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Supplementary Table S1. In vivo limiting dilution analyses of P-LSCC and K/P-LSCC. Supplementary Table S3. Likely zygosity and functional effects of KEAP1 mutations in NSCLC patients in Fig. 7A. Supplementary Table S4. Clinical characteristics of a validation cohort of stage I-III NSCLC patients treated with curative intent RT and analyzed for KEAP1/NRF2 mutation status using targeted next generation sequencing. Antibodies used in this study.

Supplementary Figure S1. Loss of Keap1 or Trp53 promotes airway basal stem cell self-renewal. Supplementary Figure S2. Lineage tracing method for airway basal stem cells. Supplementary Figure S3. Characterization of LSCCs derived from Keap1-/-;Trp53-/- or Trp53-/- tracheal cells. Supplementary Figure S4. Airway basal stem cells are the cell of origin for Trp53-/- and Keap1-/-;Trp53-/- LSCCs. Supplementary Figure S5. Gene expression analysis of P-LSCC and K/P-LSCC tumors. Supplementary Figure S6. Loss of Keap1 in LSCCs leads to protection from oxidative stress. Supplementary Figure S7. Loss of Keap1 in LSCCs leads to protection from ionizing irradiation. Supplementary Figure S8. Inhibition of xCT sensitizes radioresistant K/P-LSCCs. Supplementary Figure S9. TP53 mutation status is not associated with local failure after radiotherapy in human NSCLC patients.

Supplemental methods

Supplemental Tables S1-S12

Figures S1-S10

Purpose: The clinical utility of circulating tumor DNA (ctDNA) monitoring has been shown in tumors that harbor highly recurrent mutations. Leiomyosarcoma represents a type of tumor with a wide spectrum of heterogeneous genomic abnormalities; thus, targeting hotspot mutations or a narrow genomic region for ctDNA detection may not be practical. Here, we demonstrate a combinatorial approach that integrates different sequencing protocols for the orthogonal detection of single-nucleotide variants (SNV), small indels, and copy-number alterations (CNA) in ctDNA.Experimental Design: We employed Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for the analysis of SNVs and indels, together with a genome-wide interrogation of CNAs by Genome Representation Profiling (GRP). We profiled 28 longitudinal plasma samples and 25 tumor specimens from 7 patients with leiomyosarcoma.Results: We detected ctDNA in 6 of 7 of these patients with >98% specificity for mutant allele fractions down to a level of 0.01%. We show that results from CAPP-Seq and GRP are highly concordant, and the combination of these methods allows for more comprehensive monitoring of ctDNA by profiling a wide spectrum of tumor-specific markers. By analyzing multiple tumor specimens in individual patients obtained from different sites and at different times during treatment, we observed clonal evolution of these tumors that was reflected by ctDNA profiles.Conclusions: Our strategy allows for the comprehensive monitoring of a broad spectrum of tumor-specific markers in plasma. Our approach may be clinically useful not only in leiomyosarcoma but also in other tumor types that lack recurrent genomic alterations. Clin Cancer Res; 24(11); 2688–99. ©2018 AACR.

Figure S1 Summary of CAPP-Seq and GRP findings in plasma specimens of 7 LMS patients. Figure S2 Specificity and sensitivity of ctDNA detection by CAPP-Seq in LMS patients. Figure S3 Individual DNA copy number alteration profiles of 22 tumor specimens from 7 LMS patients. CN - copy number Figure S4 UCSC Genome Browser view of genomic region 11q24.3-q25 that was consistently lost across all tumor specimens in patients LMS2, LMS3, LMS4, LMS5 and LMS7. Figure S5 Correlation between ctDNA levels detected by CAPP-Seq (represented as VAF) and GRP (represented as percent of genome altered by copy number alterations). Table S1 Summary of clinical features of 9 LMS patients Table S2 LMS-specific CAPP-Seq selector. Table S3 Tumor specimens used for CAPP-Seq and SNP array analysis. Table S4 Depth of sequencing and % of on-target reads by CAPP-Seq. Table S5 Summary statistics for GRP. Table S6 Input of cfDNA used for CAPP-Seq and GRP. Table S7 Summary of quality control metrics from OncoScan FFPE Assay and the extent of CNAs in 22 LMS tumor specimens.

Purpose:High-grade gliomas (HGGs) are central nervous system tumors with poor prognoses and limited treatment options. Vocimagene amiretrorepvec (Toca 511) is a retroviral replicating vector encoding cytosine deaminase, which converts extended release 5-fluorocytosine (Toca FC) into the anticancer agent, 5-fluorouracil. According to preclinical studies, this therapy kills cancer cells and immunosuppressive myeloid cells in the tumor microenvironment, leading to T-cell–mediated antitumor immune activity. Therefore, we sought to elucidate this immune-related mechanism of action in humans, and to investigate potential molecular and immunologic indicators of clinical benefit from therapy.Patients and Methods:In a phase I clinical trial (NCT01470794), patients with recurrent HGG treated with Toca 511 and Toca FC showed improved survival relative to historical controls, and some had durable complete responses to therapy. As a part of this trial, we performed whole-exome DNA sequencing, RNA-sequencing, and multiplex digital ELISA measurements on tumor and blood samples.Results:Genetic analyses suggest mutations, copy-number variations, and neoantigens are linked to survival. Quantities of tumor immune infiltrates estimated by transcript abundance may potentially predict clinical outcomes. Peak values of cytokines in peripheral blood samples collected during and after therapy could indicate response.Conclusions:These results support an immune-related mechanism of action for Toca 511 and Toca FC, and suggest that molecular and immunologic signatures are related to clinical benefit from treatment.

