Genomic Characterization of Six Virus-Associated Cancers Identifies Changes in the Tumor Immune Microenvironment and Altered Genetic Programs

Update: The molecular spectrum of virus-associated high-grade B-cell non-Hodgkin lymphomas

The vast spectrum of aggressive B-cell non-Hodgkin neoplasms (B-NHL) encompasses several infrequent entities occurring in association with viral infections, posing diagnostic challenges for practitioners. In the emerging era of precision oncology, the molecular characterization of malignancies has acquired paramount significance. The pathophysiological comprehension of specific entities and the identification of targeted therapeutic options have seen rapid development. However, owing to their rarity, not all entities have undergone exhaustive molecular characterization. Considerable heterogeneity exists in the extant body of work, both in terms of employed methodologies and the scale of cases studied. Presently, therapeutic strategies are predominantly derived from observations in diffuse large B-cell lymphoma (DLBCL), the most prevalent subset of aggressive B-NHL. Ongoing investigations into the molecular profiles of these uncommon virus-associated entities are progressively facilitating a clearer distinction from DLBCL, ultimately paving the way towards individualized therapeutic approaches. This review consolidates the current molecular insights into aggressive and virus-associated B-NHL, taking into consideration the recently updated 5th edition of the WHO classification of hematolymphoid tumors (WHO-5HAEM) and the International Consensus Classification (ICC). Additionally, potential therapeutically targetable susceptibilities are highlighted, offering a comprehensive overview of the present scientific landscape in the field.

Molecular subtyping based on immune cell marker genes predicts prognosis and therapeutic response in patients with lung adenocarcinoma

OBJECTIVE

Lung adenocarcinoma (LA) is one of the most common malignancies and is responsible for the greatest number of tumor-related deaths. Our research aimed to explore the molecular subtype signatures of LA to clarify the correlation among the immune microenvironment, clinical outcomes, and therapeutic response.

METHODS

The LA immune cell marker genes (LICMGs) identified by single-cell RNA sequencing (scRNA-seq) analysis were used to discriminate the molecular subtypes and homologous immune and metabolic traits of GSE72094 LA cases. In addition, the model-building genes were identified from 1441 LICMGs by Cox-regression analysis, and a LA immune difference score (LIDscore) was developed to quantify individual differences in each patient, thereby predicting prognosis and susceptibility to immunotherapy and chemotherapy of LA patients.

RESULTS

Patients of the GSE72094 cohort were divided into two distinct molecular subtypes based on LICMGs: immune activating subtype (Cluster-C1) and metabolically activating subtype (cluster-C2). The two molecular subtypes have distinct characteristics regarding prognosis, clinicopathology, genomics, immune microenvironment, and response to immunotherapy. Among the LICMGs, LGR4, GOLM1, CYP24A1, SFTPB, COL1A1, HLA-DQA1, MS4A7, PPARG, and IL7R were enrolled to construct a LIDscore model. Low-LIDscore patients had a higher survival rate due to abundant immune cell infiltration, activated immunity, and lower genetic variation, but probably the higher levels of Treg cells in the immune microenvironment lead to immune cell dysfunction and promote tumor immune escape, thus decreasing the responsiveness to immunotherapy compared with that of the high-LIDscore patients. Overall, high-LIDscore patients had a higher responsiveness to immunotherapy and a higher sensitivity to chemotherapy than the low-LIDscore group.

CONCLUSIONS

Molecular subtypes based on LICMGs provided a promising strategy for predicting patient prognosis, biological characteristics, and immune microenvironment features. In addition, they helped identify the patients most likely to benefit from immunotherapy and chemotherapy.

Influence of pathogens on host genome and epigenome in development of head and neck cancer

BACKGROUND

Head and neck cancer (HNSCC) is a heterogeneous group of cancers, affecting multiple regions such as oral cavity, pharynx, larynx, and nasal region, each showing a distinct molecular profile. HNSCC accounts for more than 6 million cases worldwide, soaring mainly in the developing countries.

RECENT FINDINGS

The aetiology of HNSCC is complex and multifactorial, involving both genetic and environmental factors. The critical role of microbiome, which includes bacteria, viruses, and fungi, is under spotlight due to the recent reports on their contribution in the development and progression of HNSCC. This review focuses on the effect of opportunistic pathogens on the host genome and epigenome, which contributes to the disease progression. Drawing parallels from the host-pathogen interactions observed in other tumour types arising from the epithelial tissue such as colorectal cancer, the review also calls attention to the potential explorations of the role of pathogens in HNSCC biology and discusses the clinical implications of microbiome research in detection and treatment of HNSCC.

CONCLUSION

Our understanding of the genomic effects of the microbes on the disease progression and the mechanistic insights of the host-pathogen interaction will pave way to novel treatment and preventive approaches in HNSCC.

Emerging roles of plasmacytoid dendritic cell crosstalk in tumor immunity

Plasmacytoid dendritic cells (pDCs) are a pioneer cell type that produces type I interferon (IFN-I) and promotes antiviral immune responses. However, they are tolerogenic and, when recruited to the tumor microenvironment (TME), play complex roles that have long been a research focus. The interactions between pDCs and other components of the TME, whether direct or indirect, can either promote or hinder tumor development; consequently, pDCs are an intriguing target for therapeutic intervention. This review provides a comprehensive overview of pDC crosstalk in the TME, including crosstalk with various cell types, biochemical factors, and microorganisms. An in-depth understanding of pDC crosstalk in TME should facilitate the development of novel pDC-based therapeutic methods.

Natural killer cells and their exosomes in viral infections and related therapeutic approaches: where are we?

