Q-omics provides the consensus-scored PPM1F profile across patient tissues and cancer cell-line models. PPM1F expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PPM1F is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, PPM1F protein abundance shows 37,481 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight ACC, KIRC, and UCEC as cancer lineages where PPM1F 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 PPM1F — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPM1F survival associations across molecular data types. PPM1F RNA expression shows survival associations in the most cancer types (23), followed by mutation status (12) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPM1F RNA expression–survival associations across cancer types. High PPM1F expression shows unfavorable associations in ACC, MESO, LIHC and UVM, but favorable associations in HNSC and KIRC. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for PPM1F RNA expression.
This table summarizes PPM1F tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 12. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PPM1F. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPM1F shows lower tumor expression in LUAD, THCA and UCEC and higher tumor expression in KIRC, LIHC and HNSC. The KIRC box plot shows higher PPM1F RNA expression in tumor versus normal tissue (log2 FC = +1.212, t-test p < 0.001).
This table shows molecular features associated with PPM1F in patient tissues and cancer cell lines. In patient samples, PPM1F shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, PPM1F RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LIVER and LARGE_INTESTINE.