Supplementary Figures S1 to S9 and Supplementary Table S1.

Recent studies have emphasized the importance of single-cell spatial biology, yet available assays for spatial transcriptomics have limited gene recovery or low spatial resolution. Here we introduce CytoSPACE, an optimization method for mapping individual cells from a single-cell RNA sequencing atlas to spatial expression profiles. Across diverse platforms and tissue types, we show that CytoSPACE outperforms previous methods with respect to noise tolerance and accuracy, enabling tissue cartography at single-cell resolution.

Background: Although combination immunotherapies incorporating local and systemic components have shown promising results in treating solid tumors, varied tumor microenvironments (TMEs) can impact immunotherapeutic efficacy. Method: We designed and evaluated treatment strategies for breast and pancreatic cancer combining magnetic resonance-guided focused ultrasound (MRgFUS) ablation and antibody therapies. With a combination of single-cell sequencing, spectral flow cytometry, and histological analyses, we profiled an immune-suppressed KPC (Kras+/LSL-G12D; Trp53+/LSL-R172H; Pdx1-Cre) pancreatic adenocarcinoma (MT4) model and a dense epithelial neu deletion (NDL) HER2+ mammary adenocarcinoma model with a greater fraction of lymphocytes, natural killer cells and activated dendritic cells. We then performed gene ontology analysis, spectral and digital cytometry to assess the immune response to combination immunotherapies and correlation with survival studies. Result: Based on gene ontology analysis, adding ablation to immunotherapy enriched immune cell migration pathways in the pancreatic cancer model and extensively enriched wound healing pathways in the breast cancer model. With CIBERSORTx digital cytometry, aCD40 + aPD-1 immunotherapy combinations enhanced dendritic cell activation in both models. In the MT4 TME, adding the combination of aCD40 antibody and checkpoint inhibitors (aPD-1 and aCTLA-4) with ablation was synergistic, increasing activated natural killer cells and T cells in distant tumors. Furthermore, ablation with immunotherapy upregulated critical Ly6c myeloid remodeling phenotypes that enhance T-cell effector function and increased granzyme and protease encoding genes by as much as 100-fold. Ablation combined with immunotherapy then extended survival in the MT4 model to a greater extent than immunotherapy alone. Conclusion: In summary, TME profiling informed a successful multicomponent treatment protocol incorporating ablation and facilitated differentiation of TMEs in which ablation is most effective.

In cancer, complex ecosystems of interacting cell types play fundamental roles in tumor development, progression, and response to therapy. However, the cellular organization, community structure, and spatially defined microenvironments of human tumors remain poorly understood. With the emergence of new technologies for high-throughput spatial profiling of complex tissue specimens, it is now possible to identify clinically significant spatial features with high granularity. In this PSB workshop, we will highlight recent advances in this area and explore how single cell spatial profiling can advance precision cancer medicine.

Metastasis is responsible for most breast cancer–related deaths; however, identifying the cellular determinants of metastasis has remained challenging. Here, we identified a minority population of immatureTHY1+/VEGFA+tumor epithelial cells in human breast tumor biopsies that display angiogenic features and are marked by the expression of the oncogene,LMO2. Higher abundance ofLMO2+basal cells correlated with tumor endothelial content and predicted poor distant recurrence–free survival in patients. UsingMMTV-PyMT/Lmo2CreERT2mice, we demonstrated thatLmo2lineage–traced cells integrate into the vasculature and have a higher propensity to metastasize. LMO2 knockdown in human breast tumors reduced lung metastasis by impairing intravasation, leading to a reduced frequency of circulating tumor cells. Mechanistically, we find that LMO2 binds to STAT3 and is required for STAT3 activation by tumor necrosis factor–α and interleukin-6. Collectively, our study identifies a population of metastasis-initiating cells with angiogenic features and establishes the LMO2-STAT3 signaling axis as a therapeutic target in breast cancer metastasis.

SummaryMacrophages are the most abundant immune cell type in the tumor microenvironment (TME). Yet the spatial distribution and cell interactions that shape macrophage function are incompletely understood. Here we use single-cell RNA sequencing data and multiplex imaging to discriminate and spatially resolve macrophage niches within benign and malignant breast and colon tissue. We discover four distinct tissue-resident macrophage (TRM) layers within benign bowel, two TRM niches within benign breast, and three tumor-associated macrophage (TAM) populations within breast and colon cancer. We demonstrate that IL4I1 marks phagocytosing macrophages, SPP1 TAMs are enriched in hypoxic and necrotic tumor regions, and a novel subset of FOLR2 TRMs localizes within the plasma cell niche. Furthermore, NLRP3 TAMs that colocalize with neutrophils activate an inflammasome in the TME and in Crohn’s disease and are associated with poor outcomes in breast cancer patients. This work suggests novel macrophage therapy targets and provides a framework to study human macrophage function in clinical samples.

