Divergent viral presentation among human tumors and adjacent normal tissues

Ligand-receptor interactions combined with histopathology for improved prognostic modeling in HPV-negative head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is a prevalent malignancy, with HPV-negative tumors exhibiting aggressive behavior and poor prognosis. Understanding the intricate interactions within the tumor microenvironment (TME) is crucial for improving prognostic models and identifying therapeutic targets. Using BulkSignalR, we identified ligand-receptor interactions in HPV-negative TCGA-HNSC cohort (n = 395). A prognostic model incorporating 14 ligand-receptor pairs was developed using random forest survival analysis and LASSO-penalized Cox regression based on overall survival and progression-free interval of HPV-negative tumors from TCGA-HNSC. Multi-omics analysis revealed distinct molecular features between risk groups, including differences in extracellular matrix remodeling, angiogenesis, immune infiltration, and APOBEC enzyme activity. Deep learning-based tissue morphology analysis on HE-stained whole slide images further improved risk stratification, with region selection via Silicon enhancing accuracy. The integration of routine histopathology with deep learning and multi-omics data offers a clinically accessible tool for precise risk stratification, facilitating personalized treatment strategies in HPV-negative HNSC.

Investigation of Epstein-Barr virus, Cytomegalovirus, Human herpesvirus 6, and Polyoma viruses (JC virus, BK virus) among Gastric cancer patients: A cross sectional study

Background and Aims

Gastric cancer is a significant global issue with a high death rate. This malignancy could be associated with several viral agents such as EBV, CMV, HHV-6, JCV, and BKV.

Objective

Evaluation of EBV, CMV, HHV-6 ,and JCV, BKV frequency among gastric cancer patients.

Methods

In this cross-sectional study, a total number of 60 gastric cancer specimens (32 male, 28 female) were retrieved from the pathology lab. Formalin-fixed paraffin-embedded tissue was used for molecular testing. DNA was extracted from samples, according to protocol, and used for PCR reaction. Polymerase chain reactions were used to assess CMV, EBV, HHV-6, JCV, and BKV frequency.

Results and Conclusion

The mean age of the participants was 61 years and 53.3% (32) of the participants were Male. A total number of 5 samples (8.34%) were infected with viral agents. Four male gastric samples were infected with EBV (6.67%) and only one female sample contained the BKV genome (1.67%). Totally 8.34% of the samples were infected with EBV and BKV. The CMV, HHV-6, and JCV genome was not detected in the samples. In conclusion, the presence of two viral agents including EBV and BKV among male and female samples respectively, and the genome of other viruses were not detected.

Single cell deciphering of progression trajectories of the tumor ecosystem in head and neck cancer

Head and neck squamous cell carcinoma is the sixth most common cancer worldwide and has high heterogeneity and unsatisfactory outcomes. To better characterize the tumor progression trajectory, we perform single-cell RNA sequencing of normal tissue, precancerous tissue, early-stage, advanced-stage cancer tissue, lymph node, and recurrent tumors tissue samples. We identify the transcriptional development trajectory of malignant epithelial cells and a tumorigenic epithelial subcluster regulated by TFDP1. Furthermore, we find that the infiltration of POSTN+ fibroblasts and SPP1+ macrophages gradually increases with tumor progression; their interaction or interaction with malignant cells also gradually increase to shape the desmoplastic microenvironment and reprogram malignant cells to promote tumor progression. Additionally, we demonstrate that during lymph node metastasis, exhausted CD8+ T cells with high CXCL13 expression strongly interact with tumor cells to acquire more aggressive phenotypes of extranodal expansion. Finally, we delineate the distinct features of malignant epithelial cells in primary and recurrent tumors, providing a theoretical foundation for the precise selection of targeted therapy for tumors at different stages. In summary, the current study offers a comprehensive landscape and deep insight into epithelial and microenvironmental reprogramming throughout initiation, progression, lymph node metastasis and recurrence of head and neck squamous cell carcinoma.

Detection of HHV-6 Virus in specimen of a ductal pancreatic adenocarcinoma with comparison in tumor and normal tissue

AIMS

The association of human herpesvirus 6 (HHV-6) species with pancreatic cancer is controversially discussed. The aim of this study was to further investigate the postulated association and to identify the basis of HHV-6 DNA positivity reported for pancreatic cancer tissue.

METHODS

All samples of patients with pancreatic cancer (cancer and surrounding tissue) were analyzed for presence of HHV-6 DNA by PCR and then selected cases by immunohistochemistry.

RESULTS

Sixty eight per cent (68% = 52/77) of all patients were HHV-6 DNA positive in any of the samples, 49% (38/77) were positive in tumor tissue. Specimens of just one patient were HHV-6A DNA positive, all other patients were positive for HHV-6B. Immunohistochemical analysis of HHV-6 DNA positive samples did not reveal any specific HHV-6B protein positive tumor cell. In contrast, supposed immune cells presented intra- and peritumorally expressed HHV-6B-protein. The cause of presence of these cells in the tumor stroma is unknown, as of yet.

CONCLUSIONS

HHV-6 DNA-positivity of pancreatic cancer tissue described by us and others is probably not due to the infection of pancreatic cells by HHV-6, but rather due to the migration of HHV-6 positive immune cells into the pancreas. Based on our data, we suppose that there is no direct evidence for HHV-6 as a causative agent of pancreatic cancer, but further in-depth studies (including investigation of immune status of patients) are necessary to make definitive conclusions.

A deep learning approach reveals unexplored landscape of viral expression in cancer

About 15% of human cancer cases are attributed to viral infections. To date, virus expression in tumor tissues has been mostly studied by aligning tumor RNA sequencing reads to databases of known viruses. To allow identification of divergent viruses and rapid characterization of the tumor virome, we develop viRNAtrap, an alignment-free pipeline to identify viral reads and assemble viral contigs. We utilize viRNAtrap, which is based on a deep learning model trained to discriminate viral RNAseq reads, to explore viral expression in cancers and apply it to 14 cancer types from The Cancer Genome Atlas (TCGA). Using viRNAtrap, we uncover expression of unexpected and divergent viruses that have not previously been implicated in cancer and disclose human endogenous viruses whose expression is associated with poor overall survival. The viRNAtrap pipeline provides a way forward to study viral infections associated with different clinical conditions.

Identification and validation of a prognostic signature of autophagy, apoptosis and pyroptosis-related genes for head and neck squamous cell carcinoma: to imply therapeutic choices of HPV negative patients

Introduction

An effective tool is needed to predict the prognosis of head and neck squamous cell carcinoma (HNSCC). Human papillomavirus (HPV) positive HNSCC patients generally have a favorable survival and a promising responsiveness to radiotherapy, chemoradiotherapy and checkpoint blockades. However, HPV negative patients, the majority of HNSCC patients, have been largely overlooked. Cell death has been involved in the therapeutic resistance of cancers. To this end, we aimed to identify the association of autophagy, apoptosis and pyroptosis-related genes with the prognosis of HNSCC, and construct a prognostic signature to predict the prognosis for HNSCC, especially for HPV negative HNSCC.

