Q-omics provides the consensus-scored IFNA4 profile across patient tissues and cancer cell-line models. IFNA4 expression is associated with patient survival in 9 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, IFNA4 is differentially expressed in 1, with the highest sampling consensus in BRCA. Additionally, IFNA4 RNA expression shows 6,809 significant gene co-expression associations, with the highest sampling consensus in COAD. Together, these results highlight UCEC, BRCA, and COAD as cancer lineages where IFNA4 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 IFNA4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFNA4 survival associations across molecular data types. IFNA4 RNA expression shows survival associations in the most cancer types (9), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFNA4 RNA expression–survival associations across cancer types. High IFNA4 expression shows unfavorable associations in UCEC, HNSC, STAD, LIHC, CESC and KIRP. The UCEC 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 UCEC as the clearest survival context for IFNA4 RNA expression.
This table summarizes IFNA4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for IFNA4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFNA4 shows higher tumor expression in BRCA. The BRCA box plot shows higher IFNA4 RNA expression in tumor versus normal tissue (log2 FC = +0.007, t-test p = .006).
This table shows molecular features associated with IFNA4 in patient tissues and cancer cell lines. In patient samples, IFNA4 shows the broadest associations at the RNA and protein expression levels, with COAD recurring as the lineage with the largest associated feature set. In cancer cell lines, IFNA4 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 LUNG_NSCLC_LUAD and BLOOD_Myeloma.
