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Neoadjuvant intratumoral (IT) therapy could amplify the weak responses to checkpoint blockade therapy observed in breast cancer (BC). In this study, we administered neoadjuvant IT anti-canine PD-1 therapy (IT acPD-1) alone or combined with IT cowpea mosaic virus therapy (IT CPMV/acPD-1) to companion dogs diagnosed with canine mammary cancer (CMC), a spontaneous tumor resembling human BC. CMC patients treated weekly with acPD-1 (n = 3) or CPMV/acPD-1 (n = 3) for four weeks or with CPMV/acPD-1 (n = 3 patients not candidates for surgery) for up to 11 weeks did not experience immune-related adverse events. We found that acPD-1 and CPMV/acPD-1 injections resulted in tumor control and a reduction in injected tumors in all patients and in noninjected tumors located in the ipsilateral and contralateral mammary chains of treated dogs. In two metastatic CMC patients, CPMV/acPD-1 treatments resulted in the control and reduction of established lung metastases. CPMV/acPD-1 treatments were associated with altered gene expression related to TLR1-4 signaling and complement pathways. These novel therapies could be effective for CMC patients. Owing to the extensive similarities between CMC and human BC, IT CPMV combined with approved anti-PD-1 therapies could be a novel and effective immunotherapy to treat local BC and suppress metastatic BC.

The lack of optimal models to evaluate novel agents is delaying the development of effective immunotherapies against human breast cancer (BC). In this prospective open label study, we applied neoadjuvant intratumoral immunotherapy with empty cowpea mosaic virus-like particles (eCPMV) to 11 companion dogs diagnosed with canine mammary cancer (CMC), a spontaneous tumor resembling human BC. We found that two neoadjuvant intratumoral eCPMV injections resulted in tumor reduction in injected tumors in all patients and in noninjected tumors located in the ipsilateral and contralateral mammary chains of injected dogs. Tumor reduction was independent of clinical stage, tumor size, histopathologic grade, and tumor molecular subtype. RNA-seq-based analysis of injected tumors indicated a decrease in DNA replication activity and an increase in activated dendritic cell infiltration in the tumor microenvironment. Immunohistochemistry analysis demonstrated significant intratumoral increases in neutrophils, T and B lymphocytes, and plasma cells. eCPMV intratumoral immunotherapy demonstrated antitumor efficacy without any adverse effects. This novel immunotherapy has the potential for improving outcomes for human BC patients.

Determining the prognostic association of different immune cell types in the tumor microenvironment is critical for understanding cancer biology and developing new therapeutic strategies. However, this is challenging in certain cancer types, where the abundance of different immune subsets is highly correlated. In this study, we develop a computational method named TimiGP to overcome this challenge. Based on bulk gene expression and survival data, TimiGP infers cell-cell interactions that reveal the association between immune cell relative abundance and prognosis. As demonstrated in metastatic melanoma, TimiGP prioritizes immune cells critical in prognosis based on the identified cell-cell interactions. Highly consistent results are obtained by TimiGP when applied to seven independent melanoma datasets and when different cell-type marker sets are used as inputs. Additionally, TimiGP can leverage single-cell RNA sequencing data to delineate the tumor immune microenvironment at high resolutions across a wide range of cancer types., Competing Interests: Declaration of interests J.Z. reports grants from Merck, grants and personal fees from Johnson and Johnson and Novartis, and personal fees from Bristol Myers Squibb, AstraZeneca, GenePlus, Innovent, and Hengrui outside the submitted work., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: 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., Results: 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., Conclusion: In summary, our analyses revealed the prognostic value of VSIR and its potential as a target for immunotherapy, especially in AML., (© 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

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.

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., Competing Interests: The authors have declared that no competing interests exist.

The tumor suppressor p53, encoded by the TP53 gene, is mutated or nullified in nearly 50% of human cancers. It has long been debated whether TP53 mutations can be utilized as a biomarker to predict clinical outcomes of cancer patients. In this study, we applied computational methods to calculate p53 deficiency scores (PDSs) that reflect the inactivation of the p53 pathway, instead of TP53 mutation status. Compared to TP53 mutation status, the p53 deficiency gene signature is a powerful predictor of overall survival and drug sensitivity in a variety of cancer types and treatments. Interestingly, the PDSs predicted clinical outcomes more accurately than drug sensitivity in cell lines, suggesting that tumor heterogeneity and/or tumor microenvironment may play an important role in predicting clinical outcomes using p53 deficiency gene signatures., (© 2022. The Author(s).)

