Q-omics provides the consensus-scored GYG2 profile across patient tissues and cancer cell-line models. GYG2 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, GYG2 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, GYG2 RNA expression shows 16,830 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, and TGCT as cancer lineages where GYG2 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 GYG2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GYG2 survival associations across molecular data types. GYG2 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 GYG2 RNA expression–survival associations across cancer types. High GYG2 expression shows unfavorable associations in KIRC, BLCA and ACC, but favorable associations in UVM, PAAD and READ. 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 GYG2 RNA expression.
This table summarizes GYG2 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 5. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GYG2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GYG2 shows lower tumor expression in KIRC, KICH, BRCA and THCA and higher tumor expression in LUAD and LUSC. The KIRC box plot shows higher GYG2 RNA expression in normal versus tumor tissue (log2 FC = −1.161, t-test p < 0.001).
This table shows molecular features associated with GYG2 in patient tissues and cancer cell lines. In patient samples, GYG2 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, GYG2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BONE.
