Identification of aneuploidy-related gene signature to predict survival in head and neck squamous cell carcinomas
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Background: To parse the characteristics of aneuploidy related riskscore (ARS) model in head and neck squamous cell carcinomas (HNSC) and their predictive ability on patient prognosis. Methods: Molecular subtyping of HNSC specimens was clustered by Copy Number Variation (CNV) data from The Cancer Genome Atlas (TCGA) dataset applying consistent clustering, followed by immune condition evaluation, differentially expressed genes (DEGs) analysis and DEGs function annotation. Weighted gene co-expression network analysis (WGCNA), protein-protein interaction, Univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analysis were implemented to construct an ARS model. A nomogram for clinic practice was designed by rms package. Immunotherapy evaluation and drug sensitivity prediction were also carried out. Results: We stratified HNSC patients into three different molecular subgroups, with the best prognosis in C1 cluster among 3 clusters. C1 cluster displayed greatest immune infiltration status. The most DEGs between C1 and C2 groups, mainly enriched in cell cycle and immune function. We constructed a nine-gene ARS model (ICOS, IL21R, CCR7, SELL, CYTIP, ZAP70, CCR4, S1PR4 and CD79A) that effectively differentiates between high- and low-risk patients. Patients in low ARS group showed a higher sensitivity to immunotherapy. A nomogram built by integrating ARS and clinic-pathological characteristics helped predict clinic survival benefit. Drug sensitivity evaluation found that 4/9 inhibitor drugs (MK-8776, AZD5438, PD-0332991, PHA-665752) acted on the cell cycle. Conclusions: We classified 3 molecular subtypes for HNSC patients and established an ARS prognostic model, which offered a prospective direction for prognosis in HNSC.Keywords:
Nomogram
Univariate
Gene signature
Subtyping
Abstract The purpose of subtyping is to differentiate bacterial isolates beyond the classification of species or subspecies. Subtyping methods can be grouped into two broad categories based on the cellular components targeted: (1) phenotypic subtyping methods that differentiate isolates by the enzymes, proteins, or other metabolites expressed by the cell, and (2) molecular subtyping methods that discriminate isolates based on interrogation of nucleic acid sequences. The two major types of molecular subtyping methods include band-based methods based on fragment pattern data or DNA fingerprints, and methods that generate DNA sequence data. Molecular subtyping methods have shown that Listeria monocytogenes isolates can be classified into four genetic lineages or divisions. Although band-based molecular subtyping methods continue to serve as the gold standard for routine molecular subtyping of most clinically important foodborne pathogens, including L. monocytogenes, the explosion of recently completed and ongoing DNA sequencing projects, and thus available DNA sequence data, have stimulated efforts to develop highly discriminatory and high-throughput DNA sequence-based subtyping methods for L. monocytogenes. L. monocytogenes represents one of the most highly sequenced human pathogens; more than 20 genome sequences are currently available for this organism. This review provides an overview of the concepts behind subtyping and discusses the application of molecular subtyping methods, with an emphasis on DNA sequence-based subtyping methods to characterize L. monocytogenes.
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Radiotherapy is an effective treatment for head and neck squamous cell carcinoma (HNSCC), however how to predict the prognosis is not clear.Here we collected 262 radiosensitivity-associated genes, screened and constructed a prognostic nine-gene risk model through univariate COX, lasso regression, stepwise regression and multivariate COX analysis for transcriptome and clinical information of HNSCC patients obtained from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases.The reliability and robustness of the risk model were verified by receiver operating characteristic (ROC) curves, risk maps, and Kaplan-Meier (KM) curves analysis. Differences in immune cell infiltration and immune-related pathway enrichment between high-risk and low-risk subgroups were determined by multiple immune infiltration analyses. Meanwhile, the mutation map and the responses to immunotherapy were also differentiated by the prognostic nine-gene signature associated with radiosensitivity. These nine genes expression in HNSCC was verified in the Human Protein Atlas (HPA) database. After that, these nine genes expression was verified to be related to radiation resistance through in-vitro cell experiments.All results showed that the nine-gene signature associated with radiosensitivity is a potential prognostic indicator for HNSCC patients after radiotherapy and provides potential gene targets for enhancing the efficacy of radiotherapy.
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Bacteria subtyping methods not only improve our ability to detect and track human listeriosis outbreaks, but also provide useful tools to track sources of L.monocytogenes contamination throughout the food system. Additionally, the use of subtyping methods provide an opportunity to better understand the population genetics, epidemiology, and the ecology of L.monocytogenes.The last five years have seen tremendous advancements in the development of sensitive,rapid,automated,and increasingly easy to use molecular subtyping methods for L.monocytogenes This review focused on the the different subtyping methods of L.monocytogenes and it's applications.