Background: Neoantigens are presented on the cancer cell surface by peptide-restricted human leukocyte antigen (HLA) proteins and can subsequently activate cognate T cells. It has been hypothesized that the observed somatic mutations in tumors are shaped by immunosurveillance., Methods: We investigated all somatic mutations identified in The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) samples. By applying a computational algorithm, we calculated the binding affinity of the resulting neo-peptides and their corresponding wild-type peptides with the major histocompatibility complex (MHC) Class I complex. We then examined the relationship between binding affinity alterations and mutation frequency., Results: Our results show that neoantigens derived from recurrent mutations tend to have lower binding affinities with the MHC Class I complex compared to peptides from non-recurrent mutations. Tumor samples harboring recurrent SKCM mutations exhibited lower immune infiltration levels, indicating a relatively colder immune microenvironment., Conclusions: These results suggested that the occurrences of somatic mutations in melanoma have been shaped by immunosurveillance. Mutations that lead to neoantigens with high MHC class I binding affinity are more likely to be eliminated and thus are less likely to be present in tumors., Competing Interests: Author C-CC was employed by the company Chempartner Corporation. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Jiang, Schaafsma, Hong, Zhao, Zhu, Chao and Cheng.)

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., (© 2021. The Author(s), under exclusive licence to Cancer Research UK.)

Background: The Oncotype DX breast recurrence score has been introduced more than a decade ago to aid physicians in determining the need for systemic adjuvant chemotherapy in patients with early-stage, estrogen receptor (ER)+, lymph node-negative breast cancer., Methods: In this study, we utilized data from The Surveillance, Epidemiology, and End Results (SEER) Program to investigate temporal trends in Oncotype DX usage among US breast cancer patients in the first decade after the introduction of the Oncotype DX assay., Results: We found that the use of Oncotype DX has steadily increased in the first decade of use and that this increase is associated with a decreased usage of chemotherapy. Patients who utilized the Oncotype DX test tended to have improved survival compared to patients who did not use the assay even after adjusting for clinical variables associated with prognosis. In addition, chemotherapy usage in patients with high-risk scores is associated with significantly longer overall and breast cancer-specific survival compared to high-risk patients who did not receive chemotherapy. On the contrary, patients with low-risk scores who were treated with chemotherapy tended to have shorter overall survival compared to low-risk patients who forwent chemotherapy., Conclusion: We have provided a comprehensive temporal overview of the use of Oncotype DX in breast cancer patients in the first decade after Oncotype DX was introduced. Our results suggest that the use of Oncotype DX is increasing in ER+ breast cancer and that the Oncotype DX test results provide valuable information for patient treatment and prognosis., (© 2021. The Author(s).)

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., (©2020 American Association for Cancer Research.)

In recent years, the success of immunotherapy targeting immunoregulatory receptors (immune checkpoints) in cancer have generated enthusiastic support to target these receptors in a wide range of other immune related diseases. While the overwhelming focus has been on blockade of these inhibitory pathways to augment immunity, agonistic triggering via these receptors offers the promise of dampening pathogenic inflammatory responses. V-domain Ig suppressor of T cell activation (VISTA) has emerged as an immunoregulatory receptor with constitutive expression on both the T cell and myeloid compartments, and whose agonistic targeting has proven a unique avenue relative to other checkpoint pathways to suppress pathologies mediated by the innate arm of the immune system. VISTA agonistic targeting profoundly changes the phenotype of human monocytes towards an anti-inflammatory cell state, as highlighted by striking suppression of the canonical markers CD14 and Fcγr3a (CD16), and the almost complete suppression of both the interferon I (IFN-I) and antigen presentation pathways. The insights from these very recent studies highlight the impact of VISTA agonistic targeting of myeloid cells, and its potential therapeutic implications in the settings of hyperinflammatory responses such as cytokine storms, driven by dysregulated immune responses to viral infections (with a focus on COVID-19) and autoimmune diseases. Collectively, these findings suggest that the VISTA pathway plays a conserved, non-redundant role in myeloid cell function., Competing Interests: RN is an inventor on patent applications (10035857, 9631018, 9217035, 8501915, 8465740, 8236304, and 8231872) submitted by Dartmouth College, and patent applications (9890215 and 9381244) submitted by Kings College London and Dartmouth College and a co-founder of ImmuNext, a company involved in the development of VISTA-related assets. These applications cover the use of VISTA targeting for modulation of the immune response. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 ElTanbouly, Zhao, Schaafsma, Burns, Mabaera, Cheng and Noelle.)

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 naïve B cells, NK cells, and CD8+ T cells was associated with improved patient prognosis. Naïve 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., Competing Interests: Conflicts of interest All authors declared that there are no conflicts of interest.

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., (© 2020 UICC.)

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 ., (Copyright © 2020 ElTanbouly, Schaafsma, Smits, Shah, Cheng, Burns, Blazar, Noelle and Mabaera.)

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 to generate prognostic gene signatures. Using ovarian cancer and lung adenocarcinoma as examples, we provide evidence that our prognostic signatures overperform 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 ).

