Q-omics provides the consensus-scored OCRL profile across patient tissues and cancer cell-line models. OCRL expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, OCRL is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, OCRL RNA expression shows 20,146 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LGG, HNSC, and UVM as cancer lineages where OCRL 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 OCRL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OCRL survival associations across molecular data types. OCRL RNA expression shows survival associations in the most cancer types (28), followed by mutation status (8) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OCRL RNA expression–survival associations across cancer types. High OCRL expression shows unfavorable associations in LGG, BRCA and LUSC, but favorable associations in SCLC, KIRC and ACC. The LGG 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 LGG as the clearest survival context for OCRL RNA expression.
This table summarizes OCRL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for OCRL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OCRL shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, KIRP, LUAD and BRCA. The HNSC box plot shows higher OCRL RNA expression in tumor versus normal tissue (log2 FC = +0.751, t-test p < 0.001).
This table shows molecular features associated with OCRL in patient tissues and cancer cell lines. In patient samples, OCRL shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, OCRL 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 LUNG_NSCLC_LUAD and UPPER_AERODIGESTIVE_TRACT.
