Q-omics provides the consensus-scored CACUL1 profile across patient tissues and cancer cell-line models. CACUL1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, CACUL1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, CACUL1 RNA expression shows 20,828 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, HNSC, and ACC as cancer lineages where CACUL1 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 CACUL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CACUL1 survival associations across molecular data types. CACUL1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CACUL1 RNA expression–survival associations across cancer types. High CACUL1 expression shows unfavorable associations in LIHC, ACC, BLCA and UVM, but favorable associations in KIRC and SCLC. 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 CACUL1 RNA expression.
This table summarizes CACUL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CACUL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CACUL1 shows higher tumor expression in HNSC, LIHC, LUAD, BRCA, CHOL and STAD. The HNSC box plot shows higher CACUL1 RNA expression in tumor versus normal tissue (log2 FC = +0.947, t-test p < 0.001).
This table shows molecular features associated with CACUL1 in patient tissues and cancer cell lines. In patient samples, CACUL1 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, CACUL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
