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V domain immunoglobulin suppressor of T-cell activation (VISTA) is a premier target for cancer treatment due to its broad expression in many cancer types and enhanced expression upon development of adaptive immune checkpoint resistance. In the CT26 colorectal cancer model, monotherapy of small tumors with anti-VISTA resulted in slowed tumor growth. In a combination therapy setting, large CT26 tumors showed complete adaptive resistance to anti–PD-1/CTLA-4, but inclusion of anti-VISTA led to rejection of half the tumors. Mechanisms of enhanced antitumor immunity were investigated using single-cell RNA sequencing (scRNA-seq), multiplex image analysis, and flow cytometry of the tumor immune infiltrate. In both treatment models, anti-VISTA upregulated stimulated antigen presentation pathways and reduced myeloid-mediated suppression. Imaging revealed an anti-VISTA stimulated increase in contacts between T cells and myeloid cells, further supporting the notion of increased antigen presentation. scRNA-seq of tumor-specific CD8+ T cells revealed that anti-VISTA therapy induced T-cell pathways highly distinct from and complementary to those induced by anti–PD-1 therapy. Whereas anti–CTLA-4/PD-1 expanded progenitor exhausted CD8+ T-cell subsets, anti-VISTA promoted costimulatory genes and reduced regulators of T-cell quiescence. Notably, this is the first report of a checkpoint regulator impacting CD8+ T-cell quiescence, and the first indication that quiescence may be a target in the context of T-cell exhaustion and in cancer. This study builds a foundation for all future studies on the role of anti-VISTA in the development of antitumor immunity and provides important mechanistic insights that strongly support use of anti-VISTA to overcome the adaptive resistance seen in contemporary treatments involving PD-1 and/or CTLA-4. See related Spotlight by Wei, p. 3

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V domain immunoglobulin suppressor of T-cell activation (VISTA) is a premier target for cancer treatment due to its broad expression in many cancer types and enhanced expression upon development of adaptive immune checkpoint resistance. In the CT26 colorectal cancer model, monotherapy of small tumors with anti-VISTA resulted in slowed tumor growth. In a combination therapy setting, large CT26 tumors showed complete adaptive resistance to anti–PD-1/CTLA-4, but inclusion of anti-VISTA led to rejection of half the tumors. Mechanisms of enhanced antitumor immunity were investigated using single-cell RNA sequencing (scRNA-seq), multiplex image analysis, and flow cytometry of the tumor immune infiltrate. In both treatment models, anti-VISTA upregulated stimulated antigen presentation pathways and reduced myeloid-mediated suppression. Imaging revealed an anti-VISTA stimulated increase in contacts between T cells and myeloid cells, further supporting the notion of increased antigen presentation. scRNA-seq of tumor-specific CD8+ T cells revealed that anti-VISTA therapy induced T-cell pathways highly distinct from and complementary to those induced by anti–PD-1 therapy. Whereas anti–CTLA-4/PD-1 expanded progenitor exhausted CD8+ T-cell subsets, anti-VISTA promoted costimulatory genes and reduced regulators of T-cell quiescence. Notably, this is the first report of a checkpoint regulator impacting CD8+ T-cell quiescence, and the first indication that quiescence may be a target in the context of T-cell exhaustion and in cancer. This study builds a foundation for all future studies on the role of anti-VISTA in the development of antitumor immunity and provides important mechanistic insights that strongly support use of anti-VISTA to overcome the adaptive resistance seen in contemporary treatments involving PD-1 and/or CTLA-4.See related Spotlight by Wei, p. 3

Supplementary Figure S4. Additional data supporting Figure 6. In the I/V model, BALB/c mice were administered 100k CT26 cells and treated when tumors reached a size of 40mm3 with isotype (I) or anti-VISTA (V). In the CPV model, BALB/c mice were administered 100k CT26 cells and treated with anti-CTLA-4 and anti-PD-1 plus isotype (CP) or plus anti-VISTA (CPV) when tumors reached a size of 600mm3. CD45 + (A-C, E) or CD8+ AH1-tetramer+ (D) cells were isolated from the TME and analyzed by scRNAseq. (A) Stacked bar graph showing all lymphoid cluster frequencies as a proportion of the lymphoid infiltrate for I/V and CP/CPV. (B) Stacked bar graph showing NK cluster frequencies as a proportion of the NK infiltrate for I/V and CP/CPV. (C) Stacked bar graph showing CD8+ T cell cluster frequencies as a proportion of the CD8+ T cell infiltrate for I/V and CP/CPV. (D) Mean cluster frequencies as a proportion of CD8+ AH1-tetramer+ T cells in I/V or CP/CPV treatment. (E) Violin plots showing enrichment of a quiescence gene signature in CD8+ T cell clusters in the CD45 + sorted I/V dataset[58]. *P < 0.05, **P < 0.01, ***P < 0.001.