Methods

Autophagy and apoptosis-related genes were obtained from Gene Set Enrichment Analysis (GSEA) website, and pyroptosis-related genes were obtained from GSEA and Gene Ontology (GO) database. We established the cell death index (CDI) based on RNA sequencing (RNA-seq) data and clinicopathological information from The Cancer Genome Atlas (TCGA) dataset. The prognostic value of CDI was verified by Kaplan-Meier, receiver operating characteristic (ROC) and univariate and multivariate Cox regression analyses in TCGA dataset, and validated with the datasets from Gene Expression Omnibus (GEO) and Qilu Hospital of Shandong University. We further assessed the immune microenvironment of patients with high and low CDI scores. Moreover, the expression of the signature genes in HNSCC cell lines were explored.

Results

We found that CDI was an independent prognostic indicator for overall survival (hazard ratio 3.80, 95% confidential interval: 2.70-5.40, P < 0.001). Furthermore, HNSCC patients with high CDI scores obtained increased overall survival post radiation indicating benefits from radiotherapy of this subgroup. On the other hand, HPV negative HNSCC patients with low CDI exhibited increased checkpoint gene expressions, an inflamed tumor microenvironment and an enriched immune response-related functions, suggesting the potential benefits from checkpoint immunotherapies of this subgroup. Moreover, we validated the baseline and induced expressions of above 16 genes in two HPV negative HNSCC cell lines, CAL27 and SCC-15.

Discussion

We established a prognostic signature and emphasized its implements in the therapeutic choices of HPV negative HNSCC patients, the majority and the poor outcome population of HNSCC.

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.

Multi-Omics Integration Reveals the Crucial Role of Fusobacterium in the Inflammatory Immune Microenvironment in Head and Neck Squamous Cell Carcinoma

The tumor microbiome is believed to have a profound impact on tumor progression owing to its local colonization in the tumor microenvironment (TME). Using the Cancer Microbiome Atlas (TCMA), a database of curated, decontaminated microbial profiles for 3,689 oropharyngeal, esophageal, gastrointestinal, and colorectal tissue samples from 1,772 patients, we conducted a comprehensive multi-omics analysis to reveal microbial signatures among various cancers and the potential mechanisms involved in tumor progression of head and neck squamous cell carcinoma (HNSC). We found that compared with other cancer types, the tumor-resident microbiome of HNSC accounted for the highest bacterial abundance and strongest association with host TME signatures. Fusobacterium was found to be enriched in HNSC tissues, which was associated with an increased inflammatory effect and inferior prognosis. Moreover, we revealed that the microbiota-associated inflammatory TME was attributed to the competing endogenouse RNA (ceRNA) network and chromatin accessibility. IMPORTANCE Studies on revealing the composition and potential mechanisms of the tumor microbiome are still at an initial stage. We uncovered the potential contribution of the tumor-resident microbiota on the immunosuppressive microenvironment in HNSC, which will provide a new perspective for tumor microbiome research and yield valuable insights into the clinical management of HNSC.

Human cytomegalovirus alters immune cell profile with potential implications for patient survival in head and neck cancer

Cytomegalovirus (CMV) is a highly prevalent human herpes virus that exerts a strong influence on immune repertoire which may influence cancer risk. We have tested whether CMV immunoglobulin G (IgG) serostatus is associated with immune cell proportions (n = 132 population controls), human papillomavirus (HPV) co-infection and head and neck cancer risk (n = 184 cancer cases and 188 controls) and patient survival. CMV status was not associated with the proportion of Natural Killer cells, B cells or the neutrophil-to-lymphocyte ratio. However, CD8+ T cells increased with increasing categories of IgG titers (P =1.7 × 10-10), and titers were inversely associated with the CD4:CD8 ratio (P = 5.6 × 10-5). Despite these differences in T cell proportions, CMV was not associated with HPV16 co-infection. CMV seropositivity was similar in cases (52%) and controls (47%) and was not associated with patient survival (hazard ratio [HR] 1.14, 95% confidence interval [CI]: 0.70 to 1.86). However, those patients with the highest titers had the worst survival (HR 1.91, 95% CI: 1.13 to 3.23). Tumor-based data from The Cancer Genome Atlas demonstrated that the presence of CMV transcripts was associated with worse patient survival (HR 1.79, 95% CI: 0.96 to 2.78). These findings confirm that a history of CMV infection alters T cell proportions, but this does not translate to HPV16 co-infection or head and neck cancer risk. Our data suggest that high titers and active CMV virus in the tumor environment may confer worse survival.

Characterization of Epigenomic Alterations in HPV16+ Head and Neck Squamous Cell Carcinomas

BACKGROUND

Epigenetic changes associated with human papillomavirus (HPV)-driven tumors have been described; however, HPV type-specific alterations are less well understood. We sought to compare HPV16-specific methylation changes with those in virus-unassociated head and neck squamous cell carcinomas (HNSCC).

METHODS

Within The Cancer Genome Atlas, 59 HPV16+ HNSCC, 238 nonviral HNSCC (no detectable HPV or other viruses), and 50 normal head and neck tissues were evaluated. Significant differentially methylated regions (DMR) were selected, and key associated genes were identified. Partial least squares models were generated to predict HPV16 status in additional independent samples.

RESULTS

HPV infection in HNSCC is associated with type-specific methylomic profiles. Multiple significant DMRs were identified between HPV16+, nonviral, and normal samples. The most significant differentially methylated genes, SYCP2, MSX2, HLTF, PITX2, and GRAMD4, demonstrated HPV16-associated methylation patterns with corresponding alterations in gene expression. Phylogenetically related HPV types (alpha-9 species; HPV31, HPV33, and HPV35) demonstrated a similar methylation profile to that of HPV16 but differed from those seen in other types, such as HPV18 and 45 (alpha-7).

CONCLUSIONS

HNSCC linked to HPV16 and types from the same alpha species are associated with a distinct methylation profile. This HPV16-associated methylation pattern is also detected in cervical cancer and testicular germ cell tumors. We present insights into both shared and unique methylation alterations associated with HPV16+ tumors and may have implications for understanding the clinical behavior of HPV-associated HNSCC.

IMPACT

HPV type-specific methylomic changes may contribute to understanding biologic mechanisms underlying differences in clinical behavior among different HPV+ and HPV- HNSCC.

Hepatitis B Virus Integration into Transcriptionally Active Loci and HBV-Associated Hepatocellular Carcinoma

Hepatitis B Virus (HBV) DNA integrations into the human genome are considered major causative factors to HBV-associated hepatocellular carcinoma development. In the present study, we investigated whether HBV preferentially integrates parts of its genome in specific genes and evaluated the contribution of the integrations in HCC development per gene. We applied dedicated in-house developed pipelines on all of the available HBV DNA integration data and performed a statistical analysis to identify genes that could be characterized as hotspots of integrations, along with the evaluation of their association with HBV-HCC. Our results suggest that 15 genes are recurrently affected by HBV integrations and they are significantly associated with HBV-HCC. Further studies that focus on HBV integrations disrupting these genes are mandatory in order to understand the role of HBV integrations in clonal advantage gain and oncogenesis promotion, as well as to determine whether inhibition of the HBV-disrupted genes can provide a therapy strategy for HBV-HCC.

