Q-omics provides the consensus-scored RNF133 profile across patient tissues and cancer cell-line models. RNF133 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, RNF133 is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, RNF133 RNA expression shows 15,951 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight OV, KIRP, and UVM as cancer lineages where RNF133 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 RNF133 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RNF133 survival associations across molecular data types. RNF133 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RNF133 RNA expression–survival associations across cancer types. High RNF133 expression shows unfavorable associations in ACC, STAD, THYM and LIHC, but favorable associations in OV and LUAD. The OV Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .003). Together, the overview and detailed table identify OV as the clearest survival context for RNF133 RNA expression.
This table summarizes RNF133 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for RNF133. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RNF133 shows lower tumor expression in KIRP, KIRC, KICH, THCA, LUSC and UCEC. The KIRP box plot shows higher RNF133 RNA expression in normal versus tumor tissue (log2 FC = −0.277, t-test p < 0.001).
This table shows molecular features associated with RNF133 in patient tissues and cancer cell lines. In patient samples, RNF133 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, RNF133 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 OVARY and BONE.
