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    <responseDate>2026-10-14T10:41:28Z</responseDate>
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    <identifier>10.57760/sciencedb.28025</identifier>
    <datestamp>2026-06-16T09:25:19Z</datestamp>
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  <dc:date>2026-06-16</dc:date>
  <dc:title>The data of the article &amp;quot;Integrated Multi-Omics Analysis Identifies Prognostic Risk Genes and Constructs a Predictive Signature in Diffuse Large B-Cell Lymphoma&amp;quot;</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.28025</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset supports the research titled &amp;quot;Integrated Multi-Omics Analysis Identifies Prognostic Risk Genes and Constructs a Predictive Signature in Diffuse Large B-Cell Lymphoma&amp;quot; and contains two parts of original data.Supplementary Materials 1&amp;nbsp;contains the raw data from the eQTL-MR analysis identifying potential causal genes associated with DLBCL, including scatter plots, forest plots, funnel plots, and leave-one-out analysis of the assessed genes.Supplementary Materials 2&amp;nbsp;contains the raw data from the drug sensitivity analysis, documenting 87 statistically significant drugs identified in the analysis of potential sensitive drugs for the high/low-risk groups in the DLBCL prognostic model using the &amp;quot;pRRophetic&amp;quot; package.The Excel file in the Supplementary Attachment contains the first-line treatment regimens received by DLBCL patients from the GEO dataset GSE181063.</dc:description>
  <dc:subject>risk genes; DLBCL; drug sensitivity analysis</dc:subject>
  <dc:creator>Qixin Liu</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1080/16078454.2026.2700818</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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