Q-omics provides the consensus-scored ELAC1 profile across patient tissues and cancer cell-line models. ELAC1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ELAC1 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, ELAC1 RNA expression shows 19,316 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, THCA, and UVM as cancer lineages where ELAC1 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 ELAC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ELAC1 survival associations across molecular data types. ELAC1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ELAC1 RNA expression–survival associations across cancer types. High ELAC1 expression shows unfavorable associations in ACC and UVM, but favorable associations in KIRC, KIRP, LUSC and COAD. The KIRC 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 KIRC as the clearest survival context for ELAC1 RNA expression.
This table summarizes ELAC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ELAC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ELAC1 shows lower tumor expression in THCA, KICH, KIRC, KIRP, COAD and LUAD. The THCA box plot shows higher ELAC1 RNA expression in normal versus tumor tissue (log2 FC = −1.352, t-test p < 0.001).
This table shows molecular features associated with ELAC1 in patient tissues and cancer cell lines. In patient samples, ELAC1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ELAC1 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_Myeloma and LARGE_INTESTINE.
