EP300 interacting inhibitor of differentiation 2Genealiases: CRI2 · EID-2
Q-omics provides the consensus-scored EID2 profile across patient tissues and cancer cell-line models. EID2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EID2 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, EID2 RNA expression shows 19,053 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, HNSC, and UVM as cancer lineages where EID2 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 EID2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EID2 survival associations across molecular data types. EID2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) 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 EID2 RNA expression–survival associations across cancer types. High EID2 expression shows unfavorable associations in ACC, UVM, MESO, LIHC and LGG, but favorable associations in KIRC. The ACC 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 ACC as the clearest survival context for EID2 RNA expression.
This table summarizes EID2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EID2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EID2 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, UCEC, CHOL and STAD. The HNSC box plot shows higher EID2 RNA expression in tumor versus normal tissue (log2 FC = +0.545, t-test p < 0.001).
This table shows molecular features associated with EID2 in patient tissues and cancer cell lines. In patient samples, EID2 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, EID2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
