Q-omics provides the consensus-scored CACYBP profile across patient tissues and cancer cell-line models. CACYBP expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CACYBP is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, CACYBP protein abundance shows 30,898 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, HNSC, and GBM as cancer lineages where CACYBP 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 CACYBP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CACYBP survival associations across molecular data types. CACYBP RNA expression shows survival associations in the most cancer types (26), 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 CACYBP RNA expression–survival associations across cancer types. High CACYBP expression shows unfavorable associations in KIRP, LIHC, ACC, LUAD, UVM and ESCA. The KIRP 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 KIRP as the clearest survival context for CACYBP RNA expression.
This table summarizes CACYBP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CACYBP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CACYBP shows higher tumor expression in HNSC, BLCA, LUAD, KIRC, LIHC and COAD. The HNSC box plot shows higher CACYBP RNA expression in tumor versus normal tissue (log2 FC = +1.257, t-test p < 0.001).
This table shows molecular features associated with CACYBP in patient tissues and cancer cell lines. In patient samples, CACYBP 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, CACYBP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Lymphoma.