Introduction: Severe immune-related adverse events (irAEs) occur in up to 60% of melanoma patients treated with immune checkpoint inhibitors (ICIs), causing substantial treatment-related morbidity and in the most severe cases, death. There is no clinical assay to predict who will develop severe ICI-induced irAEs and who will not. Using single-cell profiling assays applied to a retrospective melanoma cohort treated with ICIs, we recently showed that higher baseline levels of circulating CD4 effector memory T (TEM) cells were associated with severe irAE development, independent of the affected organ system (Lozano et al. Nature Medicine, 2022). As part of a prospective validation study of 100 melanoma patients, here we report our initial findings on the first 24 patients accrued to date. Methods: We prospectively collected pre-ICI blood from 24 metastatic melanoma patients from two academic medical centers from February 2021 onward. Peripheral blood was collected pre-treatment on the day of immunotherapy (cycle 1 day 1). We then isolated peripheral blood mononuclear cells (PBMCs) and applied mass cytometry by time of flight (CyTOF) to profile 38 leukocyte markers including markers specific to CD4 TEM cells. Cellular subpopulations were quantified using Cytobank v9. Patients underwent routine medical oncology follow-up during and after ICI treatment including grading of irAEs using the Common Terminology Criteria for Adverse Events v5. Results: Median follow-up time after pre-ICI blood collection was 9.1 months (range 2.6-18.5). Fifteen (63%) patients received combination (anti-PD1/anti-CTLA4) ICIs while the remainder received anti-PD1 monotherapy. Eight patients developed severe (grade 3+) irAEs at a median of 8.5 weeks (range 4-21) after treatment initiation, including 4 who developed life-threatening (grade 4) irAEs. Severe and life-threatening irAE development spanned 9 separate organ systems, most commonly gastrointestinal, dermatological, and hepatic. Using CyTOF, we found that circulating CD4 TEM cells were more abundant in patients who developed severe irAEs compared to those who did not (P = 0.01; AUC = 0.81), irrespective of the involved organ systems. Moreover, median-splitting the patient cohort into two groups based on pretreatment CD4 TEM levels revealed that patients with low CD4 TEMs had significantly longer freedom from severe irAE than those with high CD4 TEMs (not reached vs. 4.6 months; P = 0.013; HR = 6.7). There was no significant difference in pretreatment CD4 TEM levels between patients with and without durable clinical benefit to ICIs (P = 0.75). Conclusion: Circulating CD4 TEM levels measured by CyTOF were associated with severe irAE development, independent of response status, in patients with advanced melanoma. These findings could form the basis for pretreatment ICI risk stratification in the future. Citation Format: Abul Usmani, Noah Earland, Wubing Zhang, Peter K. Harris, Antonietta Bacchiocchi, Aishwarya Nene, David Y. Chen, Mario Sznol, Ruth Halaban, Aaron M. Newman, Aadel A. Chaudhuri. Association between circulating CD4 memory T cell levels and severe immune-related adverse events in melanoma patients treated with immune checkpoint blockade [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6670.

The tumor microenvironment contributes to tumorigenesis, disease progression, and response to therapy in soft tissue sarcomas (STSs). However, characterizing the malignant and stromal cells that make up STSs and correlating their abundance with clinical outcomes has proven difficult in fixed clinical specimens. We employed a machine learning framework called EcoTyper (Luca et al. Cell 2021) to identify cell type-specific transcriptional states and define tumor ecotypes consisting of co-occurring cell states from bulk transcriptomes. Analyzing 292 previously published STSs profiled by bulk RNA-sequencing (RNA-Seq), we identified 23 transcriptionally-defined sarcoma cell states in malignant, immune, and other stromal cells and validated the majority of these cell states using single cell RNA-Seq. Although sarcomas originate from mesenchymal tissues, we identified four epithelial-like sarcoma cell states and observed epithelial differentiation and expression of epithelial markers within malignant sarcoma cells across histologies. Cell states reflected known and novel cell phenotypes and many were strongly associated with patient outcomes in our RNA-Seq training cohort and an independent validation cohort of STSs profiled by microarray (n=309). By identifying co-occurring cell states across STSs, we discovered 3 sarcoma ecotypes associated with underlying genomic alterations and distinct clinical outcomes. On spatial transcriptomic analysis, we observed co-localization of cell states within the same sarcoma ecotypes and spatial aggregation of ecotypes within STSs, suggesting that sarcoma ecotypes represent distinct functional units within human sarcomas. One ecotype (sarcoma ecotype 3: SE3) defined by CLEC5A/SPP1+ M2-like immunosuppressive macrophages and MYC/MTORC1-activated epithelial-like malignant cells was associated with inferior progression-free survival (PFS) in the RNA-Seq training cohort (P=0.01) and inferior metastasis-free survival in the microarray validation cohort (P=0.002). Remarkably, SE3 was associated with improved PFS in patients with metastatic STSs treated with ipilimumab and nivolumab (n=38, P=0.003) but not patients treated with chemotherapy. Furthermore, SE3 outperformed previously reported predictors of immunotherapy response in STSs, PD-L1 expression and tertiary lymphoid structures (TLS), for predicting response to immunotherapy (AUCs: SE3 0.87; PD-L1 0.81; TLS 0.62). Finally, SE3 similarly predicted response to immunotherapy in an independent validation cohort (n=29, AUC 0.89). In summary, our findings provide a high-resolution cell atlas of STSs to guide the development of novel therapeutic strategies. In addition, we have identified a predictive biomarker of response to immune checkpoint inhibition that may enable personalization of systemic therapy in patients with advanced STSs. Citation Format: Ajay Subramanian, Neda Nemat-Gorgani, Timothy J. Ellis-Caleo, David G.P. van IJzendoorn, Timothy J. Sears, Anish Somani, Bogdan A. Luca, Maggie Y. Zhou, Martina Bradic, Ileana A. Torres, Eniola Oladipo, Christin New, Deborah E. Kenney, Raffi S. Avedian, Robert J. Steffner, Michael S. Binkley, David G. Mohler, William D. Tap, Sandra P. D’Angelo, Matt van de Rijn, Kristen N. Ganjoo, Nam Q. Bui, Gregory W. Charville, Aaron M. Newman, Everett J. Moding. Identification and validation of sarcoma cellular ecosystems associated with prognosis and predictive of immunotherapy response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5960.

