Q-omics provides the consensus-scored EZH2 profile across patient tissues and cancer cell-line models. EZH2 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, EZH2 is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, EZH2 protein abundance shows 27,856 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight MESO, BLCA, and LSCC as cancer lineages where EZH2 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 EZH2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EZH2 survival associations across molecular data types. EZH2 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (7) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EZH2 RNA expression–survival associations across cancer types. High EZH2 expression shows unfavorable associations in MESO, ACC, KIRP, KIRC, LIHC and KICH. The MESO 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 MESO as the clearest survival context for EZH2 RNA expression.
This table summarizes EZH2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 4. The strongest signals are observed in BLCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for EZH2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EZH2 shows higher tumor expression in BLCA, COAD, KIRP, KIRC, HNSC and THCA. The BLCA box plot shows higher EZH2 RNA expression in tumor versus normal tissue (log2 FC = +2.578, t-test p < 0.001).
This table shows molecular features associated with EZH2 in patient tissues and cancer cell lines. In patient samples, EZH2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, EZH2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
