabling scalable measurement of the genome, transcriptome, and proteome of multiple systems at single-cell resolution. Now widely applied to cancer models, these assays offer new insights into tumour heterogeneity, which underlies cancer initiation, progression, and relapse. However, the large quantities of high-dimensional, noisy data produced by single-cell assays can complicate data analysis, obscuring biological signals with technical artefacts. In this review article, we outline the major challenges in analyzing single-cell cancer genomics data and survey the current computational tools available to tackle these. We further outline unsolved problems that we consider major opportunities for future methods development to help interpret the vast quantities of data being generated., Review article; 10 pages, 1 figure, 2 tables

Background Huntington's disease is a late onset neurological disorder caused by a trinucleotide CAG repeat expansion mutation in the HTT gene encoding for the protein huntingtin. Despite considerable ongoing research, the wild-type function of huntingtin is not yet fully understood. Objective To improve knowledge of HTT gene regulation at the transcriptional level and inform future studies aimed at uncovering the HTT gene's normal function. Methods The HTT gene region was functionally characterized through an in silico analysis using publicly available data sets. ChIP-seq data sets and the online STRING database were used to identify putative transcription factor binding sites (TFBSs) and protein-protein interactions within the HTT promoter region. siRNA-mediated knockdown and ChIP-qPCR of STAT1, a TF identified from the in silico analysis, were used to validate the bioinformatics screen. Results 16 regions containing potential regulatory genomic markers were identified. TFBSs for 59 transcription factors (TFs) were detected in one or more of the 16 candidate regions. Using these TFs, 15 clusters of protein-protein interactions were identified using STRING. siRNA-mediated knockdown of STAT1 resulted in an increase in HTT expression, and ChIP-qPCR detected enrichment of STAT1 binding at one of the predicted regions. These assays confirmed the utility of the bioinformatic analysis. Conclusions Putative regulatory regions outside of the immediate HTT promoter region have been identified with specific protein-protein interactions. Future work will focus on in vitro and in vivo studies to examine the effect of modulating identified TFBSs and altering the levels of specific TFs of interest in regulating HTT gene expression.

We studied the whole-genome point mutation and structural variation patterns of 133 tumors (59 high-grade serous (HGSC), 35 clear cell (CCOC), 29 endometrioid (ENOC), and 10 adult granulosa cell (GCT)) as a substrate for class discovery in ovarian cancer. Ab initio clustering of integrated point mutation and structural variation signatures identified seven subgroups both between and within histotypes. Prevalence of foldback inversions identified a prognostically significant HGSC group associated with inferior survival. This finding was recapitulated in two independent cohorts (n = 576 cases), transcending BRCA1 and BRCA2 mutation and gene expression features of HGSC. CCOC cancers grouped according to APOBEC deamination (26%) and age-related mutational signatures (40%). ENOCs were divided by cases with microsatellite instability (28%), with a distinct mismatch-repair mutation signature. Taken together, our work establishes the potency of the somatic genome, reflective of diverse DNA repair deficiencies, to stratify ovarian cancers into distinct biological strata within the major histotypes.

Lumbar puncture (LP) is a frequently performed diagnostic and therapeutic procedure in oncology patients. Transfusing to a minimum preprocedural platelet threshold of 50 × 10A total of 2259 LPs performed on 1137 oncology patients (adult, n = 871, and pediatric, n = 266) were retrospectively analyzed between February 2011 and December 2017. The incidence of LP-related complications for groups above and below the minimum platelet threshold was compared. Traumatic tap was defined as 500 or more red blood cells per high-power field in the cerebral spinal fluid. Groups were compared using the 2-Proportion Z-test and Fisher exact test.At time of LP, the total number of events with platelets less than 50 × 10Patients with platelet counts less than 50 × 10

Transmembrane protein 30A (TMEM30A) maintains the asymmetric distribution of phosphatidylserine, an integral component of the cell membrane and ‘eat-me’ signal recognized by macrophages. Integrative genomic and transcriptomic analysis of diffuse large B-cell lymphoma (DLBCL) from the British Columbia population-based registry uncovered recurrent biallelic TMEM30A loss-of-function mutations, which were associated with a favorable outcome and uniquely observed in DLBCL. Using TMEM30A-knockout systems, increased accumulation of chemotherapy drugs was observed in TMEM30A-knockout cell lines and TMEM30A-mutated primary cells, explaining the improved treatment outcome. Furthermore, we found increased tumor-associated macrophages and an enhanced effect of anti-CD47 blockade limiting tumor growth in TMEM30A-knockout models. By contrast, we show that TMEM30A loss-of-function increases B-cell signaling following antigen stimulation—a mechanism conferring selective advantage during B-cell lymphoma development. Our data highlight a multifaceted role for TMEM30A in B-cell lymphomagenesis, and characterize intrinsic and extrinsic vulnerabilities of cancer cells that can be therapeutically exploited. Integrative analysis in patients with diffuse large B-cell lymphoma uncovers that biallelic mutations on TMEM30A are associated with a favorable outcome and enhanced sensitivity to CD47 blockade.