Melanoma is the most aggressive type of skin cancer in the United States with an increasing incidence. Melanoma lesions often exhibit high immunogenicity, with infiltrating immune cells playing important roles in regression of tumors occurring spontaneously or caused by therapeutic treatment. Computational and experimental methods have been used to estimate the abundance of immune cells in tumors, but their applications are limited by the requirement of large gene sets or multiple antibodies. Although the prognostic role of immune cells has been appreciated, a systematic investigation of their association with clinical factors, genomic features, prognosis and treatment response in melanoma is still lacking. This study, identifies a 25-gene signature based on RNA-seq data from The Cancer Genome Atlas (TCGA)—Skin Cutaneous Melanoma (TCGA-SKCM) dataset. This signature was used to calculate sample-specific Leukocyte Infiltration Scores (LIS) in six independent melanoma microarray datasets and scores were found to vary substantially between different melanoma lesion sites and molecular subtypes. For metastatic melanoma, LIS was prognostic in all datasets with high LIS being associated with good survival. The current approach provided additional prognostic information over established clinical factors, including age, tumor stage, and gender. In addition, LIS was predictive of patient survival in stage III melanoma, and treatment efficacy of tumor-specific antigen vaccine.Implications:This study identifies a 25-gene signature that effectively estimates the level of immune cell infiltration in melanoma, which provides a robust biomarker for predicting patient prognosis.

S1. Characteristics of MYC signatures. S2. MYC activity scores capture MYC pathway activity. S3. Diverse mechanisms of MYC alterations captured by MYC activity scores. S4. Prognostic relevance of MYC score. S5. High MYC activity is associated with high proliferative rate of tumor cells.

Figure S1. LIS reflects immune cell infiltration in melanoma microenvironment. Figure S2. LIS is associated with clinical factors and provided prognostic value in addition to clinical information in melanoma. Figure S3. LIS is predictive of prognosis and immunotherapy response and correlated with genomic features in melanoma.

Table S1. Summary of the datasets Table S2. Immune related genes' correlation with ImmuneScore Table S3. 25 genes PC1 loading coefficient Table S4. Primary tumor mutation's association with LIS Table S5. Metastatic tumor mutation's association with LIS Table S6. Primary tumor CNV's association with LIS Table S7. Metastatic tumor CNV's association with LIS

c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type–specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant.Implications:By using cancer type–specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.

Supplementary Table S4: Infiltration score validation using lymphocyte fractions inferred from hematoxylin and eosin-stained tissue slides.

Viruses affect approximately 20% of all human cancers and induce expression of immunogenic viral oncoproteins that make these tumors potent targets for immune checkpoint inhibitors. In this study, we apply computational tools to The Cancer Genome Atlas (TCGA) and other genomic datasets to define how virus infection shapes the tumor immune microenvironment and genetic architecture of 6 virus-associated tumor types. Across cancers, the cellular composition of the microenvironment varied by viral status, with virus-positive tumors often exhibiting increased infiltration of cytolytic cell types compared with their virus-negative counterparts. Analyses of the infiltrating T-cell receptor repertoire in these patients revealed that Epstein–Barr virus infection was associated with decreased receptor diversity in multiple cancers, suggesting an antigen-driven clonal T-cell response. Tissue-specific gene-expression signatures capturing virus-associated transcriptomic changes successfully predicted virus status in independent datasets and were associated with both immune- and proliferation-related features that were predictive of patient prognosis. Together, the analyses presented suggest viruses have distinct effects in different tumors, with implications for immunotherapy.Significance: This study utilizes TCGA and other genomic datasets to further our understanding of how viruses affect the tumor immune response in different cancer types.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/22/6413/F1.large.jpg. Cancer Res; 78(22); 6413–23. ©2018 AACR.

Determining how immune cells functionally interact in the tumor microenvironment and identifying their biological roles and clinical values are critical for understanding cancer progression and developing new therapeutic strategies. Here we introduce TimiGP, a computational method to infer inter-cell functional interaction networks and annotate the corresponding prognostic effect from bulk gene expression and survival statistics data. When applied to metastatic melanoma, TimiGP overcomes the prognostic bias caused by immune co-infiltration and identifies the prognostic value of immune cells consistent with their anti- or pro-tumor roles. It reveals the functional interaction network in which the interaction X→Y indicates a more positive impact of cell X than Y on survival. This network provides immunological insights to facilitate the development of prognostic models, as evidenced by our computational-friendly, biologically interpretable, independently validated models. By leveraging single-cell RNA-seq data for specific immune cell subsets, TimiGP has the flexibility to delineate the tumor microenvironment at different resolutions and is readily applicable to a wide range of cancer types.