ViMIC: a database of human disease-related virus mutations, integration sites and cis-effects

Molecular mechanisms of virus-related diseases involve multiple factors, including viral mutation accumulation and integration of a viral genome into the host DNA. With increasing attention being paid to virus-mediated pathogenesis and the development of many useful technologies to identify virus mutations (VMs) and viral integration sites (VISs), much research on these topics is available in PubMed. However, knowledge of VMs and VISs is widely scattered in numerous published papers which lack standardization, integration and curation. To address these challenges, we built a pilot database of human disease-related Virus Mutations, Integration sites and Cis-effects (ViMIC), which specializes in three features: virus mutation sites, viral integration sites and target genes. In total, the ViMIC provides information on 31 712 VMs entries, 105 624 VISs, 16 310 viral target genes and 1 110 015 virus sequences of eight viruses in 77 human diseases obtained from the public domain. Furthermore, in ViMIC users are allowed to explore the cis-effects of virus-host interactions by surveying 78 histone modifications, binding of 1358 transcription regulators and chromatin accessibility on these VISs. We believe ViMIC will become a valuable resource for the virus research community. The database is available at http://bmtongji.cn/ViMIC/index.php.

Deep Learning Predicts EBV Status in Gastric Cancer Based on Spatial Patterns of Lymphocyte Infiltration

EBV infection occurs in around 10% of gastric cancer cases and represents a distinct subtype, characterized by a unique mutation profile, hypermethylation, and overexpression of PD-L1. Moreover, EBV positive gastric cancer tends to have higher immune infiltration and a better prognosis. EBV infection status in gastric cancer is most commonly determined using PCR and in situ hybridization, but such a method requires good nucleic acid preservation. Detection of EBV status with histopathology images may complement PCR and in situ hybridization as a first step of EBV infection assessment. Here, we developed a deep learning-based algorithm to directly predict EBV infection in gastric cancer from H&E stained histopathology slides. Our model can not only predict EBV infection in gastric cancers from tumor regions but also from normal regions with potential changes induced by adjacent EBV+ regions within each H&E slide. Furthermore, in cohorts with zero EBV abundances, a significant difference of immune infiltration between high and low EBV score samples was observed, consistent with the immune infiltration difference observed between EBV positive and negative samples. Therefore, we hypothesized that our model's prediction of EBV infection is partially driven by the spatial information of immune cell composition, which was supported by mostly positive local correlations between the EBV score and immune infiltration in both tumor and normal regions across all H&E slides. Finally, EBV scores calculated from our model were found to be significantly associated with prognosis. This framework can be readily applied to develop interpretable models for prediction of virus infection across cancers.

Integration of adeno-associated virus (AAV) into the genomes of most Thai and Mongolian liver cancer patients does not induce oncogenesis

BACKGROUND

Engineered versions of adeno-associated virus (AAV) are commonly used in gene therapy but evidence revealing a potential oncogenic role of natural AAV in hepatocellular carcinoma (HCC) has raised concerns. The frequency of potentially oncogenic integrations has been reported in only a few populations. AAV infection and host genome integration in another type of liver cancer, cholangiocarcinoma (CCA), has been studied only in one cohort. All reported oncogenic AAV integrations in HCC come from strains resembling the fully sequenced AAV2 and partly sequenced AAV13. When AAV integration occurs, only a fragment of the AAV genome is detectable in later DNA or RNA sequencing. The integrated fragment is typically from the 3' end of the AAV genome, and this positional bias has been only partly explained. Three research groups searched for evidence of AAV integration in HCC RNAseq samples in the Cancer Genome Atlas (TCGA) but reported conflicting results.

RESULTS

We collected and analyzed whole transcriptome and viral capture DNA sequencing in paired tumor and non-tumor samples from two liver cancer Asian cohorts from Thailand (N = 147, 47 HCC and 100 intrahepatic cholangiocarcinoma (iCCA)) and Mongolia (N = 70, all HCC). We found only one HCC patient with a potentially oncogenic integration of AAV, in contrast to higher frequency reported in European patients. There were no oncogenic AAV integrations in iCCA patients. AAV genomic segments are present preferentially in the non-tumor samples of Thai patients. By analyzing the AAV genome positions of oncogenic and non-oncogenic integrated fragments, we found that almost all the putative oncogenic integrations overlap the X gene, which is present and functional only in the strain AAV2 among all fully sequenced strains. This gene content difference could explain why putative oncogenic integrations from other AAV strains have not been reported. We resolved the discrepancies in previous analyses of AAV presence in TCGA HCC samples and extended it to CCA. There are 12 TCGA samples with an AAV segment and none are in Asian patients. AAV segments are present in preferentially in TCGA non-tumor samples, like what we observed in the Thai patients.

CONCLUSIONS

Our findings suggest a minimal AAV risk of hepatocarcinogenesis in Asian liver cancer patients. The partial genome presence and positional bias of AAV integrations into the human genome has complicated analysis of possible roles of AAV in liver cancer.

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.

Oncogenic Viruses as Entropic Drivers of Cancer Evolution

Viral infection is an indisputable causal factor for nearly 17% of all human cancers. However, the diversity and complexity of oncogenic mechanisms raises new questions as to the mechanistic role of viruses in cancer. Classical viral oncogenes have been identified for all tumor-associated viruses. These oncogenes can have multiple oncogenic activities that may or may not be utilized in a particular tumor cell. In addition, stochastic events, like viral mutation and integration, as well as heritable host susceptibilities and immune deficiencies are also implicated in tumorigenesis. A more contemporary view of tumor biology highlights the importance of evolutionary forces that select for phenotypes better adapted to a complex and changing environment. Given the challenges of prioritizing singular mechanistic causes, it may be necessary to integrate concepts from evolutionary theory and systems biology to better understand viral cancer-driving forces. Here, we propose that viral infection provides a biological “entropy” that increases genetic variation and phenotypic plasticity, accelerating the main driving forces of cancer cell evolution. Viruses can also influence the evolutionary selection criteria by altering the tumor microenvironment and immune signaling. Utilizing concepts from cancer cell evolution, population genetics, thermodynamics, and systems biology may provide new perspectives on viral oncogenesis and identify novel therapeutic strategies for treating viruses and cancer.

Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity

Simple Summary

Squamous cell carcinoma (SCC) is the most prevalent type of human cancer worldwide and represents the majority of head and neck tumors. As SCC from aerodigestive or genitourinary tracts share not only common etiology and histological features but also molecular patterns, the major objectives of this study were the establishment of a pan-SCC-related prognostic gene signature by an integrative analysis of multi-omics data and the elucidation of underlying oncogenic pathway activities as potential vulnerabilities for a more efficient and less toxic therapy. Our approach delivers a reliable molecular classifier to identify HNSCC and other SCC patients at higher risk for treatment failure with tumors characterized by a more prominent MAPK activity, who might benefit from a targeted treatment with MEK inhibitors.

