Q-omics provides the consensus-scored TOR2A profile across patient tissues and cancer cell-line models. TOR2A 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, TOR2A is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, TOR2A RNA expression shows 18,738 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where TOR2A 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 TOR2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TOR2A survival associations across molecular data types. TOR2A RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) 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 TOR2A RNA expression–survival associations across cancer types. High TOR2A expression shows unfavorable associations in ACC, KIRC, UVM and LIHC, but favorable associations in SCLC and 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 TOR2A RNA expression.
This table summarizes TOR2A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TOR2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TOR2A shows higher tumor expression in HNSC, KIRC, LIHC, BLCA, KIRP and STAD. The HNSC box plot shows higher TOR2A RNA expression in tumor versus normal tissue (log2 FC = +0.896, t-test p < 0.001).
This table shows molecular features associated with TOR2A in patient tissues and cancer cell lines. In patient samples, TOR2A 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, TOR2A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and SOFT_TISSUE.
