TOR signaling pathway regulatorGenealiases: TIP · TIP41 · TIPRL1
Q-omics provides the consensus-scored TIPRL profile across patient tissues and cancer cell-line models. TIPRL expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, TIPRL is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, TIPRL RNA expression shows 19,845 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where TIPRL 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 TIPRL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TIPRL survival associations across molecular data types. TIPRL RNA expression shows survival associations in the most cancer types (25), 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 TIPRL RNA expression–survival associations across cancer types. High TIPRL expression shows unfavorable associations in KIRP, ACC, LIHC, UVM, SCLC and MESO. The KIRP 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 KIRP as the clearest survival context for TIPRL RNA expression.
This table summarizes TIPRL 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 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TIPRL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TIPRL shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRC, LIHC, LUAD and STAD. The HNSC box plot shows higher TIPRL RNA expression in tumor versus normal tissue (log2 FC = +0.852, t-test p < 0.001).
This table shows molecular features associated with TIPRL in patient tissues and cancer cell lines. In patient samples, TIPRL 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, TIPRL 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 LUNG_NSCLC_LUSC and BLOOD_Leukemia.
