Q-omics provides the consensus-scored ECE1 profile across patient tissues and cancer cell-line models. ECE1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ECE1 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, ECE1 protein abundance shows 30,438 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, THCA, and PDAC as cancer lineages where ECE1 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 ECE1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ECE1 survival associations across molecular data types. ECE1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ECE1 RNA expression–survival associations across cancer types. High ECE1 expression shows unfavorable associations in UVM, MESO, UCS, LGG, ACC and LAML. The UVM 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 UVM as the clearest survival context for ECE1 RNA expression.
This table summarizes ECE1 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 11. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ECE1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ECE1 shows lower tumor expression in COAD and higher tumor expression in THCA, HNSC, KIRC, PAAD and STAD. The THCA box plot shows higher ECE1 RNA expression in tumor versus normal tissue (log2 FC = +1.380, t-test p < 0.001).
This table shows molecular features associated with ECE1 in patient tissues and cancer cell lines. In patient samples, ECE1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, ECE1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LIVER and LARGE_INTESTINE.
