Q-omics provides the consensus-scored EGR1 profile across patient tissues and cancer cell-line models. EGR1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EGR1 is differentially expressed in 11, with the highest sampling consensus in BLCA. Additionally, EGR1 RNA expression shows 16,031 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight ACC, BLCA, and THYM as cancer lineages where EGR1 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 EGR1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EGR1 survival associations across molecular data types. EGR1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EGR1 RNA expression–survival associations across cancer types. High EGR1 expression shows unfavorable associations in ACC, LGG, UVM, COAD and BLCA, 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 EGR1 RNA expression.
This table summarizes EGR1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 1. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EGR1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EGR1 shows lower tumor expression in BLCA, KIRP, HNSC, KICH, THCA and LIHC. The BLCA box plot shows higher EGR1 RNA expression in normal versus tumor tissue (log2 FC = −3.462, t-test p < 0.001).
This table shows molecular features associated with EGR1 in patient tissues and cancer cell lines. In patient samples, EGR1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, EGR1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and SOFT_TISSUE.
