Q-omics provides the consensus-scored CUL2 profile across patient tissues and cancer cell-line models. CUL2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, CUL2 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, CUL2 protein abundance shows 27,524 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, HNSC, and GBM as cancer lineages where CUL2 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 CUL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CUL2 survival associations across molecular data types. CUL2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CUL2 RNA expression–survival associations across cancer types. High CUL2 expression shows unfavorable associations in LIHC, ACC and SARC, but favorable associations in SKCM, KIRC and LGG. The LIHC 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 LIHC as the clearest survival context for CUL2 RNA expression.
This table summarizes CUL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 11. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CUL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CUL2 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, KIRP, COAD and BRCA. The HNSC box plot shows higher CUL2 RNA expression in tumor versus normal tissue (log2 FC = +0.495, t-test p < 0.001).
This table shows molecular features associated with CUL2 in patient tissues and cancer cell lines. In patient samples, CUL2 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, CUL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LARGE_INTESTINE.
