Q-omics provides the consensus-scored CEBPZOS profile across patient tissues and cancer cell-line models. CEBPZOS expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, CEBPZOS is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, CEBPZOS RNA expression shows 19,722 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, and UVM as cancer lineages where CEBPZOS 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 CEBPZOS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CEBPZOS survival associations across molecular data types. CEBPZOS RNA expression shows survival associations in the most cancer types (19), followed by 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 CEBPZOS RNA expression–survival associations across cancer types. High CEBPZOS expression shows unfavorable associations in LIHC, ACC, KIRP, LGG and KICH, but favorable associations in LUSC. The LIHC 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 LIHC as the clearest survival context for CEBPZOS RNA expression.
This table summarizes CEBPZOS 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 LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CEBPZOS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CEBPZOS shows lower tumor expression in KICH and THCA and higher tumor expression in LIHC, LUAD, BLCA and LUSC. The LIHC box plot shows higher CEBPZOS RNA expression in tumor versus normal tissue (log2 FC = +1.030, t-test p < 0.001).
This table shows molecular features associated with CEBPZOS in patient tissues and cancer cell lines. In patient samples, CEBPZOS 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, CEBPZOS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in OVARY and LARGE_INTESTINE.
