Q-omics provides the consensus-scored IRF4 profile across patient tissues and cancer cell-line models. IRF4 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, IRF4 is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, IRF4 RNA expression shows 17,500 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, COAD, and LSCC as cancer lineages where IRF4 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 IRF4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IRF4 survival associations across molecular data types. IRF4 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IRF4 RNA expression–survival associations across cancer types. High IRF4 expression shows favorable associations in HNSC, LUAD, UCEC, CESC, OV and COAD. The HNSC 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 HNSC as the clearest survival context for IRF4 RNA expression.
This table summarizes IRF4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for IRF4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IRF4 shows lower tumor expression in COAD, BRCA, READ and BLCA and higher tumor expression in KIRC and ESCA. The COAD box plot shows higher IRF4 RNA expression in normal versus tumor tissue (log2 FC = −2.300, t-test p < 0.001).
This table shows molecular features associated with IRF4 in patient tissues and cancer cell lines. In patient samples, IRF4 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, IRF4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