Innate immunity is the first line of the host immune system to fight against infections. Natural killer cells are the innate immunity lymphocytes responsible for fighting against virus-infected and cancerous cells. They have various mechanisms to suppress viral infections. On the other hand, viruses have evolved to utilize different ways to evade NK cell-mediated responses. Viruses can balance the response by regulating the cytokine release pattern and changing the proportion of activating and inhibitory receptors on the surface of NK cells. Exosomes are a subtype of extracellular vesicles that are involved in intercellular communication. Most cell populations can release these nano-sized vesicles, and it was shown that these vesicles produce identical outcomes to the originating cell from which they are released. In recent years, the role of NK cell-derived exosomes in various diseases including viral infections has been highlighted, drawing attention to utilizing the therapeutic potential of these nanoparticles. In this article, the role of NK cells in various viral infections and the mechanisms used by viruses to evade these important immune system cells are initially examined. Subsequently, the role of NK cell exosomes in controlling various viral infections is discussed. Finally, the current position of these cells in the treatment of viral infections and the therapeutic potential of their exosomes are reviewed. Video Abstract.

Immune Infiltration in Tumor and Adjacent Non-Neoplastic Regions Codetermines Patient Clinical Outcomes in Early-Stage Lung Cancer

INTRODUCTION

In recent years, the proportion of patients with NSCLC diagnosed at an early stage has increased continuously.

METHODS

In this study, we analyzed samples and data collected from 119 samples from 67 early stage patients with NSCLC, including 52 pairs of tumor and adjacent non-neoplastic samples, and performed RNA-sequencing analysis with high sequencing depth.

RESULTS

We found that immune-related genes were highly enriched among the differentially expressed genes and observed significantly higher inferred immune infiltration levels in adjacent non-neoplastic samples than in tumor samples. In survival analysis, the infiltration of certain immune cell types in tumor, but not adjacent non-neoplastic, samples were associated with overall patient survival, and excitingly, the differential infiltration between paired samples (tumor minus non-neoplastic) was more prognostic than expression in either non-neoplastic or tumor tissues. We also performed B cell receptor (BCR) and T cell receptor (TCR) repertoire analysis and observed more BCR/TCR clonotypes and increased BCR clonality in tumor than in non-neoplastic samples. Finally, we carefully quantified the fraction of the five histologic subtypes in our adenocarcinoma samples and found that higher histologic pattern complexity was associated with higher immune infiltration and low TCR clonality in the tumor-proximal regions.

CONCLUSIONS

Our results indicated significantly differential immune characteristics between tumor and adjacent non-neoplastic samples and suggested that the two regions provided complementary prognostic values in early-stage NSCLCs.

A lipid metabolism-based prognostic risk model for HBV-related hepatocellular carcinoma

BACKGROUND

Up to 85% of hepatocellular carcinoma (HCC) cases in China can be attributed to infection of hepatitis B virus (HBV). Lipid metabolism performs important function in hepatocarcinogenesis of HBV-related liver carcinoma. However, limited studies have explored the prognostic role of lipid metabolism in HBV-related HCC. This study established a prognostic model to stratify HBV-related HCC based on lipid metabolisms.

METHODS

Based on The Cancer Genome Atlas HBV-related HCC samples, this study selected prognosis-related lipid metabolism genes and established a prognosis risk model by performing uni- and multi-variate Cox regression methods. The final markers used to establish the model were selected through the least absolute shrinkage and selection operator method. Analysis of functional enrichment, immune landscape, and genomic alteration was utilized to investigate the inner molecular mechanism involved in prognosis.

RESULTS

The risk model independently stratified HBV-infected patients with liver cancer into two risk groups. The low-risk groups harbored longer survival times (with P < 0.05, log-rank test). TP53, LRP1B, TTN, and DNAH8 mutations and high genomic instability occurred in high-risk groups. Low-risk groups harbored higher CD8 T cell infiltration and BTLA expression. Lipid-metabolism (including "Fatty acid metabolism") and immune pathways were significantly enriched (P < 0.05) in the low-risk groups.

CONCLUSIONS

This study established a robust model to stratify HBV-related HCC effectively. Analysis results decode in part the heterogeneity of HBV-related liver cancer and highlight perturbation of lipid metabolism in HBV-related HCC. This study's findings could facilitate patients' clinical classification and give hints for treatment selection.

Immune landscape of viral cancers: Insights from single-cell sequencing

Viral infections trigger a wide range of immune responses thought to drive tumorigenesis and malignant progression. Dissecting virus-induced changes in the tumor immune microenvironment (TIME) is therefore crucial to identify key leukocyte populations that may represent novel targets for cancer therapy. Single-cell sequencing approaches have now been widely applied to the analysis of various tumors, thus enabling multiomics characterization of the highly heterogeneous TIME that bulk-sequencing cannot fully elucidate. In this review, we summarized key recent findings from sequencing studies of the immune infiltrate and antitumor response in virus-associated cancers at single cell resolution. Additionally, we also reviewed recent developments in immunotherapy for virus-associated cancers. We anticipate that the strategic use of single-cell sequencing will advance our understanding of the TIME of viral cancers, leading to the development of more potent novel treatments.

Immune Microenvironment and Immunotherapeutic Management in Virus-Associated Digestive System Tumors

The development of cancer is a multifactorial phenomenon, while it constitutes a major global health problem. Viruses are an important factor that is involved in tumorigenesis and is associated with 12.1% of all cancer cases. Major examples of oncogenic viruses which are closely associated with the digestive system are HBV, HCV, EBV, HPV, JCV, and CMV. EBV, HPV, JCV, and CMV directly cause oncogenesis by expressing oncogenic proteins that are encoded in their genome. In contrast, HBV and HCV are correlated indirectly with carcinogenesis by causing chronic inflammation in the infected organs. In addition, the tumor microenvironment contains various immune cells, endothelial cells, and fibroblasts, as well as several growth factors, cytokines, and other tumor-secreted molecules that play a key role in tumor growth, progression, and migration, while they are closely interrelated with the virus. The presence of T-regulatory and B-regulatory cells in the tumor microenvironment plays an important role in the anti-tumor immune reaction. The tumor immune microenvironments differ in each type of cancer and depend on viral infection. The alterations in the immune microenvironment caused by viruses are also reflected in the effectiveness of immunotherapy. The present review aims at shedding light on the association between viruses and digestive system malignancies, the characteristics of the tumor immune microenvironment that develop, and the possible treatments that can be administered.

