EP300 interacting inhibitor of differentiation 2BGenealiases: EID-2B · EID-3
Q-omics provides the consensus-scored EID2B profile across patient tissues and cancer cell-line models. EID2B expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, EID2B is differentially expressed in 15, with the highest sampling consensus in KICH. Additionally, EID2B RNA expression shows 20,022 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, KICH, and UVM as cancer lineages where EID2B 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 EID2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EID2B survival associations across molecular data types. EID2B RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EID2B RNA expression–survival associations across cancer types. High EID2B expression shows unfavorable associations in LIHC, ACC, MESO and STAD, but favorable associations in LUAD and UCS. 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 EID2B RNA expression.
This table summarizes EID2B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for EID2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EID2B shows lower tumor expression in KICH and LUAD and higher tumor expression in KIRP, LIHC, HNSC and CHOL. The KICH box plot shows higher EID2B RNA expression in normal versus tumor tissue (log2 FC = −1.326, t-test p < 0.001).
This table shows molecular features associated with EID2B in patient tissues and cancer cell lines. In patient samples, EID2B 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, EID2B 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 LARGE_INTESTINE and BLOOD_Leukemia.
