Q-omics provides the consensus-scored OR8D2 profile across patient tissues and cancer cell-line models. OR8D2 expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in UCS. Additionally, OR8D2 RNA expression shows 8,020 significant gene co-expression associations, with the highest sampling consensus in COAD. Together, these results highlight UCS, and COAD as cancer lineages where OR8D2 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 OR8D2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OR8D2 survival associations across molecular data types. OR8D2 RNA expression shows survival associations in the most cancer types (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OR8D2 RNA expression–survival associations across cancer types. High OR8D2 expression shows unfavorable associations in UCS, UCEC, LUSC, COAD, OV and KIRP. The UCS 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 UCS as the clearest survival context for OR8D2 RNA expression.
This table shows molecular features associated with OR8D2 in patient tissues and cancer cell lines. In patient samples, OR8D2 shows the broadest associations at the RNA and protein expression levels, with COAD recurring as the lineage with the largest associated feature set. In cancer cell lines, OR8D2 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 SKIN and OVARY.
