Q-omics provides the consensus-scored RFNG profile across patient tissues and cancer cell-line models. RFNG expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RFNG is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, RFNG RNA expression shows 18,413 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where RFNG 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 RFNG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RFNG survival associations across molecular data types. RFNG RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RFNG RNA expression–survival associations across cancer types. High RFNG expression shows unfavorable associations in ACC, KIRC, COAD and LGG, but favorable associations in UVM and BRCA. 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 RFNG RNA expression.
This table summarizes RFNG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RFNG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RFNG shows lower tumor expression in KICH and higher tumor expression in KIRC, KIRP, COAD, LIHC and BLCA. The KIRC box plot shows higher RFNG RNA expression in tumor versus normal tissue (log2 FC = +0.643, t-test p < 0.001).
This table shows molecular features associated with RFNG in patient tissues and cancer cell lines. In patient samples, RFNG 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, RFNG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and UPPER_AERODIGESTIVE_TRACT.