Immune checkpoint proteins play critical functions during the immune response to cancer and have been targeted by immune checkpoint blockade therapy. V-domain Ig suppressor of T cell activation (VSIR) is one of these immune checkpoint genes and has been investigated extensively in recent years due to its conflicting roles in cancer immunity. Specifically, in acute myeloid leukemia (AML), the prognostic value of VSIR is debated.In both patient tumor samples and cancer cell lines we find that VSIR has the highest expression in AML out of all cancer types and, in AML, has the highest expression out of all other immune checkpoint genes. Survival analysis indicated that AML patients with higher VSIR expression have significantly shorter survival than those patients with lower expression, even within established AML subgroups (e.g., FAB subtypes). Importantly, VSIR expression is predictive of progression from myelodysplastic syndromes (MDS) patients into AML, suggesting its potential role during the very early stage of AML development and progression. In addition to AML, VSIR also demonstrates prognostic values in other cancer types, including multiple myeloma and mesothelioma.In summary, our analyses revealed the prognostic value of VSIR and its potential as a target for immunotherapy, especially in AML.

BACKGROUND: The function of major histocompatibility complex (MHC) molecules is to bind peptide fragments derived from genomic mutations or pathogens and display them on the cell surface for recognition by cognate T cells to initiate an immune response. METHODS: In this study, we provide a comprehensive investigation of HLA gene expression in a pan-cancer manner involving 33 cancer types. We utilised gene expression data from several databases and immune checkpoint blockade-treated patient cohorts. RESULTS: We show that MHC expression varies strongly among cancer types and is associated with several genomic and immunological features. While immune cell infiltration was generally higher in tumours with higher HLA gene expression, CD4+ T cells showed significantly different correlations among cancer types, separating them into two clusters. Furthermore, we show that increased HLA gene expression is associated with prolonged survival in the majority of cancer types. Lastly, HLA gene expression is associated with patient response to immune checkpoint blockade, which is especially prominent for HLA class II expression in tumour biopsies taken during treatment. CONCLUSION: We show that HLA gene expression is an important feature of tumour biology that has significant impact on patient prognosis.

c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type–specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant. Implications: By using cancer type–specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.

Developing prognostic biomarkers for specific cancer types that accurately predict patient survival is increasingly important in clinical research and practice. Despite the enormous potential of prognostic signatures, proposed models have found limited implementations in routine clinical practice. Herein, we propose a generic, RNA sequencing platform-independent, statistical framework named Whole Transcriptome Signature for Prognostic Prediction (WTSPP) to generate prognostic gene signatures. Using ovarian cancer and lung adenocarcinoma as examples, we provide evidence that our prognostic signatures over-perform previous reported signatures, capture prognostic features not explained by clinical variables and expose biologically relevant prognostic pathways, including those involved in the immune system and cell cycle. Our approach demonstrates a robust method for developing prognostic gene expression signatures. In conclusion, our statistical framework can be generally applied to all cancer types for prognostic prediction and might be extended to other human diseases. The proposed method is implemented as an R package (PanCancerSig) and is freely available on GitHub (https://github.com/Cheng-Lab-GitHub/PanCancer_Signature).

OBJECTIVE Genome-wide gene expression studies implicate macrophages as mediators of fibrosis in systemic sclerosis (SSc), but little is known about how these cells contribute to fibrotic activation in SSc. We undertook this study to characterize the activation profile of SSc monocyte-derived macrophages and assessed their interaction with SSc fibroblasts. METHODS Plasma and peripheral blood mononuclear cells (PBMCs) were obtained from whole blood from SSc patients (n = 24) and age- and sex-matched healthy controls (n = 12). Monocytes were cultured with autologous or allogeneic plasma to differentiate cells into macrophages. For reciprocal activation studies, macrophages were cocultured with fibroblasts using Transwell plates. RESULTS The gene expression signature associated with blood-derived human SSc macrophages was enriched in SSc skin in an independent cohort and correlated with skin fibrosis. SSc macrophages expressed surface markers associated with activation and released CCL2, interleukin-6, and transforming growth factor β under basal conditions (n = 8) (P < 0.05). Differentiation of healthy donor monocytes in plasma from SSc patients conferred the immunophenotype of SSc macrophages (n = 13) (P < 0.05). Transwell experiments demonstrated that coculture of SSc macrophages with SSc fibroblasts induced fibroblast activation (n = 3) (P < 0.05). CONCLUSION These data demonstrate that the activation profile of SSc macrophages is profibrotic. SSc macrophages are activated under basal conditions and release mediators and express surface markers associated with both alternative and inflammatory macrophage activation. These findings also suggest that activation of SSc macrophages arises from soluble factors in local microenvironments. These studies implicate macrophages as likely drivers of fibrosis in SSc and suggest that therapeutic targeting of these cells may be beneficial in ameliorating disease in SSc patients.