Abstract

Squamous cell carcinoma (SCC) is the most prevalent histological type of human cancer, including head and neck squamous cell carcinoma (HNSCC). However, reliable prognostic gene signatures for SCC and underlying genetic and/or epigenetic principles are still unclear. We identified 37 prognostic candidate genes by best cutoff computation based on survival in a pan-SCC cohort (n = 1334) of The Cancer Genome Atlas (TCGA), whose expression stratified not only the pan-SCC cohort but also independent HNSCC validation cohorts into three distinct prognostic subgroups. The most relevant prognostic genes were prioritized by a Least Absolute Shrinkage and Selection Operator Cox regression model and were used to identify subgroups with high or low risks for unfavorable survival. An integrative analysis of multi-omics data identified FN1, SEMA3A, CDH2, FBN1, COL5A1, and ADAM12 as key nodes in a regulatory network related to the prognostic phenotype. An in-silico drug screen predicted two MEK inhibitors (Trametinib and Selumetinib) as effective compounds for high-risk SCC based on the Cancer Cell Line Encyclopedia, which is supported by a higher p-MEK1/2 immunohistochemical staining of high-risk HNSCC. In conclusion, our data identified a molecular classifier for high-risk HNSCC as well as other SCC patients, who might benefit from treatment with MEK inhibitors.

CD68+ Macrophage Infiltration Associates With Poor Outcome of HPV Negative Oral Squamous Carcinoma Patients Receiving Radiation: Poly(I:C) Enhances Radiosensitivity of CAL-27 Cells but Promotes Macrophage Recruitment Through HMGB1

Patients with human papillomavirus (HPV) negative oral squamous cell carcinoma (OSCC) generally have poor clinical outcomes and worse responses to radiotherapy. It is urgent to explore the underlining mechanisms of the distinct prognoses between HPV negative and HPV positive OSCC and to develop effective therapy strategy to increase the survival rate of HPV negative OSCC patients. We conducted a retrospective cohort of 99 resected OSCC patients to evaluate the prognosis of HPV negative and HPV positive OSCC patients receiving radiation or not. We further addressed the association of CD68⁺ macrophage infiltration with HPV status and the effects on survival of OSCC patients. We also used the TCGA-OSCC cohort for further verification. Based on the cohort study, we applied a synthetic dsRNA polymer, polyriboinosinic-polyribocytidylic acid (poly(I:C)), on CAL-27 (HPV negative OSCC cells). We co-cultured its condition medium with THP-1 derived macrophage and examined the cytokines and macrophage migration. We found that high CD68⁺ macrophage infiltration associated with poor overall survival in HPV negative OSCC patients receiving radiation. In vitro, poly(I:C) could induce apoptosis and enhance the radiosensitivity, but increase macrophage recruitment. Targeting HMGB1 could inhibit IL-6 induction and macrophage recruitment. Our findings indicated that CD68⁺ macrophage might play an important role in the outcomes of HPV negative OSCC patients receiving radiation. Our findings also suggested that radiation combined poly(I:C) might be a potential therapy strategy to increase the radiation response and prognosis of HPV negative OSCC. Notably, HMGB1 should be targeted to inhibit macrophage recruitment and enhance overall therapy effects.

Moving pan-cancer studies from basic research toward the clinic

Although all cancers share common hallmarks, we have long realized that there is no silver-bullet treatment for the disease. Many clinical oncologists specialize in a single cancer type, based predominantly on the tissue of origin. With advances brought by genetics and cancer genomic research, we now know that cancers are profoundly different, both in origins and in genetic alterations. At the same time, commonalities such as key driver mutations, altered pathways, mutational, immune and microbial signatures and other areas (many revealed by pan-cancer studies) point to the intriguing possibility of targeting common traits across diverse cancer types with the same therapeutic strategies. Studies designed to delineate differences and similarities across cancer types are thus critical in discerning the basic dynamics of oncogenesis, as well as informing diagnoses, prognoses and therapies. We anticipate growing emphases on the development and application of therapies targeting underlying commonalities of different cancer types, while tailoring to the unique tissue environment and intrinsic molecular fingerprints of each cancer type and subtype. Here we summarize the facets of pan-cancer research and how they are pushing progress toward personalized medicine.

Hepatitis B Virus DNA Integration, Chronic Infections and Hepatocellular Carcinoma

Hepatitis B Virus (HBV) is an Old World virus with a high mutation rate, which puts its origins in Africa alongside the origins of Homo sapiens, and is a member of the Hepadnaviridae family that is characterized by a unique viral replication cycle. It targets human hepatocytes and can lead to chronic HBV infection either after acute infection via horizontal transmission usually during infancy or childhood or via maternal-fetal transmission. HBV has been found in ~85% of HBV-related Hepatocellular Carcinomas (HCC), and it can integrate the whole or part of its genome into the host genomic DNA. The molecular mechanisms involved in the HBV DNA integration is not yet clear; thus, multiple models have been described with respect to either the relaxed-circular DNA (rcDNA) or the double-stranded linear DNA (dslDNA) of HBV. Various genes have been found to be affected by HBV DNA integration, including cell-proliferation-related genes, oncogenes and long non-coding RNA genes (lincRNAs). The present review summarizes the advances in the research of HBV DNA integration, focusing on the evolutionary and molecular side of the integration events along with the arising clinical aspects in the light of WHO's commitment to eliminate HBV and viral hepatitis by 2030.

Establishment of a Plasticity-Associated Risk Model Based on a SOX2- and SOX9-Related Gene Set in Head and Neck Squamous Cell Carcinoma

Recent studies highlighted SOX2 and SOX9 as key determinants for cancer-cell plasticity and demonstrated that cisplatin-induced adaptation in oral squamous cell carcinoma (SCC) is acquired by an inverse regulation of both transcription factors. However, the association between SOX2/SOX9-related genetic programs with risk factors and genetic or epigenetic alterations in primary head and neck SCC (HNSCC), and their prognostic value is largely unknown.Here, we identified differentially-expressed genes (DEG) related to SOX2 and SOX9 transcription in The Cancer Genome Atlas (TCGA)-HNSC, which enable clustering of patients into groups with distinct clinical features and survival. A prognostic risk model was established by LASSO Cox regression based on expression patterns of DEGs in TCGA-HNSC (training cohort), and was confirmed in independent HNSCC validation cohorts as well as other cancer cohorts from TCGA. Differences in the mutational landscape among risk groups of TCGA-HNSC demonstrated an enrichment of truncating NSD1 mutations for the low-risk group and elucidated DNA methylation as modulator of SOX2 expression. Gene set variation analysis (GSVA) revealed differences in several oncogenic pathways among risk groups, including upregulation of gene sets related to oncogenic KRAS signaling for the high-risk group. Finally, in silico drug screen analysis revealed numerous compounds targeting EGFR signaling with significantly lower efficacy for cancer cell lines with a higher risk phenotype, but also indicated potential vulnerabilities. IMPLICATIONS: The established risk model identifies patients with primary HNSCC, but also other cancers at a higher risk for treatment failure, who might benefit from a therapy targeting SOX2/SOX9-related gene regulatory and signaling networks.

