Q-omics provides the consensus-scored IFNL2 profile across patient tissues and cancer cell-line models. IFNL2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, IFNL2 is differentially expressed in 7, with the highest sampling consensus in HNSC. Additionally, IFNL2 RNA expression shows 6,813 significant gene co-expression associations, with the highest sampling consensus in LIHC. Together, these results highlight UCEC, HNSC, and LIHC as cancer lineages where IFNL2 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 IFNL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFNL2 survival associations across molecular data types. IFNL2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFNL2 RNA expression–survival associations across cancer types. High IFNL2 expression shows unfavorable associations in UCEC, THYM, COAD, LIHC and BRCA, but favorable associations in UCS. 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 IFNL2 RNA expression.
This table summarizes IFNL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for IFNL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFNL2 shows higher tumor expression in HNSC, BRCA, KIRC, LUAD, LUSC and COAD. The HNSC box plot shows higher IFNL2 RNA expression in tumor versus normal tissue (log2 FC = +0.221, t-test p < 0.001).
This table shows molecular features associated with IFNL2 in patient tissues and cancer cell lines. In patient samples, IFNL2 shows the broadest associations at the RNA and protein expression levels, with LIHC recurring as the lineage with the largest associated feature set. In cancer cell lines, IFNL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
