Q-omics provides the consensus-scored GPD1 profile across patient tissues and cancer cell-line models. GPD1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, GPD1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, GPD1 protein abundance shows 24,878 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRP, and HNSC as cancer lineages where GPD1 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 GPD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GPD1 survival associations across molecular data types. GPD1 RNA expression shows survival associations in the most cancer types (23), 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 GPD1 RNA expression–survival associations across cancer types. High GPD1 expression shows unfavorable associations in UVM, LGG and ESCA, but favorable associations in KIRP, BRCA and LIHC. The KIRP 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 KIRP as the clearest survival context for GPD1 RNA expression.
This table summarizes GPD1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GPD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GPD1 shows lower tumor expression in HNSC, KICH, LUSC, LUAD, LIHC and BRCA. The HNSC box plot shows higher GPD1 RNA expression in normal versus tumor tissue (log2 FC = −3.291, t-test p < 0.001).
This table shows molecular features associated with GPD1 in patient tissues and cancer cell lines. In patient samples, GPD1 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, GPD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in CNS and BONE.
