Q-omics provides the consensus-scored PPP1R2B profile across patient tissues and cancer cell-line models. PPP1R2B expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, PPP1R2B is differentially expressed in 7, with the highest sampling consensus in COAD. Additionally, PPP1R2B RNA expression shows 11,346 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight LUAD, COAD, and THYM as cancer lineages where PPP1R2B 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 PPP1R2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R2B survival associations across molecular data types. PPP1R2B RNA expression shows survival associations in the most cancer types (18), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP1R2B RNA expression–survival associations across cancer types. High PPP1R2B expression shows unfavorable associations in MESO and OV, but favorable associations in LUAD, SKCM, LUSC and READ. The LUAD 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 LUAD as the clearest survival context for PPP1R2B RNA expression.
This table summarizes PPP1R2B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for PPP1R2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R2B shows lower tumor expression in KICH, PAAD and READ and higher tumor expression in COAD, LIHC and BRCA. The COAD box plot shows higher PPP1R2B RNA expression in tumor versus normal tissue (log2 FC = +0.198, t-test p = .002).
This table shows molecular features associated with PPP1R2B in patient tissues and cancer cell lines. In patient samples, PPP1R2B shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BREAST.
