Neoadjuvant Intratumoral Immunotherapy with Cowpea Mosaic Virus Induces Local and Systemic Antitumor Efficacy in Canine Mammary Cancer Patients.

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.

TimiGP: Inferring cell-cell interactions and prognostic associations in the tumor immune microenvironment through gene pairs.

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.

VISTA Targeting of T-cell Quiescence and Myeloid Suppression Overcomes Adaptive Resistance.

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.

Immune checkpoint gene VSIR predicts patient prognosis in acute myeloid leukemia and myelodysplastic syndromes.

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.

Microglia-Based Gene Expression Signature Highly Associated with Prognosis in Low-Grade Glioma.

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.

Tumor cell intrinsic and extrinsic features predict prognosis in estrogen receptor positive breast cancer.

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.

Predicting clinical outcomes of cancer patients with a p53 deficiency gene signature.

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.

B cell infiltration is highly associated with prognosis and an immune-infiltrated tumor microenvironment in neuroblastoma.

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.

Impact of Oncotype DX testing on ER+ breast cancer treatment and survival in the first decade of use.

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.

Pan-cancer association of HLA gene expression with cancer prognosis and immunotherapy efficacy.

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.

Influence of T Cell-Mediated Immune Surveillance on Somatic Mutation Occurrences in Melanoma.

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.

MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers.

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.

VISTA Re-programs Macrophage Biology Through the Combined Regulation of Tolerance and Anti-inflammatory Pathways.

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.

Gene signature-based prediction of triple-negative breast cancer patient response to Neoadjuvant chemotherapy.

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.

An EGFR signature predicts cell line and patient sensitivity to multiple tyrosine kinase inhibitors.

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.

Pan-cancer systematic identification of lncRNAs associated with cancer prognosis.

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.

Whole transcriptome signature for prognostic prediction (WTSPP): application of whole transcriptome signature for prognostic prediction in cancer.

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 ).

Profibrotic Activation of Human Macrophages in Systemic Sclerosis.

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 ß 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.

VISTA is a checkpoint regulator for naïve T cell quiescence and peripheral tolerance.

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.