Q-omics provides the consensus-scored EQTN profile across patient tissues and cancer cell-line models. EQTN expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, EQTN is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, EQTN RNA expression shows 13,557 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCEC, HNSC, and UVM as cancer lineages where EQTN 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 EQTN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EQTN survival associations across molecular data types. EQTN RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EQTN RNA expression–survival associations across cancer types. High EQTN expression shows unfavorable associations in UCEC, ACC, UVM, READ and HNSC, but favorable associations in CHOL. The UCEC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify UCEC as the clearest survival context for EQTN RNA expression.
This table summarizes EQTN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for EQTN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EQTN shows lower tumor expression in BRCA, COAD, THCA, KICH and LUAD and higher tumor expression in HNSC. The HNSC box plot shows higher EQTN RNA expression in tumor versus normal tissue (log2 FC = +0.070, t-test p < 0.001).
This table shows molecular features associated with EQTN in patient tissues and cancer cell lines. In patient samples, EQTN 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, EQTN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
