Q-omics provides the consensus-scored GOLGA8B profile across patient tissues and cancer cell-line models. GOLGA8B expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GOLGA8B is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, GOLGA8B RNA expression shows 16,985 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, LIHC, and UVM as cancer lineages where GOLGA8B 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 GOLGA8B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GOLGA8B survival associations across molecular data types. GOLGA8B RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GOLGA8B RNA expression–survival associations across cancer types. High GOLGA8B expression shows unfavorable associations in KIRC, UVM, ACC and PRAD, but favorable associations in BLCA and PAAD. The KIRC 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 KIRC as the clearest survival context for GOLGA8B RNA expression.
This table summarizes GOLGA8B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for GOLGA8B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GOLGA8B shows lower tumor expression in BRCA and higher tumor expression in LIHC, COAD, HNSC, KIRC and CHOL. The LIHC box plot shows higher GOLGA8B RNA expression in tumor versus normal tissue (log2 FC = +1.027, t-test p < 0.001).
This table shows molecular features associated with GOLGA8B in patient tissues and cancer cell lines. In patient samples, GOLGA8B 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, GOLGA8B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_SCLC.
