Q-omics provides the consensus-scored IFNE profile across patient tissues and cancer cell-line models. IFNE expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, IFNE is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, IFNE RNA expression shows 13,266 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight LUAD, HNSC, and THYM as cancer lineages where IFNE 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 IFNE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFNE survival associations across molecular data types. IFNE RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFNE RNA expression–survival associations across cancer types. High IFNE expression shows unfavorable associations in LUAD, KIRC, UVM, COAD and ACC, but favorable associations in BRCA. The LUAD 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 LUAD as the clearest survival context for IFNE RNA expression.
This table summarizes IFNE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for IFNE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFNE shows lower tumor expression in BRCA and higher tumor expression in HNSC, THCA, COAD, LUAD and LUSC. The HNSC box plot shows higher IFNE RNA expression in tumor versus normal tissue (log2 FC = +0.621, t-test p < 0.001).
This table shows molecular features associated with IFNE in patient tissues and cancer cell lines. In patient samples, IFNE shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, IFNE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
