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Q-omics provides the consensus-scored TEC profile across patient tissues and cancer cell-line models. TEC expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, TEC is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, TEC RNA expression shows 20,193 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, HNSC, and UVM as cancer lineages where TEC 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 TEC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TEC survival associations across molecular data types. TEC RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TEC RNA expression–survival associations across cancer types. High TEC expression shows unfavorable associations in KICH and ACC, but favorable associations in SKCM, OV, KIRC and UCEC. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify SKCM as the clearest survival context for TEC RNA expression.
This table summarizes TEC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TEC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TEC shows lower tumor expression in HNSC and LUSC and higher tumor expression in KIRC, KIRP, UCEC and THCA. The HNSC box plot shows higher TEC RNA expression in normal versus tumor tissue (log2 FC = −0.966, t-test p < 0.001).
This table shows molecular features associated with TEC in patient tissues and cancer cell lines. In patient samples, TEC 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, TEC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and UPPER_AERODIGESTIVE_TRACT.
