Q-omics provides the consensus-scored OTOR profile across patient tissues and cancer cell-line models. OTOR expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, OTOR is differentially expressed in 7, with the highest sampling consensus in BRCA. Additionally, OTOR RNA expression shows 7,081 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, BRCA, and TGCT as cancer lineages where OTOR 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 OTOR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OTOR survival associations across molecular data types. OTOR RNA expression shows survival associations in the most cancer types (16), 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 OTOR RNA expression–survival associations across cancer types. High OTOR expression shows unfavorable associations in ACC, UVM, DLBC, LGG and BRCA, but favorable associations in HNSC. 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 OTOR RNA expression.
This table summarizes OTOR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 1. The strongest signals are observed in BRCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for OTOR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OTOR shows lower tumor expression in KIRC, HNSC and KIRP and higher tumor expression in BRCA, LUAD and LUSC. The BRCA box plot shows higher OTOR RNA expression in tumor versus normal tissue (log2 FC = +0.480, t-test p < 0.001).
This table shows molecular features associated with OTOR in patient tissues and cancer cell lines. In patient samples, OTOR shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, OTOR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BREAST.