Landscape of oncoviral genotype and co-infection via human papilloma and hepatitis B viral tumor in situ profiling

The role of oncoviral genotype and co-infection driving oncogenesis remains unclear. We have developed a scalable, high throughput tool for sensitive and precise oncoviral genotype deconvolution. Using tumor RNA sequencing data, we applied it to 537 virally infected liver, cervical, and head and neck tumors, providing the first comprehensive integrative landscape of tumor-viral gene expression, viral antigen immunogenicity, patient survival, and mutational profiling organized by tumor oncoviral genotype. We find that HBV and HPV genotype and co-infection serve as significant predictors of patient survival and immune activation. Finally, we demonstrate that HPV genotype is more associated with viral oncogene expression than cancer type, implying that expression may be similar across episomal and stochastic integration-based infections. While oncoviral infections are known risk factors for oncogenesis, viral genotype and co-infection are shown to strongly associate with disease progression, patient survival, mutational signatures, and putative tumor neoantigen immunogenicity, facilitating novel clinical associations with infections.

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ViralMine parses oncoviral genotypes and co-infection from in situ tumor data

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Oncoviral genotyping of TCGA CESC, HNSC, and LIHC cohorts

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Tumor fitness, immunogenicity, and mutational signatures associate with oncoviral genotype

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

The landscape of long noncoding RNA-involved and tumor-specific fusions across various cancers

The majority of the human genome encodes long noncoding RNA (lncRNA) genes, critical regulators of various cellular processes, which largely outnumber protein-coding genes. However, lncRNA-involved fusions have not been surveyed and characterized yet. Here, we present a systematic study of the lncRNA fusion landscape across cancer types and identify >30 000 high-confidence tumor-specific lncRNA fusions (using 8284 tumor and 6946 normal samples). Fusions positively correlated with DNA damage and cancer stemness and were specifically low in microsatellite instable (MSI)-High or virus-infected tumors. Moreover, fusions distribute differently among cancer molecular subtypes, but with shared enrichment in tumors that are microsatellite stable (MSS), with high somatic copy number alterations (SCNA), and with poor survival. Importantly, we find a potentially new mechanism, mediated by enhancer RNAs (eRNA), which generates secondary fusions that form densely connected fusion networks with many fusion hubs targeted by FDA-approved drugs. Finally, we experimentally validate functions of two tumor-promoting chimeric proteins derived from mRNA-lncRNA fusions, KDM4B-G039927 and EPS15L1-lncOR7C2-1. The EPS15L1 fusion protein may regulate (Gasdermin E) GSDME, critical in pyroptosis and anti-tumor immunity. Our study completes the fusion landscape in cancers, sheds light on fusion mechanisms, and enriches lncRNA functions in tumorigenesis and cancer progression.

Sequencing facility and DNA source associated patterns of virus-mappable reads in whole-genome sequencing data

Numerous viral sequences have been reported in the whole-genome sequencing (WGS) data of human blood. However, it is not clear to what degree the virus-mappable reads represent true viral sequences rather than random-mapping or noise originating from sample preparation, sequencing processes, or other sources. Identification of patterns of virus-mappable reads may generate novel indicators for evaluating the origins of these viral sequences. We characterized paired-end unmapped reads and reads aligned to viral references in human WGS datasets, then compared patterns of the virus-mappable reads among DNA sources and sequencing facilities which produced these datasets. We then examined potential origins of the source- and facility-associated viral reads. The proportions of clean unmapped reads among the seven sequencing facilities were significantly different (P < 2 × 10-16). We identified 260,339 reads that were mappable to a total of 99 viral references in 2535 samples. The majority (86.7%) of these virus-mappable reads (corresponding to 47 viral references), which can be classified into four groups based on their distinct patterns, were strongly associated with sequencing facility or DNA source (adjusted P value <0.01). Possible origins of these reads include artificial sequences in library preparation, recombinant vectors in cell culture, and phages co-contaminated with their host bacteria. The sequencing facility-associated virus-mappable reads and patterns were repeatedly observed in other datasets produced in the same facilities. We have constructed an analytic framework and profiled the unmapped reads mappable to viral references. The results provide a new understanding of sequencing facility- and DNA source-associated batch effects in deep sequencing data and may facilitate improved bioinformatics filtering of reads.

Tissue-associated microbial detection in cancer using human sequencing data

Cancer is one of the leading causes of morbidity and mortality in the globe. Microbiological infections account for up to 20% of the total global cancer burden. The human microbiota within each organ system is distinct, and their compositional variation and interactions with the human host have been known to attribute detrimental and beneficial effects on tumor progression. With the advent of next generation sequencing (NGS) technologies, data generated from NGS is being used for pathogen detection in cancer. Numerous bioinformatics computational frameworks have been developed to study viral information from host-sequencing data and can be adapted to bacterial studies. This review highlights existing popular computational frameworks that utilize NGS data as input to decipher microbial composition, which output can predict functional compositional differences with clinically relevant applicability in the development of treatment and prevention strategies.

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.

Comparative analysis of SARS-CoV-2 receptor ACE2 expression in multiple solid tumors and matched non-diseased tissues

The emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a global public health emergency. SARS-CoV-2 employs the host cell receptor ACE2 for cellular entry. Nonetheless, the differences in ACE2 expression pattern in lung versus other normal and solid tumor tissues remain incompletely characterized. Here, we analyze a large data set comprising ACE2 mRNA expression for 7592 tissue samples across 22 types of primary solid tumor and 4461 samples across matched 18 non-diseased tissues. Our results unravel eight normal tissues and 10 primary solid tumors, which might be at high risk of SARS-CoV-2 infection. These findings may provide additional insight into the prevention and treatment of SARS-CoV-2 infection, in particular for patients with these 10 vulnerable cancer types.

Unraveling most abundant mutational signatures in head and neck cancer

Genomic alterations are a driving force in the multistep process of head and neck cancer (HNC) and result from the interaction of exogenous environmental exposures and endogenous cellular processes. Each of these processes leaves a characteristic pattern of mutations on the tumor genome providing the unique opportunity to decipher specific signatures of mutational processes operative during HNC pathogenesis and to address their prognostic value. Computational analysis of whole exome sequencing data of the HIPO-HNC (Heidelberg Center for Personalized Oncology-head and neck cancer) (n = 83) and TCGA-HNSC (The Cancer Genome Atlas-Head and Neck Squamous Cell Carcinoma) (n = 506) cohorts revealed five common mutational signatures (Catalogue of Somatic Mutations in Cancer [COSMIC] Signatures 1, 2, 3, 13 and 16) and demonstrated their significant association with etiological risk factors (tobacco, alcohol and HPV16). Unsupervised hierarchical clustering identified four clusters (A, B, C1 and C2) of which Subcluster C2 was enriched for cases with a higher frequency of signature 16 mutations. Tumors of Subcluster C2 had significantly lower p16^INK4A expression accompanied by homozygous CDKN2A deletion in almost one half of cases. Survival analysis revealed an unfavorable prognosis for patients with tumors characterized by a higher mutation burden attributed to signature 16 as well as cases in Subcluster C2. Finally, a LASSO-Cox regression model was applied to prioritize clinically relevant signatures and to establish a prognostic risk score for head and neck squamous cell carcinoma patients. In conclusion, our study provides a proof of concept that computational analysis of somatic mutational signatures is not only a powerful tool to decipher environmental and intrinsic processes in the pathogenesis of HNC, but could also pave the way to establish reliable prognostic patterns.