A combination of intrinsic and extrinsic features improves prognostic prediction in malignant pleural mesothelioma

BACKGROUND

Malignant pleural mesothelioma (MPM) is a lung pleural cancer with very poor disease outcome. With limited curative MPM treatment available, it is vital to study prognostic biomarkers to categorise different patient risk groups.

METHODS

We defined gene signatures to separately characterise intrinsic and extrinsic features, and investigated their interactions in MPM tumour samples. Specifically, we calculated gene signature scores to capture the downstream pathways of major mutated driver genes (BAP1, NF2, SETD2 and TP53) as tumour-intrinsic features. Similarly, we inferred the infiltration levels for major immune cells in the tumour microenvironment to characterise tumour-extrinsic features. Lastly, we integrated these features with clinical factors to predict prognosis in MPM.

RESULTS

The gene signature scores were more prognostic than the corresponding genomic mutations, mRNA and protein expression. High immune infiltration levels were associated with prolonged survival. The integrative model indicated that tumour features provided independent prognostic values than clinical factors and were complementary with each other in survival prediction.

CONCLUSIONS

By using an integrative model that combines intrinsic and extrinsic features, we can more correctly predict the clinical outcomes of patients with MPM.

LAG-3 as a Potent Target for Novel Anticancer Therapies of a Wide Range of Tumors

LAG-3 (Lymphocyte activation gene 3) protein is a checkpoint receptor that interacts with LSEC-tin, Galectin-3 and FGL1. This interaction leads to reduced production of IL-2 and IFN-γ. LAG-3 is widely expressed in different tumor types and modulates the tumor microenvironment through immunosuppressive effects. Differential expression in various tumor types influences patient prognosis, which is often associated with coexpression with immune checkpoint inhibitors, such as TIM-3, PD-1 and CTLA-4. Here, we discuss expression profiles in different tumor types. To date, many clinical trials have been conducted using LAG-3 inhibitors, which can be divided into anti-LAG-3 monoclonal antibodies, anti-LAG-3 bispecifics and soluble LAG-3-Ig fusion proteins. LAG-3 inhibitors supress T-cell proliferation and activation by disallowing for the interaction between LAG-3 to MHC-II. The process enhances anti-tumor immune response. In this paper, we will review the current state of knowledge on the structure, function and expression of LAG-3 in various types of cancer, as well as its correlation with overall prognosis, involvement in cell-based therapies and experimental medicine. We will consider the role of compounds targeting LAG-3 in clinical trials both as monotherapy and in combination, which will provide data relating to the efficacy and safety of proposed drug candidates.

Melanoma-specific antigen-associated antitumor antibody reactivity as an immune-related biomarker for targeted immunotherapies

Background:

Immunotherapies, including cancer vaccines and immune checkpoint inhibitors have transformed the management of many cancers. However, a large number of patients show resistance to these immunotherapies and current research has provided limited findings for predicting response to precision immunotherapy treatments.

Methods:

Here, we applied the next generation phage display mimotope variation analysis (MVA) to profile antibody response and dissect the role of humoral immunity in targeted cancer therapies, namely anti-tumor dendritic cell vaccine (MelCancerVac^®) and immunotherapy with anti-PD-1 monoclonal antibodies (pembrolizumab).

Results:

Analysis of the antibody immune response led to the characterization of epitopes that were linked to melanoma-associated and cancer-testis antigens (CTA) whose antibody response was induced upon MelCancerVac® treatments of lung cancer. Several of these epitopes aligned to antigens with strong immune response in patients with unresectable metastatic melanoma receiving anti-PD-1 therapy.

Conclusions:

This study provides insights into the differences and similarities in tumor-specific immunogenicity related to targeted immune treatments. The antibody epitopes as biomarkers reflect melanoma-associated features of immune response, and also provide insights into the molecular pathways contributing to the pathogenesis of cancer. Concluding, antibody epitope response can be useful in predicting anti-cancer immunity elicited by immunotherapy.

Immunotherapy treatments, which utilize the patient’s own immune system to fight cancer, have become a standard treatment of cancer. However, for many patients’ immunotherapy does not work. During the immune response the body produces proteins called antibodies. This study characterized the antibodies produced following treatment with two different types of immunotherapies that treat skin cancer, to gain insights into how the immune system responds in different individuals. Our results demonstrate that multiple proteins that are present in patients with skin cancer are specifically targeted by the immune system during skin cancer specific immunotherapy. Our results should help further anti-cancer drug development.

Rähni et al profile antibody response in patients with varied response to cancer immunotherapies. They identify antibody epitope responses that predict anti-cancer immunity elicited by immunotherapy.

Comprehensive Analysis of the Carcinogenic Process, Tumor Microenvironment, and Drug Response in HPV-Positive Cancers

Human papillomavirus (HPV) is a common virus, and about 5% of all cancers worldwide is caused by persistent high-risk HPV infections. Here, we reported a comprehensive analysis of the molecular features for HPV-related cancer types using TCGA (The Cancer Genome Atlas) data with HPV status. We found that the HPV-positive cancer patients had a unique oncogenic process, tumor microenvironment, and drug response compared with HPV-negative patients. In addition, HPV improved overall survival for the four cancer types, namely, cervical squamous cell carcinoma (CESC), head and neck squamous cell carcinoma (HNSC), stomach adenocarcinoma (STAD), and uterine corpus endometrial carcinoma (UCEC). The stronger activity of cell-cycle pathways and lower driver gene mutation rates were observed in HPV-positive patients, which implied the different carcinogenic processes between HPV-positive and HPV-negative groups. The increased activities of immune cells and differences in metabolic pathways helped explain the heterogeneity of prognosis between the two groups. Furthermore, we constructed HPV prediction models for different cancers by the virus infection score (VIS) which was linearly correlated with HPV load and found that VIS was associated with drug response. Altogether, our study reveals that HPV-positive cancer patients have unique molecular characteristics which help the development of precision medicine in HPV-positive cancers.

