Q-omics provides the consensus-scored IRF6 profile across patient tissues and cancer cell-line models. IRF6 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, IRF6 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, IRF6 protein abundance shows 26,746 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where IRF6 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 IRF6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IRF6 survival associations across molecular data types. IRF6 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (9) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IRF6 RNA expression–survival associations across cancer types. High IRF6 expression shows unfavorable associations in PAAD, SKCM and THCA, but favorable associations in KIRC, UVM and ACC. The KIRC 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 KIRC as the clearest survival context for IRF6 RNA expression.
This table summarizes IRF6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IRF6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IRF6 shows lower tumor expression in KIRC and KIRP and higher tumor expression in HNSC, LUSC, BLCA and LIHC. The KIRC box plot shows higher IRF6 RNA expression in normal versus tumor tissue (log2 FC = −2.741, t-test p < 0.001).
This table shows molecular features associated with IRF6 in patient tissues and cancer cell lines. In patient samples, IRF6 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, IRF6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Myeloma.