Introduction: Accumulating evidence has suggested that the tumor immune microenvironment (TIME) drastically impacts cancer patients’ clinical outcomes, especially immunotherapy response. Many transcriptome-based cell-type quantification methods (e.g., TIMER, CIBERSORTx) have been developed to estimate immune cell infiltration from bulk RNA sequencing. Our aim is to reveal the cell-cell interaction and its association with clinical outcomes. Methods: We developed, TimiGP (Tumor Immune Microenvironment Illustration based on Gene Pairing), a computational method to investigate the TIME by inferring the inter-cell “functional” interaction network and estimating the clinical value of immune cells from bulk gene expression and clinical information. It was based on two assumptions: 1) The TIME is a dynamic balance between pro-and anti-tumor immune cells, whose relative functions determine the capacity of the immune system and subsequently impact clinical outcomes; 2) The pairwise relation between gene pairs can capture the relative functions between immune cells. TimiGP was applied to study the association of TIME with prognosis (7,938 samples, 23 cancer types) and the immunotherapy response (2,941 patients, 5 cancer types, 6 treatments) in pan-cancer analysis. Results: We first applied 8 existing deconvolution methods to highly immune infiltrated metastatic melanoma (MM), whose results identified both anti- and pro-tumor cell types (e.g., tumor-associated neutrophils) associated with a superior prognosis. By contrast, TimiGP overcame such prognostic bias and identified the prognostic value of immune cells consistent with their established functions. We then integrated TimiGP with single-cell RNA-seq analysis to achieve higher resolution for specific immune cell subsets than existing methods. Furthermore, we utilized TimiGP in pan-cancer analysis, which identified the TIME heterogeneity associated with survival and critical immune interactions determining the immunotherapy response across various cancer types and treatments. Besides, TimiGP could integrate the TIME insights to construct computational-friendly and interpretable models for risk evaluation or response prediction. For example, we used it to develop MM prognostic model that achieved superior performance in 5 independent validations (C-index: 0.621-0.659) than traditional methods. Conclusions: TimiGP (R package available at https://github.com/CSkylarL/TimiGP) is a novel algorithm that accepts bulk expression and clinical information to generate a prognostic/responsive score of each cell type and an inter-cell functional interaction network. It can be used to identify target-to-hit, study the underlying causes of clinical heterogeneity, and construct predictive models based on biological and clinical insights, which offer substantial potential for personalized cancer treatment. Citation Format: Chenyang Li, Wei Hong, Baoyi Zhang, Evelien Schaafsma, Alexandre Reuben, Jianjun Zhang, Chao Cheng. TimiGP: Dissect the tumor immune microenvironment and its association with survival and 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 2080.

Although estrogen-receptor-positive (ER+) breast cancer is generally associated with favorable prognosis, clinical outcome varies substantially among patients. Genomic assays have been developed and applied to predict patient prognosis for personalized treatment. We hypothesize that the recurrence risk of ER+ breast cancer patients is determined by both genomic mutations intrinsic to tumor cells and extrinsic immunological features in the tumor microenvironment. Based on the Cancer Genome Atlas (TCGA) breast cancer data, we identified the 72 most common genomic aberrations (including gene mutations and indels) in ER+ breast cancer and defined sample-specific scores that systematically characterized the deregulated pathways intrinsic to tumor cells. To further consider tumor cell extrinsic features, we calculated immune infiltration scores for six major immune cell types. Many individual intrinsic features are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. In addition, statistical learning models that integrated these features predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay. As a proof-of-concept, our study indicates the great potential of genomic and immunological features in prognostic prediction for improving breast cancer precision medicine. The framework introduced in this work can be readily applied to other cancers.Author SummaryMany genomic biomarker tests such as Oncotype DX have been developed for breast cancer and have helped guide clinical decisions. We have developed gene signatures to integrate cancer genomic and transcriptomic data to characterize the downstream effect of driver genomic events. These signatures recapitulate the de-regulated pathways underlying the corresponding driver genomic events and are more correlated with clinical phenotypes such as recurrence free survival than mutation status alone. We apply this framework to ER+ breast cancer and define gene signatures for a total of 72 most commonly observed genomic events including gene mutations, amplifications and deletions. We find that many of these gene signatures are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. We combine these tumor-intrinsic signatures with infiltration signatures for major immune cell types (tumor-extrinsic features) to construct integrative models for prognosis prediction. The models predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay.

Although estrogen-receptor-positive (ER+) breast cancer is generally associated with favorable prognosis, clinical outcome varies substantially among patients. Genomic assays have been developed and applied to predict patient prognosis for personalized treatment. We hypothesize that the recurrence risk of ER+ breast cancer patients is determined by both genomic mutations intrinsic to tumor cells and extrinsic immunological features in the tumor microenvironment. Based on the Cancer Genome Atlas (TCGA) breast cancer data, we identified the 72 most common genomic aberrations (including gene mutations and indels) in ER+ breast cancer and defined sample-specific scores that systematically characterized the deregulated pathways intrinsic to tumor cells. To further consider tumor cell extrinsic features, we calculated immune infiltration scores for six major immune cell types. Many individual intrinsic features are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. In addition, statistical learning models that integrated these features predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay (our optimized random forest model AUC = 0.841, Oncotype DX model AUC = 0.792, p = 0.04). As a proof-of-concept, our study indicates the great potential of genomic and immunological features in prognostic prediction for improving breast cancer precision medicine. The framework introduced in this work can be readily applied to other cancers.

