Q-omics provides the consensus-scored TET3 profile across patient tissues and cancer cell-line models. TET3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, TET3 is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, TET3 RNA expression shows 20,876 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight ACC, BLCA, and KIRP as cancer lineages where TET3 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 TET3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TET3 survival associations across molecular data types. TET3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (11) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TET3 RNA expression–survival associations across cancer types. High TET3 expression shows unfavorable associations in ACC, MESO, LIHC and BLCA, but favorable associations in SCLC and LUSC. 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 TET3 RNA expression.
This table summarizes TET3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for TET3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TET3 shows higher tumor expression in BLCA, HNSC, KIRC, STAD, KIRP and LUSC. The BLCA box plot shows higher TET3 RNA expression in tumor versus normal tissue (log2 FC = +2.102, t-test p < 0.001).
This table shows molecular features associated with TET3 in patient tissues and cancer cell lines. In patient samples, TET3 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, TET3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
