RPTOR independent companion of MTOR complex 2Genealiases: AVO3 · PIA · hAVO3
Q-omics provides the consensus-scored RICTOR profile across patient tissues and cancer cell-line models. RICTOR expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RICTOR is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, RICTOR RNA expression shows 21,558 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where RICTOR 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 RICTOR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RICTOR survival associations across molecular data types. RICTOR RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RICTOR RNA expression–survival associations across cancer types. High RICTOR expression shows unfavorable associations in LIHC, but favorable associations in KIRC, UCS, SCLC, LGG and BRCA. The KIRC 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 KIRC as the clearest survival context for RICTOR RNA expression.
This table summarizes RICTOR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RICTOR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RICTOR shows lower tumor expression in THCA and UCEC and higher tumor expression in HNSC, LIHC, CHOL and STAD. The HNSC box plot shows higher RICTOR RNA expression in tumor versus normal tissue (log2 FC = +0.669, t-test p < 0.001).
This table shows molecular features associated with RICTOR in patient tissues and cancer cell lines. In patient samples, RICTOR shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, RICTOR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
