Q-omics provides the consensus-scored GFOD2 profile across patient tissues and cancer cell-line models. GFOD2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GFOD2 is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, GFOD2 RNA expression shows 20,536 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where GFOD2 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 GFOD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GFOD2 survival associations across molecular data types. GFOD2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GFOD2 RNA expression–survival associations across cancer types. High GFOD2 expression shows unfavorable associations in MESO, LUAD and BLCA, but favorable associations in KIRC, THYM and UCEC. 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 GFOD2 RNA expression.
This table summarizes GFOD2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 8. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GFOD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GFOD2 shows lower tumor expression in THCA, KICH, LUAD and HNSC and higher tumor expression in BLCA and KIRC. The THCA box plot shows higher GFOD2 RNA expression in normal versus tumor tissue (log2 FC = −1.575, t-test p < 0.001).
This table shows molecular features associated with GFOD2 in patient tissues and cancer cell lines. In patient samples, GFOD2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, GFOD2 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_SCLC and BLOOD_Leukemia.
