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INTRODUCTION: Early neoplastic progression of Barretts esophagus (BE) is often treated with endoscopic therapy. Although effective, some patients are refractory to therapy or recur after apparent eradication of the BE. The goal of this study was to determine whether genomic alterations within the treated BE may be associated with persistent or recurrent disease. METHODS: We performed DNA sequencing on pre-treatment esophageal samples from 45 patients who were successfully treated by endoscopic therapy and did not recur as well as pre-treatment and post-treatment samples from 40 patients who had persistent neoplasia and 21 patients who had recurrent neoplasia. The genomic alterations were compared between groups. RESULTS: The genomic landscape was similar between all groups. Patients with persistent disease were more likely to have pre-treatment alterations involving the receptor tyrosine kinase pathway ( P = 0.01), amplifications of oncogenes ( P = 0.01), and deletions of tumor suppressor genes ( P = 0.02). These associations were no longer significant after adjusting for patient age and BE length. More than half of patients with persistent (52.5%) or recurrent (57.2%) disease showed pre-treatment and post-treatment samples that shared at least 50% of their driver mutations. DISCUSSION: Pre-treatment samples were genomically similar between those who responded to endoscopic therapy and those who had persistent or recurrent disease, suggesting there is not a strong genomic component to treatment response. Although it was expected to find shared driver mutations in pre-treatment and post-treatment samples in patients with persistent disease, the finding that an equal number of patients with recurrent disease also showed this relation suggests that many recurrences represent undetected minimal residual disease.

BACKGROUND AND AIM: Identifying clinical characteristics and outcomes of different ethnicities in the US may inform treatment for hospitalized COVID-19 patients. Aim of this study is to identify predictors of mortality among US races/ethnicities. DESIGN SETTING AND PARTICIPANTS: We retrospectively analyzed de-identified data from 9,873 COVID-19 patients who were hospitalized at 15 US hospital centers in 11 states (March 2020-November 2020). Main Outcomes and Measures: The primary outcome was to identify predictors of mortality in hospitalized COVID-19 patients. RESULTS: Among the 9,873 patients, there were 64.1% African Americans (AA), 19.8% Caucasians, 10.4% Hispanics, and 5.7% Asians, with 50.7% female. Males showed higher in-hospital mortality (20.9% vs. 15.3%, p=0.001). Non- survivors were significantly older (67 vs. 61 years) than survivors. Patients in New York had the highest in-hospital mortality (OR=3.54 (3.03 - 4.14)). AA patients possessed higher prevalence of comorbidities, had longer hospital stay, higher ICU admission rates, increased requirement for mechanical ventilation and higher in-hospital mortality compared to other races/ethnicities. Gastrointestinal symptoms (GI), particularly diarrhea, were more common among minority patients. Among GI symptoms and laboratory findings, abdominal pain (5.3%, p=0.03), elevated AST (n=2653, 50.2%, p=

Sandra M Quezada, Ankur Rustgi, Guruprasad D Jambaulikar, Raymond K Cross Department of Medicine, Division of Gastroenterology and Hepatology, University of Maryland School of Medicine, Baltimore, MD, USA Purpose: Fifteen percent of incident Crohn's disease (CD) cases are diagnosed at older ages and demonstrate colonic location and inflammatory behavior. Serologic responses to gut microbial antigens are associated with specific phenotypes, and may differ by age at diagnosis. Our aim was to identify an association between age at diagnosis of CD and responses to gut microbial antigens. Patients and methods: Levels of anti-Saccharomyces cerevisiae antibodies (ASCA) immunoglobulins A and G (IgA and IgG), antibodies to Escherichia coli outer membrane porin-C (anti-Omp-C), antibodies to clostridial flagellin (anti-CBir-1), and perinuclear anti-neutrophil cytoplasmic antibodies (p-ANCA) were compared in patients by age in three diagnosis groups: patients diagnosed at ages of

