Q-omics provides the consensus-scored PPIL6 profile across patient tissues and cancer cell-line models. PPIL6 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, PPIL6 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, PPIL6 RNA expression shows 18,824 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight ACC, KICH, and THYM as cancer lineages where PPIL6 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 PPIL6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPIL6 survival associations across molecular data types. PPIL6 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPIL6 RNA expression–survival associations across cancer types. High PPIL6 expression shows unfavorable associations in SCLC, but favorable associations in ACC, KIRP, PAAD, MESO and HNSC. The ACC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify ACC as the clearest survival context for PPIL6 RNA expression.
This table summarizes PPIL6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 2. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PPIL6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPIL6 shows lower tumor expression in KICH, THCA, LUAD, LUSC and KIRC and higher tumor expression in COAD. The KICH box plot shows higher PPIL6 RNA expression in normal versus tumor tissue (log2 FC = −2.088, t-test p < 0.001).
This table shows molecular features associated with PPIL6 in patient tissues and cancer cell lines. In patient samples, PPIL6 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PPIL6 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 CNS and UPPER_AERODIGESTIVE_TRACT.
