ecotropic viral integration site 5 likeGenealiases: []
Q-omics provides the consensus-scored EVI5L profile across patient tissues and cancer cell-line models. EVI5L expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EVI5L is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, EVI5L RNA expression shows 19,124 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where EVI5L 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 EVI5L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EVI5L survival associations across molecular data types. EVI5L RNA expression shows survival associations in the most cancer types (21), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EVI5L RNA expression–survival associations across cancer types. High EVI5L expression shows unfavorable associations in ACC, MESO, LUAD and UCS, but favorable associations in SCLC and LGG. 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 EVI5L RNA expression.
This table summarizes EVI5L 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 6. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EVI5L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EVI5L shows lower tumor expression in KIRC and READ and higher tumor expression in LIHC, KICH, HNSC and BRCA. The LIHC box plot shows higher EVI5L RNA expression in tumor versus normal tissue (log2 FC = +1.304, t-test p < 0.001).
This table shows molecular features associated with EVI5L in patient tissues and cancer cell lines. In patient samples, EVI5L 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, EVI5L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
