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IntroductionTranscriptional analyses have identified several distinct molecular subtypes in pancreatic ductal adenocarcinoma (PDAC) that have prognostic and potential therapeutic significance. However, to date, an indepth, clinicomorphological correlation of these molecular subtypes has not been performed. We sought to identify specific morphological patterns to compare with known molecular subtypes, interrogate their biological significance, and furthermore reappraise the current grading system in PDAC.DesignWe first assessed 86 primary, chemotherapy-naive PDAC resection specimens with matched RNA-Seq data for specific, reproducible morphological patterns. Differential expression was applied to the gene expression data using the morphological features. We next compared the differentially expressed gene signatures with previously published molecular subtypes. Overall survival (OS) was correlated with the morphological and molecular subtypes.ResultsWe identified four morphological patterns that segregated into two components (‘gland forming’ and ‘non-gland forming’) based on the presence/absence of well-formed glands. A morphological cut-off (≥40% ‘non-gland forming’) was established using RNA-Seq data, which identified two groups (A and B) with gene signatures that correlated with known molecular subtypes. There was a significant difference in OS between the groups. The morphological groups remained significantly prognostic within cancers that were moderately differentiated and classified as ‘classical’ using RNA-Seq.ConclusionOur study has demonstrated that PDACs can be morphologically classified into distinct and biologically relevant categories which predict known molecular subtypes. These results provide the basis for an improved taxonomy of PDAC, which may lend itself to future treatment strategies and the development of deep learning models.

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at advanced tumor stages with chemotherapy as the only treatment option. Transcriptomic analysis has defined a classical and basal-like PDAC subtype, which are regulated by epigenetic modification. The present study aimed to determine if drug-induced epigenetic reprogramming of pancreatic cancer cells affects PDAC subtype identity and chemosensitivity. Classical and basal-like PDAC cell lines PaTu-S, Capan-1, Capan-2, Colo357, PaTu-T, PANC-1 and MIAPaCa-2, were treated for a short (up to 96 h) and long (up to 30 weeks) period with histone acetyltransferase (HAT) and histone deacetylase (HDAC) inhibitors. The cells were analyzed using gene expression approaches, immunoblot analysis, and various cell assays to assess cell characteristics, such as proliferation, colony formation, cell migration and sensitivity to chemotherapeutic drugs. Classical and basal-like PDAC cell lines showed pronounced epigenetic regulation of subtype-specific genes through acetylation of lysine 27 on Histone H3 (H3K27ac). Moreover, classical cell lines revealed a significantly decreased expression of HDAC2 and increased total levels of H3K27ac in comparison with the basal-like cell lines. Following HAT inhibitor treatment, classical cell lines exhibited a loss of epithelial marker gene expression, decreased chemotherapy response gene score and increased cell migration in vitro, indicating a tumor-promoting phenotype. HDAC inhibitor treatment, however, exerted minimal reprogramming effects in both subtypes. Epigenetic reprogramming of classical and basal-like tumor cells did not have a major impact on gemcitabine response, although the gemcitabine transporter gene SLC29A1 (solute carrier family 29 member 1) was epigenetically regulated.

Background Pancreatic ductal adenocarcinoma (PDAC) exhibits profound molecular heterogeneity and poor prognosis, necessitating novel tailored therapies. The basal and classical subtypes - driven by glycolysis versus lipid metabolism - have distinct prognostic implications warranting further characterization of their underlying transcriptional mechanisms. Methods Using spatial RNA sequencing we mapped PDAC molecular subtype heterogeneity, capturing spatially-resolved gene expression signatures and generating a comprehensive high-resolution dataset of 42,035 spatial spots. Subtype assignments were validated via multiplex immunofluorescence and quantitative analyses in patient-derived organoids and xenografts. Results Our analysis resolved cancer cell signatures, deconvoluted intra-tumoral heterogeneity, and delineated an evolutional classical-to-basal trajectory. We identified metabolically ‘hot’, high-grade tumor niches characterized by concurrent enrichment of glycolysis and lipogenesis across both subtypes, nominating them as subtype-agnostic therapeutic targets. Preclinical models demonstrated that despite the basal subtype’s glycolysis dependence, both classical and basal tumors are susceptible to glycolysis inhibition. Conclusion This work demonstrates that metabolic identity, spatial context, and tumor–stroma crosstalk are an inseparable triad that drives PDAC behavior. Our findings show that aggressive metabolic tumor niches can be targeted by glycolysis inhibition in a subtype-agnostic manner, challenging the dogma of subtype-specific therapeutic silos and highlighting highly adaptable energetic niches as reservoirs that drive tumor progression.