A lepidic gene signature predicts patient prognosis and sensitivity to immunotherapy in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma, the most common type of lung cancer, has a high level of morphologic heterogeneity and is composed of tumor cells of multiple histological subtypes. It has been reported that immune cell infiltration significantly impacts clinical outcomes of patients with lung adenocarcinoma. However, it is unclear whether histologic subtyping can reflect the tumor immune microenvironment, and whether histologic subtyping can be applied for therapeutic stratification of the current standard of care.

METHODS

We inferred immune cell infiltration levels using a histological subtype-specific gene expression dataset. From differential gene expression analysis between different histological subtypes, we developed two gene signatures to computationally determine the relative abundance of lepidic and solid components (denoted as the L-score and S-score, respectively) in lung adenocarcinoma samples. These signatures enabled us to investigate the relationship between histological composition and clinical outcomes in lung adenocarcinoma using previously published datasets.

RESULTS

We found dramatic immunological differences among histological subtypes. Differential gene expression analysis showed that the lepidic and solid subtypes could be differentiated based on their gene expression patterns while the other subtypes shared similar gene expression patterns. Our results indicated that higher L-scores were associated with prolonged survival, and higher S-scores were associated with shortened survival. L-scores and S-scores were also correlated with global genomic features such as tumor mutation burdens and driver genomic events. Interestingly, we observed significantly decreased L-scores and increased S-scores in lung adenocarcinoma samples with EGFR gene amplification but not in samples with EGFR gene mutations. In lung cancer cell lines, we observed significant correlations between L-scores and cell sensitivity to a number of targeted drugs including EGFR inhibitors. Moreover, lung cancer patients with higher L-scores were more likely to benefit from immune checkpoint blockade therapy.

CONCLUSIONS

Our findings provided further insights into evaluating histology composition in lung adenocarcinoma. The established signatures reflected that lepidic and solid subtypes in lung adenocarcinoma would be associated with prognosis, genomic features, and responses to targeted therapy and immunotherapy. The signatures therefore suggested potential clinical translation in predicting patient survival and treatment responses. In addition, our framework can be applied to other types of cancer with heterogeneous histological subtypes.

EBV-associated diseases: Current therapeutics and emerging technologies

EBV is a prevalent virus, infecting >90% of the world's population. This is an oncogenic virus that causes ~200,000 cancer-related deaths annually. It is, in addition, a significant contributor to the burden of autoimmune diseases. Thus, EBV represents a significant public health burden. Upon infection, EBV remains dormant in host cells for long periods of time. However, the presence or episodic reactivation of the virus increases the risk of transforming healthy cells to malignant cells that routinely escape host immune surveillance or of producing pathogenic autoantibodies. Cancers caused by EBV display distinct molecular behaviors compared to those of the same tissue type that are not caused by EBV, presenting opportunities for targeted treatments. Despite some encouraging results from exploration of vaccines, antiviral agents and immune- and cell-based treatments, the efficacy and safety of most therapeutics remain unclear. Here, we provide an up-to-date review focusing on underlying immune and environmental mechanisms, current therapeutics and vaccines, animal models and emerging technologies to study EBV-associated diseases that may help provide insights for the development of novel effective treatments.

Antiviral Responses in Cancer: Boosting Antitumor Immunity Through Activation of Interferon Pathway in the Tumor Microenvironment

In recent years, it became apparent that cancers either associated with viral infections or aberrantly expressing endogenous retroviral elements (EREs) are more immunogenic, exhibiting an intense intra-tumor immune cell infiltration characterized by a robust cytolytic apparatus. On the other hand, epigenetic regulation of EREs is crucial to maintain steady-state conditions and cell homeostasis. In line with this, epigenetic disruptions within steady-state cells can lead to cancer development and trigger the release of EREs into the cytoplasmic compartment. As such, detection of viral molecules by intracellular innate immune sensors leads to the production of type I and type III interferons that act to induce an antiviral state, thus restraining viral replication. This knowledge has recently gained momentum due to the possibility of triggering intratumoral activation of interferon responses, which could be used as an adjuvant to elicit strong anti-tumor immune responses that ultimately lead to a cascade of cytokine production. Accordingly, several therapeutic approaches are currently being tested using this rationale to improve responses to cancer immunotherapies. In this review, we discuss the immune mechanisms operating in viral infections, show evidence that exogenous viruses and endogenous retroviruses in cancer may enhance tumor immunogenicity, dissect the epigenetic control of EREs, and point to interferon pathway activation in the tumor milieu as a promising molecular predictive marker and immunotherapy target. Finally, we briefly discuss current strategies to modulate these responses within tumor tissues, including the clinical use of innate immune receptor agonists and DNA demethylating agents.

The viral expression and immune status in human cancers and insights into novel biomarkers of immunotherapy

BACKGROUND

Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, their potential of shaping the tumor immune microenvironment (TIME) has been related to the immunotherapy of human cancers. However, the landscape of viral expressions and immune status in human cancers remains incompletely understood.

METHODS

We developed a next-generation sequencing (NGS)-based pipeline to detect viral sequences from the whole transcriptome and used machine learning algorithms to classify different TIME subtypes.

