Q-omics provides the consensus-scored TRA2A profile across patient tissues and cancer cell-line models. TRA2A expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, TRA2A is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, TRA2A protein abundance shows 21,897 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, LIHC, and PDAC as cancer lineages where TRA2A 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 TRA2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TRA2A survival associations across molecular data types. TRA2A RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TRA2A RNA expression–survival associations across cancer types. High TRA2A expression shows unfavorable associations in ACC, KIRC, LIHC, UVM and LGG, but favorable associations in UCEC. 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 TRA2A RNA expression.
This table summarizes TRA2A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for TRA2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TRA2A shows lower tumor expression in KICH and higher tumor expression in LIHC, STAD, COAD, CHOL and BLCA. The LIHC box plot shows higher TRA2A RNA expression in tumor versus normal tissue (log2 FC = +0.758, t-test p < 0.001).
This table shows molecular features associated with TRA2A in patient tissues and cancer cell lines. In patient samples, TRA2A shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, TRA2A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
