Q-omics provides the consensus-scored GFM2 profile across patient tissues and cancer cell-line models. GFM2 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GFM2 is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, GFM2 RNA expression shows 20,617 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where GFM2 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 GFM2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GFM2 survival associations across molecular data types. GFM2 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (5) 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 GFM2 RNA expression–survival associations across cancer types. High GFM2 expression shows unfavorable associations in STAD, HNSC, THCA and KICH, but favorable associations in KIRC and READ. 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 GFM2 RNA expression.
This table summarizes GFM2 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 THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for GFM2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GFM2 shows lower tumor expression in THCA and higher tumor expression in BLCA, LUAD, LIHC, BRCA and STAD. The THCA box plot shows higher GFM2 RNA expression in normal versus tumor tissue (log2 FC = −0.574, t-test p < 0.001).
This table shows molecular features associated with GFM2 in patient tissues and cancer cell lines. In patient samples, GFM2 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, GFM2 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 BLOOD_Lymphoma and BLOOD_Leukemia.
