Q-omics provides the consensus-scored OR4E2 profile across patient tissues and cancer cell-line models. OR4E2 expression is associated with patient survival in 8 of 34 cancer types, with the highest sampling consensus in MESO. Additionally, OR4E2 RNA expression shows 6,338 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight MESO, and THYM as cancer lineages where OR4E2 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 OR4E2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OR4E2 survival associations across molecular data types. OR4E2 RNA expression shows survival associations in the most cancer types (8), 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 OR4E2 RNA expression–survival associations across cancer types. High OR4E2 expression shows unfavorable associations in MESO, UVM, BRCA, LIHC and STAD, but favorable associations in PAAD. The MESO 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 MESO as the clearest survival context for OR4E2 RNA expression.
This table shows molecular features associated with OR4E2 in patient tissues and cancer cell lines. In patient samples, OR4E2 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, OR4E2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BONE.
