Q-omics provides the consensus-scored PPP1R32 profile across patient tissues and cancer cell-line models. PPP1R32 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, PPP1R32 is differentially expressed in 8, with the highest sampling consensus in LUSC. Additionally, PPP1R32 RNA expression shows 16,533 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, LUSC, and UVM as cancer lineages where PPP1R32 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 PPP1R32 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPP1R32 survival associations across molecular data types. PPP1R32 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPP1R32 RNA expression–survival associations across cancer types. High PPP1R32 expression shows unfavorable associations in KIRC, COAD and ACC, but favorable associations in LIHC, UCEC and SKCM. The LIHC 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 LIHC as the clearest survival context for PPP1R32 RNA expression.
This table summarizes PPP1R32 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 2. The strongest signals are observed in LUSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PPP1R32. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPP1R32 shows lower tumor expression in LUSC, LUAD, KIRP and BRCA and higher tumor expression in COAD and THCA. The LUSC box plot shows higher PPP1R32 RNA expression in normal versus tumor tissue (log2 FC = −1.857, t-test p < 0.001).
This table shows molecular features associated with PPP1R32 in patient tissues and cancer cell lines. In patient samples, PPP1R32 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, PPP1R32 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
