Q-omics provides the consensus-scored FGD6 profile across patient tissues and cancer cell-line models. FGD6 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, FGD6 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, FGD6 RNA expression shows 19,866 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, HNSC, and UVM as cancer lineages where FGD6 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 FGD6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FGD6 survival associations across molecular data types. FGD6 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FGD6 RNA expression–survival associations across cancer types. High FGD6 expression shows unfavorable associations in KIRP, PAAD, THCA, STAD and LIHC, but favorable associations in UCS. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for FGD6 RNA expression.
This table summarizes FGD6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, 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 FGD6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FGD6 shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRC, KIRP, LUAD and LUSC. The HNSC box plot shows higher FGD6 RNA expression in tumor versus normal tissue (log2 FC = +1.865, t-test p < 0.001).
This table shows molecular features associated with FGD6 in patient tissues and cancer cell lines. In patient samples, FGD6 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, FGD6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