RESULTS

We revealed a pan-cancer landscape of viral expressions in human cancers where 9 types of viruses were detected in 744 tumors of 25 cancer types. Viral infections showed different tissue tendencies and expression levels. Multi-omics analyses further revealed their distinct impacts on genomic, transcriptomic and immune responses. Epstein-Barr virus (EBV)-infected stomach adenocarcinoma (STAD) and Human Papillomavirus (HPV)-infected head and neck squamous cell carcinoma (HNSC) showed decreased genomic variations, significantly altered gene expressions, and effectively triggered anti-viral immune responses. We identified three TIME subtypes, in which the "Immune-Stimulation" subtype might be the promising candidate for immunotherapy. EBV-infected STAD and HPV-infected HNSC showed a higher frequency of the "Immune-Stimulation" subtype. Finally, we constructed the eVIIS pipeline to simultaneously evaluate viral infection and immune status in external datasets.

CONCLUSIONS

Viral infections are prevalent in human cancers and have distinct influences on hosts. EBV and HPV infections combined with the TIME subtype could be promising biomarkers of immunotherapy in STAD and HNSC, respectively. The eVIIS pipeline could be a practical tool to facilitate clinical practice and relevant studies.

Presence of high-risk HPVs, EBV, and MMTV in human triple-negative breast cancer

Breast cancer, the most frequent disease amongst women worldwide, accounts for the highest cancer-related mortality rate. Triple-negative breast cancer (TNBC) subtype encompasses ~15% of all breast cancers and lack estrogen, progesterone, and HER2 receptors. Although risk factors for breast cancer are well-known, factors underpinning breast cancer onset and progression remain unknown. Recent studies suggest the plausible role of oncoviruses including human papillomaviruses (HPVs), Epstein-Barr virus (EBV), and mouse mammary tumor virus (MMTV) in breast cancer pathogenesis. However, the role of these oncoviruses in TNBC is still unclear. In the current study, we explored the status of high-risk HPVs, EBV, and MMTV in a well-defined TNBC cohort from Croatia in comparison to 16 normal/non TNBC samples (controls) using polymerase chain reaction assay. We found high-risk HPVs and EBV present in 37/70 (53%) and 25/70 (36%) of the cases, respectively. The most common HPV types are 52, 45, 31, 58 and 68. We found 16% of the samples positive for co-presence of high-risk HPVs and EBV. Moreover, our data revealed that 5/70 (7%) samples are positive for MMTV. In addition, only 2/70 (3%) samples had co-presence of HPVs, EBV, and MMTV without any significant association with the clinicopathological variables. While, 6/16 (37.5%) controls were positive for HPV (p = .4), EBV was absent in all controls (0/16, 0%) (p = .01). In addition, we did not find the co-presence of the oncoviruses in the controls (p > .05). Nevertheless, further investigations are essential to understand the underlying mechanisms of multiple-oncogenic viruses' interaction in breast carcinogenesis, especially TNBC.

Crosstalk between Environmental Inflammatory Stimuli and Non-Coding RNA in Cancer Occurrence and Development

Simple Summary

Increasing evidence has indicated that chronic inflammatory processes have an influence on tumor occurrence and all stages of tumor development. A dramatic increase of studies into non-coding RNAs (ncRNAs) biology has shown that ncRNAs act as oncogenic drivers and tumor suppressors in various inflammation-induced cancers. Thus, this complex network of inflammation-associated cancers and ncRNAs offers targets for prevention from the malignant transformation from inflammation and treatment of malignant diseases.

Abstract

There is a clear relationship between inflammatory response and different stages of tumor development. Common inflammation-related carcinogens include viruses, bacteria, and environmental mutagens, such as air pollutants, toxic metals, and ultraviolet light. The expression pattern of ncRNA changes in a variety of disease conditions, including inflammation and cancer. Non-coding RNAs (ncRNAs) have a causative role in enhancing inflammatory stimulation and evading immune responses, which are particularly important in persistent pathogen infection and inflammation-to-cancer transformation. In this review, we investigated the mechanism of ncRNA expression imbalance in inflammation-related cancers. A better understanding of the function of inflammation-associated ncRNAs may help to reveal the potential of ncRNAs as a new therapeutic strategy.

Genomic and Immunologic Correlates of Indoleamine 2,3-Dioxygenase Pathway Expression in Cancer

Immune checkpoint blockade leads to unprecedented responses in many cancer types. An alternative method of unleashing anti-tumor immune response is to target immunosuppressive metabolic pathways like the indoleamine 2,3-dioxygenase (IDO) pathway. Despite promising results in Phase I/II clinical trials, an IDO-1 inhibitor did not show clinical benefit in a Phase III clinical trial. Since, a treatment can be quite effective in a specific subset without being effective in the whole cancer type, it is important to identify the subsets of cancers that may benefit from IDO-1 inhibitors. In this study, we looked for the genomic and immunologic correlates of IDO pathway expression in cancer using the Cancer Genome Atlas (TCGA) dataset. Strong CD8+ T-cell infiltration, high mutation burden, and expression of exogenous viruses [Epstein-Barr virus (EBV), Human papilloma virus (HPV), and Hepatitis C virus (HCV)] or endogenous retrovirus (ERV3-2) were associated with over-expression of IDO-1 in most cancer types, IDO-2 in many cancer types, and TDO-2 in a few cancer types. High mutation burden in ER+ HER2- breast cancer, and ERV3-2 expression in ER- HER2- and HER2+ breast, colon, and endometrial cancers were associated with over-expression of all three genes. These results may have important implications for guiding development clinical trials of IDO-1 inhibitors.

