Q-omics provides the consensus-scored TET1 profile across patient tissues and cancer cell-line models. TET1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, TET1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, TET1 RNA expression shows 21,272 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where TET1 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 TET1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TET1 survival associations across molecular data types. TET1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (10) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TET1 RNA expression–survival associations across cancer types. High TET1 expression shows unfavorable associations in ACC, STAD, BLCA and LIHC, but favorable associations in UCS and LGG. 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 TET1 RNA expression.
This table summarizes TET1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for TET1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TET1 shows lower tumor expression in KICH and higher tumor expression in HNSC, LUAD, LUSC, UCEC and LIHC. The HNSC box plot shows higher TET1 RNA expression in tumor versus normal tissue (log2 FC = +0.478, t-test p < 0.001).
This table shows molecular features associated with TET1 in patient tissues and cancer cell lines. In patient samples, TET1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, TET1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