Transcription factor (TF) STAT3 contributes to pancreatic cancer progression through its regulatory roles in both tumor cells and the tumor microenvironment (TME). In this study, we performed a systematic analysis of all TFs in patient-derived gene expression datasets and confirmed STAT3 as a critical regulator in the pancreatic TME. Importantly, we developed a novel framework that is based on TF target gene expression to distinguish between environmental- and tumor-specific STAT3 activities in gene expression studies. Using this framework, our results novelly showed that compartment-specific STAT3 activities, but not STAT3 mRNA, have prognostications towards clinical values within pancreatic cancer datasets. In addition, high TME-derived STAT3 activity correlates with an immunosuppressive TME in pancreatic cancer, characterized by CD4 T cell and monocyte infiltration and high copy number variation burden. Where environmental-STAT3 seemed to play a dominant role at primary pancreatic sites, tumor-specific STAT3 seemed dominant at metastatic sites where its high activity persisted. In conclusion, by combining compartment-specific inference with other tumor characteristics, including copy number variation and immune-related gene expression, we demonstrate our method’s utility as a tool to generate novel hypotheses about TFs in tumor biology.

Gliomas make up ~80% of malignant brain tumors in adults and are responsible for the majority of deaths from primary brain tumors. The glioma tumor microenvironment (TME) is a dynamic, heterogeneous mixture of extracellular matrix and malignant and non-malignant cells. Several ongoing clinical trials are evaluating the efficacy of therapies that target non-malignant cells, particularly immune cells. Consequently, a better understanding of the TME in glioma is pertinent. We utilized several gene expression datasets to evaluate the relationship between immune-related genes (IRGs) and patient prognosis. We generated microglia signatures using single-cell RNAseq data from human and mouse glioma cells to infer microglia abundance. Lastly, we built a LASSO Cox regression model that predicts patient survival. We found that 428 IRGs were negatively associated with survival in glioma patients. Overall survival was significantly lower in those with a high level of microglia infiltration. In addition, we also found that microglia abundance was significantly associated with several common genomic aberrations, including IDH2 and TP53 mutations. Furthermore, we found that patients with high risk scores had significantly worse overall survival than those with low risk scores in several independent datasets. Altogether, we characterized immune features predictive of overall survival in glioma and found that microglia abundance is negatively associated with survival. We developed a 23-gene risk score that can significantly stratify patients into low- and high-risk categories.

Aim Neuroblastoma is the most common extracranial solid tumor in children. Recent advances in immunotherapy Approaches, including in neuroblastoma, have shown the important role of the immune system in mounting an effective anti-tumor response. In this study, we aimed to provide a comprehensive investigation of immune cell infiltration in neuroblastoma utilizing a large number of gene expression datasets. Methods We inferred immune cell infiltration using an established immune inference method and evaluated the association between immune cell abundance and patient prognosis as well as common chromosomal abnormalities found in neuroblastoma. In addition, we evaluated co-infiltration patterns among distinct immune cell types. Results The infiltration of naive B cells, NK cells, and CD8+ T cells was associated with improved patient prognosis. Naive B cells were the most consistent indicator of prognosis and associated with an active immune tumor microenvironment. Patients with high B cell infiltration showed high co-infiltration of other immune cell types and the enrichment of immune-related pathways. The presence of high B cell infiltration was associated with both recurrence-free and overall survival, even after adjusting for clinical variables. Conclusion In this study, we have provided a comprehensive evaluation of immune cell infiltration in neuroblastoma using gene expression data. We propose an important role for B cells in the neuroblastoma tumor microenvironment and suggest that B cells can be used as a prognostic biomarker to predict recurrence-free and overall survival independently of currently utilized prognostic variables.