Insights into Hepatitis B Virus DNA Integration-55 Years after Virus Discovery

Hepatitis B virus (HBV), which was discovered in 1965, is a threat to global public health. HBV infects human hepatocytes and leads to acute and chronic liver diseases, and there is no cure. In cells infected by HBV, viral DNA can be integrated into the cellular genome. HBV DNA integration is a complicated process during the HBV life cycle. Although HBV integration normally results in replication-incompetent transcripts, it can still act as a template for viral protein expression. Of note, it is a primary driver of hepatocellular carcinoma (HCC). Recently, with the development of detection methods and research models, the molecular biology and the pathogenicity of HBV DNA integration have been better revealed. Here, we review the advances in the research of HBV DNA integration, including molecular mechanisms, detection methods, research models, the effects on host and viral gene expression, the role of HBV integrations in the pathogenesis of HCC, and potential treatment strategies. Finally, we discuss possible future research prospects of HBV DNA integration.

Sepsis-associated pathways segregate cancer groups

BACKGROUND

Sepsis and cancer are both leading causes of death, and occurrence of any one, increases the likelihood of the other. While cancer patients are susceptible to sepsis, survivors of sepsis are also susceptible to develop certain cancers. This mutual dependence for susceptibility suggests shared biology between the two disease categories. Earlier analysis had revealed a cancer-related pathway to be up-regulated in Septic Shock (SS), an advanced stage of sepsis. This has motivated a more comprehensive comparison of the transcriptomes of SS and cancer.

METHODS

Gene Set Enrichment Analysis was performed to detect the pathways enriched in SS and cancer. Thereafter, hierarchical clustering was applied to identify relative segregation of 17 cancer types into two groups vis-a-vis SS. Biological significance of the selected pathways was explored by network analysis. Clinical significance of the pathways was tested by survival analysis. A robust classifier of cancer groups was developed based on machine learning.

RESULTS

A total of 66 pathways were observed to be enriched in both SS and cancer. However, clustering segregated cancer types into two categories based on the direction of transcriptomic change. In general, there was up-regulation in SS and one group of cancer (termed Sepsis-Like Cancer, or SLC), but not in other cancers (termed Cancer Alone, or CA). The SLC group mainly consisted of malignancies of the gastrointestinal tract (head and neck, oesophagus, stomach, liver and biliary system) often associated with infection. Machine learning classifier successfully segregated the two cancer groups with high accuracy (> 98%). Additionally, pathway up-regulation was observed to be associated with survival in the SLC group of cancers.

CONCLUSION

Transcriptome-based systems biology approach segregates cancer into two groups (SLC and CA) based on similarity with SS. Host response to infection plays a key role in pathogenesis of SS and SLC. However, we hypothesize that some component of the host response is protective in both SS and SLC.

The landscape of bacterial presence in tumor and adjacent normal tissue across 9 major cancer types using TCGA exome sequencing

Identification of microbial composition directly from tumor tissue permits studying the relationship between microbial changes and cancer pathogenesis. We interrogated bacterial presence in tumor and adjacent normal tissue strictly in pairs utilizing human whole exome sequencing to generate microbial profiles. Profiles were generated for 813 cases from stomach, liver, colon, rectal, lung, head & neck, cervical and bladder TCGA cohorts. Core microbiota examination revealed twelve taxa to be common across the nine cancer types at all classification levels. Paired analyses demonstrated significant differences in bacterial shifts between tumor and adjacent normal tissue across stomach, colon, lung squamous cell, and head & neck cohorts, whereas little or no differences were evident in liver, rectal, lung adenocarcinoma, cervical and bladder cancer cohorts in adjusted models. Helicobacter pylori in stomach and Bacteroides vulgatus in colon were found to be significantly higher in adjacent normal compared to tumor tissue after false discovery rate correction. Computational results were validated with tissue from an independent population by species-specific qPCR showing similar patterns of co-occurrence among Fusobacterium nucleatum and Selenomonas sputigena in gastric samples. This study demonstrates the ability to identify bacteria differential composition derived from human tissue whole exome sequences. Taken together our results suggest the microbial profiles shift with advanced disease and that the microbial composition of the adjacent tissue can be indicative of cancer stage disease progression.

Potential prognostic impact of EBV RNA-seq reads in gastric cancer: a reanalysis of The Cancer Genome Atlas cohort

Epstein-Barr virus (EBV)-associated gastric cancer (EBVaGC), whose prognosis remains controversial, is diagnosed by in situ hybridization of EBV-derived EBER1/2 small RNAs. In The Cancer Genome Atlas (TCGA) Stomach Adenocarcinoma (STAD) project, the EBV molecular subtype was determined through a combination of multiple next-generation sequencing methods, but not by the gold standard in situ hybridization method. This leaves unanswered questions regarding the discordance of EBV positivity detected by different approaches and the threshold of sequencing reads. Therefore, we reanalyzed the TCGA-STAD RNA sequencing (RNA-seq) dataset including 375 tumor and 32 normal samples, using our analysis pipeline. We defined a reliable threshold for EBV-derived next-generation sequencing reads by mapping them to the EBV genome with three different random arbitrary alignments. We analyzed the prognostic impact of EBV status on the histopathological subtypes of gastric cancer. EBV-positive cases identified by reanalysis comprised nearly half of the cases (49.6%) independent from infiltrating lymphocyte signatures, and showed significantly longer overall survival for adenocarcinomas of the 'not-otherwise-specified' type [P = 0.016 (log-rank test); hazard ratios (HR): 0.476; 95% CI: 0.260-0.870, P = 0.016 (Cox univariate analysis)], but shorter overall survival for the tubular adenocarcinoma type [P = 0.005 (log-rank test); HR: 3.329; 95% CI: 1.406-7.885, P = 0.006 (Cox univariate analysis)]. These results demonstrate that the EBV positivity rates were higher when determined by RNA-seq than when determined by EBER1/2 in situ hybridization. The RNA-seq-based EBV positivity demonstrated distinct results for gastric cancer prognosis depending on the histopathological subtype, suggesting its potential to be used in clinical prognoses.

