Q-omics provides the consensus-scored IRF3 profile across patient tissues and cancer cell-line models. IRF3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, IRF3 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, IRF3 RNA expression shows 18,488 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where IRF3 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 IRF3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IRF3 survival associations across molecular data types. IRF3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IRF3 RNA expression–survival associations across cancer types. High IRF3 expression shows unfavorable associations in KIRC, ACC, LGG, LIHC, OV and KICH. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for IRF3 RNA expression.
This table summarizes IRF3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IRF3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IRF3 shows higher tumor expression in HNSC, COAD, KIRC, BLCA, LIHC and STAD. The HNSC box plot shows higher IRF3 RNA expression in tumor versus normal tissue (log2 FC = +0.995, t-test p < 0.001).
This table shows molecular features associated with IRF3 in patient tissues and cancer cell lines. In patient samples, IRF3 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, IRF3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and SOFT_TISSUE.