Abstract Although the E3 ligase Mdm2 and its homologue and binding partner MdmX are the major regulators of the p53 tumor suppressor protein, it is now evident that Mdm2 and MdmX have multiple functions that do not involve p53. As one example, it is known that Mdm2 can regulate cell migration, although mechanistic insight into this function is still lacking. Here we show in cells lacking p53 expression that knockdown of Mdm2 or MdmX, as well as pharmacological inhibition of the Mdm2/MdmX complex, not only reduces cell migration and invasion, but also impairs cell spreading and focal adhesion formation. In addition, Mdm2 knockdown decreases metastasis in vivo. Interestingly, Mdm2 downregulates the expression of Sprouty4, which is required for the Mdm2 mediated effects on cell migration, focal adhesion formation and metastasis. Further, our findings indicate that Mdm2 dampening of Sprouty4 is a prerequisite for maintaining RhoA levels in the cancer cells that we have studied. Taken together we describe a molecular mechanism whereby the Mdm2/MdmX complex through Sprouty4 regulates cellular processes leading to increase metastatic capability independently of p53.

Introduction and Objectives: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide and can progress to non-alcoholic steatohepatitis (NASH) and, ultimately, cirrhosis. Clostridioides difficile is the most common nosocomial cause of diarrhea and is associated with worse clinical outcomes in other liver diseases, including cirrhosis, but has not been extensively evaluated in concomitant NAFLD/NASH. Materials and Methods: We conducted a retrospective cohort study using the National Inpatient Sample database from 2015 to 2017. Patients with a diagnosis of CDI, NAFLD, and NASH were identified using International Classification of Diseases (Tenth Revision) codes. The outcomes of our study include length of stay, hospitalization cost, mortality, and predictors of mortality. Results: The CDI and NASH cohort had a higher degree of comorbidity burden and prevalence of peptic ulcer disease, congestive heart failure, diabetes mellitus, and cirrhosis. Patients with NASH and CDI had a significantly higher mortality rate compared to the CDI only cohort (mortality, 7.11 % vs. 6.36 %; P = 0.042). Patients with CDI and NASH were at increased risk for liver-related complications, acute kidney injury, and septic shock (P < 0.001) compared to patients with CDI only. Older age, intestinal complications, pneumonia, sepsis and septic shock, and liver failure conferred an increased risk of mortality among the CDI and NASH cohort. Conclusions: Patients with NASH had a higher rate of liver-related complications, progression to septic shock, and mortality rate following CDI infection compared to the CDI only cohort.

Cancer-associated fibroblasts (CAFs), a heterogenous population, can promote cancer cell proliferation, migration, invasion, immunosuppression, and therapeutic resistance in solid tumors. These effects are mediated through secretion of cytokines and growth factors, remodeling of the extracellular matrix, and providing metabolic support for cancer cells. The presence of CAFs in esophageal carcinoma are associated with reduced overall survival and increased resistance to chemotherapy and radiotherapy; thus, identifying therapeutic vulnerabilities of CAFs is a necessity. In esophageal cancer, the mechanisms for CAF recruitment, CAF-mediated promotion of tumorigenesis, metastatic dissemination, and therapeutic resistance have yet to be fully evaluated. Here, we provide an overview of the current understanding of CAFs in esophageal cancer, namely in esophageal squamous cell carcinoma and esophageal adenocarcinoma, as well as in the preneoplastic conditions that predispose to these cancers. Interestingly, there is a discrepancy in our knowledge of CAF biology between esophageal cancer subtypes, with very few studies in esophageal adenocarcinoma, and its precursor lesion Barrett’s esophagus, compared with esophageal squamous cell carcinoma. We propose that although great strides have been made, certain questions remain to which answers hopefully will emerge to have an impact on biomarker diagnostics and translational therapeutics.

