Q-omics provides the consensus-scored TECTA profile across patient tissues and cancer cell-line models. TECTA expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, TECTA is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, TECTA RNA expression shows 20,588 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight PAAD, THCA, and UVM as cancer lineages where TECTA 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 TECTA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TECTA survival associations across molecular data types. TECTA RNA expression shows survival associations in the most cancer types (21), followed by mutation status (9) 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 TECTA RNA expression–survival associations across cancer types. High TECTA expression shows unfavorable associations in DLBC, but favorable associations in PAAD, UCS, ESCA, SCLC and KIRP. The PAAD Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify PAAD as the clearest survival context for TECTA RNA expression.
This table summarizes TECTA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TECTA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TECTA shows lower tumor expression in THCA, LUSC, LUAD, KIRP, KIRC and UCEC. The THCA box plot shows higher TECTA RNA expression in normal versus tumor tissue (log2 FC = −0.848, t-test p < 0.001).
This table shows molecular features associated with TECTA in patient tissues and cancer cell lines. In patient samples, TECTA 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, TECTA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
