Q-omics provides the consensus-scored PPIL2 profile across patient tissues and cancer cell-line models. PPIL2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PPIL2 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, PPIL2 RNA expression shows 20,335 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and THCA as cancer lineages where PPIL2 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 PPIL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPIL2 survival associations across molecular data types. PPIL2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPIL2 RNA expression–survival associations across cancer types. High PPIL2 expression shows unfavorable associations in ACC, LIHC and LUSC, but favorable associations in BLCA, READ and HNSC. The ACC 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 ACC as the clearest survival context for PPIL2 RNA expression.
This table summarizes PPIL2 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 5. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PPIL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPIL2 shows lower tumor expression in THCA and higher tumor expression in LIHC, BLCA, STAD, BRCA and LUAD. The THCA box plot shows higher PPIL2 RNA expression in normal versus tumor tissue (log2 FC = −0.556, t-test p < 0.001).
This table shows molecular features associated with PPIL2 in patient tissues and cancer cell lines. In patient samples, PPIL2 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, PPIL2 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 BLOOD_Lymphoma and LARGE_INTESTINE.