Chronic hepatitis B virus (HBV) infection affects about 262 million people worldwide, leading to over 820,000 deaths each year primarily due to cirrhosis and hepatocellular carcinoma. The World Health Organization has pledged to eliminate HBV as a health threat by 2030, but currently, no countries are on track to achieve this goal. One of the barriers to HBV elimination is stigma, causing shame, denial, self-isolation, self-rejection, and depression leading to those with chronic HBV less likely to get tested or seek treatment and more likely to conceal their infection. Other barriers include limited access to care and complicated and restrictive clinical practice guidelines. Increasing public and political efforts are necessary to raise awareness, increase access to care, and change screening and treatment guidelines. The current guidance of the American Association for the Study of Liver Diseases (AASLD) recommends testing only if patients are considered at risk, but this has proven to be ineffective. We propose a simplified “test all and treat all” approach with a 5-line guideline for HBV infection. Universal screening and treatment of adults is cost-effective and can prevent transmission by effectively managing chronic HBV. All patients who are hepatitis B surface antigen (HBsAg) positive with detectable HBV-DNA should receive treatment until HBsAg is undetectable for 12 months, as HBV-DNA transmission via blood transfusion can occur even at low viral loads of 16 copies/mL, and mother-to-child transmission is still a risk even with passive-active immunoprophylaxis. Furthermore, clinical outcomes after HBsAg clearance are significantly better than the clinical outcomes of those who remain HBsAg positive.

The epidemiology of Hepatitis B virus (HBV) has drastically changed in recent decades due to public health initiatives, including universal infant vaccination programs,urbanization driving global travel, and migration patterns. Despite screening of pregnant women and newborns significantly reducing the rate of perinatal transmission in certain parts of the world, other, perhaps more uncommon, routes (e.g., parenteral) have led to outbreaks in specific areas affected by the opioid epidemic and injection drug use. Although our current understanding of the effect of genetic variants of HBV is lacking, we review current knowledge and patterns of genetic variants with geographical predominance, pathophysiology, and clinical manifestations. Serologic and molecular markers are used to screen, identify phase and activity of infection, and monitor response to antivirals and/or reactivation. This review will provide the most up-to-date summary of the epidemiology, transmission, genotype, replication, and current methods of screening to follow the various phases of HBV, including immunotolerance and reactivation.

Summary: Despite the promising outcomes of immune checkpoint inhibitors (ICIs), resistance to ICI presents a new challenge. Therefore, selecting patients for specific ICI applications is crucial for maximizing therapeutic efficacy. Herein, we curated 69 human esophageal squamous cell cancer (ESCC) patients’ tumor microenvironment (TME) single-cell transcriptomic datasets to subtype ESCC. Integrative analyses of the cellular network and transcriptional signatures of T cells and myeloid cells define distinct ESCC subtypes characterized by T cell exhaustion, and interleukin (IL) and interferon (IFN) signaling. Furthermore, this approach classifies ESCC patients into ICI responders and non-responders, as validated by whole tumor transcriptomes and liquid biopsy-based single-cell transcriptomes of anti-PD-1 ICI responders and non-responders. Our study stratifies ESCC patients based on TME transcriptional network, providing novel insights into tumor niche remodeling and potentially predicting ICI responses in ESCC patients.

Abstract The initiation and progression of cancer are intricately linked to the tumor microenvironment (TME). Understanding the function of specific cancer-TME interactions poses a major challenge due in part to the complexity of the in vivo microenvironment. Here we predict cancer-TME interactions from single cell transcriptomic maps of both human colorectal cancers (CRCs) and mouse CRC models, ask how these interactions are altered in human tumor organoid (tumoroid) cultures, and functionally recapitulate human myeloid-carcinoma interactions in vitro. Tumoroid cultures suppress gene expression programs involved in inflammation and immune cell migration, providing a reductive platform for re-establishing carcinoma-immune cell interactions in vitro. Introduction of human monocyte-derived macrophages into tumoroid cultures instructs macrophages to acquire immunosuppressive and pro-tumorigenic gene expression programs similar to those observed in vivo. This includes hallmark induction of SPP1, encoding Osteopontin, an extracellular CD44 ligand with established oncogenic effects. Taken together, these findings offer a framework for understanding CRC-TME interactions and provide a reductionist tool for modeling specific aspects of these interactions.

