Q-omics provides the consensus-scored PPL profile across patient tissues and cancer cell-line models. PPL expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PPL is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, PPL protein abundance shows 26,235 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight ACC, HNSC, and LUAD as cancer lineages where PPL 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 PPL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPL survival associations across molecular data types. PPL RNA expression shows survival associations in the most cancer types (20), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPL RNA expression–survival associations across cancer types. High PPL expression shows unfavorable associations in OV, LGG and PAAD, but favorable associations in ACC, LUSC and LIHC. The ACC 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 ACC as the clearest survival context for PPL RNA expression.
This table summarizes PPL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PPL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPL shows lower tumor expression in HNSC, KIRC, KICH and BRCA and higher tumor expression in THCA and CHOL. The HNSC box plot shows higher PPL RNA expression in normal versus tumor tissue (log2 FC = −2.018, t-test p < 0.001).
This table shows molecular features associated with PPL in patient tissues and cancer cell lines. In patient samples, PPL 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, PPL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Lymphoma.
