Q-omics provides the consensus-scored EID1 profile across patient tissues and cancer cell-line models. EID1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, EID1 is differentially expressed in 14, with the highest sampling consensus in THCA. Additionally, EID1 RNA expression shows 19,928 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where EID1 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 EID1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EID1 survival associations across molecular data types. EID1 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EID1 RNA expression–survival associations across cancer types. High EID1 expression shows unfavorable associations in DLBC, KIRP and UVM, but favorable associations in KIRC, SKCM and UCEC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for EID1 RNA expression.
This table summarizes EID1 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 1. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for EID1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EID1 shows lower tumor expression in THCA, UCEC, BLCA, LUAD, LUSC and KICH. The THCA box plot shows higher EID1 RNA expression in normal versus tumor tissue (log2 FC = −0.528, t-test p = .002).
This table shows molecular features associated with EID1 in patient tissues and cancer cell lines. In patient samples, EID1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, EID1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and UPPER_AERODIGESTIVE_TRACT.
