endothelin converting enzyme like 1Genealiases: DA5D · DINE · ECEX · XCE
Q-omics provides the consensus-scored ECEL1 profile across patient tissues and cancer cell-line models. ECEL1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, ECEL1 is differentially expressed in 13, with the highest sampling consensus in LUAD. Additionally, ECEL1 RNA expression shows 12,355 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight SKCM, LUAD, and TGCT as cancer lineages where ECEL1 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 ECEL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ECEL1 survival associations across molecular data types. ECEL1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ECEL1 RNA expression–survival associations across cancer types. High ECEL1 expression shows unfavorable associations in UVM and KIRP, but favorable associations in SKCM, HNSC, BLCA and UCEC. The SKCM 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 SKCM as the clearest survival context for ECEL1 RNA expression.
This table summarizes ECEL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for ECEL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ECEL1 shows lower tumor expression in KICH, KIRP and KIRC and higher tumor expression in LUAD, LIHC and LUSC. The LUAD box plot shows higher ECEL1 RNA expression in tumor versus normal tissue (log2 FC = +1.332, t-test p < 0.001).
This table shows molecular features associated with ECEL1 in patient tissues and cancer cell lines. In patient samples, ECEL1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, ECEL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LARGE_INTESTINE.
