Q-omics provides the consensus-scored OR5M8 profile across patient tissues and cancer cell-line models. OR5M8 expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in ACC. Additionally, OR5M8 RNA expression shows 7,005 significant gene co-expression associations, with the highest sampling consensus in COAD. Together, these results highlight ACC, and COAD as cancer lineages where OR5M8 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 OR5M8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OR5M8 survival associations across molecular data types. OR5M8 RNA expression shows survival associations in the most cancer types (10), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OR5M8 RNA expression–survival associations across cancer types. High OR5M8 expression shows unfavorable associations in ACC, CESC, LIHC, STAD, UCEC and TGCT. The ACC 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 ACC as the clearest survival context for OR5M8 RNA expression.
This table shows molecular features associated with OR5M8 in patient tissues and cancer cell lines. In patient samples, OR5M8 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, OR5M8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
