Q-omics provides the consensus-scored ENG profile across patient tissues and cancer cell-line models. ENG expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ENG is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, ENG protein abundance shows 37,398 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KICH, and GBM as cancer lineages where ENG 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 ENG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ENG survival associations across molecular data types. ENG RNA expression shows survival associations in the most cancer types (29), followed by mutation status (5) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ENG RNA expression–survival associations across cancer types. High ENG expression shows unfavorable associations in LGG, MESO and COAD, but favorable associations in KIRC, LIHC and HNSC. 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 ENG RNA expression.
This table summarizes ENG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 12. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ENG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ENG shows lower tumor expression in KICH, KIRP, LUAD and LUSC and higher tumor expression in HNSC and STAD. The KICH box plot shows higher ENG RNA expression in normal versus tumor tissue (log2 FC = −1.952, t-test p < 0.001).
This table shows molecular features associated with ENG in patient tissues and cancer cell lines. In patient samples, ENG shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ENG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and UPPER_AERODIGESTIVE_TRACT.
