Q-omics provides the consensus-scored EOGT profile across patient tissues and cancer cell-line models. EOGT expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EOGT is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, EOGT protein abundance shows 24,187 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where EOGT 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 EOGT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EOGT survival associations across molecular data types. EOGT RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EOGT RNA expression–survival associations across cancer types. High EOGT expression shows unfavorable associations in ACC, KICH, LGG, UVM, MESO and LIHC. 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 EOGT RNA expression.
This table summarizes EOGT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EOGT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EOGT shows lower tumor expression in LUSC, LUAD, BRCA and KICH and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher EOGT RNA expression in tumor versus normal tissue (log2 FC = +0.931, t-test p < 0.001).
This table shows molecular features associated with EOGT in patient tissues and cancer cell lines. In patient samples, EOGT shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, EOGT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BONE.