Mouse Mammary Tumor Virus (MMTV)-Like env Sequence in Brazilian Breast Cancer Samples: Implications in Clinicopathological Parameters in Molecular Subtypes

Background: Breast cancer (BC) is a complex disease in which susceptibility and clinical course depend on multiple factors. Evidence suggests that a mouse mammary tumor virus (MMTV)-homolog may be present in human BCs; however, little is known about its clinical implications. Methods: MMTV-like env nucleotide-sequence was searched in tumor and tumor-adjacent tissues from 217 Brazilian BC patients through nested-PCR and confirmed through PCR-sequencing. Blood samples were also tested for patients with MMTV-like env gene-positive tumors. Correlations with clinicopathological parameters were evaluated. Results: MMTV-like env sequence was detected in tumor and tumor-adjacent tissue samples from 41/217 and 30/196 patients, respectively. In blood, MMTV-like was detected in 17/32 patients. In Luminal-B tumors, MMTV-like in tumor tissue was negatively correlated with tumor size and disease stage, whereas in HER2 tumors it anti-correlated with lymph node metastasis (LNM) and disease stage. Considering blood, MMTV-like env gene positivity negatively correlated with age in general BC, while in Luminal-A tumors it positively correlated with Ki67 but negatively correlated with age and LNM. The associations with decreased LNM frequency were independent of other prognostic factors. Conclusion: MMTV-like env positivity is associated with better prognostic parameters in BC subtypes, which might be explainable by its anti-metastatic potential and by putative activation of immune milieu.

A meta-learning approach for genomic survival analysis

RNA sequencing has emerged as a promising approach in cancer prognosis as sequencing data becomes more easily and affordably accessible. However, it remains challenging to build good predictive models especially when the sample size is limited and the number of features is high, which is a common situation in biomedical settings. To address these limitations, we propose a meta-learning framework based on neural networks for survival analysis and evaluate it in a genomic cancer research setting. We demonstrate that, compared to regular transfer-learning, meta-learning is a significantly more effective paradigm to leverage high-dimensional data that is relevant but not directly related to the problem of interest. Specifically, meta-learning explicitly constructs a model, from abundant data of relevant tasks, to learn a new task with few samples effectively. For the application of predicting cancer survival outcome, we also show that the meta-learning framework with a few samples is able to achieve competitive performance with learning from scratch with a significantly larger number of samples. Finally, we demonstrate that the meta-learning model implicitly prioritizes genes based on their contribution to survival prediction and allows us to identify important pathways in cancer.

Soluble PD-1: Predictive, Prognostic, and Therapeutic Value for Cancer Immunotherapy

Programmed death protein 1 (PD-1) interaction with PD-L1 deliver immunosuppressive environment for tumor growth, and its blockade with directed monoclonal antibodies (anti-PD-1/anti-PD-L1) has shown remarkable clinical outcome. Lately, their soluble counterparts, sPD-1 and sPD-L1, have been detected in plasma, and elevated levels have been associated with advanced disease, clinical stages, and worst prognosis for cancer patients. Elevated plasma levels of sPD-L1 have been correlated with worst prognosis in several studies and has displayed a persistent outlook. On the other hand, sPD-1 levels have been inconsistent in their predictive and prognostic ability. Pretherapeutic higher sPD-1 plasma levels have shown to predict advanced disease state and to a lesser extent worst prognosis. Any increase in sPD-1 plasma level post therapeutically have been correlated with improved survival for various cancers. In vitro and in vivo studies have shown sPD-1 ability to bind PD-L1 and PD-L2 and block PD-1/PD-L1 interaction. Local delivery of sPD-1 in cancer tumor microenvironment through local gene therapy have demonstrated an increase in tumor specific CD8+ T cell immunity and tumor growth reduction. It had also exhibited enhancement of T cell immunity induced by vaccination and other gene therapeutic agents. Furthermore, it may also lessen the inhibitory effect of circulating sPD-L1 and enhance the effects of mAb-based immunotherapy. In this review, we highlight various aspects of sPD-1 role in cancer prediction, prognosis, and anti-cancer immunity, as well as, its therapeutic value for local gene therapy or systemic immunotherapy in blocking the PD-1 and PD-L1 checkpoint interactions.

Enhancing antitumor immunity through checkpoint blockade as a therapeutic strategy in T-cell lymphomas

The majority of historical therapies for managing T-cell lymphomas (TCLs) have consisted of T-cell-depleting strategies. Unfortunately, these forms of therapies can hamper the ability to mount effective antitumor immune responses. Recently, the use of checkpoint inhibitors has revolutionized the therapy of solid and hematologic malignancies. The development of immunotherapies for the management of TCL has lagged behind other malignancies given 2 central reasons: (1) the competing balance of depleting malignant T cells while simultaneously enhancing an antitumor T-cell response and (2) concern for tumor hyperprogression by blocking inhibitory signals on the surface of the malignant T cell, thereby leading to further proliferation of the malignant cells. These challenges were highlighted with the discovery that programmed cell death protein 1 (PD-1) functions paradoxically as a haploinsufficient tumor suppressor in preclinical TCL models. In contrast, some preclinical and clinical evidence suggests that PD-1/programmed death ligand 1 may become an important therapeutic tool in the management of patients with TCL. Improved understanding of the immune landscape of TCL is necessary in order to identify subsets of patients most likely to benefit from checkpoint-inhibitor therapy. With increased preclinical research focus on the tumor microenvironment, substantial strides are being made in understanding how to harness the power of the immune system to treat TCLs. In this review, designed to be a "call to action," we discuss the challenges and opportunities of using immune-modulating therapies, with a focus on checkpoint inhibitors, for the treatment of patients with TCL.