The classical swine (CS) H1N1 influenza virus, first isolated in 1930, is highly homologous to the 1918 Spanish influenza virus. CS H1N1 virus, which crossed the interspecies barrier to infect humans has become the dominantly prevalent strain in China's pig population, showing a trend of continuous transmission. However, whether subsequent adaptation of CS H1N1 to mammals would increase their pathogenicity toward humans is unknown. To address this, a mouse-adapted (MA) CS H1N1 virus (A/Swine/Guangdong/1/2011[G11-MA]) was generated through serially passaged in mouse lungs, exhibiting increased virulence compared to the wild-type (WT). Further study showed that the G11-MA strain exhibited amino acid mutations in PB2-D740N, PB1-T56I, PA-T97I and HA-K188E, and the combination of PB2-D740N with PA-T97I improved the replication ability in mammalian cells and mice. The G11-MA strain with PB2 and PA (G11/MA PB2PA) group enhanced the viral polymerase activity, with a similar survival rate and weight loss of mice compared to the G11-MA group. Our study demonstrates that the combination of PB2-D740N and PA-T97I plays a key role in the virulence phenotype of CS H1N1 influenza viruses, and provides important information for evaluating the pandemic risk of swine influenza strains.

The Influenza A virus (IAV) is a severe respiratory pathogen. C1q is the first subcomponent of the complement system’s classical pathway. C1q is composed of 18 polypeptide chains. Each of these chains contains a collagen-like region located at the N terminus, and a C-terminal globular head region organized as a heterotrimeric structure (ghA, ghB and ghC). This study was aimed at investigating the complement activation-independent modulation by C1q and its individual recombinant globular heads against IAV infection. The interaction of C1q and its recombinant globular heads with IAV and its purified glycoproteins was examined using direct ELISA and far-Western blotting analysis. The effect of the complement proteins on IAV replication kinetics and immune modulation was assessed by qPCR. The IAV entry inhibitory properties of C1q and its recombinant globular heads were confirmed using cell binding and luciferase reporter assays. C1q bound IAV virions via HA, NA and M1 IAV proteins, and suppressed replication in H1N1, while promoting replication in H3N2-infected A549 cells. C1q treatment further triggered an anti-inflammatory response in H1N1 and pro-inflammatory response in H3N2-infected cells as evident from differential expression of TNF-α, NF-κB, IFN-α, IFN-β, IL-6, IL-12 and RANTES. Furthermore, C1q treatment was found to reduce luciferase reporter activity of MDCK cells transfected with H1N1 pseudotyped lentiviral particles, indicative of an entry inhibitory role of C1q against infectivity of IAV. These data appear to demonstrate the complement-independent subtype specific modulation of IAV infection by locally produced C1q.

Chickens are highly susceptible to highly pathogenic avian influenza viruses (HPAIVs). However, the severity of infection varies depending of the viral strain and the genetic background of the host. In this study, we evaluated the pathogenesis of two HPAIVs (H7N1 and H5N8) and assessed the susceptibility to the infection of local and commercial chicken breeds from Spain. Eight chicken breeds were intranasally inoculated with 10 5 ELD 50 of A/Chicken/Italy/5093/1999 (H7N1) or A/Goose/Spain/IA17CR02699/2017 (H5N8 clade 2.3.4.4. B) and monitored during 10 days. Chickens were highly susceptible to both HPAIVs, but H7N1 was considerably more virulent than H5N8 as demonstrated by the highest mortality rates and shortest mean death times (MDT). Both HPAIVs produced severe necrosis and intense viral replication in the central nervous system, heart and pancreas; however, the lesions and replication in other tissues were virus-dependent. High levels of viral RNA were detected by the oral route with both viruses. In contrast, a low number of H5N8-inoculated chickens shed by the cloacal route, demonstrating a different pattern of viral shedding dependent of the HPAIV. We found a high variation in the susceptibility to HPAIVs between the different chicken breeds. The birds carrying the genotype AA and AG at position 2032 in chicken Mx gene presented a slightly higher, but not significant, percentage of survival and a statistically significant longer MDT than GG individuals. Our study demonstrated that the severity of HPAI infection is largely dependent of the viral isolate and host factors, underlining the complexity of HPAI infections.