Purpose: High-grade gliomas (HGGs) are central nervous system tumors with poor prognoses and limited treatment options. Vocimagene amiretrorepvec (Toca 511) is a retroviral replicating vector encoding cytosine deaminase, which converts extended release 5-fluorocytosine (Toca FC) into the anticancer agent, 5-fluorouracil. According to preclinical studies, this therapy kills cancer cells and immunosuppressive myeloid cells in the tumor microenvironment, leading to T-cell–mediated antitumor immune activity. Therefore, we sought to elucidate this immune-related mechanism of action in humans, and to investigate potential molecular and immunologic indicators of clinical benefit from therapy. Patients and Methods: In a phase I clinical trial (NCT01470794), patients with recurrent HGG treated with Toca 511 and Toca FC showed improved survival relative to historical controls, and some had durable complete responses to therapy. As a part of this trial, we performed whole-exome DNA sequencing, RNA-sequencing, and multiplex digital ELISA measurements on tumor and blood samples. Results: Genetic analyses suggest mutations, copy-number variations, and neoantigens are linked to survival. Quantities of tumor immune infiltrates estimated by transcript abundance may potentially predict clinical outcomes. Peak values of cytokines in peripheral blood samples collected during and after therapy could indicate response. Conclusions: These results support an immune-related mechanism of action for Toca 511 and Toca FC, and suggest that molecular and immunologic signatures are related to clinical benefit from treatment.

Recent studies have emphasized the importance of single-cell spatial biology, yet available assays for spatial transcriptomics have limited gene recovery or low spatial resolution. Here we introduce CytoSPACE, a method for aligning single-cell and spatial transcriptomes via convex linear optimization. Across diverse platforms and tissue types, we show that CytoSPACE outperforms previous methods with respect to noise-tolerance, accuracy, and efficiency, enabling improved analysis of spatial transcriptomics data at single-cell resolution.

Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

Severe immune-related adverse events (irAEs) occur in up to 60% of patients with melanoma treated with immune checkpoint inhibitors (ICIs). However, it is unknown whether a common baseline immunological state precedes irAE development. Here we applied mass cytometry by time of flight, single-cell RNA sequencing, single-cell V(D)J sequencing, bulk RNA sequencing and bulk T cell receptor (TCR) sequencing to study peripheral blood samples from patients with melanoma treated with anti-PD-1 monotherapy or anti-PD-1 and anti-CTLA-4 combination ICIs. By analyzing 93 pre- and early on-ICI blood samples and 3 patient cohorts (n = 27, 26 and 18), we found that 2 pretreatment factors in circulation-activated CD4 memory T cell abundance and TCR diversity-are associated with severe irAE development regardless of organ system involvement. We also explored on-treatment changes in TCR clonality among patients receiving combination therapy and linked our findings to the severity and timing of irAE onset. These results demonstrate circulating T cell characteristics associated with ICI-induced toxicity, with implications for improved diagnostics and clinical management.

Significance In the skin, tissue injury results in fibrosis in the form of a scar composed of dense extracellular matrix deposited by fibroblasts. Therapies that promote tissue regeneration rather than fibrosis remain elusive because principles of fibroblast programming and response to injury remain incompletely understood. Here, we present a multimodal -omics platform for the study of cell populations in complex tissue, which has allowed us to characterize wound healing fibroblasts across both time and space. We identify functionally distinct fibroblast subpopulations and track cell fate during the response to wounding. We demonstrate that populations of fibroblasts migrate, proliferate, and differentiate in an adaptive response to disruption of their environment. These results illustrate fundamental principles underlying the cellular response to tissue injury., In the skin, tissue injury results in fibrosis in the form of scars composed of dense extracellular matrix deposited by fibroblasts. The therapeutic goal of regenerative wound healing has remained elusive, in part because principles of fibroblast programming and adaptive response to injury remain incompletely understood. Here, we present a multimodal -omics platform for the comprehensive study of cell populations in complex tissue, which has allowed us to characterize the cells involved in wound healing across both time and space. We employ a stented wound model that recapitulates human tissue repair kinetics and multiple Rainbow transgenic lines to precisely track fibroblast fate during the physiologic response to skin injury. Through integrated analysis of single cell chromatin landscapes and gene expression states, coupled with spatial transcriptomic profiling, we are able to impute fibroblast epigenomes with temporospatial resolution. This has allowed us to reveal potential mechanisms controlling fibroblast fate during migration, proliferation, and differentiation following skin injury, and thereby reexamine the canonical phases of wound healing. These findings have broad implications for the study of tissue repair in complex organ systems.

Acral melanoma, the most common melanoma subtype among non-Caucasian individuals, is associated with poor prognosis. However, its key molecular drivers remain obscure. Here, we performed integrative genomic and clinical profiling of acral melanomas from a cohort of 104 patients treated in North America or China. We found that recurrent, late-arising amplifications of cytoband chr22q11.21 are a leading determinant of inferior survival, strongly associated with metastasis, and linked to downregulation of immunomodulatory genes associated with response to immune checkpoint blockade. Unexpectedly, LZTR1 – a known tumor suppressor in other cancers – is a key candidate oncogene in this cytoband. Silencing of LZTR1 in melanoma cell lines caused apoptotic cell death independent of major hotspot mutations or melanoma subtypes. Conversely, overexpression of LZTR1 in normal human melanocytes initiated processes associated with metastasis, including anchorage-independent growth, formation of spheroids, and increased levels of MAPK and SRC activities. Our results provide new insights into the etiology of acral melanoma and implicate LZTR1 as a key tumor promoter and therapeutic target

