Q-omics provides the consensus-scored CUL3 profile across patient tissues and cancer cell-line models. CUL3 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CUL3 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, CUL3 protein abundance shows 33,092 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KICH, and GBM as cancer lineages where CUL3 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 CUL3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CUL3 survival associations across molecular data types. CUL3 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (5) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CUL3 RNA expression–survival associations across cancer types. High CUL3 expression shows unfavorable associations in BLCA, ACC, LIHC and CESC, but favorable associations in KIRC and SCLC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for CUL3 RNA expression.
This table summarizes CUL3 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 9. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CUL3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CUL3 shows lower tumor expression in KICH, THCA, KIRC and BLCA and higher tumor expression in LIHC and CHOL. The KICH box plot shows higher CUL3 RNA expression in normal versus tumor tissue (log2 FC = −1.500, t-test p < 0.001).
This table shows molecular features associated with CUL3 in patient tissues and cancer cell lines. In patient samples, CUL3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CUL3 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 SOFT_TISSUE and BLOOD_Lymphoma.
