Q-omics provides the consensus-scored OPN1MW profile across patient tissues and cancer cell-line models. OPN1MW expression is associated with patient survival in 4 of 34 cancer types, with the highest sampling consensus in LUAD. Additionally, OPN1MW RNA expression shows 4,107 significant gene co-expression associations, with the highest sampling consensus in COAD. Together, these results highlight LUAD, and COAD as cancer lineages where OPN1MW 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 OPN1MW — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OPN1MW survival associations across molecular data types. OPN1MW RNA expression shows survival associations in the most cancer types (4), 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 OPN1MW RNA expression–survival associations across cancer types. High OPN1MW expression shows unfavorable associations in LUAD, STAD, PAAD and UCEC. The LUAD 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 LUAD as the clearest survival context for OPN1MW RNA expression.
This table shows molecular features associated with OPN1MW in patient tissues and cancer cell lines. In patient samples, OPN1MW 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, OPN1MW RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