Identifying the cells from which cancers arise, and the paths they take towards malignancy, is critical for understanding the molecular basis of tumor initiation and progression. To understand if stem and progenitor cells can serve as cells of origin for cancer, we created a model in which the CreERT2 recombinase was knocked into the endogenous locus of the stem cell determinant Msi2. When crossed to a conditional CAG-LSL-MycT58A model, Msi2-CreERT2 mice developed a diversity of tumors across tissues, including multiple pancreatic cancer subtypes: pancreatic ductal adenocarcinoma (PDAC), adenosquamous carcinoma of the pancreas (ASCP), acinar cell carcinoma (ACC), and rare anaplastic tumors. Using single cell analysis, we traced the temporal changes that occurred as normal Msi2+ cells evolved through a pre-cancerous stage to PDAC, ASCP or ACC. These results revealed that Msi2+ cells were present predominantly in pancreatic ducts and exhibited heterogeneous differentiation states in the normal pancreas. At initiation, Myc triggered oncogenic transformation in the most undifferentiated subset leading to the rise of pre-cancer cells with multi-lineage properties. Subsequently, these pre-cancer cells were driven along different fates by epigenetically activated transcriptional programs with genomic changes amplifying the progression into distinct pancreatic cancer subtypes. Finally, integrating transcriptomic and functional genomic approaches in this new model allowed us to define Ifne, Ifitm3, Atf3, Hmmr, and Raet1e as novel functional dependencies of ASCP, giving us unique insight into the most lethal of pancreatic malignancies. These data show that multiple pancreatic cancer subtypes can arise from a common pool of pre-malignant cells and provide a powerful molecular framework to understand the programs that shape divergent fates in pancreas cancer and develop approaches for early detection and interception.

Natural killer (NK) cells comprise one subset of the innate lymphoid cell (ILC) family. Despite reported antitumor functions of NK cells, their tangible contribution to tumor control in humans remains controversial. This is due to incomplete understanding of the NK cell states within the tumor microenvironment (TME). Here, we demonstrate that peripheral circulating NK cells differentiate down two divergent pathways within the TME, resulting in different end states. One resembles intraepithelial ILC1s (ieILC1) and possesses potent in vivo antitumor activity. The other expresses genes associated with immune hyporesponsiveness and has poor antitumor functional capacity. Interleukin-15 (IL-15) and direct contact between the tumor cells and NK cells are required for the differentiation into CD49a(+)CD103(+) cells, resembling ieILC1s. These data explain the similarity between ieILC1s and tissue-resident NK cells, provide insight into the origin of ieILC1s, and identify the ieILC1-like cell state within the TME to be the NK cell phenotype with the greatest antitumor activity. Because the proportions of the different ILC states vary between tumors, these findings provide a resource for the clinical study of innate immune responses against tumors and the design of novel therapy.

Recent advances in high‐throughput molecular profiling technologies and multiplexed imaging platforms have revolutionized our ability to characterize the tumor immune microenvironment. As a result, studies of tumor‐associated immune cells increasingly involve complex data sets that require sophisticated methods of computational analysis. In this review, we present an overview of key assays and related bioinformatics tools for analyzing the tumor‐associated immune system in bulk tissues and at the single‐cell level. In parallel, we describe how data science strategies and novel technologies have advanced tumor immunology and opened the door for new opportunities to exploit host immunity to improve cancer clinical outcomes.

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells. CIBERSORTx, a suite of computational tools, enables inference of cell type abundance and cell-type-specific gene expression profiles from bulk RNA profiles.

Background: Emerging data suggest that some patients with TNBC could benefit from the addition of immune-based therapy. This observation is in part due to the significant association between distinct tumor-infiltrating lymphocytes (TILs) and prognosis in TNBC. Efforts to comprehensively characterize the immune microenvironment of TNBCs are critically important to gain a better understanding of the immune landscape and how it influences response to both standard chemotherapy and immunotherapy. We previously assessed both stromal TILs (sTILs) and intraepithelial TILs (iTILs) from pre-treatment tumor samples from patients enrolled on a phase II study of neoadjuvant gemcitabine, carboplatin and iniparib (PrECOG 0105; NCT00813956). We found that both iTILS and sTILS significantly associated with pathologic response. Furthermore, we assessed a novel 'in silico flow cytometry' gene expression-based method, CIBERSORT, designed to assess overall immune content and deconvolute the relative levels of distinct leukocyte subsets in tumors. Specific leukocyte subsets significantly associated with pCR included activated memory CD4+ T cells, CD8+ T cells and M1 macrophages (all p Methods: We performed SPARTA - Spatial Perception And Regional Tumor Analysis - a multiplexed immunohistochemistry-based technology with data visualization and analysis modules that is designed to capture clinically relevant information about the tumor microenvironment in 72 pre-treatment FFPE tumor sections from patients enrolled on PrECOG 0105. SPARTA was used to test and analyze the coordinated expression of PD-L1, PD-1, CD45RO, CD4, CD8 and HLA-DRA in the study cohort from whole slide scanned images. Pathologic response at the time of surgery was evaluated using the residual cancer burden index. Germline BRCA1 and BRCA2 status was known for all patients. Results: Of 72 samples, 67 were evaluable for SPARTA analysis. Within a subset of tumors separately profiled by both SPARTA (FFPE/IHC microscopy) and CIBERSORT (Frozen/RNA GEP), we found significant correlation for clinically relevant TIL subpopulations, including for CD8+ T cells (r=0.83, p Conclusions: Spatial mapping of the immune microenvironment in primary TNBC reveals distinct immune cell populations associated with response to neoadjuvant platinum-based therapy. Citation Format: Telli ML, Vinayak S, Khododoust MS, Gruber JJ, Ford JM, Sanchez P, Banayan N, Azimi S, Tumeh PC, Newman AM, Alizadeh AA. Spatial mapping of the immune microenvironment in primary triple-negative breast cancer (TNBC) and association with neoadjuvant therapy response [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD5-12.

