Q-omics provides the consensus-scored CAMK2D profile across patient tissues and cancer cell-line models. CAMK2D expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CAMK2D is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, CAMK2D protein abundance shows 27,142 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, HNSC, and LUAD as cancer lineages where CAMK2D 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 CAMK2D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CAMK2D survival associations across molecular data types. CAMK2D RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) 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 CAMK2D RNA expression–survival associations across cancer types. High CAMK2D expression shows unfavorable associations in LGG, BLCA, SCLC and UVM, but favorable associations in KIRC and UCS. 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 CAMK2D RNA expression.
This table summarizes CAMK2D 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 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CAMK2D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CAMK2D shows lower tumor expression in COAD, UCEC, BLCA and BRCA and higher tumor expression in HNSC and KIRC. The HNSC box plot shows higher CAMK2D RNA expression in tumor versus normal tissue (log2 FC = +0.916, t-test p < 0.001).
This table shows molecular features associated with CAMK2D in patient tissues and cancer cell lines. In patient samples, CAMK2D shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, CAMK2D 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 UPPER_AERODIGESTIVE_TRACT and BONE.
