PIP5K1A and PSMD4 like (pseudogene)Genealiases: PIP5K1L1 · PIP5K1P3 · PSMD4P2 · bA429H9.1
Q-omics provides the consensus-scored PIPSL profile across patient tissues and cancer cell-line models. PIPSL 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, PIPSL is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, PIPSL RNA expression shows 18,583 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where PIPSL 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 PIPSL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PIPSL survival associations across molecular data types. PIPSL RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PIPSL RNA expression–survival associations across cancer types. High PIPSL expression shows unfavorable associations in ACC, MESO, UVM, LIHC, LUSC and STAD. 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 PIPSL RNA expression.
This table summarizes PIPSL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for PIPSL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PIPSL shows lower tumor expression in KICH and higher tumor expression in LIHC, HNSC, COAD, BRCA and STAD. The LIHC box plot shows higher PIPSL RNA expression in tumor versus normal tissue (log2 FC = +0.302, t-test p < 0.001).
This table shows molecular features associated with PIPSL in patient tissues and cancer cell lines. In patient samples, PIPSL 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, PIPSL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia.