Prolonged exposure of CD8+ T cells to antigenic stimulation, as in chronic viral infections, leads to a state of diminished function termed exhaustion. We now demonstrate that even during exhaustion there is a subset of functional CD8+ T cells defined by surface expression of SIRPα, a protein not previously reported on lymphocytes. On SIRPα+ CD8+ T cells, expression of co-inhibitory receptors is counterbalanced by expression of co-stimulatory receptors and it is only SIRPα+ cells that actively proliferate, transcribe IFNγ and show cytolytic activity. Furthermore, target cells that express the ligand for SIRPα, CD47, are more susceptible to CD8+ T cell-killing in vivo. SIRPα+ CD8+ T cells are evident in mice infected with Friend retrovirus, LCMV Clone 13, and in patients with chronic HCV infections. Furthermore, therapeutic blockade of PD-L1 to reinvigorate CD8+ T cells during chronic infection expands the cytotoxic subset of SIRPα+ CD8+ T cells.

Haematopoiesis is an essential process that evolved in multicellular animals. At the heart of this process are haematopoietic stem cells (HSCs), which are multipotent and self-renewing, and generate the entire repertoire of blood and immune cells throughout an animal's life1. Although there have been comprehensive studies on self-renewal, differentiation, physiological regulation and niche occupation in vertebrate HSCs, relatively little is known about the evolutionary origin and niches of these cells. Here we describe the haematopoietic system of Botryllus schlosseri, a colonial tunicate that has a vasculature and circulating blood cells, and interesting stem-cell biology and immunity characteristics2-8. Self-recognition between genetically compatible B. schlosseri colonies leads to the formation of natural parabionts with shared circulation, whereas incompatible colonies reject each other3,4,7. Using flow cytometry, whole-transcriptome sequencing of defined cell populations and diverse functional assays, we identify HSCs, progenitors, immune effector cells and an HSC niche, and demonstrate that self-recognition inhibits allospecific cytotoxic reactions. Our results show that HSC and myeloid lineage immune cells emerged in a common ancestor of tunicates and vertebrates, and also suggest that haematopoietic bone marrow and the B. schlosseri endostyle niche evolved from a common origin.

SUMMARYMetastasis is responsible for the majority of breast cancer-related deaths, however identifying the cellular determinants of metastasis has remained challenging. Here, we identified a minority population of immature THY1+/VEGFA+ tumor epithelial cells in human breast tumor biopsies that display angiogenic features and are marked by the expression of the oncogene, LMO2. Higher abundance of LMO2+ basal cells correlated with tumor endothelial content and predicted poor distant recurrence-free survival in patients. Using MMTV-PyMT/Lmo2CreERT2 mice, we demonstrated that Lmo2 lineage- traced cells have a higher propensity to metastasize. LMO2 knockdown in human breast tumors reduced lung metastasis by impairing intravasation, leading to a reduced frequency of circulating tumor cells. Mechanistically, we find that LMO2 binds to STAT3 and is required for STAT3 activation by TNFα and IL6. Collectively, our study identifies a population of metastasis-initiating cells with angiogenic features and establishes the LMO2-STAT3 signaling axis as a therapeutic target in breast cancer metastasis.One sentence summaryLMO2 modulates STAT3 signaling in breast cancer metastasis.

Acral melanoma, the most common melanoma subtype among non-Caucasian individuals, is associated with poor prognosis. However, its key molecular drivers remain obscure. Here, we performed integrative genomic and clinical profiling of acral melanomas from a cohort of 104 patients treated in North America or China. We found that recurrent, late-arising amplifications of cytoband chr22q11.21 are a leading determinant of inferior survival, strongly associated with metastasis, and linked to downregulation of immunomodulatory genes associated with response to immune checkpoint blockade. Unexpectedly, LZTR1 – a known tumor suppressor in other cancers – is a key candidate oncogene in this cytoband. Silencing of LZTR1 in melanoma cell lines caused apoptotic cell death independent of major hotspot mutations or melanoma subtypes. Conversely, overexpression of LZTR1 in normal human melanocytes initiated processes associated with metastasis, including anchorage-independent growth, formation of spheroids, and increased levels of MAPK and SRC activities. Our results provide new insights into the etiology of acral melanoma and implicate LZTR1 as a key tumor promoter and therapeutic target.

In the skin, tissue injury results in fibrosis in the form of scars composed of dense extracellular matrix deposited by fibroblasts. The therapeutic goal of regenerative wound healing has remained elusive in part because principles of fibroblast programming and adaptive response to injury remain incompletely understood. Here, we present a multimodal -omics platform for the comprehensive study of cell populations in complex tissue, which has allowed us to characterize the cells involved in wound healing across both time and space. We employ a stented wound model that recapitulates human tissue repair kinetics and multiple Rainbow transgenic lines to precisely track fibroblast fate during the physiologic response to injury. Through integrated analysis of single cell chromatin landscapes and gene expression states, coupled with spatial transcriptomic profiling, we are able to impute fibroblast epigenomes with temporospatial resolution. This has allowed us to define the mechanisms controlling cell fate during migration, proliferation, and differentiation following tissue injury and thereby reexamine the canonical phases of wound healing. These findings have broad implications for the study of tissue repair in complex organ systems.

