Q-omics provides the consensus-scored GFER profile across patient tissues and cancer cell-line models. GFER expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, GFER is differentially expressed in 14, with the highest sampling consensus in KIRP. Additionally, GFER protein abundance shows 27,549 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, KIRP, and PDAC as cancer lineages where GFER 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 GFER — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GFER survival associations across molecular data types. GFER RNA expression shows survival associations in the most cancer types (20), followed by mutation status (1) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GFER RNA expression–survival associations across cancer types. High GFER expression shows unfavorable associations in ACC, UCS, LIHC, ESCA, READ and PRAD. The ACC 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 ACC as the clearest survival context for GFER RNA expression.
This table summarizes GFER tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 10. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GFER. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GFER shows higher tumor expression in KIRP, KIRC, HNSC, LIHC, LUAD and BRCA. The KIRP box plot shows higher GFER RNA expression in tumor versus normal tissue (log2 FC = +0.897, t-test p < 0.001).
This table shows molecular features associated with GFER in patient tissues and cancer cell lines. In patient samples, GFER shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, GFER RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
