Q-omics provides the consensus-scored ELOC profile across patient tissues and cancer cell-line models. ELOC expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ELOC is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, ELOC RNA expression shows 18,816 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where ELOC 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 ELOC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ELOC survival associations across molecular data types. ELOC RNA expression shows survival associations in the most cancer types (28), followed by mutation status (1) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ELOC RNA expression–survival associations across cancer types. High ELOC expression shows unfavorable associations in UVM, HNSC, KIRP, KICH, LIHC and BRCA. 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 ELOC RNA expression.
This table summarizes ELOC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ELOC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ELOC shows higher tumor expression in HNSC, KIRC, COAD, LIHC, LUAD and LUSC. The HNSC box plot shows higher ELOC RNA expression in tumor versus normal tissue (log2 FC = +1.078, t-test p < 0.001).
This table shows molecular features associated with ELOC in patient tissues and cancer cell lines. In patient samples, ELOC 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, ELOC 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 BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
