Q-omics provides the consensus-scored IFNL4P1 profile across patient tissues and cancer cell-line models. IFNL4P1 expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, IFNL4P1 is differentially expressed in 3, with the highest sampling consensus in BRCA. Additionally, IFNL4P1 RNA expression shows 9,794 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight CESC, BRCA, and UVM as cancer lineages where IFNL4P1 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 IFNL4P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFNL4P1 survival associations across molecular data types. IFNL4P1 RNA expression shows survival associations in the most cancer types (14). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFNL4P1 RNA expression–survival associations across cancer types. High IFNL4P1 expression shows unfavorable associations in ACC, COAD and ESCA, but favorable associations in CESC, UCEC and STAD. The CESC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify CESC as the clearest survival context for IFNL4P1 RNA expression.
This table summarizes IFNL4P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for IFNL4P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFNL4P1 shows higher tumor expression in BRCA, LUSC and LUAD. The BRCA box plot shows higher IFNL4P1 RNA expression in tumor versus normal tissue (log2 FC = +0.058, t-test p = .042).
This table shows molecular features associated with IFNL4P1 in patient tissues and cancer cell lines. In patient samples, IFNL4P1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set.
