Q-omics provides the consensus-scored PPIA profile across patient tissues and cancer cell-line models. PPIA expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PPIA is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PPIA RNA expression shows 19,738 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, and ACC as cancer lineages where PPIA 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 PPIA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPIA survival associations across molecular data types. PPIA RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPIA RNA expression–survival associations across cancer types. High PPIA expression shows unfavorable associations in HNSC, ACC, LUAD, UVM, LIHC and KICH. The HNSC 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 HNSC as the clearest survival context for PPIA RNA expression.
This table summarizes PPIA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PPIA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPIA shows higher tumor expression in HNSC, KIRC, KIRP, COAD, BLCA and LIHC. The HNSC box plot shows higher PPIA RNA expression in tumor versus normal tissue (log2 FC = +0.933, t-test p < 0.001).
This table shows molecular features associated with PPIA in patient tissues and cancer cell lines. In patient samples, PPIA 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, PPIA 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 UPPER_AERODIGESTIVE_TRACT and BONE.
