Q-omics provides the consensus-scored GOLGA6L9 profile across patient tissues and cancer cell-line models. GOLGA6L9 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GOLGA6L9 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, GOLGA6L9 RNA expression shows 19,820 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, LIHC, and UVM as cancer lineages where GOLGA6L9 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 GOLGA6L9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GOLGA6L9 survival associations across molecular data types. GOLGA6L9 RNA expression shows survival associations in the most cancer types (24), 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 GOLGA6L9 RNA expression–survival associations across cancer types. High GOLGA6L9 expression shows unfavorable associations in KIRC, KICH, UVM, LIHC and THCA, but favorable associations in SKCM. 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 GOLGA6L9 RNA expression.
This table summarizes GOLGA6L9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for GOLGA6L9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GOLGA6L9 shows lower tumor expression in THCA and higher tumor expression in LIHC, COAD, KIRC, CHOL and KIRP. The LIHC box plot shows higher GOLGA6L9 RNA expression in tumor versus normal tissue (log2 FC = +0.342, t-test p < 0.001).
This table shows molecular features associated with GOLGA6L9 in patient tissues and cancer cell lines. In patient samples, GOLGA6L9 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, GOLGA6L9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia.
