Q-omics provides the consensus-scored GP2 profile across patient tissues and cancer cell-line models. GP2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in THYM. Among the 18 cancer types available for tumor–normal comparison, GP2 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, GP2 RNA expression shows 14,025 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight THYM, KIRC, and PDAC as cancer lineages where GP2 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 GP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GP2 survival associations across molecular data types. GP2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GP2 RNA expression–survival associations across cancer types. High GP2 expression shows unfavorable associations in THYM, KIRC, SARC, DLBC and UCS, but favorable associations in BRCA. The THYM 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 THYM as the clearest survival context for GP2 RNA expression.
This table summarizes GP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for GP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GP2 shows lower tumor expression in KIRC, KIRP, KICH, COAD and READ and higher tumor expression in LIHC. The KIRC box plot shows higher GP2 RNA expression in normal versus tumor tissue (log2 FC = −2.773, t-test p < 0.001).
This table shows molecular features associated with GP2 in patient tissues and cancer cell lines. In patient samples, GP2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, GP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
