Q-omics provides the consensus-scored PPAT profile across patient tissues and cancer cell-line models. PPAT expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, PPAT is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, PPAT protein abundance shows 20,615 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight LIHC, HNSC, and LUAD as cancer lineages where PPAT 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 PPAT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPAT survival associations across molecular data types. PPAT RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 PPAT RNA expression–survival associations across cancer types. High PPAT expression shows unfavorable associations in LIHC, MESO, KICH, KIRP and THCA, but favorable associations in READ. The LIHC 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 LIHC as the clearest survival context for PPAT RNA expression.
This table summarizes PPAT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PPAT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPAT shows higher tumor expression in HNSC, BLCA, LUAD, COAD, KIRC and STAD. The HNSC box plot shows higher PPAT RNA expression in tumor versus normal tissue (log2 FC = +1.444, t-test p < 0.001).
This table shows molecular features associated with PPAT in patient tissues and cancer cell lines. In patient samples, PPAT shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, PPAT 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 SOFT_TISSUE.