Abstract Chronic inflammation is integral to the development of esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC), although the latter has not been associated with reflux esophagitis. The L2-IL-1β transgenic mice, expressing human interleukin (IL)-1β in the oral, esophageal and forestomach squamous epithelia feature chronic inflammation and a stepwise development of Barrett’s esophagus-like metaplasia, dysplasia and adenocarcinoma at the squamo-columnar junction. However, the functional consequences of IL-1β-mediated chronic inflammation in the oral and esophageal squamous epithelia remain elusive. We report for the first time that in addition to the previously described Barrett’s esophagus-like metaplasia, the L2-IL-1β mice also develop squamous epithelial dysplasia with progression to squamous cell carcinoma (SCC) in the esophagus and the tongue. L2-IL-1β showed age-dependent progression of squamous dysplasia to SCC with approximately 40% (n = 49) and 23.5% (n = 17) incidence rates for esophageal and tongue invasive SCC respectively, by 12–15 months of age. Interestingly, SCC development and progression in L2-IL-1β was similar in both Germ Free (GF) and Specific Pathogen Free (SPF) conditions. Immunohistochemistry revealed a T cell predominant inflammatory profile with enhanced expression of Ki67, Sox2 and the DNA double-strand break marker, γ-H2AX, in the dysplastic squamous epithelia of L2-IL-1β mice. Pro-inflammatory cytokines, immunomodulatory players, chemoattractants for inflammatory cells (T cells, neutrophils, eosinophils, and macrophages) and oxidative damage marker, iNOS, were significantly increased in the esophageal and tongue tissues of L2-IL-1β mice. Our recent findings have expanded the translational utility of the IL-1β mouse model to aid in further characterization of the key pathways of inflammation driven BE and EAC as well as ESCC and Oral SCC.

Abstract Temperatures below or above optimal growth conditions are among the major stressors affecting productivity, end‐use quality, and distribution of key staple crops including rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays L.). Among temperature stresses, cold stress induces cellular changes that cause oxidative stress and slowdown metabolism, limit growth, and ultimately reduce crop productivity. Perception of cold stress by plant cells leads to the activation of cold‐responsive transcription factors and downstream genes, which ultimately impart cold tolerance. The response triggered in crops to cold stress includes gene expression/suppression, the accumulation of sugars upon chilling, and signaling molecules, among others. Much of the information on the effects of cold stress on perception, signal transduction, gene expression, and plant metabolism are available in the model plant Arabidopsis but somewhat lacking in major crops. Hence, a complete understanding of the molecular mechanisms by which staple crops respond to cold stress remain largely unknown. Here, we make an effort to elaborate on the molecular mechanisms employed in response to low‐temperature stress. We summarize the effects of cold stress on the growth and development of these crops, the mechanism of cold perception, and the role of various sensors and transducers in cold signaling. We discuss the progress in cold tolerance research at the genome, transcriptome, proteome, and metabolome levels and highlight how these findings provide opportunities for designing cold‐tolerant crops for the future.

