FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313483105> ?p ?o ?g. }

• W4313483105 abstract "Objective Invasive pituitary adenomas (IPAs) are common tumors of the nervous system tumors for which invasive growth can lead to difficult total resection and a high recurrence rate. The basement membrane (BM) is a special type of extracellular matrix and plays an important role in the invasion of pituitary adenomas (PAs). The aim of this study was to develop a risk model for predicting the invasiveness of PAs by analyzing the correlation between the expression of BM genes and immune infiltration. Methods Four datasets, featuring samples IPAs and non-invasive pituitary adenomas (NIPAs), were obtained from the Gene Expression Omnibus database (GEO). R software was then used to identify differentially expressed genes (DEGs) and analyze their functional enrichment. Protein-protein interaction (PPI) network was used to screen BM genes, which were analyzed for immune infiltration; this led to the generation of a risk model based on the correlation between the expression of BM genes and immunity. A calibration curve and receiver operating characteristic (ROC) curve were used to evaluate and validate the model. Subsequently, the differential expression levels of BM genes between IPA and NIPA samples collected in surgery were verified by Quantitative Polymerase Chain Reaction (qPCR) and the prediction model was further evaluated. Finally, based on our analysis, we recommend potential drug targets for the treatment of IPAs. Results The merged dataset identified 248 DEGs that were mainly enriching in signal transduction, the extracellular matrix and channel activity. The PPI network identified 11 BM genes from the DEGs: SPARCL1, GPC3, LAMA1, SDC4, GPC4, ADAMTS8, LAMA2, LAMC3, SMOC1, LUM and THBS2 . Based on the complex correlation between these 11 genes and immune infiltration, a risk model was established to predict PAs invasiveness. Calibration curve and ROC curve analysis (area under the curve [AUC]: 0.7886194) confirmed the good predictive ability of the model. The consistency between the qPCR results and the bioinformatics results confirmed the reliability of data mining. Conclusion Using a variety of bioinformatics methods, we developed a novel risk model to predict the probability of PAs invasion based on the correlation between 11 BM genes and immune infiltration. These findings may facilitate closer surveillance and early diagnosis to prevent or treat IPAs in patients and improve the clinical awareness of patients at high risk of IPAs." @default.
• W4313483105 created "2023-01-06" @default.
• W4313483105 creator A5009427324 @default.
• W4313483105 creator A5015182080 @default.
• W4313483105 creator A5032769690 @default.
• W4313483105 creator A5054416550 @default.
• W4313483105 creator A5057209439 @default.
• W4313483105 creator A5070770063 @default.
• W4313483105 creator A5082192610 @default.
• W4313483105 date "2023-01-04" @default.
• W4313483105 modified "2023-09-23" @default.
• W4313483105 title "A novel risk model based on the correlation between the expression of basement membrane genes and immune infiltration to predict the invasiveness of pituitary adenomas" @default.
• W4313483105 cites W1538274695 @default.
• W4313483105 cites W1566831845 @default.
• W4313483105 cites W1607070363 @default.
• W4313483105 cites W1966107523 @default.
• W4313483105 cites W1982767024 @default.
• W4313483105 cites W1987870207 @default.
• W4313483105 cites W1991106585 @default.
• W4313483105 cites W2017199818 @default.
• W4313483105 cites W2022107266 @default.
• W4313483105 cites W2033278321 @default.
• W4313483105 cites W2035618305 @default.
• W4313483105 cites W2053835153 @default.
• W4313483105 cites W2056402996 @default.
• W4313483105 cites W2058648826 @default.
• W4313483105 cites W2059084973 @default.
• W4313483105 cites W2062265555 @default.
• W4313483105 cites W2076285703 @default.
• W4313483105 cites W2088356281 @default.
• W4313483105 cites W2096086497 @default.
• W4313483105 cites W2113253187 @default.
• W4313483105 cites W2130290528 @default.
• W4313483105 cites W2142504546 @default.
• W4313483105 cites W2142879323 @default.
• W4313483105 cites W2146512944 @default.
• W4313483105 cites W2152615180 @default.
• W4313483105 cites W2153505392 @default.
• W4313483105 cites W2156543203 @default.
• W4313483105 cites W2162389215 @default.
• W4313483105 cites W2290771197 @default.
• W4313483105 cites W2315643559 @default.
• W4313483105 cites W2336147186 @default.
• W4313483105 cites W2406250479 @default.
• W4313483105 cites W2482719792 @default.
• W4313483105 cites W2500859845 @default.
• W4313483105 cites W2508593892 @default.
• W4313483105 cites W2538851899 @default.
• W4313483105 cites W2561907496 @default.
• W4313483105 cites W2574984622 @default.
• W4313483105 cites W2586116929 @default.
• W4313483105 cites W2586407709 @default.
• W4313483105 cites W2709595243 @default.
• W4313483105 cites W2749235803 @default.
• W4313483105 cites W2785792383 @default.
• W4313483105 cites W2902244724 @default.
• W4313483105 cites W2911634759 @default.
• W4313483105 cites W2911982722 @default.
• W4313483105 cites W2912668085 @default.
• W4313483105 cites W2938556209 @default.
• W4313483105 cites W2946450286 @default.
• W4313483105 cites W2946685097 @default.
• W4313483105 cites W2966340596 @default.
• W4313483105 cites W2986368198 @default.
• W4313483105 cites W2988403979 @default.
• W4313483105 cites W3007796049 @default.
• W4313483105 cites W3009474140 @default.
• W4313483105 cites W3036203472 @default.
• W4313483105 cites W3047947417 @default.
• W4313483105 cites W3049570152 @default.
• W4313483105 cites W3082639090 @default.
• W4313483105 cites W3092512688 @default.
• W4313483105 cites W3122053845 @default.
• W4313483105 cites W3133096684 @default.
• W4313483105 cites W3144992645 @default.
• W4313483105 cites W3160106392 @default.
• W4313483105 cites W3160822742 @default.
• W4313483105 cites W3162480913 @default.
• W4313483105 cites W3169680836 @default.
• W4313483105 cites W3177702707 @default.
• W4313483105 cites W3177988238 @default.
• W4313483105 cites W3211735814 @default.
• W4313483105 cites W3217307638 @default.
• W4313483105 cites W4210259876 @default.
• W4313483105 cites W4226156408 @default.
• W4313483105 cites W4280499086 @default.
• W4313483105 cites W4282838535 @default.
• W4313483105 cites W4285678281 @default.
• W4313483105 cites W4296526537 @default.
• W4313483105 cites W904255362 @default.
• W4313483105 doi "https://doi.org/10.3389/fendo.2022.1079777" @default.
• W4313483105 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36686480" @default.
• W4313483105 hasPublicationYear "2023" @default.
• W4313483105 type Work @default.
• W4313483105 citedByCount "0" @default.
• W4313483105 crossrefType "journal-article" @default.
• W4313483105 hasAuthorship W4313483105A5009427324 @default.
• W4313483105 hasAuthorship W4313483105A5015182080 @default.
• W4313483105 hasAuthorship W4313483105A5032769690 @default.
• W4313483105 hasAuthorship W4313483105A5054416550 @default.

• next