Q-omics provides the consensus-scored GPHB5 profile across patient tissues and cancer cell-line models. GPHB5 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in UCS. Additionally, GPHB5 RNA expression shows 6,200 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight UCS, and STAD as cancer lineages where GPHB5 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 GPHB5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GPHB5 survival associations across molecular data types. GPHB5 RNA expression shows survival associations in the most cancer types (16), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GPHB5 RNA expression–survival associations across cancer types. High GPHB5 expression shows unfavorable associations in UCS, ACC, COAD, READ, MESO and LIHC. The UCS 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 UCS as the clearest survival context for GPHB5 RNA expression.
This table shows molecular features associated with GPHB5 in patient tissues and cancer cell lines. In patient samples, GPHB5 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, GPHB5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD.
