Q-omics provides the consensus-scored GP6 profile across patient tissues and cancer cell-line models. GP6 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, GP6 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, GP6 protein abundance shows 14,476 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight COAD, KICH, and BRCA as cancer lineages where GP6 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 GP6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GP6 survival associations across molecular data types. GP6 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GP6 RNA expression–survival associations across cancer types. High GP6 expression shows unfavorable associations in COAD, LUAD and OV, but favorable associations in BRCA, LIHC and UCEC. The COAD 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 COAD as the clearest survival context for GP6 RNA expression.
This table summarizes GP6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GP6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GP6 shows lower tumor expression in LUAD, LUSC, THCA and LIHC and higher tumor expression in KICH and KIRC. The KICH box plot shows higher GP6 RNA expression in tumor versus normal tissue (log2 FC = +1.345, t-test p < 0.001).
This table shows molecular features associated with GP6 in patient tissues and cancer cell lines. In patient samples, GP6 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, GP6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
