Q-omics provides the consensus-scored PRKACB profile across patient tissues and cancer cell-line models. PRKACB 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, PRKACB is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, PRKACB protein abundance shows 26,482 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, COAD, and GBM as cancer lineages where PRKACB 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 PRKACB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRKACB survival associations across molecular data types. PRKACB RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) 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 PRKACB RNA expression–survival associations across cancer types. High PRKACB expression shows unfavorable associations in ACC, LIHC, MESO and HNSC, but favorable associations in KIRC and SKCM. 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 PRKACB RNA expression.
This table summarizes PRKACB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PRKACB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRKACB shows lower tumor expression in COAD, THCA, LUSC, KIRC, KICH and READ. The COAD box plot shows higher PRKACB RNA expression in normal versus tumor tissue (log2 FC = −2.635, t-test p < 0.001).
This table shows molecular features associated with PRKACB in patient tissues and cancer cell lines. In patient samples, PRKACB 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, PRKACB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
