Q-omics provides the consensus-scored TEAD3 profile across patient tissues and cancer cell-line models. TEAD3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, TEAD3 is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, TEAD3 protein abundance shows 24,501 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight UCS, LIHC, and LUAD as cancer lineages where TEAD3 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 TEAD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TEAD3 survival associations across molecular data types. TEAD3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (1) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TEAD3 RNA expression–survival associations across cancer types. High TEAD3 expression shows unfavorable associations in LGG, COAD and KIRP, but favorable associations in UCS, UVM and HNSC. The UCS 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 UCS as the clearest survival context for TEAD3 RNA expression.
This table summarizes TEAD3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 9. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for TEAD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TEAD3 shows lower tumor expression in KICH, BLCA, UCEC and KIRC and higher tumor expression in LIHC and LUSC. The LIHC box plot shows higher TEAD3 RNA expression in tumor versus normal tissue (log2 FC = +1.437, t-test p < 0.001).
This table shows molecular features associated with TEAD3 in patient tissues and cancer cell lines. In patient samples, TEAD3 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, TEAD3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
