{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T15:49:34Z","timestamp":1787240974844,"version":"build-2736575974"},"reference-count":42,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2020,6,8]],"date-time":"2020-06-08T00:00:00Z","timestamp":1591574400000},"content-version":"vor","delay-in-days":159,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BioMed Research International"],"published-print":{"date-parts":[[2020,1]]},"abstract":"<jats:p>\n                    <jats:italic>Objective<\/jats:italic>\n                    . Diffuse large B\u2010cell lymphoma (DLBCL) is a highly aggressive malignant tumor, accounting for 30\u201040% of non\u2010Hodgkin\u2019s lymphoma. Our aim was to construct novel prognostic models of candidate genes based on clinical features.\n                    <jats:italic>Methods<\/jats:italic>\n                    . RNA\u2010seq and clinical data of DLBCL were retrieved from TCGA database. Coexpression modules were constructed by WGCNA. Then, we investigated the interactions between modules and clinical features. By overall survival analysis, prognostic candidate genes from modules of interest were identified. A coexpression network of prognostic candidate genes was then constructed through WGCNA. GEPIA was used to analyze the expression of a candidate gene between DLBCL and normal samples.\n                    <jats:italic>Results<\/jats:italic>\n                    . 19 coexpression modules were constructed by 12813 genes from 52 DLBCL samples. The number of genes in modules ranged from 34 to 5457. We found that the purple module was significantly related with histological type (\n                    <jats:italic>p<\/jats:italic>\n                    value = 1\n                    <jats:italic>e<\/jats:italic>\n                    \u201004). Overall survival analysis revealed that MAFA\u2010AS1, hsa\u2010mir\u2010338, and hsa\u2010mir\u2010891a were related with prognosis of DLBCL (\n                    <jats:italic>p<\/jats:italic>\n                    value = 0.027, 0.039, and 0.022, respectively). A coexpression network was constructed for the three prognostic genes. MAFA\u2010AS1 was interacted with 36 genes, hsa\u2010mir\u2010891a was interacted with 11 genes, while no gene showed interaction with hsa\u2010mir\u2010338. Using GEPIA, we found that MAFA\u2010AS1 showed low expression in DLBCL samples (\n                    <jats:italic>p<\/jats:italic>\n                    &lt; 0.01).\n                    <jats:italic>Conclusion<\/jats:italic>\n                    . We constructed a coexpression module related with histological type and identified three candidate genes (MAFA\u2010AS1, hsa\u2010mir\u2010338, and hsa\u2010mir\u2010891a) that possessed potential value as prognostic biomarkers and therapeutic targets of DLBCL.\n                  <\/jats:p>","DOI":"10.1155\/2020\/7947208","type":"journal-article","created":{"date-parts":[[2020,6,8]],"date-time":"2020-06-08T19:32:06Z","timestamp":1591644726000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Clinical Features and Prognostic Impact of Coexpression Modules Constructed by WGCNA for Diffuse Large B\u2010Cell 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