The Cancer-Immune Set Point in Oesophageal Cancer

Immunotherapy has achieved long-term disease control in a proportion of cancer patients, but determinants of clinical benefit remain unclear. A greater understanding of antitumor immunity on an individual basis is needed to facilitate a precision oncology approach. A conceptual framework called the "cancer-immune set point" has been proposed to describe the equilibrium between factors that promote or suppress anticancer immunity and can serve as a basis to understand the variability in clinical response to immune checkpoint blockade. Oesophageal cancer has a high mutational burden, develops from pre-existing chronic inflammatory lesions and is therefore anticipated to be sensitive to immune checkpoint inhibition. However, both tumour- and patient-specific factors including the immune microenvironment, the microbiome, obesity, and host genetics contribute to an immune set point that confers a lower-than-expected response to checkpoint blockade. Immunotherapy is therefore currently confined to latter lines of treatment of advanced disease, with no reliable predictive biomarker of response. In this review, we examine oesophageal cancer in the context of the cancer-immune set point, discuss factors that contribute to response to immunotherapeutic intervention, and propose areas requiring further investigation to improve treatment response.

Genomic and immunologic correlates of LAG-3 expression in cancer

Immune checkpoint blockade leads to unprecedented responses in many cancers. Although currently available agents mostly target the PD-1 and CTLA-4 pathways, agents targeting the immune checkpoint protein LAG-3 are under active clinical development, and early clinical data show that LAG-3 expression is a biomarker of response to LAG-3 blockade. To determine which cancers may benefit most from LAG-3 blockade, we performed a pan-cancer analysis of The Cancer Genome Atlas dataset to identify genomic and immunologic correlates of LAG-3 expression. High mutation burden, and expression of exogenous virus (EBV, HPV) or endogenous retrovirus (ERV3-2), were associated with overexpression of LAG-3 in multiple cancers. Although CD8+ T-cell marker (CD8A) and LAG-3 were strongly co-expressed with each other and with PD-L1 in most cancers, there were three notable exceptions: HPV+ head-neck squamous cell cancer, renal cell cancer, and glioblastoma. These results may have important implications for guiding development clinical trials of LAG-3 blockade.

Progress Toward Identifying Exact Proxies for Predicting Response to Immunotherapies

Clinical value and utility of checkpoint inhibitors, a drug class targeting adaptive immune suppression pathways (PD-1, PDL-1, and CTLA-4), is growing rapidly and maintains status of a landmark achievement in oncology. Their efficacy has transformed life expectancy in multiple deadly cancer types (melanoma, lung cancer, renal/urothelial carcinoma, certain colorectal cancers, lymphomas, etc.). Despite significant clinical development efforts, therapeutic indication of approved checkpoint inhibitors are not as wide as the oncology community and patients would like them to be, potentially bringing into question their universal efficacy across tumor histologies. With the main goal of expanding immunotherapy applications, identifying of biomarkers to accurately predict therapeutic response and treatment related side-effects are a paramount need in the field. Specificities surrounding checkpoint inhibitors in clinic, such as unexpected tumor response patterns (pseudo- and hyper-progression), late responders, as well as specific immune mediated toxicities, complicate the management of patients. They stem from the complexities and dynamics of the tumor/host immune interactions, as well as baseline tumor biology. Search for clinically effective biomarkers therefore calls for a holistic approach, rather than implementation of a single analyte. The goal is to achieve dynamic and comprehensive acquisition, analyses and interpretation of immunological and biologic information about the tumor and the immune system, and to compute these parameters into an actionable, maximally predictive value at the individual patient level. Limitation delaying swift incorporation of validated immuno-oncology biomarkers span from standardized biospecimens acquisition and processing, selection of proficient biomarker discovery and validation methods, to establishing multidisciplinary consortiums and data sharing platforms. Multi-disciplinary efforts have already yielded some approved (PDL-1 and MSI-status) and other advanced tests (TMB, neoantigen pattern, and TIL infiltration rate). Importantly, clinical trial taskforces now recognize the imperative of the biomarker-driven trial design and execution, to enable translating biomarker discoveries into the clinical setting. This will ensure we utilize the “conspiracy” between the peripheral and intra-tumoral dynamic markers in shaping responses to checkpoint blockade, for the ultimate patient benefit.

Virus expression detection reveals RNA-sequencing contamination in TCGA

Background

Contamination of reagents and cross contamination across samples is a long-recognized issue in molecular biology laboratories. While often innocuous, contamination can lead to inaccurate results. Cantalupo et al., for example, found HeLa-derived human papillomavirus 18 (H-HPV18) in several of The Cancer Genome Atlas (TCGA) RNA-sequencing samples. This work motivated us to assess a greater number of samples and determine the origin of possible contaminations using viral sequences. To detect viruses with high specificity, we developed the publicly available workflow, VirDetect, that detects virus and laboratory vector sequences in RNA-seq samples. We applied VirDetect to 9143 RNA-seq samples sequenced at one TCGA sequencing center (28/33 cancer types) over 5 years.

Results

We confirmed that H-HPV18 was present in many samples and determined that viral transcripts from H-HPV18 significantly co-occurred with those from xenotropic mouse leukemia virus-related virus (XMRV). Using laboratory metadata and viral transcription, we determined that the likely contaminant was a pool of cell lines known as the “common reference”, which was sequenced alongside TCGA RNA-seq samples as a control to monitor quality across technology transitions (i.e. microarray to GAII to HiSeq), and to link RNA-seq to previous generation microarrays that standardly used the “common reference”. One of the cell lines in the pool was a laboratory isolate of MCF-7, which we discovered was infected with XMRV; another constituent of the pool was likely HeLa cells.

Conclusions

Altogether, this indicates a multi-step contamination process. First, MCF-7 was infected with an XMRV. Second, this infected cell line was added to a pool of cell lines, which contained HeLa. Finally, RNA from this pool of cell lines contaminated several TCGA tumor samples most-likely during library construction. Thus, these human tumors with H-HPV or XMRV reads were likely not infected with H-HPV 18 or XMRV.