Abstract One of the thrust areas of research in plant breeding is to develop crop cultivars with enhanced tolerance to abiotic stresses. Thus, identifying abiotic stress‐responsive genes (SRGs) and proteins is important for plant breeding research. However, identifying such genes via established genetic approaches is laborious and resource intensive. Although transcriptome profiling has remained a reliable method of SRG identification, it is species specific. Additionally, identifying multistress responsive genes using gene expression studies is cumbersome. Thus, endorsing the need to develop a computational method for identifying the genes associated with different abiotic stresses. In this work, we aimed to develop a computational model for identifying genes responsive to six abiotic stresses: cold, drought, heat, light, oxidative, and salt. The predictions were performed using support vector machine (SVM), random forest, adaptive boosting (ADB), and extreme gradient boosting (XGB), where the autocross covariance (ACC) and K‐mer compositional features were used as input. With ACC, K‐mer, and ACC + K‐mer compositional features, the overall accuracy of ∼60–77, ∼75–86, and ∼61–78% were respectively obtained using the SVM algorithm with fivefold cross‐validation. The SVM also achieved higher accuracy than the other three algorithms. The proposed model was also assessed with an independent dataset and obtained an accuracy consistent with cross‐validation. The proposed model is the first of its kind and is expected to serve the requirement of experimental biologists; however, the prediction accuracy was modest. Given its importance for the research community, the online prediction application, ASRpro, is made freely available (https://iasri‐sg.icar.gov.in/asrpro/) for predicting abiotic SRGs and proteins.

Background & aimsPrevious studies have examined the effects of metabolic syndrome (MetS) rather than its severity on race and ethnic disparities in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD). We used the MetS severity score, a validated sex-race-ethnicity-specific severity measure, to examine the effects of race/ethnicity on the association between MetS severity and MASLD.MethodsThis study included 10,605 adult participants from the Third National Health and Nutrition Examination Survey. The MASLD diagnosis was based on ultrasound findings in patients without excessive alcohol intake or other liver diseases. MetS severity Z-scores were calculated and stratified into four categories low (1st-50th), moderate (>50th-75th), high (>75th-90th), and very high (>90th+)]. Multivariable adjusted logistic regression models with complex survey methods were used to test the effect of MetS severity on MASLD.ResultsThe age-adjusted MASLD prevalence was 17.4%, 25.7%, 42.5, and 54.9% in adults with mild, moderate, high, and very high MetS severities, respectively (P-trend ConclusionsRacial/ethnic disparities in MetS severity play a pivotal role in the risk of MASLD. Our findings highlight the potential clinical utility of the MetS severity score in identifying at-risk individuals, which will help guide targeted prevention and tailoring management strategies to mitigate the MASLD burden.

Epithelial plasticity, or epithelial-to-mesenchymal transition (EMT), is a well-recognized form of cellular plasticity, which endows tumor cells with invasive properties and alters their sensitivity to various agents, thus representing a major challenge to cancer therapy. It is increasingly accepted that carcinoma cells exist along a continuum of hybrid epithelial-mesenchymal (E-M) states and that cells exhibiting such partial EMT (P-EMT) states have greater metastatic competence than those characterized by either extreme (E or M). We described recently a P-EMT program operating in vivo by which carcinoma cells lose their epithelial state through post-translational programs. Here, we investigate the underlying mechanisms and report that prolonged calcium signaling induces a P-EMT characterized by the internalization of membrane-associated E-cadherin (ECAD) and other epithelial proteins as well as an increase in cellular migration and invasion. Signaling through Gαq-associated G-protein-coupled receptors (GPCRs) recapitulates these effects, which operate through the downstream activation of calmodulin-Camk2b signaling. These results implicate calcium signaling as a trigger for the acquisition of hybrid/partial epithelial-mesenchymal states in carcinoma cells.

Abstract Background Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance. Results Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker–trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development. Conclusion The most promising MQTLs identified in this study may facilitate marker-assisted breeding for stripe rust resistance in wheat. Information on markers flanking the MQTLs can be utilized in genomic selection models to increase the prediction accuracy for stripe rust resistance. The candidate genes identified can also be utilized for enhancing the wheat resistance against stripe rust after in vivo confirmation/validation using one or more of the following methods: gene cloning, reverse genetic methods, and omics approaches.

