Q-omics provides the consensus-scored OCM2 profile across patient tissues and cancer cell-line models. OCM2 expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, OCM2 is differentially expressed in 2, with the highest sampling consensus in KIRC. Additionally, OCM2 protein abundance shows 12,811 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight LUAD, KIRC, and PDAC as cancer lineages where OCM2 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 OCM2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OCM2 survival associations across molecular data types. OCM2 RNA expression shows survival associations in the most cancer types (13), followed by mutation status (4) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OCM2 RNA expression–survival associations across cancer types. High OCM2 expression shows unfavorable associations in LUSC, BRCA, THCA and DLBC, but favorable associations in LUAD and MESO. The LUAD Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .013). Together, the overview and detailed table identify LUAD as the clearest survival context for OCM2 RNA expression.
This table summarizes OCM2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for OCM2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OCM2 shows lower tumor expression in THCA and higher tumor expression in KIRC. The KIRC box plot shows higher OCM2 RNA expression in tumor versus normal tissue (log2 FC = +0.020, t-test p = .008).
This table shows molecular features associated with OCM2 in patient tissues and cancer cell lines. In patient samples, OCM2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, OCM2 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_Lymphoma and OVARY.
