endothelium and lymphocyte associated ASCH domain 1Genealiases: CXorf40 · CXorf40A
Q-omics provides the consensus-scored EOLA1 profile across patient tissues and cancer cell-line models. EOLA1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, EOLA1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, EOLA1 RNA expression shows 18,681 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, HNSC, and UVM as cancer lineages where EOLA1 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 EOLA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EOLA1 survival associations across molecular data types. EOLA1 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EOLA1 RNA expression–survival associations across cancer types. High EOLA1 expression shows unfavorable associations in LGG, but favorable associations in SKCM, KIRC, PAAD, MESO and CESC. The SKCM 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 SKCM as the clearest survival context for EOLA1 RNA expression.
This table summarizes EOLA1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for EOLA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EOLA1 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, BRCA, LUAD and CHOL. The HNSC box plot shows higher EOLA1 RNA expression in tumor versus normal tissue (log2 FC = +0.673, t-test p < 0.001).
This table shows molecular features associated with EOLA1 in patient tissues and cancer cell lines. In patient samples, EOLA1 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, EOLA1 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_Myeloma and BLOOD_Leukemia.
