Q-omics provides the consensus-scored THEGL profile across patient tissues and cancer cell-line models. THEGL expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, THEGL is differentially expressed in 12, with the highest sampling consensus in LUAD. Additionally, THEGL RNA expression shows 16,792 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, LUAD, and UVM as cancer lineages where THEGL 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 THEGL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes THEGL survival associations across molecular data types. THEGL RNA expression shows survival associations in the most cancer types (19). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible THEGL RNA expression–survival associations across cancer types. High THEGL expression shows unfavorable associations in KIRC, LGG, CESC, KICH, CHOL and DLBC. The KIRC 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 KIRC as the clearest survival context for THEGL RNA expression.
This table summarizes THEGL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for THEGL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. THEGL shows lower tumor expression in KIRC and BRCA and higher tumor expression in LUAD, LUSC, HNSC and KIRP. The LUAD box plot shows higher THEGL RNA expression in tumor versus normal tissue (log2 FC = +0.225, t-test p < 0.001).
This table shows molecular features associated with THEGL in patient tissues and cancer cell lines. In patient samples, THEGL 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, THEGL 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 BLOOD_Leukemia and LARGE_INTESTINE.
