Q-omics provides the consensus-scored OR11H1 profile across patient tissues and cancer cell-line models. OR11H1 expression is associated with patient survival in 6 of 34 cancer types, with the highest sampling consensus in ESCA. Additionally, OR11H1 protein abundance shows 19,248 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ESCA, and PDAC as cancer lineages where OR11H1 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 OR11H1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OR11H1 survival associations across molecular data types. OR11H1 RNA expression shows survival associations in the most cancer types (6), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OR11H1 RNA expression–survival associations across cancer types. High OR11H1 expression shows unfavorable associations in BRCA, STAD, SKCM and GBM, but favorable associations in ESCA and OV. The ESCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify ESCA as the clearest survival context for OR11H1 RNA expression.
This table shows molecular features associated with OR11H1 in patient tissues and cancer cell lines. In patient samples, OR11H1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, OR11H1 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 BLOOD_Leukemia and LUNG_SCLC.