Single-cell RNA-sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation without prior knowledge has remained challenging. Here we describe a simple yet robust determinant of developmental potential—the number of detectably expressed genes per cell— and leverage this measure of transcriptional diversity to develop a new framework for predicting ordered differentiation states from scRNA-seq data. When evaluated on ~150,000 single-cell transcriptomes spanning 53 lineages and five species, our approach, called CytoTRACE, outperformed previous methods and ~19,000 molecular signatures for resolving experimentally-confirmed developmental trajectories. In addition, it enabled unbiased identification of tissue-resident stem cells, including cells with long-term regenerative potential. When used to analyze human breast tumors, we discovered candidate genes associated with less-differentiated luminal progenitor cells and validated GULP1 as a novel gene involved in tumorigenesis. Our study establishes a key RNA-based correlate of developmental potential and provides a new platform for robust delineation of cellular hierarchies (https://cytotrace.stanford.edu).

The functional role of U2AF1 mutations in lung adenocarcinomas (LUADs) remains incompletely understood. Here, we report a significant co-occurrence of U2AF1 S34F mutations with ROS1 translocations in LUADs. To characterize this interaction, we profiled effects of S34F on the transcriptome-wide distribution of RNA binding and alternative splicing in cells harboring the ROS1 translocation. Compared to its wild-type counterpart, U2AF1 S34F preferentially binds and modulates splicing of introns containing CAG trinucleotides at their 3′ splice junctions. The presence of S34F caused a shift in cross-linking at 3′ splice sites, which was significantly associated with alternative splicing of skipped exons. U2AF1 S34F induced expression of genes involved in the epithelial-mesenchymal transition (EMT) and increased tumor cell invasion. Finally, S34F increased splicing of the long over the short SLC34A2-ROS1 isoform, which was also associated with enhanced invasiveness. Taken together, our results suggest a mechanistic interaction between mutant U2AF1 and ROS1 in LUAD., The authors report a co-occurrence of the U2AF1 S34F splicing factor mutation and ROS1 translocations in lung adenocarcinomas and profile effects of S34F on transcriptome-wide RNA binding. They further show that U2AF1 S34F enhances invasive potential and alters splicing of ROS1 fusion transcripts

Purpose: The clinical utility of circulating tumor DNA (ctDNA) monitoring has been shown in tumors that harbor highly recurrent mutations. Leiomyosarcoma represents a type of tumor with a wide spectrum of heterogeneous genomic abnormalities; thus, targeting hotspot mutations or a narrow genomic region for ctDNA detection may not be practical. Here, we demonstrate a combinatorial approach that integrates different sequencing protocols for the orthogonal detection of single-nucleotide variants (SNV), small indels, and copy-number alterations (CNA) in ctDNA. Experimental Design: We employed Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for the analysis of SNVs and indels, together with a genome-wide interrogation of CNAs by Genome Representation Profiling (GRP). We profiled 28 longitudinal plasma samples and 25 tumor specimens from 7 patients with leiomyosarcoma. Results: We detected ctDNA in 6 of 7 of these patients with >98% specificity for mutant allele fractions down to a level of 0.01%. We show that results from CAPP-Seq and GRP are highly concordant, and the combination of these methods allows for more comprehensive monitoring of ctDNA by profiling a wide spectrum of tumor-specific markers. By analyzing multiple tumor specimens in individual patients obtained from different sites and at different times during treatment, we observed clonal evolution of these tumors that was reflected by ctDNA profiles. Conclusions: Our strategy allows for the comprehensive monitoring of a broad spectrum of tumor-specific markers in plasma. Our approach may be clinically useful not only in leiomyosarcoma but also in other tumor types that lack recurrent genomic alterations. Clin Cancer Res; 24(11); 2688–99. ©2018 AACR.

Combination checkpoint blockade (CCB) targeting inhibitory CTLA4 and PD1 receptors holds promise for cancer therapy. Immune-related adverse events (IRAEs) remain a major obstacle for the optimal application of CCB in cancer. Here, we analyzed B cell changes in patients with melanoma following treatment with either anti-CTLA4 or anti-PD1, or in combination. CCB therapy led to changes in circulating B cells that were detectable after the first cycle of therapy and characterized by a decline in circulating B cells and an increase in CD21lo B cells and plasmablasts. PD1 expression was higher in the CD21lo B cells, and B cell receptor sequencing of these cells demonstrated greater clonality and a higher frequency of clones compared with CD21hi cells. CCB induced proliferation in the CD21lo compartment, and single-cell RNA sequencing identified B cell activation in cells with genomic profiles of CD21lo B cells in vivo. Increased clonality of circulating B cells following CCB occurred in some patients. Treatment-induced changes in B cells preceded and correlated with both the frequency and timing of IRAEs. Patients with early B cell changes experienced higher rates of grade 3 or higher IRAEs 6 months after CCB. Thus, early changes in B cells following CCB may identify patients who are at increased risk of IRAEs, and preemptive strategies targeting B cells may reduce toxicities in these patients.

