Q-omics provides the consensus-scored CDKN2AIP profile across patient tissues and cancer cell-line models. CDKN2AIP 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, CDKN2AIP is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, CDKN2AIP RNA expression shows 20,440 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where CDKN2AIP 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 CDKN2AIP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CDKN2AIP survival associations across molecular data types. CDKN2AIP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) 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 CDKN2AIP RNA expression–survival associations across cancer types. High CDKN2AIP expression shows unfavorable associations in UVM and ACC, but favorable associations in KIRC, BRCA, UCS and OV. 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 CDKN2AIP RNA expression.
This table summarizes CDKN2AIP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CDKN2AIP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CDKN2AIP shows lower tumor expression in THCA, KICH, BLCA, KIRC and KIRP and higher tumor expression in CHOL. The THCA box plot shows higher CDKN2AIP RNA expression in normal versus tumor tissue (log2 FC = −0.589, t-test p < 0.001).
This table shows molecular features associated with CDKN2AIP in patient tissues and cancer cell lines. In patient samples, CDKN2AIP 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, CDKN2AIP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