AbstractDespite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

Abstract In wheat, genomic prediction accuracy (GPA) was assessed for three micronutrient traits (grain iron, grain zinc, and β‐carotenoid concentrations) using eight Bayesian regression models. For this purpose, data on 246 accessions, each genotyped with 17,937 DArT markers, were utilized. The phenotypic data on traits were available for 2013–2014 from Powerkheda (Madhya Pradesh) and for 2014–2015 from Meerut (Uttar Pradesh), India. The accuracy of the models was measured in terms of reliability, which was computed following a repeated cross‐validation approach. The predictions were obtained independently for each of the two environments after adjusting for the local effects and across environments after adjusting for the environmental effects. The Bayes ridge regression (BayesRR) model outperformed the other seven models, whereas BayesLASSO (BayesL) was the least efficient. The GPA increased with an increase in the size of the training set as well as with an increase in marker density. The GPA values differed for the three traits and were higher for the best linear unbiased estimate (BLUE) (obtained after adjusting for the environmental effects) relative to those for the two environments. The GPA also remained unaffected after accounting for the population structure. The results of the present study suggest that only the best model should be used for the estimations of genomic estimated breeding values (GEBVs) before their use for genomic selection to improve the grain micronutrient contents.

At the cellular level, membrane damage is a fundamental cause of yield loss at high temperatures (HT). We report our investigations on a subset of a peanut (Arachis hypogaea) recombinant inbred line population, demonstrating that the membrane lipid remodeling occurring at HT is consistent with homeoviscous adaptation to maintain membrane fluidity. A major alteration in the leaf lipidome at HT was the reduction in the unsaturation levels, primarily through reductions of 18:3 fatty acid chains, of the plastidic and extra-plastidic diacyl membrane lipids. In contrast, levels of 18:3-containing triacylglycerols (TGs) increased at HT, consistent with a role for TGs in sequestering fatty acids when membrane lipids undergo remodeling during plant stress. Polyunsaturated acyl chains from membrane diacyl lipids were also sequestered as sterol esters (SEs). The removal of 18:3 chains from the membrane lipids decreased the availability of susceptible molecules for oxidation, thereby minimizing oxidative damage in membranes. Our results suggest that transferring 18:3 chains from membrane diacyl lipids to TGs and SEs is a key feature of lipid remodeling for HT adaptation in peanut. Finally, QTL-seq allowed the identification of a genomic region associated with heat-adaptive lipid remodeling, which would be useful for identifying molecular markers for heat tolerance.

Therapeutic innovation for human papilloma virus-related (HPV+) head and neck squamous cell carcinomas (HNSCCs) is impaired by inadequate preclinical models and the absence of accurate biomarkers. Our study establishes the first well-characterized panel of patient-derived xenografts (PDXs) and organoids from HPV+ HNSCCs while determining fidelity of the models to the distinguishing genetic features of this cancer type. Despite low engraftment rates, whole exome sequencing showed that PDXs retain multiple distinguishing features of HPV+ HNSCC lost in existing cell lines, including PIK3CA mutations, TRAF3 deletion and the absence of EGFR amplifications. Engrafted HPV+ tumors frequently contained NOTCH1 mutations, thus providing new models for a negatively prognostic alteration in this disease. Genotype-phenotype associations in the models were then tested for prediction of tumor progression and survival in published clinical cohorts. Observation of high tumor mutational burdens (TMBs) in the faster-growing models facilitated identification of a novel association between TMB and local progression in both HPV+ and HPV- patients that was prognostic in HPV- cases. In addition, reduced E7 and p16INK4A levels found in a PDX from an outlier case with lethal outcome led to detection of similar profiles among recurrent HPV+ HNSCCs. Transcriptional data from the Cancer Genome Atlas was used to demonstrate that the lower E2F target gene expression predicted by reduced E7 levels has potential as a biomarker of disease recurrence risk. Our findings bridge a critical gap in preclinical models for HPV+ HNSCCs and simultaneously reveal novel potential applications of quantifying mutational burden and viral oncogene functions for biomarker development.