Q-omics provides the consensus-scored PAPPA profile across patient tissues and cancer cell-line models. PAPPA expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, PAPPA is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, PAPPA protein abundance shows 19,995 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight CESC, KIRC, and LSCC as cancer lineages where PAPPA 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 PAPPA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAPPA survival associations across molecular data types. PAPPA RNA expression shows survival associations in the most cancer types (26), followed by mutation status (8) 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 PAPPA RNA expression–survival associations across cancer types. High PAPPA expression shows unfavorable associations in CESC, LUSC, STAD and MESO, but favorable associations in UCS and LGG. The CESC 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 CESC as the clearest survival context for PAPPA RNA expression.
This table summarizes PAPPA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PAPPA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAPPA shows lower tumor expression in KIRC, KICH and UCEC and higher tumor expression in LUSC, HNSC and THCA. The KIRC box plot shows higher PAPPA RNA expression in normal versus tumor tissue (log2 FC = −2.905, t-test p < 0.001).
This table shows molecular features associated with PAPPA in patient tissues and cancer cell lines. In patient samples, PAPPA shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, PAPPA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BREAST.
