Q-omics provides the consensus-scored OR2T7 profile across patient tissues and cancer cell-line models. OR2T7 expression is associated with patient survival in 9 of 34 cancer types, with the highest sampling consensus in HNSC. Additionally, OR2T7 RNA expression shows 5,318 significant gene co-expression associations, with the highest sampling consensus in COAD. Together, these results highlight HNSC, and COAD as cancer lineages where OR2T7 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 OR2T7 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OR2T7 survival associations across molecular data types. OR2T7 RNA expression shows survival associations in the most cancer types (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OR2T7 RNA expression–survival associations across cancer types. High OR2T7 expression shows unfavorable associations in HNSC, BRCA, LIHC, THYM and SARC, but favorable associations in ESCA. The HNSC 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 HNSC as the clearest survival context for OR2T7 RNA expression.
This table shows molecular features associated with OR2T7 in patient tissues and cancer cell lines. In patient samples, OR2T7 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, OR2T7 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