Comparative Approach to the Temporo-Spatial Organization of the Tumor Microenvironment

The complex ecosystem in which tumor cells reside and interact, termed the tumor microenvironment (TME), encompasses all cells and components associated with a neoplasm that are not transformed cells. Interactions between tumor cells and the TME are complex and fluid, with each facet coercing the other, largely, into promoting tumor progression. While the TME in humans is relatively well-described, a compilation and comparison of the TME in our canine counterparts has not yet been described. As is the case in humans, dog tumors exhibit greater heterogeneity than what is appreciated in laboratory animal models, although the current level of knowledge on similarities and differences in the TME between dogs and humans, and the practical implications of that information, require further investigation. This review summarizes some of the complexities of the human and mouse TME and interjects with what is known in the dog, relaying the information in the context of the temporo-spatial organization of the TME. To the authors' knowledge, the development of the TME over space and time has not been widely discussed, and a comprehensive review of the canine TME has not been done. The specific topics covered in this review include cellular invasion and interactions within the TME, metabolic derangements in the TME and vascular invasion, and the involvement of the TME in tumor spread and metastasis.

High-Throughput Sequence Analysis of Peripheral T-Cell Lymphomas Indicates Subtype-Specific Viral Gene Expression Patterns and Immune Cell Microenvironments

Certain peripheral T-cell lymphomas (PTCLs) have been associated with viral infection, particularly infection with Epstein-Barr virus (EBV). However, a comprehensive virome analysis across PTCLs has not previously been reported. Here we utilized published whole-transcriptome RNA sequencing (RNA-seq) data sets from seven different PTCL studies and new RNA-seq data from our laboratory to screen for virus association, to analyze viral gene expression, and to assess B- and T-cell receptor diversity paradigms across PTCL subtypes. In addition to identifying EBV in angioimmunoblastic T-cell lymphoma (AITL) and extranodal NK/T-cell lymphoma (ENKTL), two PTCL subtypes with well-established EBV associations, we also detected EBV in several cases of anaplastic large-cell lymphoma (ALCL), and we found evidence of infection by the oncogenic viruses Kaposi's sarcoma-associated herpesvirus and human T-cell leukemia virus type 1 in isolated PTCL cases. In AITLs, EBV gene expression analysis showed expression of immediate early, early, and late lytic genes, suggesting either low-level lytic gene expression or productive infection in a subset of EBV-infected B-lymphocyte stromal cells. Deconvolution of immune cell subpopulations demonstrated a greater B-cell signal in AITLs than in other PTCL subtypes, consistent with a larger role for B-cell support in the pathogenesis of AITL. Reconstructed T-cell receptor (TCR) and B-cell receptor (BCR) repertoires demonstrated increased BCR diversity in AITLs, consistent with a possible EBV-driven polyclonal response. These findings indicate potential alternative roles for EBV in PTCLs, in addition to the canonical oncogenic mechanisms associated with EBV latent infection. Our findings also suggest the involvement of other viruses in PTCL pathogenesis and demonstrate immunological alterations associated with these cancers.IMPORTANCE In this study, we utilized next-generation sequencing data from 7 different studies of peripheral T-cell lymphoma (PTCL) patient samples to globally assess viral associations, provide insights into the contributions of EBV gene expression to the tumor phenotype, and assess the unique roles of EBV in modulating the immune cell tumor microenvironment. These studies revealed potential roles for EBV replication genes in some PTCL subtypes, the possible role of additional human tumor viruses in rare cases of PTCLs, and a role for EBV in providing a unique immune microenvironmental niche in one subtype of PTCLs. Together, these studies provide new insights into the understudied role of tumor viruses in PTCLs.

The promise of combining cancer vaccine and checkpoint blockade for treating HPV-related cancer

Human papillomavirus (HPV)-associated intraepithelial neoplasia or cancers are ideal candidates for cancer immunotherapy since HPV oncoproteins, such as E6 and E7 proteins of high-risk HPVs, could be utilized as foreign antigens. In HPV-associated cancers as well as nonviral cancers, the cancer cells may evade host immunity through the expression of immune checkpoint molecules, downregulation of human leukocyte antigen, and activation of immune regulatory cells. Because of these immune suppressive mechanisms, HPV therapeutic vaccines have shown little efficacy against HPV-associated cancers, although they have shown efficacy in treating HPV-associated intraepithelial neoplasias. Recently, checkpoint blockade emerged as a promising new treatment for solid cancers; however, these therapies have shown only modest efficacy against HPV-associated cancers. Here we reviewed literature analyzing a combinatory therapy using an immune checkpoint inhibitor and an HPV therapeutic vaccine for treating HPV-associated cancers to compensate for shortfalls of each monotherapy. Complimentary modes of T cell activation would be deployed; as vaccines would directly stimulate the T cells, while checkpoint inhibitors would do so by releasing inhibition. Some promising studies using animal models and early human clinical trials raised a possibility that such combinations may be efficacious in regressing HPV-associated cancers. Epitope spreading (the phenomenon in which non-targeted antigens become new targets of immune response) may play a critical role mechanistically. Currently ongoing studies will shed light as to whether such combination therapy would indeed be a promising new treatment paradigm. Current and future studies must also determine the adverse effect profile of such a combination treatment.

Immune checkpoint inhibitors in the treatment of virus-associated cancers

Among all malignant tumors that threaten human health, virus-related tumors account for a large proportion. The treatment of these tumors is still an urgent problem to be resolved. The immune system is the "guard" of the human body, resisting the invasion of foreign substances such as viruses. Studies have shown that immunotherapy has clinical significance in the treatment of a variety of tumors. In particular, the emergence of immune checkpoint inhibitors (ICIs) in recent years has opened a new door to cancer therapy. Considering the potential role of ICIs in the treatment of virus-related cancers, we focused on their therapeutic effect in virus-associated cancers and explored whether the therapeutic effect in virus-associated cancers was related to virus infection status. Although there is no clear statistical significance indicates that ICIs are more effective in virus-associated cancers than non-virus infections, the efficacy of checkpoint inhibitors in the treatment of virus-related cancers is promising. We believe that this research provides a good direction for the implementation of individualized precision medicine.