Q-omics provides the consensus-scored ENO1 profile across patient tissues and cancer cell-line models. ENO1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ENO1 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, ENO1 protein abundance shows 22,465 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KICH, KIRC, and BRCA as cancer lineages where ENO1 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 ENO1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ENO1 survival associations across molecular data types. ENO1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ENO1 RNA expression–survival associations across cancer types. High ENO1 expression shows unfavorable associations in KICH, HNSC, ACC, LIHC, BLCA and BRCA. The KICH 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 KICH as the clearest survival context for ENO1 RNA expression.
This table summarizes ENO1 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 8. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ENO1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ENO1 shows higher tumor expression in KIRC, COAD, HNSC, BLCA, LUSC and STAD. The KIRC box plot shows higher ENO1 RNA expression in tumor versus normal tissue (log2 FC = +1.500, t-test p < 0.001).
This table shows molecular features associated with ENO1 in patient tissues and cancer cell lines. In patient samples, ENO1 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, ENO1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