Background VISTA is a negative checkpoint regulator prominently expressed in the TME of a wide variety of cancers. In a preclinical model of colorectal cancer, monotherapy of small tumors (40 mm3) with anti-VISTA results in markedly slowed tumor growth. Mice bearing significantly larger tumors (600 mm3) are resistant to anti-PD-1 and anti-CTLA4 treatment and all mice die following treatment, indicating checkpoint resistance. Inclusion of anti-VISTA leads to complete rejection of 50% of tumors. Methods The underlying therapeutic mechanisms of leading to enhanced anti-tumor immunity in both models was investigated by high-dimensional scRNAseq of the CD45+ immune infiltrate of tumors 10 days after treatment initiation. Results In both modes, anti-VISTA treatment stimulated several pathways involving myeloid activation and antigen-presentation. Multi-spectral imaging of anti-VISTA treated tumors supported increased antigen presentation, and suppression assays showed that the myeloid infiltrate was less suppressive to T cells. Transcriptional analysis of tumor-specific CD8 T cells showed that anti-VISTA therapy induced T cell pathways highly distinct from the anti-exhaustion effects of anti-PD-1 therapy. Conclusions These data document the unique and complementary impact of targeting VISTA in contrast to PD-1 and CTLA-4 in both the myeloid and T cell lineages. These mechanistic insights strongly support the use of anti-VISTA to overcome the checkpoint resistance seen in contemporary treatments involving PD-1. Ethics Approval All mouse studies described in this work were carried out in accordance with the principles of the Guide for the Care and Use of Animals and were approved by the Institutional Animal Care and Use Committee of Dartmouth College, NH, USA (protocol 2012).

We present the novel finding that V-domain Ig suppressor of T cell activation (VISTA) negatively regulates innate inflammation through the transcriptional and epigenetic re-programming of macrophages. Representative of VISTA re-programming is the ability of VISTA agonistic antibodies to augment LPS tolerance and reduce septic shock lethality in mice. This anti-inflammatory effect of anti-VISTA was mimicked in vitro demonstrating that anti-VISTA treatment caused a significant reduction in LPS-induced IL-12p40, IL-6, CXCL2, and TNF; all hallmark pro-inflammatory mediators of endotoxin shock. Even under conditions that typically “break” LPS tolerance, VISTA agonists sustained a macrophage anti-inflammatory profile. Analysis of the proteomic and transcriptional changes imposed by anti-VISTA show that macrophage re-programming was mediated by a composite profile of mediators involved in both macrophage tolerance induction (IRG1, miR221, A20, IL-10) as well as transcription factors central to driving an anti-inflammatory profile (e.g., IRF5, IRF8, NFKB1). These findings underscore a novel and new activity of VISTA as a negative checkpoint regulator that induces both tolerance and anti-inflammatory programs in macrophages and controls the magnitude of innate inflammation in vivo.

EGFR is an oncogene with a high frequency of activating mutations in nonsmall cell lung cancer (NSCLC). EGFR inhibitors have been FDA-approved for NSCLC and have shown efficacy in patients with certain EGFR mutations. However, only 9% to 26% of these patients achieve objective responses. In our study, we developed an EGFR gene signature based on The Cancer Genome Atlas (TCGA) RNA-seq data of lung adenocarcinoma (LUAD) to direct the preselection of patients for more effective EGFR-targeted therapy. This signature infers baseline EGFR signaling pathway activity (denoted as EGFR score) in tumor samples, which is associated with tumor sensitivity to EGFR inhibitors and other tyrosine kinase inhibitors (TKIs). EGFR score predicted sensitivity of lung cancer cell lines to Erlotinib, Gefitinib and Sorafenib. Importantly, EGFR score calculated from pretreated samples was associated with patient response to Gefitinib and Sorafenib in lung cancer. Additionally, integration of the EGFR signature with TCGA LUAD data showed that it accurately predicted functional effects of different somatic EGFR mutations, and identified other mutations affecting EGFR pathway activity. Finally, using cancer cell line and clinical trial data, the EGFR score was associated with patient response to TKIs in liver cancer and other cancer types. The EGFR signature provides a useful biomarker that can expand the application of EGFR inhibitors or other TKIs and improve their treatment efficacy through patient stratification.

treatment. Significantly, VISTA shows broad expression in many cancer types, with enhanced expression upon development of adaptive immune checkpoint resistance. In the CT26 colon cancer model, growth of small tumors (40mm3), are retarded by anti-VISTA monotherapy, and are readily rejected following anti-CTLA4/anti-PD-L1 (CP)therapy. In contrast, very large tumors (>600mm3), are refractory to CP therapy. However, combinatorial therapy of CP with anti-VISTA leads to rejection of about half the tumors. Both in monotherapy and combination therapy the mechanisms of enhanced anti-tumor immunity were investigated using scRNAseq, multiplex image analysis and flow cytometry of the tumor immune infiltrate. In both treatment models, anti-VISTA upregulated stimulated myeloid antigen-presentation pathways and reduced myeloid mediated suppression. Multi-spectral imaging revealed an anti-VISTA stimulated increase in contacts between CD8+ T cells and myeloid cells, further supporting the notion of increased antigen presentation upon anti-VISTA treatment. Transcriptional analysis of antigen-specific CD8 T cells showed that anti-VISTA therapy induced T cell pathways highly distinct from the anti-exhaustion effects of CP. These data suggest the non-redundancy of CP and anti-VISTA treatment, and support the use of these treatments in combination to overcome the adaptive resistance seen in contemporary treatments involving PD-1 and/or CTLA-4. Research was supported by NIH grants R01AR070760 (R.J.N.), R01CA214062 (R.J.N.), and 1R21CA227996 (C.C.) and the Cancer Prevention Research Institute of Texas (CPRIT) (RR180061 to C.C.). C.C. is a CPRIT Scholar in Cancer Research.

