Q-omics provides the consensus-scored IRF2-DT profile across patient tissues and cancer cell-line models. IRF2-DT expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, IRF2-DT is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, IRF2-DT RNA expression shows 18,864 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SKCM, KICH, and ACC as cancer lineages where IRF2-DT shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for IRF2-DT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IRF2-DT survival associations across molecular data types. IRF2-DT RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IRF2-DT RNA expression–survival associations across cancer types. High IRF2-DT expression shows unfavorable associations in LGG and ACC, but favorable associations in SKCM, BRCA, STAD and READ. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for IRF2-DT RNA expression.
This table summarizes IRF2-DT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for IRF2-DT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IRF2-DT shows lower tumor expression in KICH, THCA, LUAD, KIRC and BRCA and higher tumor expression in STAD. The KICH box plot shows higher IRF2-DT RNA expression in normal versus tumor tissue (log2 FC = −1.649, t-test p < 0.001).
This table shows molecular features associated with IRF2-DT in patient tissues and cancer cell lines. In patient samples, IRF2-DT shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set.
