Q-omics provides the consensus-scored TES profile across patient tissues and cancer cell-line models. TES expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, TES is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, TES protein abundance shows 24,780 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, and GBM as cancer lineages where TES 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 TES — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TES survival associations across molecular data types. TES RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) 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 TES RNA expression–survival associations across cancer types. High TES expression shows unfavorable associations in HNSC, PAAD, CESC, MESO and LGG, but favorable associations in COAD. The HNSC 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 HNSC as the clearest survival context for TES RNA expression.
This table summarizes TES tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for TES. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TES shows lower tumor expression in BLCA, THCA and READ and higher tumor expression in HNSC, KIRC and KIRP. The HNSC box plot shows higher TES RNA expression in tumor versus normal tissue (log2 FC = +1.259, t-test p < 0.001).
This table shows molecular features associated with TES in patient tissues and cancer cell lines. In patient samples, TES 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, TES RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in OVARY and LARGE_INTESTINE.
