Q-omics provides the consensus-scored IFNA14 profile across patient tissues and cancer cell-line models. IFNA14 expression is associated with patient survival in 8 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, IFNA14 is differentially expressed in 3, with the highest sampling consensus in KIRC. Additionally, IFNA14 RNA expression shows 5,802 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight STAD, and KIRC as cancer lineages where IFNA14 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 IFNA14 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFNA14 survival associations across molecular data types. IFNA14 RNA expression shows survival associations in the most cancer types (8), 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 IFNA14 RNA expression–survival associations across cancer types. High IFNA14 expression shows unfavorable associations in STAD, OV, PAAD, SCLC, ACC and UCEC. The STAD 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 STAD as the clearest survival context for IFNA14 RNA expression.
This table summarizes IFNA14 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for IFNA14. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFNA14 shows lower tumor expression in KIRC, KICH and KIRP. The KIRC box plot shows higher IFNA14 RNA expression in normal versus tumor tissue (log2 FC = −0.317, t-test p < 0.001).
This table shows molecular features associated with IFNA14 in patient tissues and cancer cell lines. In patient samples, IFNA14 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, IFNA14 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BREAST.
