Bioinformatics Analysis of GFAP as a Potential Key Regulator in Different Immune Phenotypes of Prostate Cancer

<div>Identification of a key node within the genetic and epigenetic regulatory networks. (a) The integration of DEG, lncRNA, miRNA, and methylation analyses to determine upregulated differentially expressed genes in groups <svg height="8.8423pt" id="M86" style="vertical-align:-0.2064009pt" version="1.1" viewbox="-0.0498162 -8.6359 15.0796 8.8423" width="15.0796pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M645 631C614 643 545 666 457 666C215 666 23 519 23 283C23 90 158 -16 337 -16C412 -16 489 2 522 10C543 39 590 127 606 167L580 181C519 89 459 18 348 18C201 18 122 136 122 287C122 464 244 632 435 632C544 632 602 595 608 472L639 475C643 526 645 581 645 631Z"></path></g><g transform="matrix(.013,0,0,-0.013,8.684,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"></path></g></svg> and <span class="nowrap"><svg height="8.8423pt" id="M87" style="vertical-align:-0.2064009pt" version="1.1" viewbox="-0.0498162 -8.6359 15.0796 8.8423" width="15.0796pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M645 631C614 643 545 666 457 666C215 666 23 519 23 283C23 90 158 -16 337 -16C412 -16 489 2 522 10C543 39 590 127 606 167L580 181C519 89 459 18 348 18C201 18 122 136 122 287C122 464 244 632 435 632C544 632 602 595 608 472L639 475C643 526 645 581 645 631Z"></path></g><g transform="matrix(.013,0,0,-0.013,8.684,0)"><path d="M412 140C382 77 369 73 315 73H129L270 222C362 320 402 379 402 466C402 571 322 635 234 635C177 635 130 609 99 576L42 495L64 475C90 514 133 568 201 568C274 568 318 519 318 435C318 349 255 267 193 193C144 135 87 78 32 23V0H405C417 45 427 89 440 131L412 140Z"></path></g></svg>.</span> (b) The four genes positively associated with prognosis were confirmed using a random forest blot in TCGA-PRAD cohort. (c) A Kaplan-Meier analysis of the 4-gene model using TGCA-PRAD cohort. (d) GFAP was identified as a key hub gene within the network using a protein-protein interaction analysis of the STRING Consortium database. (e) Spearman’s correlation analysis was performed to analyze correlations between GFAP transcription levels and immune-cell subsets for TCGA-PRAD cohort.</div>

BioMed Research International

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Figure 5

Figure 5: Bioinformatics Analysis of GFAP as a Potential Key Regulator in Different Immune Phenotypes of Prostate Cancer 