The only effective measure to decrease morbidity and mortality caused by the influenza virus in the human population is worldwide vaccination. Vaccination produces neutralizing antibodies that target the HA1 subunit of the HA (hemagglutinin) protein and are strain specific. The effectiveness of new influenza vaccines are linked to two factors, the correct prediction of the circulating strains in the population in a particular season and the concentration of the HA1 protein in the vaccine formulation. With the advent of the licensing of quadrivalent vaccines, pharmaceutical manufacturers are under considerable pressure due to time constraints and dedicated resources to deliver 194–198 million doses (2020–2021 U.S. market) of vaccine. Considering the valuable resources needed to produce the influenza vaccine in a timely manner, the efficient quantitation of the HA1 protein (the main component in the influenza vaccine) is required. Currently the only method approved by regulatory agencies for quantitation of the HA antigen in vaccines is the single radial immunodiffusion assay (SRID), an antibody dependent assay that is not time efficient. Time efficient methods that are antibody independent e.g. reverse phase-high performance liquid chromatography (RP-HPLC) or size exclusion-HPLC (SE-HPLC) are available. An improved method implementing reverse phase-ultra performance liquid chromatography (RP-UPLC) has been developed to quantitate the HA1 protein antigen present in the high yield reassortant vaccine seed viruses from influenza A H1N1 and H3N2 subtypes harvested from inoculated embryonated chicken eggs. This method differentiates between high yield and lower yielding reassortants in order to select the best vaccine candidate seed virus with the highest growth ‘in ovo’. This direct capability to monitor the HA1 concentration of potential reassortant seed viruses and to choose the best yielding HA influenza reassortant when faced with multiple viral seed candidates provides a major advantage on the industrial scale to the influenza vaccine process.

Loss-of-function genetic screens in model organisms have elucidated numerous biological processes, but the diploid genome of mammalian cells has precluded large-scale gene disruption. We used insertional mutagenesis to develop a screening method to generate null alleles in a human cell line haploid for all chromosomes except chromosome 8. Using this approach, we identified host factors essential for infection with influenza and genes encoding important elements of the biosynthetic pathway of diphthamide, which are required for the cytotoxic effects of diphtheria toxin and exotoxin A. We also identified genes needed for the action of cytolethal distending toxin, including a cell-surface protein that interacts with the toxin. This approach has both conceptual and practical parallels with genetic approaches in haploid yeast.

Background Glioblastoma (GBM) can be divided into subtypes according to their genomic features, including Proneural (PN), Neural (NE), Classical (CL) and Mesenchymal (ME). However, it is a difficult task to unify various genomic expression profiles which were standardized with various procedures from different studies and to manually classify a given GBM sample into a subtype. Methods An algorithm was developed to unify the genomic profiles of GBM samples into a standardized normal distribution (SND), based on their internal expression ranks. Deep neural networks (DNN) and convolutional DNN (CDNN) models were trained on original and SND data. In addition, expanded SND data by combining various The Cancer Genome Atlas (TCGA) datasets were used to improve the robustness and generalization capacity of the CDNN models. Results The SND data kept unimodal distribution similar to their original data, and also kept the internal expression ranks of all genes for each sample. CDNN models trained on the SND data showed significantly higher accuracy compared to DNN and CDNN models trained on primary expression data. Interestingly, the CDNN models classified the NE subtype with the lowest accuracy in the GBM datasets, expanded datasets and in IDH wide type GBMs, consistent with the recent studies that NE subtype should be excluded. Furthermore, the CDNN models also recognized independent GBM datasets, even with small set of genomic expressions. Conclusions The GBM expression profiles can be transformed into unified SND data, which can be used to train CDNN models with high accuracy and generalization capacity. These models suggested NE subtype may be not compatible with the 4 subtypes classification system.

The pandemic influenza A(H1N1) 2009 virus caused significant morbidity and mortality worldwide thus necessitating the need to understand the host factors that influence its control. Previously, the complement system has been shown to provide protection during the seasonal influenza virus infection, however, the role of individual complement pathways is not yet clear. Here, we have dissected the role of intact complement as well as of its individual activation pathways during the pandemic influenza virus infection using mouse strains deficient in various complement components. We show that the virus infection in C3-/- mice results in increased viral load and 100% mortality, which can be reversed by adoptive transfer of naïve wild-type (WT) splenocytes, purified splenic B cells, or passive transfer of immune sera from WT, but not C3-/- mice. Blocking of C3a and/or C5a receptor signaling in WT mice using receptor antagonists and use of C3aR-/- and C5aR-/- mice showed significant mortality after blocking/ablation of C3aR, with little or no effect after blocking/ablation of C5aR. Intriguingly, deficiency of C4 and FB in mice resulted in only partial mortality (24%-32%) suggesting a necessary cross-talk between the classical/lectin and alternative pathways for providing effective protection. In vitro virus neutralization experiments performed to probe the cross-talk between the various pathways indicated that activation of the classical and alternative pathways in concert, owing to coating of viral surface by antibodies, is needed for its efficient neutralization. Examination of the virus-specific complement-binding antibodies in virus positive subjects showed that their levels vary among individuals. Together these results indicate that cooperation between the classical and alternative pathways not only result in efficient direct neutralization of the pandemic influenza virus, but also lead to the optimum generation of C3a, which when sensed by the immune cells along with the antigen culminates in generation of effective protective immune responses.