Q-omics provides the consensus-scored EML6 profile across patient tissues and cancer cell-line models. EML6 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, EML6 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, EML6 RNA expression shows 21,078 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KIRC, and UVM as cancer lineages where EML6 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 EML6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EML6 survival associations across molecular data types. EML6 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EML6 RNA expression–survival associations across cancer types. High EML6 expression shows unfavorable associations in ACC, KICH and KIRP, but favorable associations in HNSC, SCLC and PAAD. The HNSC 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 HNSC as the clearest survival context for EML6 RNA expression.
This table summarizes EML6 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for EML6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EML6 shows lower tumor expression in KIRC, KICH, THCA and KIRP and higher tumor expression in HNSC and LIHC. The KIRC box plot shows higher EML6 RNA expression in normal versus tumor tissue (log2 FC = −0.962, t-test p < 0.001).
This table shows molecular features associated with EML6 in patient tissues and cancer cell lines. In patient samples, EML6 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, EML6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
