Q-omics provides the consensus-scored GIGYF2 profile across patient tissues and cancer cell-line models. GIGYF2 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, GIGYF2 is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, GIGYF2 RNA expression shows 21,651 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, LIHC, and ACC as cancer lineages where GIGYF2 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 GIGYF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GIGYF2 survival associations across molecular data types. GIGYF2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GIGYF2 RNA expression–survival associations across cancer types. High GIGYF2 expression shows unfavorable associations in ACC, LUSC, OV and LIHC, but favorable associations in KIRC and UCS. 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 GIGYF2 RNA expression.
This table summarizes GIGYF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for GIGYF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GIGYF2 shows lower tumor expression in THCA, BLCA and UCEC and higher tumor expression in LIHC, CHOL and STAD. The LIHC box plot shows higher GIGYF2 RNA expression in tumor versus normal tissue (log2 FC = +0.767, t-test p < 0.001).
This table shows molecular features associated with GIGYF2 in patient tissues and cancer cell lines. In patient samples, GIGYF2 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, GIGYF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
