Q-omics provides the consensus-scored CREBBP profile across patient tissues and cancer cell-line models. CREBBP expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CREBBP is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, CREBBP protein abundance shows 25,117 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where CREBBP 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 CREBBP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CREBBP survival associations across molecular data types. CREBBP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (10) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CREBBP RNA expression–survival associations across cancer types. High CREBBP expression shows unfavorable associations in ACC, but favorable associations in KIRC, HNSC, BRCA, UCS and THYM. 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 CREBBP RNA expression.
This table summarizes CREBBP 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 5. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CREBBP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CREBBP shows lower tumor expression in THCA and higher tumor expression in KIRC, KIRP, HNSC, LIHC and CHOL. The KIRC box plot shows higher CREBBP RNA expression in tumor versus normal tissue (log2 FC = +0.572, t-test p < 0.001).
This table shows molecular features associated with CREBBP in patient tissues and cancer cell lines. In patient samples, CREBBP 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, CREBBP 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 LARGE_INTESTINE and BLOOD_Leukemia.