Korrespondenz zu 10.1200/JCO.2018.78.5246

Background: Hematopoietic stem and progenitor cells (HSPCs) are capable of generating all human blood cells. Although these cells have been extensively evaluated using both sorted (Corces et al. Nat. Genet. 2016) and single cell assays (Pellin et al. Nat. Commun. 2019), there remains significant uncertainty as to the degree of heterogeneity within HSPC subpopulations and their relevance to disease. The phenotypic diversity within HSPCs needs to be better characterized in order to understand the pathogenesis of numerous blood disorders including hematologic malignancies. To address this need, we extensively characterized healthy bone marrow mononuclear cells (BMMCs) with both whole transcriptome analysis (WTA) and surface marker evaluation. We hypothesized that by utilizing concurrent RNA and multiplexed (n=35) surface marker analysis, we could not only improve HSPC clustering but also characterize specific phenotypic states along unique hematopoietic differentiation trajectories. This analysis allowed us to identify new subpopulations within currently defined hematopoietic stem cells (HSCs), multipotent progenitors (MPPs) and lymphoid primed multipotent progenitors (LMPPs). Methods: Three healthy adult BMMC samples were stained with antibody conjugated oligonucleotides (BD Abseq) and analyzed using a nanowell cell capture system (BD Rhapsody). We filtered 8,070 high quality cells for 2,508 HSPCs, myeloid cells, and lymphocyte precursors. These cells were first clustered using matrix factorization in order to identify unique HSPC states. Novel clusters within the HSC, MPP, and LMPP subpopulations were purified using flow cytometry, and functionally evaluated with both in vitro and in vivo assays. Results: The antibody-derived tags (ADTs) obtained from BD Abseq comprised 33 of the most informative features (n=2000) and resulted in more stable clustering as determined by within sum of squares (WSS = 898 versus 934 for mRNA alone for 20 clusters). Additionally, we were able to design a targeted HSPC panel (n=500 genes) with Abseq which identified similar cell clusters compared to the WTA alone and WTA plus ADT data (Rand index = 0.88). HSPC clustering identified the putative hematopoietic stem cell (HSC), a multipotent progenitor (MPP), and a new lymphoid primed multipotent progenitor (LMPP). A new computational sorting strategy was derived to purify these primitive HSPCs, and subsequently validated with flow cytometry. The functional evaluation of these sorted populations revealed that HSC and MPP cells were capable of increased serial replating ability in vitro suggesting enhanced self-renewal capabilities compared to LMPP cells. All three HSPC subpopulations produced gradients of erythroid and myeloid colonies in methylcellulose, and T-cells in T-cell expansion assays in vitro. The HSCs were the only cells that were able to produce long term engraftment in immunodeficient mice after serial transplantations. Additionally, common myeloid progenitor (CMP), granulocyte-monocyte progenitor (GMP), and megakaryocyte-erythroid progenitor (MEP) clusters that expressed canonical surface markers were identified. The primitive HSPC clusters were converted into a signature matrix using CIBERSORTx (Newman et al. Nat. Biotechnol. 2019), and bulk acute myeloid leukemia (AML) and healthy samples were deconvolved into respective healthy cell clusters. Using multivariate Cox proportional hazard analysis, we found that high levels of MPPs at diagnosis was the strongest feature associated with worse overall survival (HR = 78.46, 95% confidence interval 7.32-828). Interestingly, after performing paired analysis of diagnostic and relapse cases, the HSC and LMPP expanded significantly in relapsed AML after chemotherapy (p < 0.05) whereas the MPP expanded considerably after stem cell transplant but did not reach significance (p = 0.09). Conclusions: In summary, we identified new cell type clusters within previously defined HSC, MPP, and LMPP subpopulations, and unique surface marker associations using combined single cell WTA and surface marker analysis. We were able to purify these primitive HSPCs using these new markers, in addition to classical markers like CD34, CD90, and CD45RA. Importantly, deconvolution analysis provided preliminary insights into their clinical relevance in AML. Disclosures Ediriwickrema: Nanosive SAS: Patents & Royalties. Majeti: BeyondSpring Inc: Membership on an entity's Board of Directors or advisory committees; Circbio inc: Membership on an entity's Board of Directors or advisory committees; Kodikaz Therapeutics Solutions Inc: Membership on an entity's Board of Directors or advisory committees; Coherus Biosciences: Membership on an entity's Board of Directors or advisory committees; Acuta Capital Partners: Consultancy; Gilead Sciences, Inc: Patents & Royalties.

Biological heterogeneity in diffuse large B cell lymphoma (DLBCL) is partly driven by cell-of-origin subtypes and associated genomic lesions, but also by diverse cell types and cell states in the tumor microenvironment (TME). However, dissecting these cell states and their clinical relevance at scale remains challenging. Here, we implemented EcoTyper, a machine learning framework integrating transcriptome deconvolution and single-cell RNA sequencing, to characterize clinically relevant DLBCL cell states and ecosystems. Using this approach, we identified five cell states of malignant B cells that vary in prognostic associations and differentiation status. We also identified striking variation in cell states for 12 other lineages comprising the TME and forming cell-state interactions in stereotyped ecosystems. While cell-of-origin subtypes have distinct TME composition, DLBCL ecosystems capture clinical heterogeneity within existing subtypes and extend beyond cell-of-origin and genotypic classes. These results resolve the DLBCL microenvironment at systems-level resolution and identify opportunities for therapeutic targeting (https://ecotyper.stanford.edu/lymphoma).

Determining how cells vary with their local signaling environment and organize into distinct cellular communities is critical for understanding processes as diverse as development, aging, and cancer. Here we introduce EcoTyper, a machine learning framework for large-scale identification and validation of cell states and multicellular communities from bulk, single-cell, and spatially resolved gene expression data. When applied to 12 major cell lineages across 16 types of human carcinoma, EcoTyper identified 69 transcriptionally defined cell states. Most states were specific to neoplastic tissue, ubiquitous across tumor types, and significantly prognostic. By analyzing cell-state co-occurrence patterns, we discovered ten clinically distinct multicellular communities with unexpectedly strong conservation, including three with myeloid and stromal elements linked to adverse survival, one enriched in normal tissue, and two associated with early cancer development. This study elucidates fundamental units of cellular organization in human carcinoma and provides a framework for large-scale profiling of cellular ecosystems in any tissue.