Q-omics provides the consensus-scored PPM1B profile across patient tissues and cancer cell-line models. PPM1B expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PPM1B is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, PPM1B RNA expression shows 20,778 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SKCM, KICH, and ACC as cancer lineages where PPM1B 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 PPM1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPM1B survival associations across molecular data types. PPM1B RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPM1B RNA expression–survival associations across cancer types. High PPM1B expression shows unfavorable associations in KIRP, UVM and UCEC, but favorable associations in SKCM, KIRC and BRCA. The SKCM 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 SKCM as the clearest survival context for PPM1B RNA expression.
This table summarizes PPM1B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PPM1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPM1B shows lower tumor expression in KICH, THCA, KIRC, COAD and READ and higher tumor expression in LIHC. The KICH box plot shows higher PPM1B RNA expression in normal versus tumor tissue (log2 FC = −1.190, t-test p < 0.001).
This table shows molecular features associated with PPM1B in patient tissues and cancer cell lines. In patient samples, PPM1B 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, PPM1B 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 BLOOD_Leukemia and LARGE_INTESTINE.
