Q-omics provides the consensus-scored ECD profile across patient tissues and cancer cell-line models. ECD expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, ECD is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, ECD RNA expression shows 20,103 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, and ACC as cancer lineages where ECD 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 ECD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ECD survival associations across molecular data types. ECD RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3) 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 ECD RNA expression–survival associations across cancer types. High ECD expression shows unfavorable associations in LIHC, UVM, ACC and HNSC, but favorable associations in KIRC and LGG. The LIHC 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 LIHC as the clearest survival context for ECD RNA expression.
This table summarizes ECD tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ECD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ECD shows lower tumor expression in KICH and higher tumor expression in LIHC, LUAD, COAD, BRCA and HNSC. The LIHC box plot shows higher ECD RNA expression in tumor versus normal tissue (log2 FC = +1.129, t-test p < 0.001).
This table shows molecular features associated with ECD in patient tissues and cancer cell lines. In patient samples, ECD shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ECD RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
