Q-omics provides the consensus-scored OCIAD1 profile across patient tissues and cancer cell-line models. OCIAD1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, OCIAD1 is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, OCIAD1 RNA expression shows 19,487 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, THCA, and ACC as cancer lineages where OCIAD1 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 OCIAD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OCIAD1 survival associations across molecular data types. OCIAD1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OCIAD1 RNA expression–survival associations across cancer types. High OCIAD1 expression shows unfavorable associations in UVM, LUAD, HNSC, KIRP and CESC, but favorable associations in BRCA. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify UVM as the clearest survival context for OCIAD1 RNA expression.
This table summarizes OCIAD1 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 6. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for OCIAD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OCIAD1 shows lower tumor expression in THCA, KIRP and KIRC and higher tumor expression in LIHC, BRCA and LUAD. The THCA box plot shows higher OCIAD1 RNA expression in normal versus tumor tissue (log2 FC = −1.033, t-test p < 0.001).
This table shows molecular features associated with OCIAD1 in patient tissues and cancer cell lines. In patient samples, OCIAD1 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, OCIAD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