Background Monocytes are an essential cellular component of the innate immune system that support the host's effectiveness to combat a range of infectious pathogens. Hemopoietic cell transplantation (HCT) results in transient monocyte depletion, but the factors that regulate recovery of monocyte populations are not fully understood. In this study, we investigated whether the composition of the gastrointestinal microbiota is associated with the recovery of monocyte homeostasis after HCT. Methods We performed a single-center, prospective, pilot study of 18 recipients of either autologous or allogeneic HCT. Serial blood and stool samples were collected from each patient during their HCT hospitalization. Analysis of the gut microbiota was done using 16S rRNA gene sequencing, and flow cytometric analysis was used to characterize the phenotypic composition of monocyte populations. Results Dynamic fluctuations in monocyte reconstitution occurred after HCT, and large differences were observed in monocyte frequency among patients over time. Recovery of absolute monocyte counts and subsets showed significant variability across the heterogeneous transplant types and conditioning intensities; no relationship to the microbiota composition was observed in this small cohort. Conclusion In this pilot study, a relationship between the microbiota composition and monocyte homeostasis could not be firmly established. However, we identify multivariate associations between clinical factors and monocyte reconstitution post-HCT. Our findings encourage further longitudinal surveillance of the intestinal microbiome and its link to immune reconstitution.

BackgroundSingle-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.ResultsWe observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, includingFOSandJUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.ConclusionsThe method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

Hodgkin lymphoma is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of noncancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding cross-talk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 Hodgkin lymphoma tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the Hodgkin lymphoma–specific immune microenvironment at single-cell resolution. Single-cell expression profiling identified a novel Hodgkin lymphoma–associated subset of T cells with prominent expression of the inhibitory receptor LAG3, and functional analyses established this LAG3+ T-cell population as a mediator of immunosuppression. Multiplexed spatial assessment of immune cells in the microenvironment also revealed increased LAG3+ T cells in the direct vicinity of MHC class II–deficient tumor cells. Our findings provide novel insights into TME biology and suggest new approaches to immune-checkpoint targeting in Hodgkin lymphoma. Significance: We provide detailed functional and spatial characteristics of immune cells in classic Hodgkin lymphoma at single-cell resolution. Specifically, we identified a regulatory T-cell–like immunosuppressive subset of LAG3+ T cells contributing to the immune-escape phenotype. Our insights aid in the development of novel biomarkers and combination treatment strategies targeting immune checkpoints. See related commentary by Fisher and Oh, p. 342. This article is highlighted in the In This Issue feature, p. 327

We performed phylogenetic analysis of high-grade serous ovarian cancers (68 samples from seven patients), identifying constituent clones and quantifying their relative abundances at multiple intraperitoneal sites. Through whole-genome and single-nucleus sequencing, we identified evolutionary features including mutation loss, convergence of the structural genome and temporal activation of mutational processes that patterned clonal progression. We then determined the precise clonal mixtures comprising each tumor sample. The majority of sites were clonally pure or composed of clones from a single phylogenetic clade. However, each patient contained at least one site composed of polyphyletic clones. Five patients exhibited monoclonal and unidirectional seeding from the ovary to intraperitoneal sites, and two patients demonstrated polyclonal spread and reseeding. Our findings indicate that at least two distinct modes of intraperitoneal spread operate in clonal dissemination and highlight the distribution of migratory potential over clonal populations comprising high-grade serous ovarian cancers.