The landscape of viral associations in human cancers

Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, for which whole-genome and-for a subset-whole-transcriptome sequencing data from 2,658 cancers across 38 tumor types was aggregated, we systematically investigated potential viral pathogens using a consensus approach that integrated three independent pipelines. Viruses were detected in 382 genome and 68 transcriptome datasets. We found a high prevalence of known tumor-associated viruses such as Epstein-Barr virus (EBV), hepatitis B virus (HBV) and human papilloma virus (HPV; for example, HPV16 or HPV18). The study revealed significant exclusivity of HPV and driver mutations in head-and-neck cancer and the association of HPV with APOBEC mutational signatures, which suggests that impaired antiviral defense is a driving force in cervical, bladder and head-and-neck carcinoma. For HBV, HPV16, HPV18 and adeno-associated virus-2 (AAV2), viral integration was associated with local variations in genomic copy numbers. Integrations at the TERT promoter were associated with high telomerase expression evidently activating this tumor-driving process. High levels of endogenous retrovirus (ERV1) expression were linked to a worse survival outcome in patients with kidney cancer.

Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma

Background

Immune-related genes (IRGs) were linked to the prognosis of head and neck squamous cell carcinoma (HNSCC). This study aimed to identify the effects of an immune-related gene signature (IRGS) that can predict the of HNSCC prognosis.

Methods

The expression data of 770 HNSCC patients from the TCGA database and the GEO database were used. To explore a predictive model, the Cox proportional hazards model was applied. The Kaplan–Meier survival analysis, as well as univariate and multivariate analyses were performed to evaluate the independent predictive value of IRGS. To explore biological functions of IRGS, enrichment analyses and pathway annotation for differentially expressed genes (DEGs) in different immune groups were applied, as well as the immune infiltration.

Results

A prognostic signature comprising 27 IRGs was generated. IRGS significantly stratified HNSCC patients into high and low immune risk groups in regard to overall survival in the training cohort (HR = 3.69, 95% CI 2.73–4.98, P < 0.001). Likewise, IRGS could be linked to the prognosis of HNSCC in patients of the validation cohort (HR = 1.84, 95% CI 1.21–2.81, P < 0.01). Even after adjusting for TNM stage, IRGS was maintained as an independent predictor in the multivariate analysis (HR = 3.62, 95% CI 2.58–5.09, P < 0.001), and in the validation cohort (HR = 1.73, 95% CI 1.12–2.67, P = 0.014). The IFN-α response, the IFN-γ response, IL-2/STAT5 signaling, and IL-6/JAK/STAT3 signaling were all negatively correlated with the immune risk (P < 0.01). Immune infiltration of the high-risk group was significantly lower than that of the low-risk group (P < 0.01). Most notably, the infiltration of CD8 T cells, memory-activated CD4 T cells, and regulatory T cells was strongly upregulated in the low immune risk groups, while memory resting CD4 T cell infiltration was downregulated (P < 0.01).

Conclusion

Our analysis provides a comprehensive prognosis of the immune microenvironments and outcomes for different individuals. Further studies are needed to evaluate the clinical application of this signature.

The transcription factor FOXM1 regulates the balance between proliferation and aberrant differentiation in head and neck squamous cell carcinoma

Sustained expression of FOXM1 is a hallmark of nearly all human cancers including squamous cell carcinomas of the head and neck (HNSCC). HNSCCs partially preserve the epithelial differentiation program, which recapitulates fetal and adult traits of the tissue of tumor origin but is deregulated by genetic alterations and tumor-supporting pathways. Using shRNA-mediated knockdown, we demonstrate a minimal impact of FOXM1 on proliferation and migration of HNSCC cell lines under standard cell culture conditions. However, FOXM1 knockdown in three-dimensional (3D) culture and xenograft tumor models resulted in reduced proliferation, decreased invasion, and a more differentiated-like phenotype, indicating a context-dependent modulation of FOXM1 activity in HNSCC cells. By ectopic overexpression of FOXM1 in HNSCC cell lines, we demonstrate a reduced expression of cutaneous-type keratin K1 and involucrin as a marker of squamous differentiation, supporting the role of FOXM1 in modulation of aberrant differentiation in HNSCC. Thus, our data provide a strong rationale for targeting FOXM1 in HNSCC. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Effect Sizes of Somatic Mutations in Cancer

A major goal of cancer biology is determination of the relative importance of the genetic alterations that confer selective advantage to cancer cells. Tumor sequence surveys have frequently ranked the importance of substitutions to cancer growth by P value or a false-discovery conversion thereof. However, P values are thresholds for belief, not metrics of effect. Their frequent misuse as metrics of effect has often been vociferously decried, even in cases when the only attributable mistake was omission of effect sizes. Here, we propose an appropriate ranking-the cancer effect size, which is the selection intensity for somatic variants in cancer cell lineages. The selection intensity is a metric of the survival and reproductive advantage conferred by mutations in somatic tissue. Thus, they are of fundamental importance to oncology, and have immediate relevance to ongoing decision making in precision medicine tumor boards, to the selection and design of clinical trials, to the targeted development of pharmaceuticals, and to basic research prioritization. Within this commentary, we first discuss the scope of current methods that rank confidence in the overrepresentation of specific mutated genes in cancer genomes. Then we bring to bear recent advances that draw upon an understanding of the development of cancer as an evolutionary process to estimate the effect size of somatic variants leading to cancer. We demonstrate the estimation of the effect sizes of all recurrent single nucleotide variants in 22 cancer types, quantifying relative importance within and between driver genes.

HPViewer: sensitive and specific genotyping of human papillomavirus in metagenomic DNA

Motivation

Shotgun DNA sequencing provides sensitive detection of all 182 HPV types in tissue and body fluid. However, existing computational methods either produce false positives misidentifying HPV types due to shared sequences among HPV, human and prokaryotes, or produce false negative since they identify HPV by assembled contigs requiring large abundant of HPV reads.

Results

We designed HPViewer with two custom HPV reference databases masking simple repeats and homology sequences respectively and one homology distance matrix to hybridize these two databases. It directly identified HPV from short DNA reads rather than assembled contigs. Using 100 100 simulated samples, we revealed that HPViewer was robust for samples containing either high or low number of HPV reads. Using 12 shotgun sequencing samples from respiratory papillomatosis, HPViewer was equal to VirusTAP, and Vipie and better than HPVDetector with the respect to specificity and was the most sensitive method in the detection of HPV types 6 and 11. We demonstrated that contigs-based approaches had disadvantages of detection of HPV. In 1573 sets of metagenomic data from 18 human body sites, HPViewer identified 104 types of HPV in a body-site associated pattern and 89 types of HPV co-occurring in one sample with other types of HPV. We demonstrated HPViewer was sensitive and specific for HPV detection in metagenomic data.

Availability and implementation

HPViewer can be accessed at https://github.com/yuhanH/HPViewer/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Infectious Agents in Bovine Red Meat and Milk and Their Potential Role in Cancer and Other Chronic Diseases

Red meat and dairy products have frequently been suggested to represent risk factors for certain cancers, chronic neurodegenerative diseases, and autoimmune and cardiovascular disorders. This review summarizes the evidence and investigates the possible involvement of infectious factors in these diseases. The isolation of small circular single-stranded DNA molecules from serum and dairy products of Eurasian Aurochs (Bos taurus)-derived cattle, obviously persisting as episomes in infected cells, provides the basis for further investigations. Gene expression of these agents in human cells has been demonstrated, and frequent infection of humans is implicated by the detection of antibodies in a high percentage of healthy individuals. Epidemiological observations suggest their relationship to the development multiple sclerosis, to heterophile antibodies, and to N-glycolylneuraminic acid (Neu5Gc) containing cell surface receptors.

