glycosylphosphatidylinositol anchored high density lipoprotein binding protein 1Genealiases: GPI-HBP1 · HYPL1D
Q-omics provides the consensus-scored GPIHBP1 profile across patient tissues and cancer cell-line models. GPIHBP1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GPIHBP1 is differentially expressed in 15, with the highest sampling consensus in LUAD. Additionally, GPIHBP1 RNA expression shows 26,495 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LUAD, and GBM as cancer lineages where GPIHBP1 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 GPIHBP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GPIHBP1 survival associations across molecular data types. GPIHBP1 RNA expression shows survival associations in the most cancer types (24), 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 GPIHBP1 RNA expression–survival associations across cancer types. High GPIHBP1 expression shows unfavorable associations in LUSC, BLCA and COAD, but favorable associations in KIRC, THCA and LGG. The KIRC 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 KIRC as the clearest survival context for GPIHBP1 RNA expression.
This table summarizes GPIHBP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for GPIHBP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GPIHBP1 shows lower tumor expression in LUAD, KICH, BLCA, KIRP, LUSC and UCEC. The LUAD box plot shows higher GPIHBP1 RNA expression in normal versus tumor tissue (log2 FC = −4.173, t-test p < 0.001).
This table shows molecular features associated with GPIHBP1 in patient tissues and cancer cell lines. In patient samples, GPIHBP1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, GPIHBP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
