Q-omics provides the consensus-scored TRNT1 profile across patient tissues and cancer cell-line models. TRNT1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, TRNT1 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, TRNT1 RNA expression shows 20,417 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UCS, KIRC, and ACC as cancer lineages where TRNT1 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 TRNT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TRNT1 survival associations across molecular data types. TRNT1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 TRNT1 RNA expression–survival associations across cancer types. High TRNT1 expression shows unfavorable associations in ACC, LIHC, MESO, KICH and LUAD, but favorable associations in UCS. The UCS 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 UCS as the clearest survival context for TRNT1 RNA expression.
This table summarizes TRNT1 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TRNT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TRNT1 shows lower tumor expression in KIRC and higher tumor expression in BLCA, LIHC, STAD, COAD and READ. The KIRC box plot shows higher TRNT1 RNA expression in normal versus tumor tissue (log2 FC = −0.893, t-test p < 0.001).
This table shows molecular features associated with TRNT1 in patient tissues and cancer cell lines. In patient samples, TRNT1 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, TRNT1 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 STOMACH and BLOOD_Leukemia.
