interferon regulatory factor 1Genealiases: IMD117 · IRF-1 · MAR
Q-omics provides the consensus-scored IRF1 profile across patient tissues and cancer cell-line models. IRF1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, IRF1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, IRF1 RNA expression shows 17,098 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, KIRC, and UVM as cancer lineages where IRF1 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 IRF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IRF1 survival associations across molecular data types. IRF1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) 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 IRF1 RNA expression–survival associations across cancer types. High IRF1 expression shows unfavorable associations in KIRP, UVM and LGG, but favorable associations in SKCM, BRCA and KIRC. 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 IRF1 RNA expression.
This table summarizes IRF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for IRF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IRF1 shows lower tumor expression in LUSC, KICH and LUAD and higher tumor expression in KIRC, STAD and BRCA. The KIRC box plot shows higher IRF1 RNA expression in tumor versus normal tissue (log2 FC = +1.617, t-test p < 0.001).
This table shows molecular features associated with IRF1 in patient tissues and cancer cell lines. In patient samples, IRF1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, IRF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