Although naive T cells comprise about 90% of circulating and 20% of tissue restricted T cells, most studies on T cells emphasize effector, regulatory or memory functions. The consensus that all naive cells comprise a functionally monomorphic population is challenged by our recent findings. A redefinition of the naive T cell state shows that these cells are heterogeneous, with pre-programed differentiation trajectories. VISTA (V-domain Ig suppressor of T cell activation) is an immune checkpoint restricted to the hematopoietic compartment. Here, using single cell sequencing, we demonstrate unexpected loss of quiescence in VISTA deficient CD4+ T cells compared to Wild Type CD4+ T cells. The quiescence module, defined by Klf2, Klf6, Btg1, Btg2 expression, is lost in VISTA deficient mice. Conversely, there is an expansion of the stem-cell memory-like cluster, defined by Tcf7, Bcl2, and Il7r. This altered subset make-up due to VISTA deficiency demonstrates that naive T cell heterogeneity is tightly regulated. Consequently, we identified 5 subsets in healthy adult mice using single cell sequencing of naive CD4+ T cells. These include a quiescence cluster, memory-like cluster, TCR reactive cluster, IFN responsive cluster and T cell undifferentiated cluster. This heterogeneity is imprinted in the thymus, maintained in the periphery, and is not influenced by the TCR repertoire. Tracking the differentiation trajectory of these naive CD4+ T cells shows biased lineage commitment dependent on progenitor cluster identity. Thus, thymic imprinting and peripheral maintenance of varied naive T cell identities determines T cell fate. Supported by 5R01AR070760-05

Colorectal cancer (CRC) is a major cause of cancer-associated deaths worldwide. Recently, oral administration of resveratrol (trans-3,5,4'-trihydroxystilbene) has been reported to significantly reduce tumor proliferation in colorectal cancer patients, however, with little specific information on functional connections. The pathogenesis and development of colorectal cancer is a multistep process that can be categorized using three phenotypic pathways, respectively, chromosome instability (CIN), microsatellite instability (MSI), and CpG island methylator (CIMP). Targets of resveratrol, including a high-affinity binding protein, quinone reductase 2 (QR2), have been identified with little information on disease association. We hypothesize that the relationship between resveratrol and different CRC etiologies might be gleaned using publicly available databases. A web-based microarray gene expression data-mining platform, Oncomine, was selected and used to determine whether QR2 may serve as a mechanistic and functional biotarget within the various CRC etiologies. We found that QR2 messenger RNA (mRNA) is overexpressed in CRC characterized by CIN, particularly in cells showing a positive KRAS (Kirsten rat sarcoma viral oncogene homolog) mutation, as well as by the MSI but not the CIMP phenotype. Mining of Oncomine revealed an excellent correlation between QR2 mRNA expression and certain CRC etiologies. Two resveratrol-associated genes, adenomatous polyposis coli (APC) and TP53, found in CRC were further mined, using cBio portal and Colorectal Cancer Atlas which predicted a mechanistic link to exist between resveratrol→QR2/TP53→CIN. Multiple web-based data mining can provide valuable insights which may lead to hypotheses serving to guide clinical trials and design of therapies for enhanced disease prognosis and patient survival. This approach resembles a BioGPS, a capability for mining web-based databases that can elucidate the potential links between compounds to provide correlations of these interactions with specific diseases.