Dynamic host immune response in virus-associated cancers

Viruses drive carcinogenesis in human cancers through diverse mechanisms that have not been fully elucidated but include promoting immune escape. Here we investigated associations between virus-positivity and immune pathway alteration for 2009 tumors across six virus-related cancer types. Analysis revealed that for 3 of 72 human papillomavirus (HPV)-positive head and neck squamous cell carcinoma (HNSC) the HPV genome integrated in immune checkpoint genes PD-L1 or PD-L2, driving elevated expression in the corresponding gene. In addition to the previously described upregulation of the PD-1 immunosuppressive pathway in Epstein-Barr virus (EBV)-positive stomach tumors, we also observed upregulation of the PD-1 pathway in cytomegalovirus (CMV)-positive tumors. Furthermore, we found signatures of T-cell and B-cell response in HPV-positive HNSC and EBV-positive stomach tumors and HPV-positive HNSC patients were associated with better survival when T-cell signals were detected. Our work reveals that viral infection may recruit immune effector cells, and upregulate PD-1 and CTLA-4 immunosuppressive pathways.

Interpretation of EBV infection in pan-cancer genome considering viral life cycle: LiEB (Life cycle of Epstein-Barr virus)

We report a novel transcriptomic analysis workflow called LiEB (Life cycle of Epstein-Barr virus) to characterize distributions of oncogenic virus, Epstein-Barr virus (EBV) infection in human tumors. We analyzed 851 The Cancer Genome Atlas whole-transcriptome sequencing (WTS) data to investigate EBV infection by life cycle information using three-step LiEB workflow: 1) characterize virus infection generally; 2) align transcriptome sequences against a hybrid human-EBV genome, and 3) quantify EBV gene expression. Our results agreed with EBV infection status of public cell line data. Analysis in stomach adenocarcinoma identified EBV-positive cases involving PIK3CA mutations and/or CDKN2A silencing with biologically more determination, compared to previous reports. In this study, we found that a small number of colorectal adenocarcinoma cases involved with EBV lytic gene expression. Expression of EBV lytic genes was also observed in 3% of external colon cancer cohort upon WTS analysis. Gene set enrichment analysis showed elevated expression of genes related to E2F targeting and interferon-gamma responses in EBV-associated tumors. Finally, we suggest that interpretation of EBV life cycle is essential when analyzing its infection in tumors, and LiEB provides high capability of detecting EBV-positive tumors. Observation of EBV lytic gene expression in a subset of colon cancers warrants further research.

APOBEC-induced mutations and their cancer effect size in head and neck squamous cell carcinoma

Recent studies have revealed the mutational signatures underlying the somatic evolution of cancer, and the prevalences of associated somatic genetic variants. Here we estimate the intensity of positive selection that drives mutations to high frequency in tumors, yielding higher prevalences than expected on the basis of mutation and neutral drift alone. We apply this approach to a sample of 525 head and neck squamous cell carcinoma exomes, producing a rank-ordered list of gene variants by selection intensity. Our results illustrate the complementarity of calculating the intensity of selection on mutations along with tallying the prevalence of individual substitutions in cancer: while many of the most prevalently-altered genes were heavily selected, their relative importance to the cancer phenotype differs from their prevalence and from their P value, with some infrequent variants exhibiting evidence of strong positive selection. Furthermore, we extend our analysis of effect size by quantifying the degree to which mutational processes (such as APOBEC mutagenesis) contributes mutations that are highly selected, driving head and neck squamous cell carcinoma. We calculate the substitutions caused by APOBEC mutagenesis that make the greatest contribution to cancer phenotype among patients. Lastly, we demonstrate via in vitro biochemical experiments that the APOBEC3B protein can deaminate the cytosine bases at two sites whose mutant states are subject to high net realized selection intensities-PIK3CA E545K and E542K. By quantifying the effects of mutations, we deepen the molecular understanding of carcinogenesis in head and neck squamous cell carcinoma.

Human Herpesvirus 6 and Malignancy: A Review

In order to determine the role of human herpesvirus 6 (HHV-6) in human disease, several confounding factors, including methods of detection, types of controls, and the ubiquitous nature of the virus, must be considered. This is particularly problematic in the case of cancer, in which rates of detection vary greatly among studies. To determine what part, if any, HHV-6 plays in oncogenesis, a review of the literature was performed. There is evidence that HHV-6 is present in certain types of cancer; however, detection of the virus within tumor cells is insufficient for assigning a direct role of HHV-6 in tumorigenesis. Findings supportive of a causal role for a virus in cancer include presence of the virus in a large proportion of cases, presence of the virus in most tumor cells, and virus-induced in-vitro cell transformation. HHV-6, if not directly oncogenic, may act as a contributory factor that indirectly enhances tumor cell growth, in some cases by cooperation with other viruses. Another possibility is that HHV-6 may merely be an opportunistic virus that thrives in the immunodeficient tumor microenvironment. Although many studies have been carried out, it is still premature to definitively implicate HHV-6 in several human cancers. In some instances, evidence suggests that HHV-6 may cooperate with other viruses, including EBV, HPV, and HHV-8, in the development of cancer, and HHV-6 may have a role in such conditions as nodular sclerosis Hodgkin lymphoma, gastrointestinal cancer, glial tumors, and oral cancers. However, further studies will be required to determine the exact contributions of HHV-6 to tumorigenesis.

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

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.

Cellular Genomic Sites of Hepatitis B Virus DNA Integration

Infection with the Hepatitis B Virus (HBV) is one of the strongest risk-factors for liver cancer (hepatocellular carcinoma, HCC). One of the reported drivers of HCC is the integration of HBV DNA into the host cell genome, which may induce pro-carcinogenic pathways. These reported pathways include: induction of chromosomal instability; generation of insertional mutagenesis in key cancer-associated genes; transcription of downstream cancer-associated cellular genes; and/or formation of a persistent source of viral protein expression (particularly HBV surface and X proteins). The contribution of each of these specific mechanisms towards carcinogenesis is currently unclear. Here, we review the current knowledge of specific sites of HBV DNA integration into the host genome, which sheds light on these mechanisms. We give an overview of previously-used methods to detect HBV DNA integration and the enrichment of integration events in specific functional and structural cellular genomic sites. Finally, we posit a theoretical model of HBV DNA integration during disease progression and highlight open questions in the field.

Neutral Theory and the Somatic Evolution of Cancer

Kimura's neutral theory argued that positive selection was not responsible for an appreciable fraction of molecular substitutions. Correspondingly, quantitative analysis reveals that the vast majority of substitutions in cancer genomes are not detectably under selection. Insights from the somatic evolution of cancer reveal that beneficial substitutions in cancer constitute a small but important fraction of the molecular variants. The molecular evolution of cancer community will benefit by incorporating the neutral theory of molecular evolution into their understanding and analysis of cancer evolution-and accepting the use of tractable, predictive models, even when there is some evidence that they are not perfect.