Q-omics provides the consensus-scored GFOD1 profile across patient tissues and cancer cell-line models. GFOD1 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, GFOD1 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, GFOD1 protein abundance shows 21,871 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where GFOD1 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 GFOD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GFOD1 survival associations across molecular data types. GFOD1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (9) 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 GFOD1 RNA expression–survival associations across cancer types. High GFOD1 expression shows unfavorable associations in KIRP, UCEC, BRCA and BLCA, but favorable associations in KIRC and THCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for GFOD1 RNA expression.
This table summarizes GFOD1 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 HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GFOD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GFOD1 shows lower tumor expression in LUAD, BRCA and KICH and higher tumor expression in HNSC, KIRC and LIHC. The HNSC box plot shows higher GFOD1 RNA expression in tumor versus normal tissue (log2 FC = +0.944, t-test p < 0.001).
This table shows molecular features associated with GFOD1 in patient tissues and cancer cell lines. In patient samples, GFOD1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, GFOD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and LARGE_INTESTINE.
