Q-omics provides the consensus-scored GPC3 profile across patient tissues and cancer cell-line models. GPC3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, GPC3 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, GPC3 RNA expression shows 17,878 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight STAD, KIRC, and LUAD as cancer lineages where GPC3 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 GPC3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GPC3 survival associations across molecular data types. GPC3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GPC3 RNA expression–survival associations across cancer types. High GPC3 expression shows unfavorable associations in STAD, KIRP, ACC and UVM, but favorable associations in KICH and UCS. The STAD 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 STAD as the clearest survival context for GPC3 RNA expression.
This table summarizes GPC3 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 3. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GPC3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GPC3 shows lower tumor expression in KIRC, KIRP, THCA, KICH and LUAD and higher tumor expression in LIHC. The KIRC box plot shows higher GPC3 RNA expression in normal versus tumor tissue (log2 FC = −4.532, t-test p < 0.001).
This table shows molecular features associated with GPC3 in patient tissues and cancer cell lines. In patient samples, GPC3 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, GPC3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and SOFT_TISSUE.
