Q-omics provides the consensus-scored ERG profile across patient tissues and cancer cell-line models. ERG expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ERG is differentially expressed in 15, with the highest sampling consensus in LUAD. Additionally, ERG protein abundance shows 22,435 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, LUAD, and LSCC as cancer lineages where ERG 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 ERG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERG survival associations across molecular data types. ERG RNA expression shows survival associations in the most cancer types (21), followed by mutation status (9) 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 ERG RNA expression–survival associations across cancer types. High ERG expression shows unfavorable associations in KIRP, CESC, UVM, BLCA and STAD, but favorable associations in KIRC. 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 ERG RNA expression.
This table summarizes ERG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ERG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERG shows lower tumor expression in LUAD, KICH, LUSC, KIRP and THCA and higher tumor expression in HNSC. The LUAD box plot shows higher ERG RNA expression in normal versus tumor tissue (log2 FC = −2.206, t-test p < 0.001).
This table shows molecular features associated with ERG in patient tissues and cancer cell lines. In patient samples, ERG 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, ERG 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 BONE and BLOOD_Leukemia.
