torsin 1A interacting protein 2Genealiases: IFRG15 · LULL1 · NET9
Q-omics provides the consensus-scored TOR1AIP2 profile across patient tissues and cancer cell-line models. TOR1AIP2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, TOR1AIP2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, TOR1AIP2 RNA expression shows 19,685 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where TOR1AIP2 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 TOR1AIP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TOR1AIP2 survival associations across molecular data types. TOR1AIP2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TOR1AIP2 RNA expression–survival associations across cancer types. High TOR1AIP2 expression shows unfavorable associations in UVM, BLCA, KIRP, CESC, ACC and LGG. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify UVM as the clearest survival context for TOR1AIP2 RNA expression.
This table summarizes TOR1AIP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, 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 TOR1AIP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TOR1AIP2 shows lower tumor expression in KICH and higher tumor expression in HNSC, BLCA, LIHC, BRCA and STAD. The HNSC box plot shows higher TOR1AIP2 RNA expression in tumor versus normal tissue (log2 FC = +0.855, t-test p < 0.001).
This table shows molecular features associated with TOR1AIP2 in patient tissues and cancer cell lines. In patient samples, TOR1AIP2 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, TOR1AIP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
