Q-omics provides the consensus-scored OR14J1 profile across patient tissues and cancer cell-line models. OR14J1 expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in THCA. Additionally, OR14J1 RNA expression shows 6,130 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight THCA, and STAD as cancer lineages where OR14J1 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 OR14J1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OR14J1 survival associations across molecular data types. OR14J1 RNA expression shows survival associations in the most cancer types (10), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OR14J1 RNA expression–survival associations across cancer types. High OR14J1 expression shows unfavorable associations in THCA, LGG, KICH, UCEC, DLBC and COAD. The THCA 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 THCA as the clearest survival context for OR14J1 RNA expression.
This table shows molecular features associated with OR14J1 in patient tissues and cancer cell lines. In patient samples, OR14J1 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, OR14J1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and LARGE_INTESTINE.
