Matches in SemOpenAlex for { <https://semopenalex.org/work/W2904316920> ?p ?o ?g. }
- W2904316920 endingPage "142" @default.
- W2904316920 startingPage "131" @default.
- W2904316920 abstract "Transcriptional dysregulation is one of the most important features of cancer genesis and progression. Applying gene expression dysregulation information to predict the development of cancers is useful for cancer diagnosis. However, previous studies mainly focused on the relationship between a single gene and cancer. Prognostic prediction using combined gene models remains limited.Gene expression profiles were downloaded from The Cancer Genome Atlas and the data sets were randomly divided into training data sets and test data sets. A six-gene signature associated with head and neck squamous cell carcinoma (HNSCC) and overall survival (OS) was identified according to a training cohort by using weighted gene correlation network analysis and least absolute shrinkage and selection operator Cox regression. The test data set and gene expression omnibus (GEO) data set were used to validate this signature.We identified six candidate genes, namely, FOXL2NB, PCOLCE2, SPINK6, ULBP2, KCNJ18, and RFPL1, and, using a six-gene model, predicted the risk of death of head and neck squamous cell carcinoma in The Cancer Genome Atlas. At a selected cutoff, patients were clustered into low- and high-risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics of OS, disease-specific survival (DSS), and progression-free survival (PFS) were as high as 0.766, 0.731, and 0.623, respectively. Then, the test data set and the GEO data set were used to evaluate our model, and we found that the OS time in the high-risk group was significantly shorter than in the low-risk group in both data sets, and the receiver operating characteristics of test data set were 0.669, 0.675, and 0.614, respectively. Furthermore, univariate and multivariate Cox regression analyses showed that the risk score was independent of clinicopathological features.The six-gene model could predict the OS of HNSCC patients and improve therapeutic decision-making." @default.
- W2904316920 created "2018-12-22" @default.
- W2904316920 creator A5035316822 @default.
- W2904316920 creator A5068428294 @default.
- W2904316920 creator A5081090509 @default.
- W2904316920 date "2018-12-01" @default.
- W2904316920 modified "2023-10-16" @default.
- W2904316920 title "A six-mRNA prognostic model to predict survival in head and neck squamous cell carcinoma" @default.
- W2904316920 cites W1196042158 @default.
- W2904316920 cites W1530219213 @default.
- W2904316920 cites W1562855786 @default.
- W2904316920 cites W1835769532 @default.
- W2904316920 cites W1964081206 @default.
- W2904316920 cites W1966013725 @default.
- W2904316920 cites W1966327575 @default.
- W2904316920 cites W1970784141 @default.
- W2904316920 cites W2021733365 @default.
- W2904316920 cites W2026161963 @default.
- W2904316920 cites W2035379844 @default.
- W2904316920 cites W2035618305 @default.
- W2904316920 cites W2037730193 @default.
- W2904316920 cites W2041953257 @default.
- W2904316920 cites W2050658289 @default.
- W2904316920 cites W2054318449 @default.
- W2904316920 cites W2055448355 @default.
- W2904316920 cites W2064810566 @default.
- W2904316920 cites W2092878233 @default.
- W2904316920 cites W2102912734 @default.
- W2904316920 cites W2107632586 @default.
- W2904316920 cites W2110664940 @default.
- W2904316920 cites W2112613176 @default.
- W2904316920 cites W2124302413 @default.
- W2904316920 cites W2130178313 @default.
- W2904316920 cites W2130410032 @default.
- W2904316920 cites W2131597845 @default.
- W2904316920 cites W2133650808 @default.
- W2904316920 cites W2152032358 @default.
- W2904316920 cites W2152239989 @default.
- W2904316920 cites W2159482845 @default.
- W2904316920 cites W2160085967 @default.
- W2904316920 cites W2238758434 @default.
- W2904316920 cites W2252881723 @default.
- W2904316920 cites W2261766559 @default.
- W2904316920 cites W2266981417 @default.
- W2904316920 cites W2345801243 @default.
- W2904316920 cites W2518132552 @default.
- W2904316920 cites W2518890474 @default.
- W2904316920 cites W2521260605 @default.
- W2904316920 cites W2523680188 @default.
- W2904316920 cites W2527289641 @default.
- W2904316920 cites W2554827519 @default.
- W2904316920 cites W2571911919 @default.
- W2904316920 cites W2591834340 @default.
- W2904316920 cites W2592760610 @default.
- W2904316920 cites W2606575226 @default.
- W2904316920 cites W2748794149 @default.
- W2904316920 cites W2764283394 @default.
- W2904316920 cites W2766527179 @default.
- W2904316920 cites W2767145937 @default.
- W2904316920 cites W2768700270 @default.
- W2904316920 cites W2790774242 @default.
- W2904316920 cites W2803072064 @default.
- W2904316920 cites W2917837889 @default.
- W2904316920 doi "https://doi.org/10.2147/cmar.s185875" @default.
- W2904316920 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6305138" @default.
- W2904316920 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30588115" @default.
- W2904316920 hasPublicationYear "2018" @default.
- W2904316920 type Work @default.
- W2904316920 sameAs 2904316920 @default.
- W2904316920 citedByCount "24" @default.
- W2904316920 countsByYear W29043169202019 @default.
- W2904316920 countsByYear W29043169202020 @default.
- W2904316920 countsByYear W29043169202021 @default.
- W2904316920 countsByYear W29043169202022 @default.
- W2904316920 countsByYear W29043169202023 @default.
- W2904316920 crossrefType "journal-article" @default.
- W2904316920 hasAuthorship W2904316920A5035316822 @default.
- W2904316920 hasAuthorship W2904316920A5068428294 @default.
- W2904316920 hasAuthorship W2904316920A5081090509 @default.
- W2904316920 hasBestOaLocation W29043169201 @default.
- W2904316920 hasConcept C104317684 @default.
- W2904316920 hasConcept C10515644 @default.
- W2904316920 hasConcept C121608353 @default.
- W2904316920 hasConcept C126322002 @default.
- W2904316920 hasConcept C143998085 @default.
- W2904316920 hasConcept C150194340 @default.
- W2904316920 hasConcept C2776530083 @default.
- W2904316920 hasConcept C2776833033 @default.
- W2904316920 hasConcept C2779733811 @default.
- W2904316920 hasConcept C50382708 @default.
- W2904316920 hasConcept C54355233 @default.
- W2904316920 hasConcept C58471807 @default.
- W2904316920 hasConcept C60644358 @default.
- W2904316920 hasConcept C69991583 @default.
- W2904316920 hasConcept C71924100 @default.
- W2904316920 hasConcept C86803240 @default.
- W2904316920 hasConceptScore W2904316920C104317684 @default.
- W2904316920 hasConceptScore W2904316920C10515644 @default.