Q-omics provides the consensus-scored GPLD1 profile across patient tissues and cancer cell-line models. GPLD1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, GPLD1 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, GPLD1 RNA expression shows 20,071 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, KICH, and UVM as cancer lineages where GPLD1 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 GPLD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GPLD1 survival associations across molecular data types. GPLD1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) 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 GPLD1 RNA expression–survival associations across cancer types. High GPLD1 expression shows unfavorable associations in UCEC, but favorable associations in LIHC, LUAD, HNSC, LUSC and BRCA. The LIHC 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 LIHC as the clearest survival context for GPLD1 RNA expression.
This table summarizes GPLD1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GPLD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GPLD1 shows lower tumor expression in KICH, COAD, BRCA, ESCA, THCA and CHOL. The KICH box plot shows higher GPLD1 RNA expression in normal versus tumor tissue (log2 FC = −0.751, t-test p < 0.001).
This table shows molecular features associated with GPLD1 in patient tissues and cancer cell lines. In patient samples, GPLD1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, GPLD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