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Biochemical recurrence
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Head and neck squamous cell carcinoma (HNSCC) is still a menace to public wellbeing globally. However, the underlying molecular events influencing the carcinogenesis and prognosis of HNSCC are poorly known.Gene expression profiles of The Cancer Genome Atlas (TCGA) HNSCC dataset and GSE37991 were downloaded from the TCGA database and gene expression omnibus, respectively. The common differentially expressed metabolic enzymes (DEMEs) between HNSCC tissues and normal controls were screened out. Then a DEME-based molecular signature and a clinically practical nomogram model were constructed and validated.A total of 23 commonly upregulated and 9 commonly downregulated DEMEs were identified in TCGA HNSCC and GSE37991. Gene ontology analyses of the common DEMEs revealed that alpha-amino acid metabolic process, glycosyl compound metabolic process, and cellular amino acid metabolic process were enriched. Based on the TCGA HNSCC cohort, we have built up a robust DEME-based prognostic signature including HPRT1, PLOD2, ASNS, TXNRD1, CYP27B1, and FUT6 for predicting the clinical outcome of HNSCC. Furthermore, this prognosis signature was successfully validated in another independent cohort GSE65858. Moreover, a potent prognostic signature-based nomogram model was constructed to provide personalized therapeutic guidance for treating HNSCC. In vitro experiment revealed that the knockdown of TXNRD1 suppressed malignant activities of HNSCC cells.Our study has successfully developed a robust DEME-based signature for predicting the prognosis of HNSCC. Moreover, the nomogram model might provide useful guidance for the precision treatment of HNSCC.
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Consistent subtyping is employed in some gradual type systems to validate type conversions. The original definition by Siek and Taha serves as a guideline for designing gradual type systems with subtyping. Polymorphic types à la System F also induce a subtyping relation that relates polymorphic types to their instantiations. However Siek and Taha's definition is not adequate for polymorphic subtyping. The first goal of this paper is to propose a generalization of consistent subtyping that is adequate for polymorphic subtyping, and subsumes the original definition by Siek and Taha. The new definition of consistent subtyping provides novel insights with respect to previous polymorphic gradual type systems, which did not employ consistent subtyping. The second goal of this paper is to present a gradually typed calculus for implicit (higher-rank) polymorphism that uses our new notion of consistent subtyping. We develop both declarative and (bidirectional) algorithmic versions for the type system. We prove that the new calculus satisfies all static aspects of the refined criteria for gradual typing, which are mechanically formalized using the Coq proof assistant.
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Conventional, phenotypic, and DNA-based subtyping methods allow differentiation of Listeria monocytogenes beyond the species and subspecies level. Bacterial subtyping methods not only improve our ability to detect and track human listeriosis outbreaks, but also provide tools to track sources of L. monocytogenes contamination throughout the food system. The use of subtyping methods also provides an opportunity to better understand the population genetics, epidemiology, and ecology of L. monocytogenes. The last 5 years have seen tremendous advancements in the development of sensitive, rapid, automated, and increasingly easy-to-use molecular subtyping methods for L. monocytogenes. This review highlights key aspects of different L. monocytogenes subtyping methods and provides examples of their application in public health, food safety, population genetics, and epidemiology. A significant focus is on the application of subtyping methods to define L. monocytogenes subtypes and clonal groups, which may differ in phenotypic characteristics and pathogenic potential.
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Abstract Background: Head and neck squamous cell carcinoma (HNSCC) is most diagnosed at an advanced stage with poor prognosis. Single gene biomarkers cannot have enough predictive ability in HNSCC. Glycolysis participating in cancers was verified. Thus, this study aimed to identify glycolysis-related gene signature predict the outcome of HNSCC. Methods: The mRNA expression data of HNSCC downloaded The Cancer Genome Atlas (TCGA) project was analyzed by Gene Set Enrichment Analysis (GSEA). We use the Cox proportional regression model to construct a prognostic model. Kaplan–Meier and receiver operating characteristic (ROC) curves were employed to estimate the signature. We also analyzed the relationship of the signature and cancer subtypes. Results: We identified nine glycolysis-related genes including G6PD, EGFR, ALDH2, GPR87, STC2, PDK3, ELF3, STC1 and GNPDA1 as prognosis-related genes signature in HNSCC. HNSCC patients were divided into high and low risk group according to the signature. High risk group showed more poor prognosis and the risk score can precisely predict the prognosis of HNSCC. Additionally, the signature also can be used in cancer subtypes. Conclusion: This study established the 9-mRNA glycolysis signature which may serve as a prospective biomarker for prognosis and novel treatment target in HNSCC.
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The breast cancer is a usual and serious malignant tumor which threatens the women′s health.Molecular subtyping bases on the molecular level, and provides a new classification method for the breast cancer pathology classification, and plays an important guidance significance for the clinical treatment.At present, the breast cancer molecular subtyping is mainly divided into the following subtypes: the Luminal A type and Luminal B type, HER-2 overexpression and the triple negative breast cancer.Different molecular subtyping has different characteristics in treatment reaction, prognosis and the clinical application situation.
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Breast neoplasms; Molecular subtyping; Clinic Treatment
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