Background: With the goal of translating biological discovery into clinical actionability, deciphering crosstalk in the cellular ecosystem of the tumor microenvironment (TME) has emerged as a research focus. Although comparatively little is known about the immune biology of diffuse large B-cell lymphoma (DLBCL), as reflected in clonal selection of specific somatic gene mutations in response to immune system pressure and the specific composition of the TME, PRAME has emerged as a prominent member of the cancer germline antigen/ tumor associated antigen (TAA) family of proteins. It is expressed in various types of cancers, but generally not in normal tissues, apart from male germinal cells, and triggers autologous T-cell mediated immune responses. PRAME is highlighted as a new cancer therapeutic target of T-cell or antibody-based immunotherapies with promising anti-tumor responses in early phase clinical trials and pre-clinical models for several types of cancers. In the context of developing new immunotherapies, targeting TAAs that are presented by major histocompatibility complexes on tumor cells is a promising therapeutic strategy for patients that experience treatment failure. Material and methods: We performed integrative genomic analysis of whole-transcriptome RNAseq, targeted genomic sequencing, and high-resolution copy number analysis in 347 de novo DLBCL tumors from patients uniformly treated with R-CHOP. Findings were correlated with pathological and clinical parameters, as well as TME composition. Using DLBCL-derived cell lines (7 EZH2 mutated and 5 wt) and CRISPR-Cas9 genome editing, we performed in vitro functional studies to characterize cell-intrinsic effects of PRAME knockout. Moreover, we studied EZH2 inhibition in a murine model of Ezh2 mutant lymphoma with a focus on mechanistic links between EZH2 activity and PRAME expression, as well as TME composition (cell-extrinsic effects). Results: We discovered recurrent, and highly focal deletions of 22q11.22 including the PRAME gene, which were associated with poor treatment outcome, independent of pathological and clinical risk factors. To explore PRAME-deletion-associated phenotypes and interaction with the tumor microenvironment (TME), we analyzed corresponding RNAseq, immunohistochemistry (IHC), and flow-cytometry data from our DLBCL cohort and utilized enzyme-linked immunospot (ELISPOT) assays using patient-derived peripheral blood mononuclear cells. PRAME deletions contributed to an immunologically "cold" TME, representing a somatically acquired mechanism to evade anti-tumor T-cell response (cell-extrinsic effect). Using PRAME knock out by CRISPR-Cas9 in vitro, TRAIL-mediated apoptotic signaling was impaired. In addition, PRAME down-modulation was strongly associated with somatic EZH2 Y641 mutations in DLBCL. Using proximity ligation assays and co-IP, we demonstrated that PRAME directly interacted with EZH2 as a negative regulator, establishing a link between PRAME deletions and EZH2 mutations with anti-apoptotic signaling in DLBCL (cell-intrinsic effect). An in vivo murine model of Ezh2 mutant lymphoma showed decreased T-cell infiltration in the TME and Ezh2 inhibition induced PRAME restoration as compared to vehicle controls. IHC for CD3, CD4, FOXP3, and GZMB revealed significant increases in various T-cell populations of the TME, including Tregs and cytotoxic T cells. EZH2 inhibition with EPZ-6438 abrogated these dualistic effects leading to increased immune cell infiltration in the tumor microenvironment and acceleration of apoptosis via PRAME restoration. Moreover, restoration of PRAME antigen presentation by EZH2 inhibition resulted in enhancement of PRAME binding using a T-cell receptor mimic PRAME antibody (Pr20), suggesting immunotherapeutic potential. Conclusion: Our findings highlight multiple functions of PRAME during lymphomagenesis. PRAME restoration by EZH2 inhibition provides a preclinical rationale for synergistic therapies combining epigenetic re-programming with PRAME-targeted therapies. Disclosures Dao: Eureka Therapeutics: Consultancy. Melnick:Jubilant: Consultancy; Epizyme: Consultancy; Constellation: Consultancy; Janssen: Research Funding; Daiichi Sankyo: Research Funding. Scheinberg:Lantheus: Current equity holder in private company; Eureka Therapeutics: Consultancy, Current equity holder in private company, Patents & Royalties: Eureka Therapuetics and MSKCC have filed patent on this ScFV and TCRm; Actinium: Consultancy, Current equity holder in private company; Contrafect: Current equity holder in private company; Sapience: Consultancy, Current equity holder in private company; Iovance: Current equity holder in private company; Enscyse: Current equity holder in private company; Arvenas: Current equity holder in private company; Pfizer: Consultancy, Current equity holder in private company; Sellas: Consultancy, Current equity holder in private company; Oncopep: Consultancy. Scott:Janssen: Consultancy, Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; Celgene: Consultancy; Roche/Genentech: Research Funding. Steidl:Curis Inc: Consultancy; Roche: Consultancy; AbbVie: Consultancy; Seattle Genetics: Consultancy; Bayer: Consultancy; Bristol-Myers Squibb: Research Funding; Juno Therapeutics: Consultancy.

Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

Single-cell RNA sequencing (scRNA-seq) has enabled decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types, performed through unsupervised clustering followed by manual annotation, or via “mapping” procedures to existing data. However, manual interpretation scales poorly to large datasets, mapping approaches require purified or pre-annotated data, and both are prone to batch effects. To overcome these issues we present CellAssign (www.github.com/irrationone/cellassign), a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined or de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while controlling for batch and sample effects. We demonstrate the advantages of CellAssign through extensive simulations and analysis of tumor microenvironment composition in high grade serous ovarian cancer and follicular lymphoma.

SummaryRegulatory programs that control the function of stem cells are active in cancer and confer properties that promote progression and therapy resistance. However, the impact of a stem cell-like tumor phenotype (“sternness”) on the immunological properties of cancer has not been systematically explored. Using gene expression-based metrics, we evaluate the association of stemness with immune cell infiltration and genomic, transcriptomic, and clinical parameters across 21 solid cancers. We find pervasive negative associations between cancer stemness and anticancer immunity. This occurs despite high stemness cancers exhibiting increased mutation load, cancer-testis antigen expression, and intratumoral heterogeneity. Stemness was also strongly associated with cell-intrinsic suppression of endogenous retroviral expression and type I interferon signaling and increased expression of several therapeutically accessible signaling pathways. Thus, stemness is not only a fundamental process in cancer progression but may represent a unifying mechanism linking antigenicity, intratumoral heterogeneity, and immune suppression across cancers.

High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between T cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion.

Student creation of educational materials has the capacity both to enhance learning and to decrease costs. Three successive honors-style classes of undergraduate students in a cancer genetics class worked with a new software system, CuboCube, to create an e-textbook. CuboCube is an open-source learning materials creation system designed to facilitate e-textbook development, with an ultimate goal of improving the social learning experience for students. Equipped with crowdsourcing capabilities, CuboCube provides intuitive tools for nontechnical and technical authors alike to create content together in a structured manner. The process of e-textbook development revealed both strengths and challenges of the approach, which can inform future efforts. Both the CuboCube platform and the Cancer Genetics E-textbook are freely available to the community.

