Q-omics provides the consensus-scored OR4A47 profile across patient tissues and cancer cell-line models. OR4A47 expression is associated with patient survival in 9 of 34 cancer types, with the highest sampling consensus in KIRC. Additionally, OR4A47 RNA expression shows 3,230 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight KIRC, and STAD as cancer lineages where OR4A47 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 OR4A47 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OR4A47 survival associations across molecular data types. OR4A47 RNA expression shows survival associations in the most cancer types (9), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OR4A47 RNA expression–survival associations across cancer types. High OR4A47 expression shows unfavorable associations in KIRC, BRCA, LAML, KIRP, ACC and READ. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for OR4A47 RNA expression.
This table shows molecular features associated with OR4A47 in patient tissues and cancer cell lines. In patient samples, OR4A47 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, OR4A47 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 OVARY and LARGE_INTESTINE.