Introduction: Lupus anticoagulants (LA) are a heterogeneous group of immunoglobulins that develop spontaneously, with autoimmune disorders or transiently in association with acute infectious or inflammatory conditions. Transient LA are generally presumed to be harmless, while LA that persist over time may be a risk factor for venous and arterial thrombosis. Accordingly, persistence of LA after a first thrombotic episode may signal a recommendation for long term thromboprophylaxis with an anticoagulant, thus, to guide therapy, correct interpretation of LA test results is paramount. LA test interpretation is complicated, however, and clinicians must understand the LA test characteristics, the importance of timing of testing and the implications of positive, negative and equivocal test results to use the information effectively for clinical decision making. We undertook this study to ascertain how clinicians at our institution approach LA testing and to identify knowledge gaps that may amenable to educational interventions aimed at improving patient care in this area. Methods: Our laboratory uses a combination of the dilute Russell viper venom time (dRVVT) and silica clotting time (SCT) for LA screening (Instrumentation Laboratories, Bedford MA, USA). A positive test for either dRVVT or SCT is considered positive for LA. Negative tests for both are required to exclude the presence of LA in a given patient. We provide cutoff values for negative, positive and indeterminate test results and recommend repeat testing after 12 weeks for any indeterminate or positive test to establish persistence in accordance with current guidelines. We recommend NOT testing patients who are currently anticoagulated with a direct oral anticoagulant (DOAC) due to the potential for a false positive test result. We retrospectively analyzed 715 completed LA tests between April 1, 2018 and April 30, 2019 to determine the proportion of positive, negative and indeterminate test results. We then reviewed individual patient records to identify patient and provider characteristics and document additional diagnostic actions taken based on the initial test results. We report our findings descriptively. Results: The average age of patients undergoing laboratory testing for LA was 46.9 years, (median, 47.0 years), with a preponderance of females (73%). The majority of tests were ordered by rheumatology or hematology providers (53%). Anticoagulation with a DOAC was present in 74 (10%). A negative initial test (dRVVT and SCT both negative) was documented in 413 patients (58%), and was repeated in nine individuals (2%) at a second time point. A positive test (dRVVT and/or SCT positive) was documented in 170 (24%), of which 53 (31%) were repeated subsequently and 18 (11%) were themselves repeat tests to follow up on a previous positive test, leaving 99 (58%) initial positive tests that were not repeated. The majority of repeat tests were conducted at a time point Conclusion: We discovered a surprisingly high rate of inappropriate LA test usage at our institution. The results of this investigation will guide our efforts to develop interventions aimed at informing our clinicians about best practices for laboratory testing for LA, and provide opportunities to leverage the features of the electronic health record to improve test ordering procedures. Disclosures No relevant conflicts of interest to declare.

SummaryThe immune response is governed by a highly complex set of interactions among cells and mediators. T cells may be rendered dysfunctional by the presence of high levels of antigen in the absence of co-stimulation while myeloid cells may be programmed towards an immunosuppressive state that promotes cancer growth and metastasis while deterring tumor immunity. In addition, inhibitory programs driven by immune checkpoint regulators dampen anti-tumor immunity. The ideal cancer immunotherapy treatment will improve both cross-priming in the tumor microenvironment and relieve suppression by the inhibitory checkpoints. Recently, blockade of programmed cell death 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) has elicited impressive results, but not in all patients, so additional targets are under investigation. V-set immunoglobulin domain suppressor of T cell activation (VISTA) is a novel immunoregulatory receptor that is broadly expressed on cells of the myeloid and lymphoid lineages, and is frequently implicated as a poor prognostic indicator in multiple cancers. Importantly, antibody targeting of VISTA uniquely engages both innate and adaptive immunity. This, combined with the expression of VISTA and its non-redundant activities compared to other immune checkpoint regulators, qualifies VISTA to be a promising target for improving cancer immunotherapy.

A VISTA on naïve T cell fate T cell quiescence and tolerance restrain the immune system from becoming overactive and attacking healthy tissue. Negative checkpoint regulators normally limit T cell responses to help safeguard against conditions such as autoimmunity. ElTanbouly et al. report that the checkpoint regulator VISTA (V-type immunoglobulin domain-containing suppressor of T cell activation) restricts early stages of T cell activation by shaping the inherent heterogeneity of the naïve CD4 + T cell compartment to one that is more uniformly quiescent and silent (see the Perspective by Brown and Rudensky). Therapeutic targeting of VISTA using an agonistic antibody in mice curbed the development of graft-versus-host disease and promoted the death of naïve T cells abnormally activated by self-antigen. VISTA thus represents a distinctive immunoregulatory molecule that controls naïve T cell function by maintaining quiescence and peripheral tolerance. Science , this issue p. eaay0524 ; see also p. 247

Genome-wide gene expression studies implicate macrophages as mediators of fibrosis in Systemic sclerosis (SSc), and we have shown that macrophages constitute the dominant inflammatory signature in SSc tissue. However, little is known about how these cells contribute to fibrotic activation in SSc. Using a bioinformatics approach, we show that the gene expression profile of blood-derived human SSc macrophages is significantly enriched in SSc patient skin. We characterize the immunophenotype of human SSc macrophages as pro-fibrotic, demonstrating that these cells are activated under basal conditions, expressing elevated levels of surface markers associated with activation and releasing CCL2, IL-6, and TGF-beta. We also show that STAT3 is phosphorylated in macrophage from SSc patient compared to the healthy donor, and the phosphorylation is attenuated after IL-6 blockade, suggesting that increased expression of IL-6 by SSc macrophages accounts, at least in part, for increased signaling. Moreover, our results suggest that activation of SSc macrophages arises from soluble factors, as differentiation of healthy donor monocytes in SSc patient-derived plasma confers the immunophenotype of SSc patient macrophages. For the first time, we show that co-culture of human SSc macrophages with SSc fibroblasts induces fibroblast activation. Collectively, these studies implicate macrophages as likely drivers of fibrosis in SSc and suggest therapeutic targeting of these cells may be beneficial in ameliorating disease in SSc patients.