INTRODUCTION: Classic Hodgkin lymphoma (cHL) is uniquely characterized by an extensively dominant microenvironment composed primarily of different types of non-cancerous immune cells with a rare population (~1%) of tumor cells. Detailed characterization of these cellular components and their spatial relationship is crucial to understand crosstalk and therapeutic targeting in the cellular ecosystem of the tumor microenvironment (TME). METHODS: In this study, we performed high dimensional and spatial profiling of immune cells in the TME of cHL. Single cell RNA sequencing (scRNA-seq) was performed with the 10x Genomics platform on cell suspensions collected from lymph nodes of 22 cHL patients, including 12 of nodular sclerosis subtype, 9 of mixed cellularity subtype and 1 of lymphocyte-rich subtype, with 5 reactive lymph nodes (RLNs) serving as normal controls. Illumina sequencing (HiSeq 2500) was performed to yield single-cell expression profiles for 127,786 cells. We also performed multicolor IHC and imaging mass cytometry (IMC) on TMA slides from the same patients. RESULTS: Unsupervised clustering using PhenoGraph identified 22 cell clusters including 12 T cell clusters, 7 B cell clusters and 1 macrophage cluster. While most immune cell populations were common between cHL and RLN, we observed an enrichment of cells from cHL in all 3 regulatory T cell (Treg) clusters. The most cHL-enriched cluster was characterized by high expression of LAG3, in addition to common Treg markers such as IL2RA (CD25) and TNFRSF18 (GITR), but lacked expression of FOXP3, consistent with a type 1 regulatory (Tr1) T cell population. LAG3+ T cells in cHL had high expression of immune-suppressive cytokines IL-10 and TGF-b . In vitro exposure of T cells to cHL cell line supernatant induced significantly higher levels of LAG3 in naïve T cells compared to co-culture with other lymphoma cell line supernatant or medium only. CD4+ LAG3+ T cells isolated by FACS also suppressed the proliferation of responder CD4+ T cells when co-cultured in vitro. Additionally, Luminex analysis revealed that cHL cell lines secrete substantial amounts of cytokines and chemokines that can promote Tr1 cell differentiation (e.g. IL-6). Our scRNA-seq analysis revealed that LAG3 expression was significantly higher in cHL cases with loss of major histocompatibility class II (MHC-II) expression on HRS cells as compared to MHC-II positive cases (P = 0.019), but was not correlated with EBV status or histological subtype. Strikingly, LAG3 was identified as the most up-regulated gene in cells from MHC-II negative cases compared to MHC-II positive cases. Topological analysis using multicolor IHC and IMC revealed that in MHC-II negative cases, HRS cells were surrounded by LAG3+ T cells. In these cases, the density of LAG3+ T cells in HRS cell-rich regions was significantly increased, and the average distance between an HRS cell and its closest LAG3+ T cell neighbor was significantly shorter. These associations were confirmed in an independent cohort of 166 cHL patients. Finally, we observed a trend towards an inferior disease-specific survival (DSS; P = 0.072) and overall survival (OS; P = 0.12) in cases with an increased number of LAG3+ T cells. A high proportion of LAG3+ T cells (> 20%) was identified as an independent prognostic factor for DSS by multivariate Cox regression. CONCLUSIONS: Our results reveal a diverse TME composition with inflammatory and immunosuppressive cellular components that are linked to MHC class II expression status on HRS cells (Figure). Unprecedented transcriptional and spatial profiling at the single cell level has established the pathogenic importance of HRS cell-induced CD4+ LAG3+ T cells as a mediator of immunosuppression in cHL, with potential implications for novel therapeutic approaches. Figure Disclosures Savage: Seattle Genetics, Inc.: Consultancy, Honoraria, Research Funding; BMS, Merck, Novartis, Verastem, Abbvie, Servier, and Seattle Genetics: Consultancy, Honoraria. Scott:Roche/Genentech: Research Funding; Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding. Steidl:Bristol-Myers Squibb: Research Funding; Nanostring: Patents & Royalties: Filed patent on behalf of BC Cancer; Roche: Consultancy; Seattle Genetics: Consultancy; Bayer: Consultancy; Juno Therapeutics: Consultancy; Tioma: Research Funding.

Single cell RNA sequencing (scRNAseq) is a powerful tool, particularly for studying complex biological systems, such as tumor heterogeneity and the tumor microenvironment, which may not be resolved by sequencing of bulk material. Nonetheless, it is not without limitations, which include the technical challenges of generating a high quality single cell suspension. Dissociation of tissue to single cell suspension requires mechanical and enzymatic disruption, and the effect of these methods on gene expression or cellular population bias has not been established. In this study, we examined the effects of enzymatic dissociation on cell population capture and transcriptional changes at single cell resolution in breast and ovarian cancer patient samples, patient-derived breast cancer xenografts and cultured cell lines. scRNAseq data showed that enzymatic dissociation of tissues at 37oC with collagenase resulted in significant induction of heat shock, stress and immediate response genes, which was conserved across all tissues. This gene expression induction was not observed when tissues were dissociated at 6oC with a protease derived from a Himalayan glacier soil bacterium. Moreover, dissociation of patient tumors at low temperature enhanced the abundance of rare cell populations, including B-cells, T-Cells and cytotoxic T-cells, which were significantly depleted following dissociation at 37oC. These biases resulting from standard sample preparation methods could significantly affect biological interpretation of scRNAseq data, and can be minimized by dissociation of tissues at low temperature. Note: This abstract was not presented at the meeting. Citation Format: Ciara H. O'Flanagan, Kieran R. Campbell, Farhia Kabeer, Allen Zhang, Jamie Lim, Sohrab P. Shah, Samuel Aparicio. Temperature-dependent transcription artifacts and cell population biases in scRNAseq data are minimized by tissue dissociation at low temperatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4706.

This article extends the methodology in Sack and Elsasser [2004] and Roush [2007] to define and measure the performance of the Treasury inflation-protected securities (TIPS) program in terms of the relative cost over issuing equivalent nominal securities. The relative cost is driven by the change of the breakeven inflation and, in particular, that of the liquidity-adjusted inflation risk premium when the inflation expectation is stable. We use all 96 TIPS issuances since the inception of the program (January 1997) to June 2012 to calculate a 185-month time series of relative costs at CUSIP and aggregate levels. As of June 2012, we find that the TIPS program has accumulated a relative saving of $7.06 billion. If past is prologue, we would expect relative savings from the TIPS program to continue.