Q-omics provides the consensus-scored ECHS1 profile across patient tissues and cancer cell-line models. ECHS1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, ECHS1 is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, ECHS1 protein abundance shows 23,107 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCS, KIRP, and GBM as cancer lineages where ECHS1 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 ECHS1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ECHS1 survival associations across molecular data types. ECHS1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) 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 ECHS1 RNA expression–survival associations across cancer types. High ECHS1 expression shows unfavorable associations in UCS, UVM, ACC and LAML, but favorable associations in KIRP and KIRC. The UCS 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 UCS as the clearest survival context for ECHS1 RNA expression.
This table summarizes ECHS1 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 7. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ECHS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ECHS1 shows lower tumor expression in KIRP, HNSC, KIRC, COAD and KICH and higher tumor expression in LUAD. The KIRP box plot shows higher ECHS1 RNA expression in normal versus tumor tissue (log2 FC = −1.506, t-test p < 0.001).
This table shows molecular features associated with ECHS1 in patient tissues and cancer cell lines. In patient samples, ECHS1 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, ECHS1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