Neoadjuvant chemotherapy is the current standard of care for large, advanced, and/or inoperable tumors, including triple-negative breast cancer. Although the clinical benefits of neoadjuvant chemotherapy have been illustrated through numerous clinical trials, more than half of the patients do not experience therapeutic benefit and needlessly suffer from side effects. Currently, no clinically applicable biomarkers are available for predicting neoadjuvant chemotherapy response in triple-negative breast cancer; the discovery of such a predictive biomarker or marker profile is an unmet need. In this study, we introduce a generic computational framework to calculate a response-probability score (RPS), based on patient transcriptomic profiles, to predict their response to neoadjuvant chemotherapy. We first validated this framework in ER-positive breast cancer patients and showed that it predicted neoadjuvant chemotherapy response with equal performance to several clinically used gene signatures, including Oncotype DX and MammaPrint. Then, we applied this framework to triple-negative breast cancer data and, for each patient, we calculated a response probability score (TNBC-RPS). Our results indicate that the TNBC-RPS achieved the highest accuracy for predicting neoadjuvant chemotherapy response compared to previously proposed 143 gene signatures. When combined with additional clinical factors, the TNBC-RPS achieved a high prediction accuracy for triple-negative breast cancer patients, which was comparable to the prediction accuracy of Oncotype DX and MammaPrint in ER-positive patients. In conclusion, the TNBC-RPS accurately predicts neoadjuvant chemotherapy response in triple-negative breast cancer patients and has the potential to be clinically used to aid physicians in stratifying patients for more effective neoadjuvant chemotherapy., (© 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

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., (© 2020, American College of Rheumatology.)

Background: The "dark matter" of the genome harbors several non-coding RNA species including Long non-coding RNAs (lncRNAs), which have been implicated in neoplasia but remain understudied. RNA-seq has provided deep insights into the nature of lncRNAs in cancer but current RNA-seq data are rarely accompanied by longitudinal patient survival information. In contrast, a plethora of microarray studies have collected these clinical metadata that can be leveraged to identify novel associations between gene expression and clinical phenotypes., Methods: In this study, we developed an analysis framework that computationally integrates RNA-seq and microarray data to systematically screen 9,463 lncRNAs for association with mortality risk across 20 cancer types., Results: In total, we identified a comprehensive list of associations between lncRNAs and patient survival and demonstrate that these prognostic lncRNAs are under selective pressure and may be functional. Our results provide valuable insights that facilitate further exploration of lncRNAs and their potential as cancer biomarkers and drug targets., Competing Interests: The authors declare that they have no competing interests., (© 2020 Ung et al.)

Negative checkpoint regulators (NCRs) temper the T cell immune response to self-antigens and limit the development of autoimmunity. Unlike all other NCRs that are expressed on activated T lymphocytes, V-type immunoglobulin domain-containing suppressor of T cell activation (VISTA) is expressed on naïve T cells. We report an unexpected heterogeneity within the naïve T cell compartment in mice, where loss of VISTA disrupted the major quiescent naïve T cell subset and enhanced self-reactivity. Agonistic VISTA engagement increased T cell tolerance by promoting antigen-induced peripheral T cell deletion. Although a critical player in naïve T cell homeostasis, the ability of VISTA to restrain naïve T cell responses was lost under inflammatory conditions. VISTA is therefore a distinctive NCR of naïve T cells that is critical for steady-state maintenance of quiescence and peripheral tolerance., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

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.

The role of negative checkpoint regulators (NCRs) in human health and disease cannot be overstated. V-domain Ig-containing Suppressor of T-cell Activation (VISTA) is an Ig superfamily protein predominantly expressed within the hematopoietic compartment and has been studied for its role in the negative regulation of T cell responses. The findings presented in this study show that, unlike all other NCRs, VISTA deficiency dramatically impacts on macrophage cytokine and chemokine production, as well as the chemotactic response of VISTA-deficient macrophages. A select group of inflammatory chemokines, including CCL2, CCL3, CCL4, and CCL5, was strikingly elevated in culture supernatants from VISTA KO macrophages. VISTA deficiency also altered chemokine receptor recycling and profoundly disrupted myeloid chemotaxis. The impact of VISTA deficiency on chemotaxis in vivo was apparent with the reduced ability of both KO macrophages and MDSCs to migrate to the tumor microenvironment. This is the first demonstration of an NCR impacting on myeloid mediator production and chemotaxis, and will guide the use of anti-VISTA therapeutics to manipulate the chemotaxis of inflammatory macrophages or immunosuppressive MDSCs in inflammatory diseases and cancer., (Copyright © 2019 Broughton, ElTanbouly, Schaafsma, Deng, Sarde, Croteau, Li, Nowak, Mabaera, Smits, Kuta, Noelle and Lines.)

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., (©2018 American Association for Cancer Research.)

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 ., (©2018 American Association for Cancer Research.)

Large-scale genomic data have been utilized to generate unprecedented biological findings and new hypotheses. To delineate functional elements in the human genome, the Encyclopedia of DNA Elements (ENCODE) project has generated an enormous amount of genomic data, yielding around 7,000 data profiles in different cell and tissue types. In this article, we reviewed the systematic analyses that have integrated ENCODE data with other data sources to reveal new biological insights, ranging from human genome annotation to the identification of new candidate drugs. These analyses demonstrate the critical impact of ENCODE data on basic biology and translational research., Competing Interests: Declarations of interest: none.

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.