Q-omics provides the consensus-scored ELP2 profile across patient tissues and cancer cell-line models. ELP2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ELP2 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, ELP2 protein abundance shows 20,941 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight ACC, KIRC, and UCEC as cancer lineages where ELP2 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 ELP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ELP2 survival associations across molecular data types. ELP2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ELP2 RNA expression–survival associations across cancer types. High ELP2 expression shows unfavorable associations in ACC, MESO and UVM, but favorable associations in BRCA, DLBC and OV. The ACC 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 ACC as the clearest survival context for ELP2 RNA expression.
This table summarizes ELP2 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 9. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ELP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ELP2 shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, LIHC, BRCA and COAD. The KIRC box plot shows higher ELP2 RNA expression in tumor versus normal tissue (log2 FC = +0.422, t-test p < 0.001).
This table shows molecular features associated with ELP2 in patient tissues and cancer cell lines. In patient samples, ELP2 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, ELP2 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 BREAST and LARGE_INTESTINE.
