Q-omics provides the consensus-scored OCEL1 profile across patient tissues and cancer cell-line models. OCEL1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LAML. Among the 18 cancer types available for tumor–normal comparison, OCEL1 is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, OCEL1 RNA expression shows 18,288 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LAML, COAD, and ACC as cancer lineages where OCEL1 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 OCEL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OCEL1 survival associations across molecular data types. OCEL1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) 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 OCEL1 RNA expression–survival associations across cancer types. High OCEL1 expression shows unfavorable associations in LAML, LGG, READ, ESCA and SCLC, but favorable associations in KIRC. The LAML Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify LAML as the clearest survival context for OCEL1 RNA expression.
This table summarizes OCEL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 3. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for OCEL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OCEL1 shows lower tumor expression in COAD, THCA, LUSC, READ and KICH and higher tumor expression in KIRC. The COAD box plot shows higher OCEL1 RNA expression in normal versus tumor tissue (log2 FC = −1.205, t-test p < 0.001).
This table shows molecular features associated with OCEL1 in patient tissues and cancer cell lines. In patient samples, OCEL1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, OCEL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BONE and SOFT_TISSUE.
